Miracle-dz/UniFAR-FTUs huggingface dataset:
Complexation of multiple mineral elements by fermentation and its application in laying hens

To overcome the problems with current mineral supplements for laying hens including low absorption, mineral antagonism, and high cost, we developed mineral element fermentation complexes (MEFC) by synergistically fermenting bean dregs and soybean meal with strains and proteases and complexing with mineral elements. The fermentation complexation process was optimized based on the small peptide and organic acid contents and the complexation rate of mineral elements after fermentation. The optimal conditions were as follows: the total inoculum size was 5% (v/w), 15% (w/w) wheat flour middling was added to the medium, and mineral elements (with 4% CaCO3) were added after the completion of aerobic fermentation, fermentation at 34°C and 11 days of fermentation. Under these conditions, the complexation rates of Ca, Fe, Cu, Mn, and Zn were 90.62, 97.24, 73.33, 94.64, and 95.93%, respectively. The small peptide, free amino acid, and organic acid contents were 41.62%, 48.09 and 183.53 mg/g, respectively. After 60 days of fermentation, 82.11% of the Fe in the MEFC was ferrous ions, indicating that fermentation had a good antioxidant effect on ferrous ion, and the antioxidant protection period was at least 60 days. Fourier transform infrared spectroscopy showed that the mineral ions were complexed with amino and carboxyl groups. The added mineral elements promoted microbial growth, protein degradation, and organic acid secretion and significantly improved fermentation efficiency. Animal experiments showed that MEFC had positive effects on several parameters, including production performance (average daily feed intake, P < 0.05; egg production rate, P < 0.05; and average egg weight, P < 0.05), mineral absorption, intestinal morphology (villus height to crypt depth ratio in the jejunum and ileum, P < 0.05), and blood routine and biochemical indexes (red blood cells, P < 0.05; hemoglobin, P < 0.05). This study provides theoretical support for the development of mineral complexes for laying hens via fermentation.
Structural gray matter features and behavioral preliterate skills predict future literacy – A machine learning approach

When children learn to read, their neural system undergoes major changes to become responsive to print. There seem to be nuanced interindividual differences in the neurostructural anatomy of regions that later become integral parts of the reading network. These differences might affect literacy acquisition and, in some cases, might result in developmental disorders like dyslexia. Consequently, the main objective of this longitudinal study was to investigate those interindividual differences in gray matter morphology that might facilitate or hamper future reading acquisition. We used a machine learning approach to examine to what extent gray matter macrostructural features and cognitive-linguistic skills measured before formal literacy teaching could predict literacy 2 years later. Forty-two native German-speaking children underwent T1-weighted magnetic resonance imaging and psychometric testing at the end of kindergarten. They were tested again 2 years later to assess their literacy skills. A leave-one-out cross-validated machine-learning regression approach was applied to identify the best predictors of future literacy based on cognitive-linguistic preliterate behavioral skills and cortical measures in a priori selected areas of the future reading network. With surprisingly high accuracy, future literacy was predicted, predominantly based on gray matter volume in the left occipito-temporal cortex and local gyrification in the left insular, inferior frontal, and supramarginal gyri. Furthermore, phonological awareness significantly predicted future literacy. In sum, the results indicate that the brain morphology of the large-scale reading network at a preliterate age can predict how well children learn to read.
RNA-seq analysis reveals key genes associated with seed germination of Fritillaria taipaiensis P.Y.Li by cold stratification

Seed dormancy is an adaptive strategy for environmental evolution. However, the molecular mechanism of the breaking of seed dormancy at cold temperatures is still unclear, and the genetic regulation of germination initiated by exposure to cold temperature requires further investigation. In the initial phase of the current study, the seed coat characteristics and embryo development of Fritillaria taipaiensis P.Y. Li at different temperatures (0°C, 4°C, 10°C & 25°C) was recorded. The results obtained demonstrated that embryo elongation and the dormancy-breaking was most significantly affected at 4°C. Subsequently, transcriptome analyses of seeds in different states of dormancy, at two stratification temperatures (4°C and 25°C) was performed, combined with weighted gene coexpression network analysis (WGCNA) and metabolomics, to explore the transcriptional regulation of seed germination in F. taipaiensis at the two selected stratification temperatures. The results showed that stratification at the colder temperature (4°C) induced an up-regulation of gene expression involved in gibberellic acid (GA) and auxin biosynthesis and the down-regulation of genes related to the abscisic acid (ABA) biosynthetic pathway. Thereby promoting embryo development and the stimulation of seed germination. Collectively, these data constitute a significant advance in our understanding of the role of cold temperatures in the regulation of seed germination in F. taipaiensis and also provide valuable transcriptomic data for seed dormancy for other non-model plant species.
ANALYTICAL AND NUMERICAL STUDY OF LARGE BUBBLE/BUBBLE AND BUBBLE/FLOW INTERACTIONS

