Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of "Chelavite" Mineral Supplement Use on Cadmium and Lead Content in Blood, Wool and Milk of Heavy Cows

The purpose of this research was to study the influence of this supplement use on the concentration of cadmium and lead in blood serum, wool and milk of heavy cows. The cows of milking herd of black-and-white breed, of 3-5 years old were the object of research. Their yearly milk production was 6 thousand litters (control and experimental group, each having 15 heads). The cows have been fed according to the balanced ration for heavy cows. The mineral supplement dose was determined according to the instruction for application for cows of experimental group with feed. The curative dose was 0.6 ml for 10 kg of body mass 1 time a day during 30 days. The samples were taken before giving the mineral supplement “Chelavite” and after the course had finished. The device Unicam AAS-939 was used to determine the cadmium and lead content in blood, wool and milk by way of atomic absorption spectrophotometry. It has been found that the cadmium level reduced by 2.35 times, the lead level reduced by 1,5 times in cows blood, the cadmium level reduced by 1.33 times, the lead level reduced by 4.34 times in cows wool, the cadmium level reduced by 2.2 times, the lead level reduced by 3.7 times in cows milk after giving them mineral supplement “Chelavite”. Thus, the application of chelate compounds in form of “Chelavite” for cows reduces concentration of heavy metals such as cadmium and lead. Then this is one of the ways to improve the milk quality.
Training Restricted Boltzmann Machines With a D-Wave Quantum Annealer

Restricted Boltzmann Machine (RBM) is an energy-based, undirected graphical model. It is commonly used for unsupervised and supervised machine learning. Typically, RBM is trained using contrastive divergence (CD). However, training with CD is slow and does not estimate the exact gradient of the log-likelihood cost function. In this work, the model expectation of gradient learning for RBM has been calculated using a quantum annealer (D-Wave 2000Q), where obtaining samples is faster than Markov chain Monte Carlo (MCMC) used in CD. Training and classification results of RBM trained using quantum annealing are compared with the CD-based method. The performance of the two approaches is compared with respect to the classification accuracies, image reconstruction, and log-likelihood results. The classification accuracy results indicate comparable performances of the two methods. Image reconstruction and log-likelihood results show improved performance of the CD-based method. It is shown that the samples obtained from quantum annealer can be used to train an RBM on a 64-bit “bars and stripes” dataset with classification performance similar to an RBM trained with CD. Though training based on CD showed improved learning performance, training using a quantum annealer could be useful as it eliminates computationally expensive MCMC steps of CD.
Single-Cell RNA Sequencing Analysis of Chicken Anterior Pituitary: A Bird’s-Eye View on Vertebrate Pituitary

It is well-established that anterior pituitary contains multiple endocrine cell populations, and each of them can secrete one/two hormone(s) to regulate vital physiological processes of vertebrates. However, the gene expression profiles of each pituitary cell population remains poorly characterized in most vertebrate groups. Here we analyzed the transcriptome of each cell population in adult chicken anterior pituitaries using single-cell RNA sequencing technology. The results showed that: (1) four out of five known endocrine cell clusters have been identified and designated as the lactotrophs, thyrotrophs, corticotrophs, and gonadotrophs, respectively. Somatotrophs were not analyzed in the current study. Each cell cluster can express at least one known endocrine hormone, and novel marker genes (e.g., CD24 and HSPB1 in lactotrophs, NPBWR2 and NDRG1 in corticotrophs; DIO2 and SOUL in thyrotrophs, C5H11ORF96 and HPGDS in gonadotrophs) are identified. Interestingly, gonadotrophs were shown to abundantly express five peptide hormones: FSH, LH, GRP, CART and RLN3; (2) four non-endocrine/secretory cell types, including endothelial cells (expressing IGFBP7 and CFD) and folliculo-stellate cells (FS-cells, expressing S100A6 and S100A10), were identified in chicken anterior pituitaries. Among them, FS-cells can express many growth factors, peptides (e.g., WNT5A, HBEGF, Activins, VEGFC, NPY, and BMP4), and progenitor/stem cell-associated genes (e.g., Notch signaling components, CDH1), implying that the FS-cell cluster may act as a paracrine/autocrine signaling center and enrich pituitary progenitor/stem cells; (3) sexually dimorphic expression of many genes were identified in most cell clusters, including gonadotrophs and lactotrophs. Taken together, our data provides a bird’s-eye view on the diverse aspects of anterior pituitaries, including cell composition, heterogeneity, cell-to-cell communication, and gene expression profiles, which facilitates our comprehensive understanding of vertebrate pituitary biology.
Evaluation of Septoria Nodorum Blotch (SNB) Resistance in Glumes of Wheat (Triticum aestivum L.) and the Genetic Relationship With Foliar Disease Response

