Miracle-dz/UniFAR-FTUs huggingface dataset:
Pentose Phosphate Pathway Reactions in Photosynthesizing Cells

The pentose phosphate pathway (PPP) is divided into an oxidative branch that makes pentose phosphates and a non-oxidative branch that consumes pentose phosphates, though the non-oxidative branch is considered reversible. A modified version of the non-oxidative branch is a critical component of the Calvin–Benson cycle that converts CO2 into sugar. The reaction sequence in the Calvin–Benson cycle is from triose phosphates to pentose phosphates, the opposite of the typical direction of the non-oxidative PPP. The photosynthetic direction is favored by replacing the transaldolase step of the normal non-oxidative PPP with a second aldolase reaction plus sedoheptulose-1,7-bisphosphatase. This can be considered an anabolic version of the non-oxidative PPP and is found in a few situations other than photosynthesis. In addition to the strong association of the non-oxidative PPP with photosynthesis metabolism, there is recent evidence that the oxidative PPP reactions are also important in photosynthesizing cells. These reactions can form a shunt around the non-oxidative PPP section of the Calvin–Benson cycle, consuming three ATP per glucose 6-phosphate consumed. A constitutive operation of this shunt occurs in the cytosol and gives rise to an unusual labeling pattern of photosynthetic metabolites while an inducible shunt in the stroma may occur in response to stress.
Assessing Automated Facial Action Unit Detection Systems for Analyzing Cross-Domain Facial Expression Databases

In the field of affective computing, achieving accurate automatic detection of facial movements is an important issue, and great progress has already been made. However, a systematic evaluation of systems that now have access to the dynamic facial database remains an unmet need. This study compared the performance of three systems (FaceReader, OpenFace, AFARtoolbox) that detect each facial movement corresponding to an action unit (AU) derived from the Facial Action Coding System. All machines could detect the presence of AUs from the dynamic facial database at a level above chance. Moreover, OpenFace and AFAR provided higher area under the receiver operating characteristic curve values compared to FaceReader. In addition, several confusion biases of facial components (e.g., AU12 and AU14) were observed to be related to each automated AU detection system and the static mode was superior to dynamic mode for analyzing the posed facial database. These findings demonstrate the features of prediction patterns for each system and provide guidance for research on facial expressions.
Spark Analysis Based on the CNN-GRU Model for WEDM Process

Wire electrical discharge machining (WEDM), widely used to fabricate micro and precision parts in manufacturing industry, is a nontraditional machining method using discharge energy which is transformed into thermal energy to efficiently remove materials. A great amount of research has been conducted based on pulse characteristics. However, the spark image-based approach has little research reported. This paper proposes a discharge spark image-based approach. A model is introduced to predict the discharge status using spark image features through a synchronous high-speed image and waveform acquisition system. First, the relationship between the spark image features (e.g., area, energy, energy density, distribution, etc.) and discharge status is explored by a set of experiments). Traditional methods have claimed that pulse waveform of “short” status is related to the status of non-machining while through our research, it is concluded that this is not always true by conducting experiments based on the spark images. Second, a deep learning model based on Convolution neural network (CNN) and Gated recurrent unit (GRU) is proposed to predict the discharge status. A time series of spark image features extracted by CNN form a 3D feature space is used to predict the discharge status through GRU. Moreover, a quantitative labeling method of machining state is proposed to improve the stability of the model. Due the effective features and the quantitative labeling method, the proposed approach achieves better predict result comparing with the single GRU model.
Regulatory SNPs: Altered Transcription Factor Binding Sites Implicated in Complex Traits and Diseases

