Miracle-dz/UniFAR-FTUs huggingface dataset:
Quality Changes of Sardine (Sardina pilchardus W.,1792) During Frozen Storage

In the present study, physical, chemical, microbiological and sensory changes of sardine as whole (Group A) and fillet (Group B) forms were determined during frozen storage at -18°C, but all samples were shocked at -40°C before. According to the statistical analysis results, there were significant differences (P<0.05) between TBA, FA (ex), FA (dest) values of two groups during the frozen storage while there were no significant differences (P>0.05) between pH and TVB-N values of two groups. It was found that, total viable count of Group A kept its initial value at the end of the frozen storage while total viable count of Group B showed a decrease during the storage period. Coliform bacteria count stayed almost at the same level for Group A and Group B during the storage and coagulase-positive S. aureus was not detected. No significant differences (P>0.05) were observed in the colour, smell, chewy texture and flavor properties of two groups.
Comparison of Methods for Harvest Prediction in ‘Gigante’ Cactus Pear

Behavior analysis and plant expression are the answers the researcher needs to construct predictive models that minimize the effects of the uncertainties of field production. The objective of this study was to compare the simple and multiple linear regression methods and the artificial neural networks to allow the maximum security in the prediction of harvest in ‘Gigante’ cactus pear. The uniformity test was conducted at the Federal Institute of Bahia, Campus Guanambi, Bahia, Brazil, coordinates 14°13′30″ S, 42°46′53″ W and altitude of 525 m. At 930 days after planting, we evaluated 384 basic units, in which were measured the following variables: plant height (PH); cladode length (CL), width (CW) and thickness (CT); cladode number (CN); total cladode area (TCA); cladode area (CA) and cladode yield (Y). For the comparison between the artificial neural networks (ANN) and regression models (single and multiple-SLR and MLR), we considered the mean prediction error (MPE), the mean quadratic error (MQE), the mean square of deviation (MSD) and the coefficient of determination (R2). The values estimated by the ANN 7-5-1 showed the best proximity to the data obtained in field conditions, followed by ANN 6-2-1, MLR (TCA and CT), SLR (TCA) and SLR (CN). In this way, the ANN models with the topologies 7-2-1 and 6-2-1, MLR with the variables total cladode area and cladode thickness and SLR with the isolated descriptors total cladode area and cladode number, explain 85.1; 81.5; 76.3; 74.09 and 65.87%, respectively, of the yield variation. The ANNs were more efficient at predicting the yield of the ‘Gigante’ cactus pear when compared to the simple and multiple linear regression models.
Mixed aerobic-anaerobic incubation conditions induce proteolytic activity from in vitro salivary biofilms

ABSTRACT Oral biofilms have not been studied using both metabolome and protein profiling concurrently. Bacteria produce proteases that lead to degradation of functional salivary proteins. The novel protocol described here allows for complete characterisation of in vitro oral biofilms, including proteolytic, metabolic, and microbiome analysis. Biofilms were grown on hydroxyapatite discs from whole mouth saliva, using sterilised saliva as a growth-medium, in different growth environments. Salivary protein degradation was assessed from spent saliva growth-medium using SDS-polyacrylamide gel electrophoresis (SDS-PAGE), and metabolic activity by nuclear magnetic resonance (NMR). Discs were assessed for depth and coverage of biofilms by confocal laser scanning microscopy (CLSM), and biofilms were collected at the end of the experiment for 16S rRNA gene sequence analysis. There was a significant difference in biofilm viability, salivary protein degradation, and metabolites identified between biofilms grown aerobically and biofilms exposed to an anaerobic environment. Bacterial 16S rRNA gene sequencing showed the predominant genus in the 7-day aerobic biofilms was Streptococcus, in aerobic-anaerobic and anaerobic 7-day biofilms Porphyromonas, and in aerobic-anaerobic and anaerobic 13-day biofilms Fusobacterium. This data suggests new growth requirements and capabilities for analysing salivary biofilms in vitro, which can be used to benefit future research into oral bacterial biofilms.
A cross-species neural integration of gravity for motor optimization

