Miracle-dz/UniFAR-FTUs huggingface dataset:
Dairy Products Quality from a Consumer Point of View: Study among Polish Adults

The aims of the current study were (a) to deepen the understanding of food quality from animal origin with particular emphasis on dairy products, including yoghurt; (b) to determine the level of acceptance of methods and ingredients used to enhance the quality of food from animal origin; (c) to identify how the perception of animal products quality affects the acceptance of changes in production methods and (d) to identify the projective image of consumers purchasing high-quality yoghurt. The data were collected using a CAPI (Computer Assisted Personal Interview) survey on a sample of 983 consumers. The k-means clustering method (k-means clustering algorithm is an unsupervised algorithm that is used to segment the interest area from the background) was used to identify five clusters of consumers. Moreover, the logistic regression models were used in order to examine the impact of opinions related to the quality of product on acceptance of food production methods. The results showed that food quality is generally perceived by consumers using the following attributes: its freshness, naturalness, production method, as well as appearance, taste and smell, but when it comes to the quality of food from animal origin, convenience, connected with the availability, nutritional value and health benefits is of primary importance. The most accepted production method of high-quality food is animal production that takes into consideration the welfare of farm animals. Results also show that the increase in the level of education among the surveyed people contributed to the acceptance of ensuring welfare of farm animals as a method of increasing food quality while consumers′ openness to new products favored the acceptance of adding health-promoting ingredients to livestock feed. As regards the assessment of the level of acceptance of enhancing food with beneficial ingredients, people for whom health aspects were important declared their willingness to accept such a method of increasing food quality. The research findings can be used to develop educational campaigns as well as marketing communication of enterprises operating on the food market. Furthermore, the results could be used to strengthen the competitive position of food enterprises searching for innovative solutions.
Impact of Pre-Blood Collection Factors on Plasma Metabolomic Profiles

Demographic, lifestyle and biospecimen-related factors at the time of blood collection can influence metabolite levels in epidemiological studies. Identifying the major influences on metabolite concentrations is critical to designing appropriate sample collection protocols and considering covariate adjustment in metabolomics analyses. We examined the association of age, sex, and other short-term pre-blood collection factors (time of day, season, fasting duration, physical activity, NSAID use, smoking and alcohol consumption in the days prior to collection) with 133 targeted plasma metabolites (acylcarnitines, amino acids, biogenic amines, sphingolipids, glycerophospholipids, and hexoses) among 108 individuals that reported exposures within 48 h before collection. The differences in mean metabolite concentrations were assessed between groups based on pre-collection factors using two-sided t-tests and ANOVA with FDR correction. Percent differences in metabolite concentrations were negligible across season, time of day of collection, fasting status or lifestyle behaviors at the time of collection, including physical activity or the use of tobacco, alcohol or NSAIDs. The metabolites differed in concentration between the age and sex categories for 21.8% and 14.3% metabolites, respectively. In conclusion, extrinsic factors in the short period prior to collection were not meaningfully associated with concentrations of selected endogenous metabolites in a cross-sectional sample, though metabolite concentrations differed by age and sex. Larger studies with more coverage of the human metabolome are warranted.
A Review on Microdevices for Isolating Circulating Tumor Cells

Cancer metastasis is the primary cause of high mortality of cancer patients. Enumeration of circulating tumor cells (CTCs) in the bloodstream is a very important indicator to estimate the therapeutic outcome in various metastatic cancers. The aim of this article is to review recent developments on the CTC isolation technologies in microdevices. Based on the categories of biochemical and biophysical isolation approaches, a literature review and in-depth discussion will be included to provide an overview of this challenging topic. The current excellent developments suggest promising CTC isolation methods in order to establish a precise indicator of the therapeutic outcome of cancer patients.
Isolation, Characterization and Chemical Synthesis of Large Spectrum Antimicrobial Cyclic Dipeptide (l-leu-l-pro) from Streptomyces misionensis V16R3Y1 Bacteria Extracts. A Novel 1H NMR Metabolomic Approach