The vast majority of the genetic variants (mainly SNPs) associated with various human traits and diseases map to a noncoding part of the genome and are enriched in its regulatory compartment, suggesting that many causal variants may affect gene expression. The leading mechanism of action of these SNPs consists in the alterations in the transcription factor binding via creation or disruption of transcription factor binding sites (TFBSs) or some change in the affinity of these regulatory proteins to their cognate sites. In this review, we first focus on the history of the discovery of regulatory SNPs (rSNPs) and systematized description of the existing methodical approaches to their study. Then, we brief the recent comprehensive examples of rSNPs studied from the discovery of the changes in the TFBS sequence as a result of a nucleotide substitution to identification of its effect on the target gene expression and, eventually, to phenotype. We also describe state-of-the-art genome-wide approaches to identification of regulatory variants, including both making molecular sense of genome-wide association studies (GWAS) and the alternative approaches the primary goal of which is to determine the functionality of genetic variants. Among these approaches, special attention is paid to expression quantitative trait loci (eQTLs) analysis and the search for allele-specific events in RNA-seq (ASE events) as well as in ChIP-seq, DNase-seq, and ATAC-seq (ASB events) data.
COVID-19 Vaccine Acceptance in Azuay Province, Ecuador: A Cross-Sectional Online Survey

We investigated the COVID-19 vaccination acceptance level in Azuay province, Ecuador through an online survey from 12th to 26th February (before the start of the COVID-19 vaccination campaign in Ecuador). Overall, 1219 respondents participated in the survey. The mean age was 32 ± 13 years; 693 participants (57%) were female. In total, 1109 (91%) of the participants indicated they were willing to be vaccinated with a COVID-19 vaccine, if the vaccine is at least 95% effective; 835 (68.5%) if it is 90% effective and 493 (40.5%) if it is 70% effective; 676 (55.5%) participants indicated they feared side effects and 237 (19.4%) thought the vaccine was not effective. Older age, having had a postgraduate education, a history of a negative COVID-19 test, a high level of worry of contracting COVID-19, believing that COVID-19 infection can be prevented with a vaccine and understanding there is currently an effective vaccine against COVID-19 were associated with higher vaccination acceptance. A vaccination education campaign will be needed to increase the knowledge of Ecuadorians about the COVID-19 vaccine and to increase their trust in the vaccine. People with a lower education level and living in rural areas may need to be targeted during such a campaign.
A Comprehensive Review and Perspective on Natural Sources as Dipeptidyl Peptidase-4 Inhibitors for Management of Diabetes

Type 2 diabetes mellitus (T2DM) is an increasing global public health problem, and its prevalence is expected to rise in coming decades. Dipeptidyl peptidase-4 (DPP-4) is a therapeutic target for the management of T2DM, and its inhibitors prevent the degradation of glucose-dependent insulinotropic peptide and glucagon-like peptide 1, and thus, maintain their endogenous levels and lower blood glucose levels. Various medicinal plant extracts and isolated bioactive compounds exhibit DPP-4 inhibitory activity. In this review, we discussed different natural sources that have been shown to have anti-diabetic efficacy with a particular emphasis on DPP-4 inhibition. Furthermore, the effect of DPP-4 inhibition on pancreatic beta cell function, skeletal muscle function, and the glucose-lowering mechanisms were also discussed. We believe that scientists looking for novel compounds with therapeutic promise against T2DM will be able to develop antidiabetic drugs using these natural sources.
Potential Use of Gut Microbiota Composition as a Biomarker of Heat Stress in Monogastric Species: A Review