Muscle patterns reveal how humans and monkeys save muscle effort by taking advantage of gravity effects. Recent kinematic results, combined with model simulations, have provided support for the hypothesis that the human brain shapes motor patterns that use gravity effects to minimize muscle effort. Because many different muscular activation patterns can give rise to the same trajectory, here, we specifically investigate gravity-related movement properties by analyzing muscular activation patterns during single-degree-of-freedom arm movements in various directions. Using a well-known decomposition method of tonic and phasic electromyographic activities, we demonstrate that phasic electromyograms (EMGs) present systematic negative phases. This negativity reveals the optimal motor plan’s neural signature, where the motor system harvests the mechanical effects of gravity to accelerate downward and decelerate upward movements, thereby saving muscle effort. We compare experimental findings in humans to monkeys, generalizing the Effort-optimization strategy across species.
Megafauna Seed Dispersal in the Neotropics: A Meta-Analysis Shows No Genetic Signal of Loss of Long-Distance Seed Dispersal

Restricted gene flow may lead to the loss of genetic diversity and higher genetic differentiation among populations, but the genetic consequences of megafauna extinction for plant populations still remain to be assessed. We performed a phylogenetic-independent meta-analysis across 102 Neotropical plants to test the hypothesis that plant species with megafaunal seed dispersal syndrome have a lower genetic diversity and a higher genetic differentiation than those without it. We classified as megafauna-dependent plant species those that potentially relied only on megafauna to seed dispersal, and as megafauna-independent those that relied on megafauna and other seed dispersers. Our data comprised 98 studies using microsatellite markers. We found no statistical difference in genetic diversity and differentiation between plants with megafauna and non-megafauna seed dispersal syndrome, although the statistical power to detect differences in genetic differentiation was low. Moreover, we found no statistical difference between megafauna-dependent and megafauna-independent plant species. We then used generalized linear mixed models and phylogenetic generalized least square models to investigate the effects of megafaunal seed dispersal syndromes and reproductive traits on variation in genetic diversity and genetic differentiation. We found no effect of megafaunal syndrome, rather, reproductive traits, such as pollination mode, mating, and breeding systems, showed significant effects. Our findings show that the genetic studies of Neotropical plants performed so far show no difference in genetic diversity and differentiation in plants with megafaunal compared to those with non-megafaunal seed dispersal syndromes. Our results also provide evidence pointing out that plant species with megafaunal seed dispersal syndromes may have used different strategies to counterbalance the extinction of their mutualistic megafauna dispersers, such as the dispersal by extant mammals that may promote long-distance seed dispersal. Our results also reinforce the importance of pollination to long-distance gene flow in Neotropical plants.
New Ratios for Performance Improvement for Identifying Acyl-CoA Dehydrogenase Deficiencies in Expanded Newborn Screening: A Retrospective Study

Some success in identifying acyl-CoA dehydrogenase (ACAD) deficiencies before they are symptomatic has been achieved through tandem mass spectrometry. However, there has been several challenges that need to be confronted, including excess false positives, the occasional false negatives and indicators selection. To select ideal indicators and evaluate their performance for identifying ACAD deficiencies, data from 352,119 newborn babies, containing 20 cases, were used in this retrospective study. A total of three new ratios, C4/C5DC+C6-OH, C8/C14:1, and C14:1/C16-OH, were selected from 43 metabolites. Around 903 ratios derived from pairwise combinations of all metabolites via multivariate logistic regression analysis were used. In the current study, the regression analysis was performed to identify short chain acyl-CoA dehydrogenase (SCAD) deficiency, medium chain acyl-CoA dehydrogenase (MCAD) deficiency, and very long chain acyl-CoA dehydrogenase (VLCAD) deficiency. In both model-building and testing data, the C4/C5DC+C6-OH, C8/C14:1 and C14:1/C16-OH were found to be better indicators for SCAD, MCAD and VLCAD deficiencies, respectively, compared to [C4, (C4, C4/C2)], [C8, (C6, C8, C8/C2, C4DC+C5-OH/C8:1)], and [C14:1, (C14:1, C14:1/C16, C14:1/C2)], respectively. In addition, 22 mutations, including 5 novel mutations and 17 reported mutations, in ACADS, ACADM, and ACADL genes were detected in 20 infants with ACAD deficiency by using high-thorough sequencing based on target capture. The pathogenic mutations of c.1031A > G in ACADS, c. 449_452delCTGA in ACADM and c.1349G > A in ACADL were found to be hot spots in Suzhou patients with SCAD, MCAD, and VLCAD, respectively. In conclusion, we had identified three new ratios that could improve the performance for ACAD deficiencies compared to the used indicators. We considered to utilize C4/C5DC+C6-OH, C8/C14:1, and C14:1/C16-OH as primary indicators for SCAD, MCAD, and VLCAD deficiency, respectively, in further expanded newborn screening practice. In addition, the spectrum of mutations in Suzhou population enriches genetic data of Chinese patients with one of ACAD deficiencies.
The Association between PON1 (Q192R and L55M) Gene Polymorphisms and Risk of Cancer: A Meta-Analysis Based on 43 Studies

