Miracle-dz/UniFAR-FTUs huggingface dataset:
Metformin attenuates depressive-like behaviour of methamphetamine withdrawal in mice: A mechanistic approach

Abstract Objectives Methamphetamine (METH) as a potent psychostimulant drug with a high potency of dependence rate that results in neurotoxicity has become a major drug of abuse in many parts of the world. Unfortunately, there is limited evidence regarding treatment of METH withdrawal syndrome. Therefore, we aimed to investigate whether metformin mitigate the methamphetamine (METH) withdrawal syndrome in male mice. Based on the literature, depression and anxiety are the major METH withdrawal symptoms. Methods Here, METH (2 mg/kg) was administered to mice twice a day for 14 constitutive days to induce animal model of METH-induced withdrawal syndrome. To do this, mice in control group and those with METH withdrawal syndrome were divided into treatment (receiving metformin in 3 doses of 50, 100 and 200 mg/kg for 10 days) and non-treatment sub-groups. Following the behavioural test, the animals were sacrificed; their hippocampus was dissected to measure oxidative stress parameters and expression of cellular energy homeostasis and immune-inflammatory genes. Results Our data revealed that metformin provoked antidepressant effects in behavioural tests through AMPK overexpression as an important mitochondrial energetic sensor and inhibition of Tlr4 overexpression in the immune system gene expression. In addition, metformin was able to improve oxidative stress biomarkers and neuronal damage in the hippocampus and restore cellular energy homeostasis and immune system gene expression. Conclusions The data suggested that metformin can influence the hippocampus through targeting mitochondria and their performance, and consequently, neuroinflammation responses and brain metabolic changes. It is supposed to be a new therapeutic option in clinical trials of depression and anxiety following METH withdrawal treatment.
Graph Few-Shot Learning via Restructuring Task Graph

Existing graph few-shot learning (FSL) methods usually train a model on many task graphs and transfer the learned model to a new task graph. However, the task graphs often contain a great number of isolated nodes, which results in the severe deficiency of learned node embeddings. Furthermore, in the training process, the neglect of task information also constrains the model’s expressive ability. In this brief, we propose a novel metric-based graph few-shot learning approach via restructuring task graph (GFL-RTG). To solve the problems above, we innovatively restructure the task graph by adding class nodes and a task node to the original individual task graph. We first add class nodes and determine the connectivity between class nodes and others via their similarity. Then, we utilize a graph pooling network to learn a task embedding, which is regarded as a task node. Finally, the new task graph is restructured by combining class nodes, task node, and original nodes, which is then used as input to the metric-based graph neural network (GNN) to conduct few-shot learning. Our extensive experiments on three graph-structured datasets demonstrate that our proposed method generally outperforms the state-of-the-art baselines in few-shot learning.
EFFICIENCY GAIN OF REDUCED RIPPLE CURRENT WITH ZVS DC-DC CONVERTER

The force era market, has indicated clear development. Be that as it may, a high voltage and productivity increase is key for the power module and PV board and for different machines. The high step –up converter in the proposed converter gives swell free information current. The full scaffold converter gives high voltage pick up. An APWM Full Bridge Boost converter are generally utilized as a part of utilization where the yield voltage is extensively higher than the info voltage. Zero Voltage Switching(ZVS )is commonly executed in the switches.ZVS APWM DC-DC Full extension converter that does not have any downsides of that different converters of this sort have, for example, entangled auxillary circuit,. increased current anxiety in the primary force switches and the heap subordinate ZVS operation. In this proposed strategy an interleaved procedure of Boost and Full Bridge converter is used.The diverse methods of operation of MOSFET has been talked about. Besides converter has high proficiency due to delicate exchanging operation in switches. A 24V information voltage, 350V yield voltage, and 168W yield power reproduction circuit of the proposed converter has been executed and its effectiveness is up to 87.5%.
Hybrid Electromagnetic and Non-Linear Modeling and Design of SIW Cavity-Backed Active Antennas