Streptomyces is the most frequently described genus of Actinomycetes, a producer of biologically active secondary metabolites. Indeed, the Streptomyces species produces about 70% of antibiotics and 60% of antifungal molecules used in agriculture. Our study was carried out with the goal of isolating and identifying antimicrobial secondary metabolites from Streptomyces misionensis V16R3Y1 isolated from the date palm rhizosphere (southern Tunisia). This strain presented a broad range of antifungal activity against Fusarium oxysporum, Aspergillus flavus, Penicillium expansum, Aspergillus niger, Candida albicans, Candida metapsilosis, and Candida parapsilosis and antibacterial activity against human pathogenic bacteria, including Escherichia fergusonii, Staphylococcus aureus, Salmonella enterica, Enterococcus faecalis, Bacillus cereus and Pseudomonas aeruginosa. The purification procedure entailed ethyl acetate extract, silica gel column, and thin layer chromatography. Based on 1H NMR metabolomic procedure application, also supported by the GC-MS analysis, cyclic dipeptide (l-Leucyl-l-Proline) was identified as the major compound in the bioactive fraction. In order to confirm the identity of the active compound and to have a large quantity thereof, a chemical synthesis of the cyclic dipeptide was performed. The synthetic compound was obtained with a very good yield (50%) and presented almost the same effect compared to the extracted fraction. This study indicates for the first time that Streptomyces misionensis V16R3Y1 exhibits a broad spectrum of antimicrobial activities, produced cyclic dipeptide (l-Leucyl-l-Proline) and might have potential use as a natural agent for pharmaceutical and agri-food applications.
PoisonRec: An Adaptive Data Poisoning Framework for Attacking Black-box Recommender Systems

Data-driven recommender systems that can help to predict users’ preferences are deployed in many real online service platforms. Several studies show that they are vulnerable to data poisoning attacks, and attackers have the ability to mislead the system to perform as their desires. Considering the realistic scenario, where the recommender system is usually a black-box for attackers and complex algorithms may be deployed in them, how to learn effective attack strategies on such recommender systems is still an under-explored problem. In this paper, we propose an adaptive data poisoning framework, PoisonRec, which can automatically learn effective attack strategies on various recommender systems with very limited knowledge. PoisonRec leverages the reinforcement learning architecture, in which an attack agent actively injects fake data (user behaviors) into the recommender system, and then can improve its attack strategies through reward signals that are available under the strict black-box setting. Specifically, we model the attack behavior trajectory as the Markov Decision Process (MDP) in reinforcement learning. We also design a Biased Complete Binary Tree (BCBT) to reformulate the action space for better attack performance. We adopt 8 widely-used representative recommendation algorithms as our testbeds, and make extensive experiments on 4 different real-world datasets. The results show that PoisonRec has the ability to achieve good attack performance on various recommender systems with limited knowledge.
Application of In Vivo Imaging Techniques for Monitoring Natural Killer Cell Migration and Tumor Infiltration

In recent years, the use of natural killer (NK) cell-based immunotherapy has shown promise against various cancer types. To some extent therapeutic potential of NK cell-based immunotherapy depends on migration of NK cells towards tumors in animal models or human subjects and subsequent infiltration. Constant improvement in the pharmacological and therapeutic properties of NK cells is driving the performance and use of NK cell-based immunotherapies. In this review, we summarize the molecular imaging techniques used in monitoring the migration and infiltration of NK cells in vivo at preclinical and clinical levels. A review of pros and cons of each molecular imaging modality is done. Finally, we provide our perception of the usefulness of molecular imaging approaches for in vivo monitoring of NK cells in preclinical and clinical scenarios.
In Vitro-Generated Hypertrophic-Like Adipocytes Displaying PPARG Isoforms Unbalance Recapitulate Adipocyte Dysfunctions In Vivo