Q192R and L55M polymorphism were considered to be associated with the development of multiple cancers. Nevertheless, the results of these researches were inconclusive and controversial. Therefore, we conducted a meta-analysis of all eligible case-control studies to assess the association between PON1 (Q192R and L55M) gene polymorphisms and risk of cancer. With the STATA 14.0 software, we evaluated the strength of the association by using the odds ratios (ORs) and 95% confidence intervals (CIs). A total of 43 case-control publications 19887 cases and 23842 controls were employed in our study. In all genetic models, a significant association between PON1-L55M polymorphisms and overall cancer risk was observed. Moreover, in the stratified analyses by cancer type, polymorphism of PON1-L55M played a risk factor in the occurrence of breast cancer, hematologic cancer, and prostate cancer. Similarly, an increased risk was observed in the Caucasian and Asian population as well as hospital-based group and population-based group. For PON1-Q192R polymorphisms, in the stratified analyses by cancer type, PON1-Q192R allele was associated with reduced cancer risks in breast cancer. Furthermore, for racial stratification, there was a reduced risk of cancer in recession model in Caucasian population. Similarly, in the stratification analysis of control source, the overall risk of cancer was reduced in the heterozygote comparison and dominant model in the population-based group. In conclusion, PON1-Q192R allele decreased the cancer risk especially breast cancer; there was an association between PON1-L55M allele and increased overall cancer risk. However, we need a larger sample size, well-designed in future and at protein levels to confirm these findings.
Hummingbirds budget energy flexibly in response to changing resources

A key component of individual fitness is the ability to manage energy stores in response to variable resource availability, but because directly measuring energy budgets is difficult, daily energy management is rarely measured. Hummingbirds' energy management is relatively simple to model compared to other endotherms because they have high mass‐specific metabolic rates and store little fat. We determined which aspects of the hummingbird daily energy budget (i.e. thermoregulation, daytime activity costs, night‐time costs) change at the individual level in response to environmental variation. We found that daily energy expenditure varied threefold in two populations of broad‐billed hummingbirds (Cynanthus latirostris). Our model indicated the energy budget was distributed in the following proportions: daytime activity, 59% (range 22%–84%); thermoregulation, 23% (11%–32%); basal metabolism, 7% (3%–16%); and night‐time energy, 17% (6%–37%). Activity costs were higher at the hotter, homogeneous site and during the early‐wet season at both sites. Increased daily energy expenditure was related to decreased nectar availability and not significantly related to temperature or bird mass. With climate change, the indirect energetic costs of shifting resources could have greater impacts on endotherm energy budgets than direct costs such as thermoregulation. Increased foraging and activity costs could decrease the energy available to birds for somatic repair and reproduction, potentially causing differential fitness across seasons and sites. A free Plain Language Summary can be found within the Supporting Information of this article.
Recurrent neural network weight estimation through backward tuning

We consider another formulation of weight estimation in recurrent networks, proposing a notation for a large amount of recurrent network units that helps formulating the estimation problem. Reusing a “good old” control-theory principle, improved here using a backward-tuning numerical stabilization heuristic, we obtain a numerically stable and rather efficient second-order and distributed estimation, without any meta-parameter to adjust. The relation with existing technique is discussed at each step. The proposed method is validated using reverse engineering tasks.
Genomic prediction for commercial traits using univariate and multivariate approaches in Nile tilapia (Oreochromis niloticus)

