Miracle-dz/UniFAR-FTUs huggingface dataset:
FIRST NEIGHBOURHOOD ZAGREB INDEX OF SOME NANOSTRUCTURES

Motivated by chemical applications of topological indices in the QSPR/QSAR analysis, we introduce here a new topological index that we call, First Neighbourhood Zagreb Index (FNZI) and denote it by NM1(G). In this paper, FNZI is tested with physicochemical properties of octane isomers such as entropy, acentric factor, enthalpy of vaporization (HVAP) and DHVAP using the linear models. The FNZI shows excellent correlation with these chemical properties. Specially, high correlation with acentric factor (coefficient of correlation 0.994557). Later, we obtain bounds for NM1(G) in terms of order and size of original graph and determine the extremal graphs which achieve the bounds. Finally, as an application we compute the FNZI of line graphs of subdivision graphs of 2Dlattice, nanotube and nanotorus of 4 8[ , ] TUC C p q .
A current-mode latch sense amplifier and a static power saving input buffer for low-power architecture

Two circuit schemes for reducing power dissipation are proposed. The first is a current-mode latch sense amplifier that achieves power reduction without degradation of the access speed compared with conventional current-mirror sense amplifier operation. The other is a static power saving input buffer (SPSIB) for reducing static power. These circuits are applied to 512-kb high-speed SRAMs, and the efficiencies are simulated by SPICE simulations. The current-mode latch sense amplifier effectively reduces the power, and the SPSIB reduces current in the interface circuit. <<ETX>>
Malvidin 3-Glucoside Modulated Gut Microbial Dysbiosis and Global Metabolome Disrupted in a Murine Colitis Model Induced by Dextran Sulfate Sodium.

SCOPE This study aimed to elucidate the mechanisms of the anthocyanin malvidin 3-glucoside (MV) in alleviating gut dysbiosis using a murine colitis model induced by dextran sulfate sodium (DSS). METHODS AND RESULTS The effect of MV on the structure and function of the colon microbiome and microbial metabolism was evaluated using 16S rRNA gene sequencing, global metabolomics, and a network algorithm based on the random-matrix theory. MV ingestion improved histopathological scores and increased IL10 expression in the colon mucosa of colitis mice. While DSS had a profound effect on the gut microbiome and significantly decreased both microbial richness and evenness, MV further reduced evenness but promoted microbial interactions and restored the Firmicutes/Bacteroidetes ratio repressed by DSS. Moreover, MV reduced the abundance of pathogenic bacteria, such as Ruminococcus gnavus, in colitis mice and had a strong modulatory effect on microbial co-occurrence patterns and gut metabolites. In addition, MV reversed several key inflammatory mediators, including sphingolipid metabolites, from elevated levels in DSS colitis mice. As a bioactive ingredient, MV exerted its effect on the gut microbiome in a mechanism that differed from the whole blueberry. CONCLUSION MV ingestion ameliorated intestinal inflammation by modulating colon epithelium integrity, gut microbiome, and key inflammatory mediators. This article is protected by copyright. All rights reserved.
A high-throughput and multiplex microsphere immunoassay based on non-structural protein 1 can discriminate three flavivirus infections