The presence of cavities in a liquid can have significant effects on its behaviour and its flow characteristics. In practical flow situations, these effects cannot be fully understood or predicted without addressing complicated, but nonetheless fundamental phenomena associated with the dynamics, interactions, and deformation of bubbles. The importance of these phenomena has long been recognized, but has largely been neglected due to the difficulty of the associated mathematical problems. In this contribution, bubble shape oscillations in response to nonuniform flow fields and/or due to their interaction with other bubbles are considered using both a matched asymptotic expansions technique and a fully three-dimensional boundary integral method. Results from both approaches in a few particular cases are compared, and the limits of application of these methods for these cases is assessed.
Subjective cognitive decline is associated with a higher risk of objective cognitive decline: A cross-sectional and longitudinal study

Background Subjective cognitive decline (SCD) is considered as an independent risk factor for objective cognitive impairment, such as dementia and mild cognitive impairment (MCI), but the mechanism is unclear. Methods The current study consisted of two parts, the first of which included 1,010 older adults with SCD and 535 normal controls and was followed for 1 year. The second cross-sectional study included 94 older adults with SCD and 64 healthy controls. Unlike the first cohort, subjects in the second study underwent magnetic resonance imaging and had more detailed neuropsychological tests, such as Mini- mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Digit Span, Auditory Verbal Learning Test (AVLT), Associative Learning Test (ALT), Verbal Fluency (VF), Wechsler's filling and Wechsler's building blocks. Results In cohort 1, we found that SCD had a higher risk of objective cognitive impairment compared to normal controls (X2 = 20.354, p = 0.002), and the results of Cox Regression analysis also suggest that SCD was a risk factor for objective cognitive decline (p < 0.001, HR = 2.608, 95%CI: 2.213–3.075). In study 2, we found that the scores of MoCA, digit span, verbal fluency, and Wechsler's filling of SCD elderly were significantly lower than those of normal controls, but the cortical thickness of the rostral middle frontal gyrus (RMFG) was significantly higher than that of normal controls (p < 0.05). Conclusions SCD is a cognition-related disease with multi-cognitive domain impairment, which is associated with a higher risk of objective cognitive impairment. Moreover, the increased cortical thickness of the left rostral middle frontal gyrus (RMFG) might be an important mechanism of cognitive decline in SCD.
The Next-to-Minimal Supersymmetric extension of the Standard Model reviewed

The next-to-minimal supersymmetric extension of the Standard Model (NMSSM) is one of the most favored supersymmetric models. After an introduction to the model, the Higgs sector and the neutralino sector are discussed in detail. Theoretical, experimental, and cosmological constraints are studied. Eventually, the Higgs potential is investigated in the approach of bilinear functions. Emphasis is placed on aspects which are different from the minimal supersymmetric extension.
Dry season forage assessment across senegalese rangelands using earth observation data