Septoria nodorum blotch (SNB) is a necrotrophic disease of wheat prominent in some parts of the world, including Western Australia (WA) causing significant losses in grain yield. The genetic mechanisms for resistance are complex involving multiple quantitative trait loci. In order to decipher comparable or independent regulation, this study identified the genetic control for glume compared to foliar resistance across four environments in WA against 37 different isolates. High proportion of the phenotypic variation across environments was contributed by genotype (84.0% for glume response and 82.7% for foliar response) with genotype-by-environment interactions accounting for a proportion of the variation for both glume and foliar response (14.7 and 16.2%, respectively). Despite high phenotypic correlation across environments, most of the eight and 14 QTL detected for glume and foliar resistance using genome wide association analysis (GWAS), respectively, were identified as environment-specific. QTL for glume and foliar resistance neither co-located nor were in LD in any particular environment indicating autonomous genetic mechanisms control SNB response in adult plants, regulated by independent biological mechanisms and influenced by significant genotype-by- environment interactions. Known Snn and Tsn loci and QTL were compared with 22 environment-specific QTL. None of the eight QTL for glume or the 14 for foliar response were co-located or in linkage disequilibrium with Snn and only one foliar QTL was in LD with Tsn loci on the physical map. Therefore, glume and foliar response to SNB in wheat is regulated by multiple environment-specific loci which function independently, with limited influence of known NE-Snn interactions for disease progression in Western Australian environments. Breeding for stable resistance would consequently rely on recurrent phenotypic selection to capture and retain favorable alleles for both glume and foliar resistance relevant to a particular environment.
Parent and Child Reports of Parenting Behaviors: Agreement Among a Longitudinal Study of Drug Court Participants

Identifying ways to support children of parents with substance use disorder is a critical public health issue. This study focused on the parent-child relationship as a critical catalyst in child resilience. Using data from a longitudinal cohort study, the aims of this study were to: (1 ) examine the agreement between parent and child reports of parenting behaviors and (2 ) describe the association between agreement and child mental health. Participants were 50 parent-child dyads that included parents enrolled in an adult drug court and their children, aged 8–18. Overall, agreement (i.e., concordance) between parent and child reports of parenting was slight to fair. Parents reported their parenting behaviors to be slightly more positive than how children rated the same behaviors in the areas of: involvement, 0.53 (SD = 0.80); positive parenting, 0.66 (SD = 0.87), and monitoring behaviors, 0.46 (SD = 0.90). Parents also rated themselves, in comparison to their children's reports, as using less inconsistent discipline, −0.33 (SD = 1.00), and less corporal punishment, 0.13 (SD = 1.01). Agreement was related to some, but not all, child mental health outcomes. When parents rating their parenting as more positive than their child reported, that had a negative effect on child self-esteem and personal adjustment. Contrary to hypotheses, we did not find a significant relationship between positive parenting and internalizing problems. Findings have implications for obtaining parent and child reports of parenting within the drug court system, and for identifying children at higher risk for externalizing problems.
Keeping the Breath in Mind: Respiration, Neural Oscillations, and the Free Energy Principle

Scientific interest in the brain and body interactions has been surging in recent years. One fundamental yet underexplored aspect of brain and body interactions is the link between the respiratory and the nervous systems. In this article, we give an overview of the emerging literature on how respiration modulates neural, cognitive and emotional processes. Moreover, we present a perspective linking respiration to the free-energy principle. We frame volitional modulation of the breath as an active inference mechanism in which sensory evidence is recontextualized to alter interoceptive models. We further propose that respiration-entrained gamma oscillations may reflect the propagation of prediction errors from the sensory level up to cortical regions in order to alter higher level predictions. Accordingly, controlled breathing emerges as an easily accessible tool for emotional, cognitive, and physiological regulation.
The Complete Mitochondrial DNA of Trypanosoma cruzi: Maxicircles and Minicircles