The explosive spread of Zika virus (ZIKV) and associated complications in flavivirus-endemic regions underscore the need for sensitive and specific serodiagnostic tests to distinguish ZIKV, dengue virus (DENV) and other flavivirus infections. Compared with traditional envelope protein-based assays, several nonstructural protein 1 (NS1)-based assays showed improved specificity, however, none can detect and discriminate three flaviviruses in a single assay. Moreover, secondary DENV infection and ZIKV infection with previous DENV infection, both common in endemic regions, cannot be discriminated. In this study, we developed a high-throughput and multiplex IgG microsphere immunoassay (MIA) using the NS1 proteins of DENV1-DENV4, ZIKV and West Nile virus (WNV) to test samples from reverse-transcription-polymerase-chain reaction-confirmed cases, including primary DENV1, DENV2, DENV3, WNV and ZIKV infections, secondary DENV infection, and ZIKV infection with previous DENV infection. Combination of four DENV NS1 IgG MIAs revealed a sensitivity of 94.3% and specificity of 97.2% to detect DENV infection. The ZIKV and WNV NS1 IgG MIAs had a sensitivity/specificity of 100%/87.9% and 86.1%/78.4%, respectively. A positive correlation was found between the readouts of enzyme-linked immunosorbent assay and MIA for different NS1 tested. Based on the ratio of relative median fluorescence intensity of ZIKV NS1 to DENV1 NS1, the IgG MIA can distinguish ZIKV infection with previous DENV infection and secondary DENV infection with a sensitivity of 88.9–90.0% and specificity of 91.7–100.0%. The multiplex and high-throughput assay could be applied to serodiagnosis and serosurveillance of DENV, ZIKV and WNV infections in endemic regions.
The Scs disulfide reductase system cooperates with the metallochaperone CueP in Salmonella copper resistance

The human pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium) contains a complex disulfide bond (Dsb) catalytic machinery. This machinery encompasses multiple Dsb thiol-disulfide oxidoreductases that mediate oxidative protein folding and a less-characterized suppressor of copper sensitivity (scs) gene cluster, associated with increased tolerance to copper. To better understand the function of the Salmonella Scs system, here we characterized two of its key components, the membrane protein ScsB and the periplasmic protein ScsC. Our results revealed that these two proteins form a redox pair in which the electron transfer from the periplasmic domain of ScsB (n-ScsB) to ScsC is thermodynamically driven. We also demonstrate that the Scs reducing pathway remains separate from the Dsb oxidizing pathways and thereby avoids futile redox cycles. Additionally, we provide new insight into the molecular mechanism underlying Scs-mediated copper tolerance in Salmonella. We show that both ScsB and ScsC can bind toxic copper(I) with femtomolar affinities and transfer it to the periplasmic copper metallochaperone CueP. Our results indicate that the Salmonella Scs machinery has evolved a dual mode of action, capable of transferring reducing power to the oxidizing periplasm and protecting against copper stress by cooperating with the cue regulon, a major copper resistance mechanism in Salmonella. Overall, these findings expand our understanding of the functional diversity of Dsb-like systems, ranging from those mediating oxidative folding of proteins required for infection to those contributing to defense mechanisms against oxidative stress and copper toxicity, critical traits for niche adaptation and survival.
Estimation of the Uncertainties Related to the Measurement of the Size and Quantities of Individual Silver Nanoparticles in Confectionery

E174 (silver) is a food additive that may contain silver nanoparticles (AgNP). Validated methods are needed to size and quantify these particles in a regulatory context. However, no validations have yet been performed with food additives or real samples containing food additives requiring a sample preparation step prior to analysis. A single-particle inductively coupled plasma mass spectrometry (spICP-MS) method was developed and validated for sizing and quantifying the fraction of AgNP in E174 and in products containing E174, and associated uncertainties related to sample preparation, analysis and data interpretation were unraveled. The expanded measurement uncertainty for AgNP sizing was calculated to be 16% in E174-containing food products and increased up to 23% in E174 itself. The E174 food additives showed a large silver background concentration combined with a relatively low number of nanoparticles, making data interpretation more challenging than in the products. The standard uncertainties related to sample preparation, analysis, and challenging data interpretation were respectively 4.7%, 6.5%, and 6.0% for triplicate performances. For a single replicate sample, the uncertainty related to sample preparation increased to 6.8%. The expanded measurement uncertainty related to the concentration determination was 25–45% in these complex samples, without a clear distinction between additives and products. Overall, the validation parameters obtained for spICP-MS seem to be fit for the purpose of characterizing AgNP in E174 or E174-containing products.
Sputtered LiCoO2 Cathode Materials for All-Solid-State Thin-Film Lithium Microbatteries