Reduced neo-adipogenesis and dysfunctional lipid-overloaded adipocytes are hallmarks of hypertrophic obesity linked to insulin resistance. Identifying molecular features of hypertrophic adipocytes requires appropriate in vitro models. We describe the generation of a model of human hypertrophic-like adipocytes directly comparable to normal adipose cells and the pathologic evolution toward hypertrophic state. We generate in vitro hypertrophic cells from mature adipocytes, differentiated from human mesenchymal stem cells. Combining optical, confocal, and transmission electron microscopy with mRNA/protein quantification, we characterize this cellular model, confirming specific alterations also in subcutaneous adipose tissue. Specifically, we report the generation and morphological/molecular characterization of human normal and hypertrophic-like adipocytes. The latter displays altered morphology and unbalance between canonical and dominant negative (PPARGΔ5) transcripts of PPARG, paralleled by reduced expression of PPARγ targets, including GLUT4. Furthermore, the unbalance of PPARγ isoforms associates with GLUT4 down-regulation in subcutaneous adipose tissue of individuals with overweight/obesity or impaired glucose tolerance/type 2 diabetes, but not with normal weight or glucose tolerance. In conclusion, the hypertrophic-like cells described herein are an innovative tool for studying molecular dysfunctions in hypertrophic obesity and the unbalance between PPARγ isoforms associates with down-regulation of GLUT4 and other PPARγ targets, representing a new hallmark of hypertrophic adipocytes.
Preparation of Biphenyl-Conjugated Bromotyrosine for Inhibition of PD-1/PD-L1 Immune Checkpoint Interactions

Cancer immunotherapy has been revolutionized by the development of monoclonal antibodies (mAbs) that inhibit interactions between immune checkpoint molecules, such as programmed cell-death 1 (PD-1), and its ligand PD-L1. However, mAb-based drugs have some drawbacks, including poor tumor penetration and high production costs, which could potentially be overcome by small molecule drugs. BMS-8, one of the potent small molecule drugs, induces homodimerization of PD-L1, thereby inhibiting its binding to PD-1. Our assay system revealed that BMS-8 inhibited the PD-1/PD-L1 interaction with IC50 of 7.2 μM. To improve the IC50 value, we designed and synthesized a small molecule based on the molecular structure of BMS-8 by in silico simulation. As a result, we successfully prepared a biphenyl-conjugated bromotyrosine (X) with IC50 of 1.5 μM, which was about five times improved from BMS-8. We further prepared amino acid conjugates of X (amino-X), to elucidate a correlation between the docking modes of the amino-Xs and IC50 values. The results suggested that the displacement of amino-Xs from the BMS-8 in the pocket of PD-L1 homodimer correlated with IC50 values. This observation provides us a further insight how to derivatize X for better inhibitory effect.
A Study on the Effect of Macro- and Micro- Nutrients on Nannochloropsis oceanica Growth, Fatty Acid Composition and Magnetic Harvesting Efficiency

The effect of iron, manganese, phosphorus and nitrogen on growth and lipid synthesis of the microalgae Nannochloropsis oceanica CCMP1779, as well as their impact on the magnetic harvesting efficiency, are examined under their depriving cell culture conditions. Herein, it is demonstrated that nitrogen and manganese depletion primarily reduced cell growth while phosphorus and iron restriction led to higher dry biomass. Subsequently, the role of those nutrients on fatty acids profile was examined. Phosphorus and nitrogen restriction resulted in lower and higher lipid content, respectively. High amounts of polyunsaturated fatty acids like eicosapentaenoic acid are produced under iron and manganese depletion. Phosphorus deprivation favors monounsaturated fatty acids such as C18:1 and C16:1, while nitrogen restriction favors saturated fatty acid production like C14:0, C16:0 and C18:0. Since the presence/absence of macro- and micro-elements may affect the overall electrostatic charges on the outmost microalgae surface, it was also analyzed how these elements affect the magnetic harvesting efficiency. Results showed that phosphorus deprivation led to the best magnetic harvesting efficiency of N. oceanica cells (93%) as compared to other nutrient starvation as well as standard medium.
The Influence of Caerulomycin A on the Intestinal Microbiota in SD Rats