Simple Summary Heat stress is a significant environmental challenge faced by food animal production worldwide because of its adverse effects on animal performance and productivity. Trillions of microorganisms living in the gut are essential for host health by participating in various digestive, immune, and metabolic activities. At the same time, they are known to be sensitive to changes in the surrounding environment. The present review summarizes current research progress of how the gut microbial community responds to elevated ambient heat in monogastric animal species and discusses the use of the gut microbiota composition as a potential indicator for heat stress. Abstract Heat stress is a current challenge for livestock production, and its impact could dramatically increase if global temperatures continue to climb. Exposure of agricultural animals to high ambient temperatures and humidity would lead to substantial economic losses because it compromises animal performance, productivity, health, and welfare. The gut microbiota plays essential roles in nutrient absorption, energy balance, and immune defenses through profound symbiotic interactions with the host. The homeostasis of those diverse gut microorganisms is critical for the host’s overall health and welfare status and also is sensitive to environmental stressors, like heat stress, reflected in altered composition and functionality. This article aims to summarize the research progress on the interactions between heat stress and gut microbiome and discuss the potential use of the gut microbiota composition as a biomarker of heat stress in monogastric animal species. A comprehensive understanding of the gut microbiota’s role in responding to or regulating physiological activities induced by heat stress would contribute to developing mitigation strategies.
Energy-Constrained Design of Joint NOMA-Diversity Schemes with Imperfect Interference Cancellation

This study proposes a set of novel random access protocols combining Packet Repetition (PR) schemes, such as Contention Resolution Diversity Slotted Aloha (CRDSA) and Irregular Repetition SA (IRSA), with Non Orthogonal Multiple Access (NOMA). Differently from previous NOMA/CRDSA and NOMA/IRSA proposals, this work analytically derives the energy levels considering two realistic elements: the residual interference due to imperfect Interference Cancellation (IC), and the presence of requirements on the power spent for the transmission. More precisely, the energy-limited scenario is based on the relationship between the average available energy and the selected code modulation pair, thus being of specific interest for the implementation of the Internet of Things (IoT) technology in forthcoming fifth-generation (5G) systems. Moreover, a theoretical model based on the density evolution method is developed and numerically validated by extensive simulations to evaluate the limiting throughput and to explore the actual performance of different NOMA/PR schemes in energy-constrained scenarios.
Exhaled Breath Condensate—A Non-Invasive Approach for Diagnostic Methods in Asthma

The pathophysiology of asthma has been intensively studied, but its underlying mechanisms such as airway inflammation, control of airway tone, and bronchial reactivity are still not completely explained. There is an urgent need to implement novel, non-invasive diagnostic tools that can help to investigate local airway inflammation and connect the molecular pathways with the broad spectrum of clinical manifestations of asthma. The new biomarkers of different asthma endotypes could be used to confirm diagnosis, predict asthma exacerbations, or evaluate treatment response. In this paper, we briefly describe the characteristics of exhaled breath condensate (EBC) that is considered to be an interesting source of biomarkers of lung disorders. We look at the composition of EBC, some aspects of the collection procedure, the proposed biomarkers for asthma, and its clinical implications. We also indicate the limitations of the method and potential strategies to standardize the procedure of EBC collection and analytical methods.
Development of an Intelligent Data-Driven System to Recommend Personalized Fashion Design Solutions

In the context of fashion/textile innovations towards Industry 4.0, a variety of digital technologies, such as 3D garment CAD, have been proposed to automate, optimize design and manufacturing processes in the organizations of involved enterprises and supply chains as well as services such as marketing and sales. However, the current digital solutions rarely deal with key elements used in the fashion industry, including professional knowledge, as well as fashion and functional requirements of the customer and their relations with product technical parameters. Especially, product design plays an essential role in the whole fashion supply chain and should be paid more attention to in the process of digitalization and intelligentization of fashion companies. In this context, we originally developed an interactive fashion and garment design system by systematically integrating a number of data-driven services of garment design recommendation, 3D virtual garment fitting visualization, design knowledge base, and design parameters adjustment. This system enables close interactions between the designer, consumer, and manufacturer around the virtual product corresponding to each design solution. In this way, the complexity of the product design process can drastically be reduced by directly integrating the consumer’s perception and professional designer’s knowledge into the garment computer-aided design (CAD) environment. Furthermore, for a specific consumer profile, the related computations (design solution recommendation and design parameters adjustment) are performed by using a number of intelligent algorithms (BIRCH, adaptive Random Forest algorithms, and association mining) and matching with a formalized design knowledge base. The proposed interactive design system has been implemented and then exposed through the REST API, for designing garments meeting the consumer’s personalized fashion requirements by repeatedly running the cycle of design recommendation—virtual garment fitting—online evaluation of designer and consumer—design parameters adjustment—design knowledge base creation, and updating. The effectiveness of the proposed system has been validated through a business case of personalized men’s shirt design.
Water Extract of Rubus coreanus Prevents Inflammatory Skin Diseases In Vitro Models