─ This paper presents the modeling and implementation of planar passive and active cavity-backed antennas in substrate integrated waveguide (SIW) technology. The cavity-backed topology helps suppressing the undesired surfacewave modes and may provide better phase noise performance in the antenna oscillator. The use of SIW technology allows for a compact and costeffective implementation of the structure. The design of the active antenna involves both electromagnetic full-wave modeling for the radiating structure and nonlinear analysis of the active circuitry through harmonic balance and transient simulations. Single substrate prototypes of both passive and active antennas operating in X band are presented and measured, showing good agreement with simulated results. Index Terms ─ Active antenna, cavity-backed antenna, harmonic-balance technique, substrate integrated waveguide (SIW).
Adversarial Evolving Neural Network for Longitudinal Knee Osteoarthritis Prediction

Knee osteoarthritis (KOA) as a disabling joint disease has doubled in prevalence since the mid-20th century. Early diagnosis for the longitudinal KOA grades has been increasingly important for effective monitoring and intervention. Although recent studies have achieved promising performance for baseline KOA grading, longitudinal KOA grading has been seldom studied and the KOA domain knowledge has not been well explored yet. In this paper, a novel deep learning architecture, namely adversarial evolving neural network (A-ENN), is proposed for longitudinal grading of KOA severity. As the disease progresses from mild to severe level, ENN involves the progression patterns for accurately characterizing the disease by comparing an input image it to the template images of different KL grades using convolution and deconvolution computations. In addition, an adversarial training scheme with a discriminator is developed to obtain the evolution traces. Thus, the evolution traces as fine-grained domain knowledge are further fused with the general convolutional image representations for longitudinal grading. Note that ENN can be applied to other learning tasks together with existing deep architectures, in which the responses characterize progressive representations. Comprehensive experiments on the Osteoarthritis Initiative (OAI) dataset were conducted to evaluate the proposed method. An overall accuracy was achieved as 62.7%, with the baseline, 12-month, 24-month, 36-month, and 48-month accuracy as 64.6%, 63.9%, 63.2%, 61.8% and 60.2%, respectively.
Intrinsic variation effect in memristive neural network with weight quantization

To analyze the effect of the intrinsic variations of the memristor device on the neuromorphic system, we fabricated 32 × 32 Al2O3/TiO x -based memristor crossbar array and implemented 3 bit multilevel conductance as weight quantization by utilizing the switching characteristics to minimize the performance degradation of the neural network. The tuning operation for 8 weight levels was confirmed with a tolerance of ±4 μA (±40 μS). The endurance and retention characteristics were also verified, and the random telegraph noise (RTN) characteristics were measured according to the weight range to evaluate the internal stochastic variation effect. Subsequently, a memristive neural network was constructed by off-chip training with differential memristor pairs for the Modified National Institute of Standards and Technology (MNIST) handwritten dataset. The pre-trained weights were quantized, and the classification accuracy was evaluated by applying the intrinsic variations to each quantized weight. The intrinsic variations were applied using the measured weight inaccuracy given by the tuning tolerance, RTN characteristics, and the fault device yield. We believe these results should be considered when the pre-trained weights are transferred to a memristive neural network by off-chip training.
Machine Learning Study of Metabolic Networks vs ChEMBL Data of Antibacterial Compounds

Antibacterial drugs (AD) change the metabolic status of bacteria, contributing to bacterial death. However, antibiotic resistance and the emergence of multidrug-resistant bacteria increase interest in understanding metabolic network (MN) mutations and the interaction of AD vs MN. In this study, we employed the IFPTML = Information Fusion (IF) + Perturbation Theory (PT) + Machine Learning (ML) algorithm on a huge dataset from the ChEMBL database, which contains >155,000 AD assays vs >40 MNs of multiple bacteria species. We built a linear discriminant analysis (LDA) and 17 ML models centered on the linear index and based on atoms to predict antibacterial compounds. The IFPTML-LDA model presented the following results for the training subset: specificity (Sp) = 76% out of 70,000 cases, sensitivity (Sn) = 70%, and Accuracy (Acc) = 73%. The same model also presented the following results for the validation subsets: Sp = 76%, Sn = 70%, and Acc = 73.1%. Among the IFPTML nonlinear models, the k nearest neighbors (KNN) showed the best results with Sn = 99.2%, Sp = 95.5%, Acc = 97.4%, and Area Under Receiver Operating Characteristic (AUROC) = 0.998 in training sets. In the validation series, the Random Forest had the best results: Sn = 93.96% and Sp = 87.02% (AUROC = 0.945). The IFPTML linear and nonlinear models regarding the ADs vs MNs have good statistical parameters, and they could contribute toward finding new metabolic mutations in antibiotic resistance and reducing time/costs in antibacterial drug research.
Animal Model Deletion of Decay-Accelerating Factor (CD55) Exacerbates Autoimmune Disease Development in MRL/lpr Mice