Background Over the past three decades, Nile tilapia industry has grown into a significant aquaculture industry spread over 120 tropical and sub-tropical countries around the world accounting for 7.4% of global aquaculture production in 2015. Across species, genomic selection has been shown to increase predictive ability and genetic gain, also extending into aquaculture. Hence, the aim of this paper is to compare the predictive abilities of pedigree- and genomic-based models in univariate and multivariate approaches, with the aim to utilize genomic selection in a Nile tilapia breeding program. A total of 1444 fish were genotyped (48,960 SNP loci) and phenotyped for body weight at harvest (BW), fillet weight (FW) and fillet yield (FY). The pedigree-based analysis utilized a deep pedigree, including 14 generations. Estimated breeding values (EBVs and GEBVs) were obtained with traditional pedigree-based (PBLUP) and genomic (GBLUP) models, using both univariate and multivariate approaches. Prediction accuracy and bias were evaluated using 5 replicates of 10-fold cross-validation with three different cross-validation approaches. Further, impact of these models and approaches on the genetic evaluation was assessed based on the ranking of the selection candidates. Results GBLUP univariate models were found to increase the prediction accuracy and reduce bias of prediction compared to other PBLUP and multivariate approaches. Relative to pedigree-based models, prediction accuracy increased by ∼20% for FY, >75% for FW and >43% for BW. GBLUP models caused major re-ranking of the selection candidates, with no significant difference in the ranking due to univariate or multivariate GBLUP approaches. The heritabilities using multivariate GBLUP models for BW, FW and FY were 0.19 ± 0.04, 0.17 ± 0.04 and 0.23 ± 0.04 respectively. BW showed very high genetic correlation with FW (0.96 ± 0.01) and a slightly negative genetic correlation with FY (−0.11 ± 0.15). Conclusion Predictive ability of genomic prediction models is substantially higher than for classical pedigree-based models. Genomic selection is therefore beneficial to the Nile tilapia breeding program, and it is recommended in routine genetic evaluations of commercial traits in the Nile tilapia breeding nucleus.
Effects of soil inoculation with arbuscular mycorrhizal fungi on plant growth and nutrient uptake of some Mediterranean species grown under rainfed field conditions

1. Background & Objectives Low-input farming systems often suffer nutrient deficits that limit plant performance. The symbiosis between plants and arbuscular mycorrhizal (AM) fungi efficiently promotes plant growth and nutrient uptake, especially in growth-limiting environments (Smith and Read, 2008). AM symbiosis seems to be particularly efficient for the acquisition of low-mobility nutrients such as phosphorus (P), magnesium, and zinc, although it traditionally has been considered irrelevant for plant nitrogen (N) nutrition. However, there is increasing evidence that AM symbiosis plays a significant role in plant N capture, especially under conditions of stress (such as water and nutrient stress). These benefits mainly have been observed in pot studies; field studies have often produced contradictory results (Kaschuk et al., 2010). The present work evaluated the effect of a multispecies AM fungi soil inoculum on the biomass uptake of P and N in two cereals, oat (Avena sativa) and barley (Hordeum vulgare), and two legumes, lentil (Lens culinaris) and fenugreek (Trigonella foenum graecum), all grown in the field.
Biodiesel as a carrier for pesticide formulations: a green chemistry approach

Abstract This article discusses the present status and future scope of biodiesel as a carrier/diluents and alternative source to hazardous volatile organic compounds for liquid pesticide formulations. Development of user and environment-friendly liquid pesticide formulations for sustainable agriculture is the key focus of today’s agrochemical industries. Organic solvents play an important role in ensuring the efficient distribution and delivery of active ingredients (a.i.) during application of liquid pesticide formulations. Presently used petroleum-based solvents have many disadvantages such as low flash points, high volatility, flammability, phytotoxicity, and inhalation problems to users, etc. However, at present it seems that the use of renewable resources, especially plant oils, oils ester (fatty acids alkyl ester) like biodiesel has the capacity to replace the traditional petroleum-based solvents in liquid pesticide formulations with having sustainable characteristics like high flash point, safer storage, transportation and application. Biodiesel which is easily reproducible from waste cooking oil, waste edible oil, animal fat, etc. may be a suitable alternative green solvent for liquid pesticide formulations in the near future.
Structural insights into the molecular mechanisms of the Mycobacterium evolvability factor Mfd