The mitochondrial DNA of Trypanosomatids, known as the kinetoplast DNA or kDNA or mtDNA, consists of a few maxicircles and thousands of minicircles concatenated together into a huge complex network. These structures present species-specific sizes, from 20 to 40 Kb in maxicircles and from 0.5 to 10 Kb in minicircles. Maxicircles are equivalent to other eukaryotic mitochondrial DNAs, while minicircles contain coding guide RNAs involved in U-insertion/deletion editing processes exclusive of Trypanosomatids that produce the maturation of the maxicircle-encoded transcripts. The knowledge about this mitochondrial genome is especially relevant since the expression of nuclear and mitochondrial genes involved in oxidative phosphorylation must be coordinated. In Trypanosoma cruzi (T. cruzi), the mtDNA has a dual relevance; the production of energy, and its use as a phylogenetic marker due to its high conservation among strains. Therefore, this study aimed to assemble, annotate, and analyze the complete repertoire of maxicircle and minicircle sequences of different T. cruzi strains by using DNA sequencing. We assembled and annotated the complete maxicircle sequence of the Y and Bug2148 strains. For Bug2148, our results confirm that the maxicircle sequence is the longest assembled to date, and is composed of 21 genes, most of them conserved among Trypanosomatid species. In agreement with previous results, T. cruzi minicircles show a conserved structure around 1.4 Kb, with four highly conserved regions and other four hypervariable regions interspersed between them. However, our results suggest that the parasite minicircles display several sizes and numbers of conserved and hypervariable regions, contrary to those previous studies. Besides, this heterogeneity is also reflected in the three conserved sequence blocks of the conserved regions that play a key role in the minicircle replication. Our results using sequencing technologies of second and third-generation indicate that the different consensus sequences of the maxicircles and minicircles seem to be more complex than previously described indicating at least four different groups in T. cruzi minicircles.
Improved Smart Pseudoscopic-to-Orthoscopic Conversion Algorithm for Integral Imaging With Pixel Information Averaging

The smart pseudoscopic-to-orthoscopic conversion (SPOC) algorithm can synthesize a new elemental image array (EIA) using the already captured EIA, but the algorithm only relies on one simulated ray to establish the mapping relationship between the display pixels and the synthetic pixels. This paper improves the SPOC algorithm and proposes the average SPOC algorithm, which fully considers the converging effect of the synthetic lens on the ray. In the average SPOC algorithm, the simulated rays start from the synthetic pixel, pass through the upper and lower edges of the corresponding synthetic lens, and intersect the display lenses, respectively. Then, the value of the synthetic pixel is equivalent to the average value of display pixels, which correspond to the display lenses covered by the rays. Theoretical analysis points out that the average SPOC algorithm can effectively alleviate the matching error between the display pixels and the synthetic pixels, thereby improving the accuracy of the synthetic elemental image array (SEIA) and the reconstruction effect. According to the experimental results we get, the superiority of the average SPOC algorithm is verified.
Quantitative Monitoring of Bolt Looseness Using Multichannel Piezoelectric Active Sensing and CBAM-Based Convolutional Neural Network