Decay-accelerating factor (DAF, CD55) is a glyco-sylphosphatidylinositol-anchored membrane protein that restricts complement activation on autologous cells. It is also a ligand for CD97, an activation-asso-ciated lymphocyte antigen with seven transmembrane domains. It is widely expressed on cells of both the hematopoietic and nonhematopoietic lineages. of DAF is associated with the hemolytic anemia syndrome paroxysmal nocturnal hemoglobinuria, the in vivo biology of is poorly We addressed the in vivo function of DAF in a knockout mouse model and describe here that deletion of DAF exacerbates autoimmune disease development in MRL/lpr mice, a model for human systemic lupus erythematosus. Compared to DAF-sufficient littermate controls, DAF-deficient female MRL/lpr mice developed exacerbated lymphadenopathy and splenomegaly, higher serum anti-chromatin autoantibody levels, and aggravated dermatitis. Consistent with the phenotype of aggravated dermatitis in DAF-deficient mice, Northern and Western blots and immunofluorescence studies showed DAF to be expressed abundantly in the mouse skin, suggesting that it may play a particularly important role in this tissue. Histology and immunostaining demonstrated inflammatory infiltrate and focal C3 deposition in early skin lesions, mostly along the dermal-epidermal junction. These results reveal a protective function of DAF in the development of a systemic autoimmune syndrome and suggest that dysfunction or down-regulation of DAF may contribute to autoimmune disease pathogenesis and manifestation. (Am J Pathol 2002, 161:1077–1086) In the current study, we addressed this by investigating the effect of on autoimmune disease development in MRL/ lpr Two homologous genes, arranged in on have identified One similar The The this study, we have crossed a GPI-DAF gene KO mouse, in our laboratory, with the MRL/lpr mouse, and compared autoimmune development in GPI-DAF gene-sufficient and gene-deficient littermate controls. Our results reveal a significant protective role for DAF in this model of systemic autoimmune disease.
Immunoassay for the discrimination of free prostate-specific antigen (fPSA) forms with internal cleavages at Lys 145 or Lys 146 from fPSA without internal cleavages at Lys 145 or Lys 146

Total levels of circulating prostate-specific antigen (tPSA) are strongly associated with prostate cancer (PCa) risk and outcome but benign prostate disease is the most frequent cause of a moderately elevated PSA level. Free PSA (fPSA) forms are independently associated with PCa risk and contribute modest diagnostic enhancements above and beyond tPSA alone. We developed an immunoassay for fPSA subfractions containing internal cleavages at Lys 145 or Lys 146 (fPSA-N). The assay was based on blocking intact single-chain fPSA (fPSA-I) with antibody 4D4 which does not detect PSA containing internal cleavages at Lys 145 or Lys 146 . We also measured fPSA-N in blood from healthy volunteers and in anti-coagulated plasma from 76 men with or without evidence of PCa at biopsy. The analytical and functional detection limits of this assay were 0.016 ng/mL and 0.10 ng/mL, respectively. The median recovery of male fPSA-N from female plasma was 95.0 %. All 12 female samples (average age 28 years) had fPSA-N concentrations at or below the analytical detection limit. The median fPSA-N concentration (0.050 ng/mL) in 9 healthy male volunteers (age < 40 years) was below the functional detection limit, 0.420 ng/mL in 27 patients with benign prostate conditions and 0.239 ng/mL in 49 patients with PCa. Deming regression analysis of the patient samples showed that the measured fPSA-N concentrations were generally 23% lower than the previously calculated (fPSA minus fPSA-I) concentrations, likely due to differences in the antibody combinations used. In conclusion, we have developed a sensitive, specific and direct immunoassay for fPSA-N which can be used to study the clinical relevance of this PSA isoform.
Mapping of a Yeast G Protein (cid:98)(cid:103) Signaling Interaction