This review article presents the literature survey on radio frequency (RF)-magnetron sputtered LiCoO2 thin films used as cathode materials in all-solid-state rechargeable lithium microbatteries. As the process parameters lead to a variety of texture and preferential orientation, the influence of the sputtering conditions on the deposition of LiCoO2 thin films are considered. The electrochemical performance is examined as a function of composition of the sputter Ar/O2 gas mixture, gas flow rate, pressure, nature of substrate, substrate temperature, deposition rate, and annealing temperature. The state-of-the-art of lithium microbatteries fabricated by the rf-sputtering method is also reported.
A Plasmodium berghei putative serine-threonine kinase 2 (PBANKA_0311400) is required for late liver stage development and timely initiation of blood stage infection

ABSTRACT In Plasmodium, protein kinases govern key biological processes of the parasite life cycle involved in the establishment of infection, dissemination and sexual reproduction. The rodent malaria model Plasmodium berghei encodes for 66 putative eukaryotic protein kinases (ePKs) as identified through modelling domain signatures and are highly conserved in Plasmodium falciparum. We report here the functional characterisation of a putative serine-threonine kinase PBANKA_0311400 identified in this kinome analysis and designate it as Pbstk2. To elucidate its role, we knocked out Pbstk2 locus and performed a detailed phenotypic analysis at different life cycle stages. The Pbstk2 knockout (KO) was not compromised in asexual blood stage propagation, transmission and development in the mosquito vector. The Pbstk2 KO produced viable salivary gland sporozoites that successfully transformed into exo-erythrocytic forms (EEFs) and were morphologically indistinguishable from wild-type GFP (WT GFP) with regard to size and shape until 48 h. An intravenous dose of 1×103 Pbstk2 KO sporozoites in C57BL/6 mice failed to establish blood stage infection and a higher dose of 5X103 showed a 2–3 day delay in prepatency as compared to WT GFP parasites. Consistent with such an observation, analysis of in vitro EEF development at 62 h revealed that the hepatic merozoite numbers were reduced to nearly 40% as compared to WT GFP and showed meagre expression of MSP1. Our studies provide evidence for the role of PbSTK2 in late liver stage development and for the successful establishment of a timely blood stage infection. Summary: Requirement of a putative serine threonine kinase 2 (PBANKA_0311400) for Plasmodium berghei liver stage development.
Illumination robust face recognition using spatial adaptive shadow compensation based on face intensity prior

Robust face recognition under illumination variations is an important and challenging task in a face recognition system, particularly for face recognition in the wild. In this paper, a face image preprocessing approach, called spatial adaptive shadow compensation (SASC), is proposed to eliminate shadows in the face image due to different lighting directions. First, spatial adaptive histogram equalization (SAHE), which uses face intensity prior model, is proposed to enhance the contrast of each local face region without generating visible noises in smooth face areas. Adaptive shadow compensation (ASC), which performs shadow compensation in each local image block, is then used to produce a wellcompensated face image appropriate for face feature extraction and recognition. Finally, null-space linear discriminant analysis (NLDA) is employed to extract discriminant features from SASC compensated images. Experiments performed on the Yale B, Yale B extended, and CMU PIE face databases have shown that the proposed SASC always yields the best face recognition accuracy. That is, SASC is more robust to face recognition under illumination variations than other shadow compensation approaches.
A Learning Scheme for EMG Based Decoding of Dexterous, In-Hand Manipulation Motions