The bolted connection is widely utilized in engineering to practically and rigidly couple structural components. The integrity of the connection is paramount to the safety of the structure and has prompted the development of many monitoring methods, including the piezoelectricity-based active sensing method. However, the active sensing method cannot quantify bolt looseness due to the unclear relationship between bolt looseness and the single monitoring index typically used in the active sensing method. Thus, the authors propose the unique combination of a one-dimensional convolutional neural network (1DCNN) and multichannel active sensing for quantitative monitoring of bolted connections. In an experiment, piezoelectric ceramic transducer (PZT) patches are bonded on steel plates connected by a bolt. Each patch is wired to a multichannel active sensing monitoring system. After obtaining multichannel stress wave signals at different looseness levels, a looseness vector is calculated to generate training and validation datasets. A baseline 1DCNN model and a novel model improved using the convolutional block attention module (CBAM) are used to monitor the bolt looseness. Finally, the authors verify that the multichannel active sensing method combined with the 1DCNN model can accurately perform quantitative monitoring of bolt looseness, and the monitoring accuracy of the baseline 1DCNN model is above 91.07% in three different specimens. Compared with the baseline 1DCNN model, the monitoring accuracy of the CBAMCNN model improved by approximately 5%. Overall, the method proposed in this article offers a new and highly accurate approach for quantitative monitoring of bolted connections.
Message Design Choices Don't Make Much Difference to Persuasiveness and Can't Be Counted On—Not Even When Moderating Conditions Are Specified

Persuaders face many message design choices: narrative or non-narrative format, gain-framed or loss-framed appeals, one-sided or two-sided messages, and so on. But a review of 1,149 studies of 30 such message variations reveals that, although there are statistically significant differences in persuasiveness between message forms, it doesn't make much difference to persuasiveness which option is chosen (as evidenced by small mean effect sizes, that is, small differences in persuasiveness: median mean rs of about 0.10); moreover, choosing the on-average-more-effective option does not consistently confer a persuasive advantage (as evidenced by 95% prediction intervals that include both positive and negative values). Strikingly, these results obtain even when multiple moderating conditions are specified. Implications for persuasive message research and practice are discussed.
Connecting Metabolism to Mastitis: Hyperketonemia Impaired Mammary Gland Defenses During a Streptococcus uberis Challenge in Dairy Cattle

β-hydroxybutyrate (BHB) has been associated with disease incidence in early lactation dairy cattle, but such associations do not demonstrate causation. Therefore, the objective of this study was to examine the effects of BHB during an intramammary Streptococcus uberis challenge. A secondary objective was to elucidate the mechanisms behind BHB effects on cytokine transcript abundance using the RAW 264.7 cell line. Late lactation multiparous dairy cows (n = 12) were continuously infused intravenously with either BHB to induce hyperketonemia (target concentration: 1.8 mM) or with saline (CON) for 72 h during a S. uberis intramammary challenge. Body temperature, dry matter intake (DMI), milk production, and milk S. uberis cfu were measured daily until one week post-challenge. Blood samples were collected during infusion to assess changes in metabolism (glucose, insulin, glucagon, NEFA, and cortisol) and systemic inflammation (IL-1β and SAA). Mammary biopsies were conducted at 72 h post-challenge to assess transcript abundance of inflammation-associated genes. BHB-infused cows exhibited a delayed febrile response, noted by a lesser vaginal temperature during the final day of infusion, followed by a greater vaginal temperature 6 d post-challenge. Consequently, BHB-infused cows had greater S. uberis cfu on d 4, 6, and 7 as compared to CON. Accordingly, BHB-infused cows consumed less DM, produced less milk, had reduced blood glucose, and had increased cortisol concentrations, however, no effects were seen on other systemic parameters or transcript abundance of inflammation-related genes in mammary tissue. To elucidate mechanisms behind the impaired immune defenses, RAW 264.7 cells were transfected with a GPR109A siRNA for 24 h and then treated with or without 1.8 mM BHB and challenged or left unchallenged with S. uberis for an additional 3 h. Transfection with siRNA reduced Gpr109a by 75%. Although BHB treatment did not significantly increase Il10, GPR109A knockdown as compared to the scrambled control reduced Il10 by 90% in S. uberis challenged macrophages treated with BHB, suggesting that macrophage immune responses to S. uberis can be altered via a GPR109A-dependent mechanism. Taken together, these data suggest that BHB altered the immune response promoting tolerance toward S. uberis rather than resistance.
Assessing the Diversity and Biomedical Potential of Microbes Associated With the Neptune’s Cup Sponge, Cliona patera