The mating pathway of Saccharomyces cerevisiae is widely used as a model system for G protein-coupled receptor-mediated signaltransduction. Following receptoractivation by thebinding ofmating pheromones, G protein (cid:98)(cid:103) subunits transmit the signal to a MAP kinase cascade, which involves interaction of G (cid:98) (Ste4p) with the MAP kinase scaffold protein Ste5p. Here, we identify residues in Ste4p required for the interaction with Ste5p. These residues deﬁne a new signaling interface close to the Ste20p binding site within the G (cid:98)(cid:103) coiled-coil. Ste4p mutants defective in the Ste5p interaction interact efﬁciently with Gpa1p (G (cid:97) ) and Ste18p (G (cid:103) ) but cannot function in signal transduction because cells expressing these mutants are sterile. Ste4 L65S is temperature-sensitive for its interaction with Ste5p, and also for signaling. We have identiﬁed a Ste5p mutant (L196A) that displays a synthetic interaction defect with Ste4 L65S, providing strong evidence that Ste4p and Ste5p interact directly in vivo through an interface that involves hydrophobic residues. The correlation between disruption of the Ste4p-Ste5p interaction and sterility conﬁrms the importance of this interaction in signal transduction. Identiﬁcation of the G (cid:98)(cid:103) coiled-coil in Ste5p binding may set a precedent for G (cid:98)(cid:103) -effector interactions in more complex organisms. Structural modeling: The Gpa1p/Ste4p/Ste18p structure modeled on the coordinates of mammalian Gi (cid:97) 1 (cid:98) 1 2 the Brookhaven realized using RasMol program, developed by Roger at Glaxo
Structural Analysis of Mispaired DNA Termini Transitioning to DNA Polymerase Pre-catalytic Complexes Supports an Induced Fit Fidelity Mechanism

High fidelity DNA synthesis requires that polymerases display a strong preference for right nucleotide insertion. When the wrong nucleotide is inserted, the polymerase deters extension from the mismatched DNA terminus. Twenty-three crystallographic structures of DNA polymerase β with terminal template-primer mismatches were determined as binary DNA and ternary precatalytic substrate complexes. These structures indicate that the mismatched termini adopt various distorted conformations that attempt to satisfy stacking and hydrogen bonding interactions. The binary complex structures indicate an induced strain in the mismatched template nucleotide. Addition of a non-hydrolysable incoming nucleotide stabilizes the templating nucleotide with concomitant strain in the primer terminus. Several dead-end ternary complex structures suggest that DNA synthesis might occur as the enzyme transitions from an open to closed complex. The structures are consistent with an induced fit mechanism where a mismatched terminus is misaligned relative to the correct incoming nucleotide to deter or delay further DNA synthesis.
INVITED South American Leaf Blight of the Rubber Tree ( Hevea spp.): New Steps in Plant Domestication using Physiological Features and Molecular Markers

† Background Rubber trees ( Hevea spp.) are perennial crops of Amazonian origin that have been spread over the whole tropical belt to guarantee worldwide production of natural rubber. This crop plant has found its place in many national economies of producing countries, and although its domestication by selection of suitable genotypes was very slow, it contributes a lot to the welfare of small farmers worldwide. Its development is limited by severe diseases. In South America, the main fungal disease of rubber trees is the South American leaf blight (SALB) caused by the ascomycete Microcyclus ulei . This fungus inhibits natural rubber production on a commercial scale in South and Central America. † Scope The disease is still restricted to its continent of origin, but its potential to be distributed around the world rises with every transcontinental airline connection that directly links tropical regions. The need to develop control measures against the disease is an urgent task and must be carried out on an international scale. All control efforts so far taken since 1910 have ended in a miserable failure. Even the use of modern systemic fungicides and use of greatly improved application techniques have failed to prevent large losses and dieback of trees. The results of research dealing with both the disease and the pathosystem over more than 50 years are summarized and placed into perspective. † Future Prospects A detailed knowledge of this host–pathogen combination requires understanding of the dynamics of Hevea leaf development, the biochemical potential for cyanide liberation, and molecular data for several types of resistance factors. Resolution of the Hevea –SALB problem may serve as a model for future host–pathogen studies of perennial plants requiring a holistic approach.
Cytotoxic Necrotizing Factor 1 Prevents Apoptosis via the Akt/I (cid:1) B Kinase Pathway: Role of Nuclear Factor- (cid:1) B and Bcl-2 □ V