Electromyography (EMG) based interfaces are the most common solutions for the control of robotic, orthotic, prosthetic, assistive, and rehabilitation devices, translating myoelectric activations into meaningful actions. Over the last years, a lot of emphasis has been put into the EMG based decoding of human intention, but very few studies have been carried out focusing on the continuous decoding of human motion. In this work, we present a learning scheme for the EMG based decoding of object motions in dexterous, in-hand manipulation tasks. We also study the contribution of different muscles while performing these tasks and the effect of the gender and hand size in the overall decoding accuracy. To do that, we use EMG signals derived from 16 muscle sites (8 on the hand and 8 on the forearm) from 11 different subjects and an optical motion capture system that records the object motion. The object motion decoding is formulated as a regression problem using the Random Forests methodology. Regarding feature selection, we use the following time-domain features: root mean square, waveform length and zero crossings. A 10-fold cross validation procedure is used for model assessment purposes and the feature variable importance values are calculated for each feature. This study shows that subject specific, hand specific, and object specific decoding models offer better decoding accuracy that the generic models.
High expression of the vacuole membrane protein 1 (VMP1) is a potential marker of poor prognosis in HER2 positive breast cancer

Background Fusion genes result from genomic structural changes, which can lead to alterations in gene expression that supports tumor development. The aim of the study was to use fusion genes as a tool to identify new breast cancer (BC) genes with a role in BC progression. Methods Fusion genes from breast tumors and BC cell lines were collected from publications. RNA-Seq data from tumors and cell lines were retrieved from databanks and analyzed for fusions with SOAPfuse or the analysis was purchased. Fusion genes identified in both tumors (n = 1724) and cell lines (n = 45) were confirmed by qRT-PCR and sequencing. Their individual genes were ranked by selection criteria that included correlation of their mRNA level with copy number. The expression of the top ranked gene was measured by qRT-PCR in normal tissue and in breast tumors from an exploratory cohort (n = 141) and a validation cohort (n = 277). Expression levels were correlated with clinical and pathological factors as well as the patients’ survival. The results were followed up in BC cohorts from TCGA (n = 818) and METABRIC (n = 2509). Results Vacuole membrane protein 1 (VMP1) was the most promising candidate based on specific selection criteria. Its expression was higher in breast tumor tissue than normal tissue (p = 1x10-4), and its expression was significantly higher in HER2 positive than HER2 negative breast tumors in all four cohorts analyzed. High expression of VMP1 associated with breast cancer specific survival (BCSS) in cohort 1 (hazard ratio (HR) = 2.31, CI 1.27–4.18) and METABRIC (HR = 1.26, CI 1.02–1.57), and also after adjusting for HER2 expression in cohort 1 (HR = 2.03, CI 1.10–3.72). BCSS was not significant in cohort 2 or TCGA cohort, which may be due to differences in treatment regimens. Conclusions The results suggest that high VMP1 expression is a potential marker of poor prognosis in HER2 positive BC. Further studies are needed to elucidate how VMP1 could affect pathways supportive of tumorigenesis.
Human DNA Telomeres in Presence of Oxidative Lesions: The Crucial Role of Electrostatic Interactions on the Stability of Guanine Quadruplexes

By using all atom molecular dynamics simulations, we studied the behavior of human DNA telomere sequences in guanine quadruplex (G4) conformation and in the presence of oxidative lesions, namely abasic sites. In particular, we evidenced that while removing one guanine base induces a significant alteration and destabilization of the involved leaflet, human telomere oligomers tend, in most cases, to maintain at least a partial quadruplex structure, eventually by replacing the empty site with undamaged guanines of different leaflets. This study shows that (i) the disruption of the quadruplex leaflets induces the release of at least one of the potassium cations embedded in the quadruplex channel and that (ii) the electrostatic interactions of the DNA sequence with the aforementioned cations are fundamental to the maintenance of the global quadruplex structure.
Temporal and spatial spread of Hypoderma actaeon infection in roe deer from peninsular Spain determined by an indirect enzyme‐linked immunosorbent assay