Atopic dermatitis (AD) is a chronic inflammatory skin disease caused by immune hypersensitivity reaction. The cause of AD is unclear, but its symptoms have a negative effect on quality of life; various treatment methods to alleviate these symptoms are underway. In the present study, we aimed to evaluate in vitro antioxidant and anti-inflammatory effects of Rubus coreanus water extract (RCW) on AD. Total phenolic compounds and flavonoid content of RCW were 4242.40 ± 54.84 mg GAE/g RCE and 1010.99 ± 14.75 mg CE/g RCW, respectively. RCW reduced intracellular reactive oxygen species level and increased the action of antioxidant enzymes, such as catalase, superoxide dismutase, and glutathione peroxidase in tumor necrosis factor-α (TNF-α)/interferon-γ (IFN-γ)-stimulated HaCaT cells. Moreover, mRNA expression of the pro-inflammatory cytokines, including TNF-α, interleukin-1β, and interleukin-6, was downregulated by RCW in the TNF-α/IFN-γ-stimulated cells. The levels of inflammatory chemokines (thymus- and activation-regulated chemokine; eotaxin; macrophage-derived chemokine; regulated on activation, normal T-cell expressed and secreted; and granulocyte-macrophage colony-stimulating factor) and intercellular adhesion molecule-1 were decreased in the TNF-α/IFN-γ-stimulated HaCaT cells after RCW treatment. Additionally, the mRNA expression levels of filaggrin and involucrin, proteins that form the skin, were increased by RCW. Furthermore, RCW inhibited the nuclear factor kappa-light-chain-enhancer of the activated B cells pathway in the TNF-α/IFN-γ-stimulated HaCaT cells. Collectively, the present investigation indicates that RCW is a potent substance that inhibits AD.
Transient Reduction of FMD-Response and L-Arginine Accompanied by Increased Levels of E-Selectin, VCAM, and ICAM after Prolonged Strenuous Exercise

We assessed endothelial function by flow-mediated dilatation (FMD), levels of the NO-precursor L-arginine, and markers of endothelial inflammation before, at the finish line, and one week after the Norseman Xtreme triathlon. The race is an Ironman distance triathlon with a total elevation of 5200 m. Nine male participants were included. They completed the race in 14.5 (13.4–15.3) h. FMD was significantly reduced to 3.1 (2.1–5.0)% dilatation compared to 8.7 (8.2–9.3)% dilatation before the race (p < 0.05) and was normalized one week after the race. L-arginine showed significantly reduced levels at the finish line (p < 0.05) but was normalized one week after the race. Markers of endothelial inflammation E-Selectin, VCAM-1, and ICAM-1 all showed a pattern with increased values at the finish line compared to before the race (all p < 0.05), with normalization one week after the race. In conclusion, we found acutely reduced FMD with reduced L-arginine levels and increased E-Selectin, VCAM-1, and ICAM-1 immediately after the Norseman Xtreme triathlon. Our findings indicate a transient reduced endothelial function, measured by the FMD-response, after prolonged strenuous exercise that could be explained by reduced NO-precursor L-arginine levels and increased endothelial inflammation.
What We Know So Far about the Metabolite-Mediated Microbiota-Intestinal Immunity Dialogue and How to Hear the Sound of This Crosstalk