Cytotoxic necrotizing factor 1 (CNF1) is a protein toxin produced by some pathogenic strains of Escherichia coli that speciﬁcally activates Rho, Rac, and Cdc42 GTPases. We previously reported that this toxin prevents the ultraviolet-B– induced apoptosis in epithelial cells, with a mechanism that remained to be deﬁned. In this work, we show that the proteasomal degradation of the Rho GTPase is necessary to achieve cell death protection, because inhibition of Rho degradation abolishes the prosurvival activity of CNF1. We hypothesize that Rho inactivation allows the activity of Rac to become dominant. This in turn leads to stimulation of the phosphoinositide 3-kinase/Akt/I (cid:1) B kinase/nuclear factor- (cid:1) B prosurvival pathway and to a remarkable modiﬁcation in the architecture of the mitochondrial network, mainly consisting in the appearance of elongated and interconnected mitochondria. Importantly, we found that Bcl-2 silencing reduces the ability of CNF1 to protect cells against apoptosis and that it also prevents the CNF1-induced mitochondrial changes. It is worth noting that the ability of a bacterial toxin to induce such a remodeling of the mitochondrial network is herein reported for the ﬁrst time. The possible pathophysiological relevance
Nucleic Acids Research

The degradation of the polycistronic tra-mRNA of the resistance plasmid RI-19 leads to the accumulation of a well defined series of stable mRNA species. The majority of the most stable mRNAs contains the message for the traA gene only. The differently sized stable mRNAs possess a common 3'terminus within the traL gene but vary at their 5'ends. The 3'terminus probably results from protection against exoribonucleases by a secondary structural feature. We propose that the 5'ends are generated by endoribonucleolytic cleavage. The stability of this part of the tra-mRNA exceeds 30 minutes and probably increases the rate of expression ofthe traA gene product propiin, the precursor of the sex pilus subunit. The expression of propilin and its processing into a protein of the molecular weight of mature pilin is demonstrated with the isolated gene. The sequence of the so far unknown genes traL and traE of Rl-19 is presented. INTRODUCTION It has become increasingly evident in the last years that the stability ofmRNA in prokaryotic organisms represents a major factor in the efficiency of gene expression (1). Differential mRNA stability may be as important as transcriptional or translational control. Bacterial mRNA stabilities vary greatly; generally the half-life appears to be in the order of a few minutes. A number of mRNAs, however, are considerably more stable, like the mRNA for OmpA, the major outer membrane protein of E. coli. The stability of the monocistronic ompA message was found to be growth-rate dependent (2). Other examples have been reported showing that certain segments in a polycistronic mRNA decay significantly slower than the rest of the molecule like the 3'portion ofthepuftranscript ofRhodobacter capsulatus which is rapidly degraded to give rise to either of two slowly decaying mRNA remnants (3). In the case of the papA mRNA within the pap pili gene cluster a primary transcript also encoding the papB regulatory gene product is endonucleolytically cleaved. The cleavage results in the rapid decay of the papB encoding 5'half of the mRNA, whereas the papA encoding 3'half remains as a stable transcript. In this way mRNAs coding for the major pilus subunit accumulate (4). Another example of differential mRNA stability is the polycistronic malEFG operon of E.coli (5). In E.coli two enzymes are primarily responsible for the bulk degredation of mRNA, RNase II and polynucleotide phosphorylase (5). These enzymes are 3'-5' exoribonucleases. Special secondary structures within or at the end of a mRNA are known to protect the upstream lying message against the degrading activity of the 3' -5' exoribonucleases (1). No 5'-3' exoribonuclease has yet been identified in E. coli (6). On the basis of the latest results it has been proposed that in addition to the better characterized 3' exoribonucleases Volume 17 Number 4 1989