Strengthening of feed security in the Sahel is urgently needed given the climate change and growing human population. A prerequisite to this is sustainable use of rangeland forage resources for livestock. Many studies have focused on the assessment of rangeland resources during the rainy season, while only a few have focused on the dry season which is the longest and most demanding period for livestock in Sahelian rangelands. The objective of this study is to develop remote sensing-based models for estimating dry season forage vegetation mass. To that end, 29 vegetation indices calculated from each of the MODIS-MCD43A4 (500 m), Landsat-8 (30 m), and Sentinel-2 (10 m) satellite products were used and tested against in situ data collected during three field-measurement campaigns in 2021 at eleven monitoring sites across Senegalese rangelands. Four statistical models were tested, namely, random forest, gradient boosting machines, and simple linear and multiple linear regressions. The two main vegetation mass variables modeled from remote sensing imagery were the standing herbaceous and litter dry mass (BH) and total forage dry mass (BT) with a dry mass of woody plant leaves added to BH. Overall, Sentinel-2 data provided the best performance for the assessment of BH with multiple linear regression (R2 = 0.74; RMSE = 378 kg DM/ha) using NDI5 (Normalized Difference Index5), GRCI (Green Residue Cover Index), SRI (Simple Ratio Index), TCARI (Transformed Chlorophyll Absorption in Reflectance Index), and DFI (Dead Fuel Index) indices. For BT, the best model was also obtained from Sentinel-2 data, including RVI3 (Ratio Vegetation Index3) (R2 = 0.78; RMSE = 496 kg DM/ha). Results showed the suitability of combining the red, green, blue, NIR, SWIR1, and SWIR2 bands in monitoring forage availability during the dry season. Our study revealed that the spectral richness of the optical sensor systems Sentinel-2, Landsat-8, and MODIS-MCD43A4 allowed for accurate assessments of dry-season forage mass of semi-arid rangelands. Adding to this, the high spatial and temporal resolution of Sentinel-2 satellite imagery makes this a promising data source for timely monitoring. These findings can support the monitoring of the animal feed balance in Sahelian countries and contribute to enhancing the resilience of pastoralism toward feed shortage through early warning systems.
Determination of the large scale volume weighted halo velocity bias in simulations

A profound assumption in peculiar velocity cosmology is b(v) = 1 at sufficiently large scales, where bv is the volume-weighted halo(galaxy) velocity bias with respect to the matter velocity field. However, this fundamental assumption has not been robustly verified in numerical simulations. Furthermore, it is challenged by structure formation theory (Bardeen, Bond, Kaiser and Szalay, Astrophys. J. 304, 15 (1986); Desjacques and Sheth, Phys. Rev D 81, 023526 (2010), which predicts the existence of velocity bias (at least for proto-halos) due to the fact that halos reside in special regions (local density peaks). The major obstacle to measuring the volume-weighted velocity from N-body simulations is an unphysical sampling artifact. It is entangled in the measured velocity statistics and becomes significant for sparse populations. With recently improved understanding of the sampling artifact (Zhang, Zheng and Jing, 2015, PRD; Zheng, Zhang and Jing, 2015, PRD), for the first time we are able to appropriately correct this sampling artifact and then robustly measure the volume-weighted halo velocity bias. (1) We verify b(v) = 1 within 2% model uncertainty at k less than or similar to 0.1 h/Mpc and z = 0-2 for halos of mass similar to 10(12)-10(13) h(-1) M-circle dot and, therefore, consolidate a foundation for the peculiar velocity cosmology. (2) We also find statistically significant signs of bv. 1 at k greater than or similar to 0.1 h/Mpc. Unfortunately, whether this is real or caused by a residual sampling artifact requires further investigation. Nevertheless, cosmology based on the k greater than or similar to 0.1 h/Mpc velocity data should be careful with this potential velocity bias.
Effects of replacing soybean meal with linseed meal in broiler diet on selected broilers’ blood parameters, meat chemical composition, fatty acid profiles, and sensory characteristics