Caerulomycin A (CRM A) is the first example of natural caerulomycins with a 2,2′-bipyridyl ring core and 6-aldoxime functional group from Streptomyces caeruleus and recently from marine-derived Actinoalloteichus cyanogriseus WH1-2216-6. Our previous study revealed that CRM A showed anti-tumor activity against human colorectal cancer (CRC) both in vitro and in vivo. Because some intestinal flora can affect the occurrence and development of CRC, the influence of CRM A on the intestinal flora is worthy of study in Sprague–Dawley (SD) rats. The high throughput sequencing of the V3-V4 hypervariable region in bacterial 16S rDNA gene results showed that the CRM A affected the diversity of intestinal flora of the SD rats treated with CRM A for 2, 3 and 4 weeks. Further analysis indicated that the abundance of genera Prevotella_1, Prevotellaceae_UCG-001, and Lactobacillus were increased while the that of genera Alloprevotella and Ruminiclostridium_1 were decreased. For the CRC related intestinal flora, the abundance of genera Bacteroides, Fusobacterium, Enterococcus, Escherichia-Shigella, Klebsiella, Streptococcus, Ruminococcus_2, and Peptococcus of SD rats treated with CRM A were decreased, while that of abundance of genera Bifidobacterium, Lactobacillus, Faecalibacterium, Blautia, Oscillibacter, and Clostridium were increased. The results indicated that CRM A could influence the intestinal flora by inhibiting some species of harmful flora and improving the beneficial bacteria in intestinal flora in the SD rats. The results may provide a new idea for revealing the mechanism of the anti-CRC activity of CRM A.
Cysteine protease RD21A regulated by E3 ligase SINAT4 is required for drought-induced resistance to Pseudomonas syringae in Arabidopsis.

Plants can be simultaneously exposed to multiple stresses. The interplay of abiotic and biotic stresses may result in synergistic or antagonistic effects on plant development and health. Temporary drought stress can stimulate plant immunity; however, the molecular mechanism of drought-induced immunity is largely unknown. In this study, we demonstrate that cysteine protease RD21A is required for drought-induced immunity. Temporarily drought-treated wild type Arabidopsis plants become more sensitive to bacterial pathogen associated molecular pattern (PAMP), flg22, for triggering the stomatal closure, which results in increased resistance to Pseudomonas syringae pv. tomato DC3000 (Pst-DC3000). Knocking out rd21a inhibits the flg22-triggered stomatal closure and compromises the drought-induced immunity. Ubiquitin E3 ligase SINAT4 interacts with RD21A and promotes its degradation in vivo. The overexpression of SINAT4 also consistently compromised the drought-induced immunity to Pst-DC3000. A bacterial type III effector AvrRxo1 interacts with both SINAT4 and RD21A, enhancing SINAT4 activity, promoting the degradation of RD21A in vivo. Therefore, RD21A could be a positive regulator of drought-induced immunity, which can be targeted by pathogen virulence effectors during pathogenesis.
Antibiotic Substrate Selectivity of Pseudomonas aeruginosa MexY and MexB Efflux Systems Is Determined by a Goldilocks Affinity

Resistance-nodulation-division (RND) efflux pumps are important contributors to bacterial antibiotic resistance. In this study, we combined evolutionary sequence analyses, computational structural modeling, and ligand docking to develop a framework that can explain the known antibiotic substrate selectivity differences between two Pseudomonas aeruginosa RND transporters, MexY and MexB. For efficient efflux, antibiotic substrates must possess a “Goldilocks affinity”: binding strong enough to allow interaction with transporter but not so tight as to impede movement through the pump. ABSTRACT Resistance-nodulation-division (RND) efflux pumps are important contributors to bacterial antibiotic resistance. In this study, we combined evolutionary sequence analyses, computational structural modeling, and ligand docking to develop a framework that can explain the known antibiotic substrate selectivity differences between two Pseudomonas aeruginosa RND transporters, MexY and MexB. For efficient efflux, antibiotic substrates must possess a “Goldilocks affinity”: binding strong enough to allow interaction with transporter but not so tight as to impede movement through the pump.
Association between Periodontitis and High Blood Pressure: Results from the Study of Periodontal Health in Almada-Seixal (SoPHiAS)

Periodontitis is a common chronic inflammatory disease which could have an important impact on blood pressure (BP). This study aimed to explore (a) the association between periodontal health and BP in a large representative cohort, (b) the predictive value of diagnosis of periodontitis in undiagnosed raised BP and (c) whether age is a mediator of this relationship. In total, 1057 randomly recruited individuals (mean age, 60.9 ± 16.3 years, 57.7% women) underwent periodontal clinical assessment and one-single BP measurement using an automated sphygmomanometer device. Logistic and linear regression models were used to estimate the odds of hypertension based on periodontitis case definitions. Mediation analysis was performed to understand the effect of age on the association of periodontitis with hypertension. Adjusted logistic model for gender, smoking habits and body mass index confirmed the association between high BP and periodontitis (OR = 2.31, 95%CI: 1.75–3.04, p < 0.001). Among 168 participants with undiagnosed high BP (15.9% of the study sample), 62.5% had periodontitis (n = 105). In this study, the association between periodontitis with both systolic blood pressure (SBP) (77.6%, p < 0.001) and diastolic blood pressure (DBP) (66.0%, p < 0.001) was mediated by age. Periodontitis is closely linked to BP in a representative Portuguese population.
Cross-border spread of blaNDM-1- and blaOXA-48-positive Klebsiella pneumoniae: a European collaborative analysis of whole genome sequencing and epidemiological data, 2014 to 2019