Mfd is a highly conserved ATP dependent DNA translocase that mediates the role of Transcription-Coupled-DNA-Repair(TCR) in bacteria. The molecular mechanisms and conformational remodelling that occurs in Mfd upon ATP binding, hydrolysis, and DNA translocation are poorly defined. Here we report a series of crystal and electron microscopy(EM) structures of Mfd from Mycobacterium tuberculosis (MtbMfd) and Mycobacterium smegmatis Mfd, solved in both the apo and nucleotide-bound states. The structures reveal the mechanism of nucleotide-binding, which lead to the remodeling of the Walker A motif at the catalytic pocket, inducing a flip-flop action of the hinge and flexible linker regions. Specifically, nucleotide binding unlocks the Translocation in RecG motif of the D6-domain to induce a ratchet-like motion. Functional studies of MtbMfd-RNAP complexes show that MtbMfd rescues stalled Transcription Elongation Complexes. We also report negative-stain and cryo-EM single particle reconstructions of MtbMfd higher order oligomer, that reveal an unexpected dodecameric assembly state. Given that Mfd accelerates the evolution of antimicrobial resistance(AMR), our results establish a framework for the design of new “anti-evolution” therapeutics to counter AMR.
Characterization of the Th cytokines profile in ovine spleen during early pregnancy

ABSTRACT The spleen combines the innate and adaptive immune systems, and the early conceptus must regulate the maternal intrauterine immune and systemic immune response during early pregnancy in sheep. However, it is unclear whether early pregnancy exerts its effects on the characterization of the T helper (Th) cytokines profile in the spleen during early pregnancy in ewes. In this study, spleens were obtained at day 16 of the oestrous cycle and at days 13, 16 and 25 of pregnancy (n = 6 for each group) from ewes, and qRT-PCR, western blot and immunohistochemistry analysis were used to analyze the Th cytokines profile of the spleens. Our results showed that there was down-regulation of IFN-γ at days 13 and 16 of pregnancy, but there was upregulation of IL-2, IL-5 and IL-6 at day 25 of pregnancy, TNF-β at days 16 and 25 of pregnancy, and IL-4 and IL-10 in all pregnant groups. Immunohistochemistry results showed that the IL-6 protein was limited to the capsule, trabeculae and splenic cords. This paper reported, for the first time, that characterization of the Th cytokines profile varied in the maternal spleen during early pregnancy, which may be essential for successful pregnancy in sheep.
Endogenous opioid peptides and brain development: Endomorphin‐1 and Nociceptin play a sex‐specific role in the control of oligodendrocyte maturation and brain myelination

The generation of fully functional oligodendrocytes, the myelinating cells of the central nervous system, is preceded by a complex maturational process. We previously showed that the timing of oligodendrocyte differentiation and rat brain myelination were altered by perinatal exposure to buprenorphine and methadone, opioid analogs used for the management of pregnant addicts. Those observations suggested the involvement of the μ‐opioid receptor (MOR) and the nociceptin/orphanin FQ receptor (NOR). However, it remained to be determined if these receptors and their endogenous ligands could indeed control the timing of myelination under normal physiological conditions of brain development. We now found that the endogenous MOR ligand endomorphin‐1 (EM‐1) exerts a striking stimulatory action on cellular and morphological maturation of rat pre‐oligodendrocytes, but unexpectedly, these effects appear to be restricted to the cells from the female pups. Critically, this stimulation is abolished by coincubation with the endogenous NOR ligand nociceptin. Furthermore, NOR antagonist treatment of 9‐day‐old female pups results in accelerated brain myelination. Interestingly, the lack of sex‐dependent differences in developmental brain levels of EM‐1 and nociceptin, or oligodendroglial expression of MOR and NOR, suggests that the observed sex‐specific responses may be highly dependent on important intrinsic differences between the male and female oligodendrocytes. The discovery of a significant effect of EM‐1 and nociceptin in the developing female oligodendrocytes and brain myelination, underscores the need for further studies investigating brain sex‐related differences and their implications in opioid use and abuse, pain control, and susceptibility and remyelinating capacity in demyelinating disease as multiple sclerosis.