The study was conducted with the objective of determining the effects of the dietary replacement of soybean meal with graded levels of linseed meal on selected blood parameters, meat composition, fatty acid profiles, and meat quality of broiler chickens. Cobb500 broilers were fed diets containing linseed meal at 0% (T1), 6.5% (T2), 13% (T3), 19.5 (T4), and 26% (T5), replacing 0% to 100% soybean meal in compound rations for 45 days. The experiment was conducted using a completely randomized design with five treatments, each replicated three times with 12 birds. Blood hematological indices were not affected (P>0.05) by treatment diets while among the blood biochemistry triglyceride and cholesterol concentrations in T1 were higher (P<0.05) than in T3, T4, and T5. Glucose was higher in T3, T4, and T5 than in T1 and T2 (P<0.01). The breast and thigh proximate composition for crude protein (CP), ether extract (EE), ash, carbohydrate, and gross energy were similar (P>0.05) among treatments. The sensory scores for breast and thigh meat samples were not different (P>0.05) among treatments. The palmitic acid content of breast and thigh meat was higher (P<0.05) in T1 and T2 than in the other treatments. Eliadic and stearic acid concentrations in thigh meat were greater (P<0.05) in T1, T2, and T3 than in T4 and T5. The oleic and linoleic acid contents of thigh meat were higher (P<0.05) in T2 and T3 than in the rest of the treatments. Breast linolenic acid was high (P<0.05) in T5 but similar in thigh meat. Total saturated fatty acid (SFA) showed a decreasing trend with an increasing level of linseed meal (LSM) in the ration. The ratio of monounsaturated fatty acid (MUFA) to SFA for breast and thigh was higher in T4 and T5 than in T1 and T2. Breast meat ratio of omega-6 (n-6) to omega-3 (n-3) showed a decreasing trend as the level of LSM replacement for soybean meal (SBM) in the ration increased. Generally, linseed meal replacement levels up to 26% in the broilers’ diet improves the essential fatty acid content of chicken meat without affecting the proximate composition and the chickens’ normal blood indices and does not alter meat sensory attributes.
Artificial intelligence promotes the diagnosis and screening of diabetic retinopathy

Deep learning evolves into a new form of machine learning technology that is classified under artificial intelligence (AI), which has substantial potential for large-scale healthcare screening and may allow the determination of the most appropriate specific treatment for individual patients. Recent developments in diagnostic technologies facilitated studies on retinal conditions and ocular disease in metabolism and endocrinology. Globally, diabetic retinopathy (DR) is regarded as a major cause of vision loss. Deep learning systems are effective and accurate in the detection of DR from digital fundus photographs or optical coherence tomography. Thus, using AI techniques, systems with high accuracy and efficiency can be developed for diagnosing and screening DR at an early stage and without the resources that are only accessible in special clinics. Deep learning enables early diagnosis with high specificity and sensitivity, which makes decisions based on minimally handcrafted features paving the way for personalized DR progression real-time monitoring and in-time ophthalmic or endocrine therapies. This review will discuss cutting-edge AI algorithms, the automated detecting systems of DR stage grading and feature segmentation, the prediction of DR outcomes and therapeutics, and the ophthalmic indications of other systemic diseases revealed by AI.
Solving the regulation puzzle of periderm development using advances in fruit skin

Periderm protects enlarged organs of most dicots and gymnosperms as a barrier to water loss and disease invasion during their secondary growth. Its development undergoes a complex process with genetically controlled and environmental stress-induced characters. Different development of periderm makes the full and partial russet of fruit skin, which diverges in inheritance with qualitative and quantitative characters, respectively, in pear pome. In addition to its specific genetics, fruit periderm has similar development and structure as that of stem and other organs, making it an appropriate material for periderm research. Recently, progress in histochemical as well as transcriptome and proteome analyses, and quantitative trait locus (QTL) mapping have revealed the regulatory molecular mechanism in the periderm based on the identification of switch genes. In this review, we concentrate on the periderm development, propose the conservation of periderm regulation between fruit and other plant organs based on their morphological and molecular characteristics, and summarize a regulatory network with the elicitors and repressors for the tissue development. Spontaneous programmed-cell death (PCD) or environmental stress produces the original signal that triggers the development of periderm. Spatio-temporal specific PCD produced by PyPPCD1 gene and its homologs can play a key role in the coordinated regulation of cell death related tissue development.
Review on Plant-Based Management in Combating Antimicrobial Resistance - Mechanistic Perspective