Trillions of microorganisms, termed the “microbiota”, reside in the mammalian gastrointestinal tract, and collectively participate in regulating the host phenotype. It is now clear that the gut microbiota, metabolites, and intestinal immune function are correlated, and that alterations of the complex and dynamic host-microbiota interactions can have deep consequences for host health. However, the mechanisms by which the immune system regulates the microbiota and by which the microbiota shapes host immunity are still not fully understood. This article discusses the contribution of metabolites in the crosstalk between gut microbiota and immune cells. The identification of key metabolites having a causal effect on immune responses and of the mechanisms involved can contribute to a deeper insight into host-microorganism relationships. This will allow a better understanding of the correlation between dysbiosis, microbial-based dysmetabolism, and pathogenesis, thus creating opportunities to develop microbiota-based therapeutics to improve human health. In particular, we systematically review the role of soluble and membrane-bound microbial metabolites in modulating host immunity in the gut, and of immune cells-derived metabolites affecting the microbiota, while discussing evidence of the bidirectional impact of this crosstalk. Furthermore, we discuss the potential strategies to hear the sound of such metabolite-mediated crosstalk.
The Role of Th17 Response in COVID-19

COVID-19 is an acute infectious disease of the respiratory system caused by infection with the SARS-CoV-2 virus (Severe Acute Respiratory Syndrome Coronavirus 2). Transmission of SARS-CoV-2 infections occurs through droplets and contaminated objects. A rapid and well-coordinated immune system response is the first line of defense in a viral infection. However, a disturbed and over-activated immune response may be counterproductive, causing damage to the body. Severely ill patients hospitalised with COVID-19 exhibit increased levels of many cytokines, including Interleukin (IL)-1β, IL-2, IL-6, IL-7, IL-8, IL-10, IL-17, granulocyte colony stimulating factor (G-CSF), monocyte chemoattractant protein 1 (MCP-1) and tumor necrosis factor (TNF). Increasing evidence suggests that Th17 cells play an important role in the pathogenesis of COVID-19, not only by activating cytokine cascade but also by inducing Th2 responses, inhibiting Th1 differentiation and suppressing Treg cells. This review focuses on a Th17 pathway in the course of the immune response in COVID-19, and explores plausible targets for therapeutic intervention.
Patterns of Oral Microbiota in Patients with Apical Periodontitis

In this study, microbial diversity of the root canal microbiota related to different endodontic infections was investigated. In total, 45 patients with endo–perio lesions (8 patients), chronic periapical periodontitis (29 patients) and pulp necrosis (8 patients) were recruited. In 19 (42.2%) patients there was secondary infection of root canals. Microbial specimens were collected from root canals of non-vital teeth with or without changes in periapical area visible in X-ray. Then, oral microbiota were detected and identified using the culture method and real-time PCR amplification primers and hydrolysis-probe detection with the 16S rRNA gene as the target. Overall, 1434 species/genes from 41 different genera of 90 various microbial species were retrieved. Of the major reported phyla, Firmicutes (62.9%), Actinobacteria (14.0%), Bacteroidetes (12.1%), Proteobacteria (9.1%) and Fusobacteria (4.2%) were detected. Of the bacterial species, 54.6% were strict anaerobes. Corynebacterium matruchotii (p = 0.039) was present significantly more frequently in chronic periapical periodontitis. Moreover, the higher values of Decayed, Missing and Filled Permanent Teeth index were positively correlated with relative abundance of Actinomyces spp. (p = 0.042), Lactobacillus spp. (p = 0.006), Propionibacterium spp. (p = 0.024) and Rothia spp. (p = 0.002). The multivariate analyses revealed differences in total root canal samples, where components that affected grouping of root samples into four main categories were identified. Anaerobic Gram-negative bacteria predominated in root canals of teeth with pulp necrosis and periapical lesions. Facultative anaerobic Gram-positive bacteria predominated in canals with secondary infections. All detected members of mixed population groups that might serve as keystone species contributed to the entire community in its clinical relevance.