Analysis of sequencing data for 143 blaNDM-1- and blaOXA-48-positive Klebsiella pneumoniae isolates from 13 European national collections and the public domain resulted in the identification of 15 previously undetected multi-country transmission clusters. For 10 clusters, cases had prior travel/hospitalisation history in countries outside of the European Union including Egypt, Iran, Morocco, Russia, Serbia, Tunisia and Turkey. These findings highlight the benefit of European whole genome sequencing-based surveillance and data sharing for control of antimicrobial resistance.
Effects of Additional Mg2+ on the Growth and Lipid Accumulation of Monoraphidium Sp. FXY-10 under Mixotrophic Conditions

The effects of additional Mg2+ on the growth and lipid accumulation of the microalgae Monoraphidium sp. FXY-10 under mixotrophic conditions were investigated. 100 μmol Mg2+ were added to the growth media during the stationary growth phase. Compared with the control (35.25%), the highest lipid content reached up to 37.13% biomass after Mg2+ was added to the media. Moreover, the higher lipid productivity of 79.83 mg L1 d1 and the biomass productivity of 214.65 mg L1 d1 were attained in the Mg2+-supplemented cultures, as compared with cultures without supplemented (72.95 mg L1 d1 and 179.28 mg L1 d1, respectively). The use of Mg2+ supplements were proven to stimulate cell regrowth, prolong the stationary phase, and promote lipid accumulation in Monoraphidium sp. FXY-10.
DIRECT DIELECTRIC BARRIER DISCHARGE IONIZATION PROMOTES RAPID AND SIMPLE LUBRICANT OIL FINGERPRINTING.

Petroleomics, which is the characterization, separation and quantification of the components of petroleum and crude oil, is an emerging area of study. However, the repertoire of analytical methods available to understand commercial automotive lubricant oils (ALOs) is very limited. Ambient mass spectrometry is one of the most sensitive analytical methods for real-time and in situ chemical analysis. With this technique, the chemical fingerprinting of ALOs can be performed quickly and simply using dielectric barrier discharge ionization time-of-flight mass spectrometry (DBDI-TOFMS). The mass spectra of thirty-five samples were obtained without any sample preparation or extraction in positive ion mode, and no carryover was observed. To elucidate the similarities and differences between the ALO samples, the data generated from these spectra were analyzed using four chemometric techniques: principal component analysis (PCA), multivariate curve resolution (MCR), hierarchical cluster analysis (HCA), and Pattern Recognition Entropy (PRE). The ALO samples were readily differentiated according to their American Petroleum Institute (API) classification and base oil types: mineral, semi-synthetic, and synthetic. The development of this new methodology will aid in the semi-quantitative control analysis of ALOs and offers an improved ability to identify the components therein.
A dynamic bayesian network approach for electro-optical system performance monitoring digital twin

This paper proposes a digital twin model based on dynamic Bayesian network (DBN) for the electro-optical system for its performance monitoring. In this model, a system-level performance indicator from the perspective of the energy domain using Modulation Transfer Function (MTF) is first developed, which avoids tedious modeling of performance interactions between the multiple subsystems of the electro-optical system. Then, a DBN is constructed from the evolution of MTF to denote the dynamic performance degradation process and the propagation of epistemic uncertainty. In order to make the digital twin model capable of tracking and predicting the system performance states, an improved Gaussian particle fdter with kernel smoothing (GPF-KS) is proposed as the inference algorithm for DBN. A real dataset collected in the laboratory environment is used to validate the feasibility of the digital twin model and verify the effectiveness of the GPF-KS inference algorithm. The results show that our method is effective forjoint estimation of states andparameters, leading to reliable estimation andprediction of the electro-optical system on-line health-status.