Antimicrobial resistance (AMR) occurs when microbes no longer respond to any pharmacological agents, rendering the conventional antimicrobial agents ineffective. AMR has been classified as one of the top 10 life-threatening global health problems needed multilevel attention and global cooperation to attain the Sustainable Development Goals (SDGs) according to the World Health Organization (WHO), making the discovery of a new and effective antimicrobial agent a priority. The recommended treatments for drug-resistant microbes are available but limited. Furthermore, the transformation of microbes over time increases the risk of developing drug resistance. Hence, plant metabolites such as terpenes, phenolic compounds and alkaloids are widely studied due to their antibacterial, antiviral, antifungal and antiparasitic effects. Plant-derived antimicrobials are preferred due to their desirable efficacy and safety profile. Plant metabolites work by targeting microbial cell membranes, interfering with the synthesis of microbial DNA/RNA/enzymes and disrupting quorum sensing and efflux pump expression. They also work synergistically with conventional antibiotics to enhance antimicrobial effects. Accordingly, this review aims to identify currently available pharmacological therapies against microbes and AMR, as well as to discuss the importance of plant and secondary metabolites as a possible solution for AMR together with their mechanisms of action. All the information was obtained from government databases, WHO websites, PubMed, Springer, Google Scholar and Science Direct. Based on the information obtained, AMR is regarded as a significant warning to global healthcare. Plant derivatives such as secondary metabolites may be considered as potential therapeutic targets to mitigate the non-ending AMR.
Rhodococcus strains as a good biotool for neutralizing pharmaceutical pollutants and obtaining therapeutically valuable products: Through the past into the future

Active pharmaceutical ingredients present a substantial risk when they reach the environment and drinking water sources. As a new type of dangerous pollutants with high chemical resistance and pronounced biological effects, they accumulate everywhere, often in significant concentrations (μg/L) in ecological environments, food chains, organs of farm animals and humans, and cause an intense response from the aquatic and soil microbiota. Rhodococcus spp. (Actinomycetia class), which occupy a dominant position in polluted ecosystems, stand out among other microorganisms with the greatest variety of degradable pollutants and participate in natural attenuation, are considered as active agents with high transforming and degrading impacts on pharmaceutical compounds. Many representatives of rhodococci are promising as unique sources of specific transforming enzymes, quorum quenching tools, natural products and novel antimicrobials, biosurfactants and nanostructures. The review presents the latest knowledge and current trends regarding the use of Rhodococcus spp. in the processes of pharmaceutical pollutants’ biodegradation, as well as in the fields of biocatalysis and biotechnology for the production of targeted pharmaceutical products. The current literature sources presented in the review can be helpful in future research programs aimed at promoting Rhodococcus spp. as potential biodegraders and biotransformers to control pharmaceutical pollution in the environment.
Novel peanut-specific human IgE monoclonal antibodies enable screens for inhibitors of the effector phase in food allergy

Background 10% of US residents have food allergies, including 2% with peanut allergy. Mast cell mediators released during the allergy effector phase drive allergic reactions. Therefore, targeting sensitized mast cells may prevent food allergy symptoms. Objective We used novel, human, allergen-specific, IgE monoclonal antibodies (mAbs) created using human hybridoma techniques to design an in vitro system to evaluate potential therapeutics targeting sensitized effector cells. Methods Two human IgE mAbs specific for peanut, generated through human hybridoma techniques, were used to sensitize rat basophilic leukemia (RBL) SX-38 cells expressing the human IgE receptor (FcϵRI). Beta-hexosaminidase release (a marker of degranulation), cytokine production, and phosphorylation of signal transduction proteins downstream of FcϵRI were measured after stimulation with peanut. Degranulation was also measured after engaging inhibitory receptors CD300a and Siglec-8. Results Peanut-specific human IgE mAbs bound FcϵRI, triggering degranulation after stimulation with peanut in RBL SX-38 cells. Sensitized RBL SX-38 cells stimulated with peanut increased levels of phosphorylated SYK and ERK, signal transduction proteins downstream of FcϵRI. Engaging inhibitory cell surface receptors CD300a or Siglec-8 blunted peanut-specific activation. Conclusion Allergen-specific human IgE mAbs, expressed from human hybridomas and specific for a clinically relevant food allergen, passively sensitize allergy effector cells central to the in vitro models of the effector phase of food allergy. Peanut reproducibly activates and induces degranulation of RBL SX-38 cells sensitized with peanut-specific human IgE mAbs. This system provides a unique screening tool to assess the efficacy of therapeutics that target allergy effector cells and inhibit food allergen-induced effector cell activation.