Marine sponges are known to host a complex microbial consortium that is essential to the health and resilience of these benthic invertebrates. These sponge-associated microbes are also an important source of therapeutic agents. The Neptune’s Cup sponge, Cliona patera, once believed to be extinct, was rediscovered off the southern coast of Singapore in 2011. The chance discovery of this sponge presented an opportunity to characterize the prokaryotic community of C. patera. Sponge tissue samples were collected from the inner cup, outer cup and stem of C. patera for 16S rRNA amplicon sequencing. C. patera hosted 5,222 distinct OTUs, spanning 26 bacterial phyla, and 74 bacterial classes. The bacterial phylum Proteobacteria, particularly classes Gammaproteobacteria and Alphaproteobacteria, dominated the sponge microbiome. Interestingly, the prokaryotic community structure differed significantly between the cup and stem of C. patera, suggesting that within C. patera there are distinct microenvironments. Moreover, the cup of C. patera had lower diversity and evenness as compared to the stem. Quorum sensing inhibitory (QSI) activities of selected sponge-associated marine bacteria were evaluated and their organic extracts profiled using the MS-based molecular networking platform. Of the 110 distinct marine bacterial strains isolated from sponge samples using culture-dependent methods, about 30% showed quorum sensing inhibitory activity. Preliminary identification of selected QSI active bacterial strains revealed that they belong mostly to classes Alphaproteobacteria and Bacilli. Annotation of the MS/MS molecular networkings of these QSI active organic extracts revealed diverse classes of natural products, including aromatic polyketides, siderophores, pyrrolidine derivatives, indole alkaloids, diketopiperazines, and pyrone derivatives. Moreover, potential novel compounds were detected in several strains as revealed by unique molecular families present in the molecular networks. Further research is required to determine the temporal stability of the microbiome of the host sponge, as well as mining of associated bacteria for novel QS inhibitors.
Non-Deterministic Updates of Boolean Networks

Boolean networks are discrete dynamical systems where each automaton has its own Boolean function for computing its state according to the configuration of the network. The updating mode then determines how the configuration of the network evolves over time. Many of updating modes from the literature, including synchronous and asynchronous modes, can be defined as the composition of elementary deterministic configuration updates, i.e., by functions mapping configurations of the network. Nevertheless, alternative dynamics have been introduced using ad-hoc auxiliary objects, such as that resulting from binary projections of Memory Boolean networks, or that resulting from additional pseudo-states for Most Permissive Boolean networks. One may wonder whether these latter dynamics can still be classified as updating modes of finite Boolean networks, or belong to a different class of dynamical systems. In this paper, we study the extension of updating modes to the composition of non-deterministic updates, i.e., mapping sets of finite configurations. We show that the above dynamics can be expressed in this framework, enabling a better understanding of them as updating modes of Boolean networks. More generally, we argue that non-deterministic updates pave the way to a unifying framework for expressing complex updating modes, some of them enabling transitions that cannot be computed with elementary and non-elementary deterministic updates.
Facile and green synthesis of fluorescent carbon dots from onion waste and their potential applications as sensor and multicolour imaging agents

Here, we report a novel, facile and green approach for the synthesis of highly fluorescent carbon dots (CDs) with 28% quantum yield by utilizing onion waste as a precursor and by employing a simple autoclave. Optical and physicochemical properties of as synthesized CDs were studied using transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), dynamic light scattering (DLS), X-ray diffraction (XRD), Raman, thermogravimetric analysis (TGA), Fourier transform infrared (FT-IR), UV-visible, fluorescence spectroscopy and elemental analysis. These CDs exhibited high aqueous dispersibility, excitation dependent fluorescence emission and excellent stability to various effects like pH, high ionic strength and continuous irradiation. It was observed that the presence of Fe3+ ions could result in a strong fluorescence quenching, hence these CDs were applied as a fluorescent probe for the selective & sensitive detection of Fe3+ ions and a good linear correlation (R2 = 0.996) in the range of 0–20 μM with a detection limit of 0.31 μM was obtained. Cytotoxicity studies performed on both normal (HEK-293 cells) and cancerous (HeLa) cells revealed their excellent biocompatibility and they were further employed as fluorescent probes for multicoloured (blue, green and red) imaging of HeLa cells. Impressed by their high selectivity, photo stability and excellent biocompatibility, the Fe3+ detection capability of these CDs was further evaluated in HeLa cells and applied for real water samples.