The host switching of Hypoderma actaeon (Diptera: Oestridae), a specific parasite of red deer (Cervus elaphus), towards roe deer (Capreolus capreolus) has been recently reported in Spain. To provide information about the temporal and spatial spreading of H. actaeon infection in roe deer, 244 serum samples from animals hunted in Spain between 2013 and 2018 were analysed by an indirect enzyme‐linked immunosorbent assay. The overall seropositivity was 13.9%. Seropositivity was higher in continental (27.7%) and mountainous (12%) areas from central Spain, followed by southern‐Mediterranean (11.2%) and northern‐oceanic regions (3.5%). Differences were significant between central‐continental and northern‐oceanic regions (P = 0.003). No differences were found according to the sex and age of roe deer (P > 0.05). In 2013, all seropositive animals were concentrated in two distant areas in central and southern Spain, suggesting that the host switch could have occurred independently in both regions. Changes in the pattern of distribution of red deer and roe deer could have favoured the spreading of this myiasis towards roe deer, indicating that roe deer may become infested by H. actaeon in areas where both cervids coexist at high densities.
FaceParser – A new face segmentation approach and labeleddatabase

Background and objective: A novel face parsing method is proposed in this paper which partition facial image into six semantic classes. Unlike previous approaches which segmented a facial image into three or four classes, we extended the class labels to six. Materials and Methods: A data-set of 464 images taken from FEI, MIT-CBCL, Pointing’04 and SiblingsDB databases was annotated. A discriminative model was trained by extracting features from squared patches. The built model was tested on two different semantic segmentation approaches – pixel-based and super-pixel-based semantic segmentation (PB_SS and SPB_SS). Results : A pixel labeling accuracy (PLA) of 94.68% and 90.35% was obtained with PB_SS and SPB_SS methods respectively on frontal images. Conclusions : A new method for face parts parsing was proposed which efficiently segmented a facial image into its constitute parts.
Discovery of small molecule agonists targeting neuropeptide Y4 receptor using homology modeling and virtual screening

Neuropeptide Y4 receptor has the most significant effect on body weight and fat mass in its physiological functions, and the activation of Y4 receptor has explicit role on losing weight. The Y4 receptor has been successfully applied in the development of anti‐obesity agent, thus representing a potential therapeutic target for obesity treatment. Here, we reported the first discovery of small molecule agonists targeting Y4 receptor: three Y4 receptor models with active and inactive conformations were built, each model was submitted following structure‐based virtual screening, and finally six hits were identified as Y4 receptor agonists. These results confirm the reliability of the constructed Y4 receptor models and the proposed computational strategy for investigating novel Y4 receptor agonists. These new small molecule Y4 receptor agonists will contribute to the further development of Y4 agonists as potential therapeutics and functional probes.
A Cancer Survival Prediction Method Based on Graph Convolutional Network

Background and objective: Cancer, as the most challenging part in the human disease history, has always been one of the main threats to human life and health. The high mortality of cancer is largely due to the complexity of cancer and the significant differences in clinical outcomes. Therefore, it will be significant to improve accuracy of cancer survival prediction, which has become one of the main fields of cancer research. Many calculation models for cancer survival prediction have been proposed at present, but most of them generate prediction models only by using single genomic data or clinical data. Multiple genomic data and clinical data have not been integrated yet to take a comprehensive consideration of cancers and predict their survival. Method: In order to effectively integrate multiple genomic data (including genetic expression, copy number alteration, DNA methylation and exon expression) and clinical data and apply them to predictive studies on cancer survival, similar network fusion algorithm (SNF) was proposed in this paper to integrate multiple genomic data and clinical data so as to generate sample similarity matrix, min-redundancy and max-relevance algorithm (mRMR) was used to conduct feature selection of multiple genomic data and clinical data of cancer samples and generate sample feature matrix, and finally two matrixes were used for semi-supervised training through graph convolutional network (GCN) so as to obtain a cancer survival prediction method integrating multiple genomic data and clinical data based on graph convolutional network (GCGCN). Result: Performance indexes of GCGCN model indicate that both multiple genomic data and clinical data play significant roles in the accurate survival time prediction of cancer patients. It is compared with existing survival prediction methods, and results show that cancer survival prediction method GCGCN which integrates multiple genomic data and clinical data has obviously superior prediction effect than existing survival prediction methods. Conclusion: All study results in this paper have verified effectiveness and superiority of GCGCN in the aspect of cancer survival prediction.