Metagenomics approaches for the detection and surveillance of emerging and recurrent plant pathogens

Globalization has a dramatic effect on the trade and movement of seeds, fruits and vegetables, with a corresponding increase in economic losses caused by the introduction of transboundary plant pathogens. Current diagnostic techniques provide a useful and precise tool to enact surveillance protocols regarding specific organisms, but this approach is strictly targeted, while metabarcoding and shotgun metagenomics could be used to simultaneously detect all known pathogens and potentially new ones. This review aims to present the current status of high-throughput sequencing (HTS) diagnostics of fungal and bacterial plant pathogens, discuss the challenges that need to be addressed, and provide direction for the development of methods for the detection of a restricted number of related taxa (specific surveillance) or all of the microorganisms present in a sample (general surveillance). HTS techniques, particularly metabarcoding, could be useful for the surveillance of soilborne, seedborne and airborne pathogens, as well as for identifying new pathogens and determining the origin of outbreaks. Metabarcoding and shotgun metagenomics still suffer from low precision, but this issue can be limited by carefully choosing primers and bioinformatic algorithms. Advances in bioinformatics will greatly accelerate the use of metagenomics to address critical aspects related to the detection and surveillance of plant pathogens in plant material and foodstuffs

The Polycomb protein, Bmi1, regulates insulin sensitivity

Objective: The Polycomb Repressive Complexes (PRC) 1 and 2 function to epigenetically repress target genes. The PRC1 component, Bmi1, plays a crucial role in maintenance of glucose homeostasis and beta cell mass through repression of the Ink4a/Arf locus. Here we have explored the role of Bmi1 in regulating glucose homeostasis in the adult animal, which had not been previously reported due to poor postnatal survival of Bmi1−/− mice. Methods: The metabolic phenotype of Bmi1+/− mice was characterized, both in vivo and ex vivo. Glucose and insulin tolerance tests and hyperinsulinemic-euglycemic clamps were performed. The insulin signaling pathway was assessed at the protein and transcript level. Results: Here we report a negative correlation between Bmi1 levels and insulin sensitivity in two models of insulin resistance, aging and liver-specific insulin receptor deficiency. Further, heterozygous loss of Bmi1 results in increased insulin sensitivity in adult mice, with no impact on body weight or composition. Hyperinsulinemic-euglycemic clamp reveals increased suppression of hepatic glucose production and increased glucose disposal rate, indicating elevated glucose uptake to peripheral tissues, in Bmi1+/− mice. Enhancement of insulin signaling, specifically an increase in Akt phosphorylation, in liver and, to a lesser extent, in muscle appears to contribute to this phenotype. Conclusions: Together, these data define a new role for Bmi1 in regulating insulin sensitivity via enhancement of Akt phosphorylation

Fertility, mortality, milk output, and body thermoregulation of growing Hy-Plus rabbits fed on diets supplemented with multi-enzymes preparation

Feed cost represents about 60–70 % of rabbit keeping costs; therefore, maximizing utilization of nutrients is essential for the profitability and sustainability of rabbit production. Consequently, it has become very necessary to look for locally available, cheap, and nutritionally safe feed additives that would help to cut down production costs and improve production efficiency. Since the European Union banned most of the antibiotic growth promoters in animal nutrition due to cross and multiple resistances, much research has been conducted to explore the use of multi-enzymes as effective substitutes.The aim of this study was to evaluate the fertility status, milk output, mortality, and body thermoregulation of rabbit does as affected by different levels of multi-enzyme extracts (EZ) in their diets. A total of 120 Hy-Plus rabbit does were divided into four comparable experimental groups (n = 30 does per group). Animals of each group were divided in six pens (five animals per pen), and each pen was used as an experimental unit. The first group was kept untreated and fed a commercial diet alone without enzyme extracts (EZ0), while the other groups were fed the same diet but supplemented with 1 (EZ1), 3 (EZ3), and 5 (EZ5) kg/ton of enzyme extracts, respectively. Feeding EZ additive increased (P < 0.05) conception and kindling rates, litter size and weight at birth, and litter size and bunny weight at weaning, with decreasing (P < 0.05) abortion rate. Moreover, total milk yield increased (P < 0.05) with increasing level of enzyme supplementation. Pre-weaning mortality decreased (P < 0.05) with EZ inclusion. Signs of vitality (rectal temperature, skin temperature, earlobe temperature, respiration rate, and pulse rate) were improved with EZ inclusion. For all results, 5 kg EZ/ton of feed was more effective than 1 and 3 kg EZ/ton feed. It can be concluded that supplementation of EZ in rabbit diet decreased mortality rate and enhanced fertility status and milk output

Impact of Genetic Polymorphism of Myeloid Differentiation Primary Response Gene 88, Enhancer of Zeste Homolog 2, and B-cell Lymphoma 2 like 11 in Patients with Diffuse Large B Cell Lymphoma Treated with Rituximab, Cyclophosphamide, Doxorubicin, Vincristin

BACKGROUND: Despite the growing landscape of genetic drivers in Diffuse Large B-cell Lymphoma, yet their clinical implication is still unclear and R-CHOP regimen remains a “one size fits all” therapy. We aimed in this study to examine the prevalence of EZH2, BCL211 and MYD 88 genetic polymorphisms in DLBCL patients and correlate the results with various clinical and survival outcomes. METHODS: Genotyping of MYD88 (rs387907272 T/C), EZH2 (rs3757441 C/T), and BCL2L11 (rs3789068 A/G) polymorphisms were conducted using real time polymerase chain reaction analysis in a total of 75 DLBCL patients. RESULTS: Most of our cases carried the wild TT genotype of MYD88 gene (64%), the mutant TT genotype of EZH2 gene (52%) and the wild AA genotype of BCL2L11 gene (48%). Regarding cell of origin, Germinal Centre (GC) phenotype was present in 56% of cases while 44% expressed the Post-GC (PGC) phenotype. Poor response outcome to first line R-CHOP was significantly correlated with the mutated CC genotype of MYD 88 (p=0.02), while better response to R-CHOP was significantly associated with younger age &lt;50 years (p &lt;0.0001), good PS (p=0.046), normal LDH level (p=0.003), earlier stage (p &lt;0.0001), good IPI score (p=0.009), absence of extranodal disease (p &lt;0.0001) and absence of bulky disease (p=0.004). The median PFS and the 2 year OS were significantly higher in younger age, earlier stage, good IPI score, absence of extranodal disease, absence of bulky disease and in GC phenotype. CONCLUSIONS: Our results emphasized that the mutated genotype of MYD 88 gene polymorphism is significantly associated with poor response to R-CHOP therapy

Feed intake, nutrient digestibility, nitrogen utilization, and ruminal fermentation activities in sheep fed Atriplex halimus ensiled with three developed enzyme cocktails

The effects of feeding Atriplex halimus treated with three developed enzyme cocktails to Barki sheep on feed intake, nutrient digestibility, N utilization, and ruminal fermentation were assessed. A. halimus was ensiled with two developed enzyme cocktails of ZAD1® (Z1) and/or ZAD2® (Z2) as liquid enzyme preparations (2 l/t) with 5% molasses and ensiled for 30 days. Three Barki rams (45 ± 3.2 kg) were used per treatment in five consecutive digestibility trials, while three ewes fitted with a permanent rumen fistula were used as source of inoculum for in vitro rumen fermentation trials. Barley grain (300 g/animal/day) was fed as energy supplement during the experimental trial for all diets. Five diets were composed as follows: A. halimus (leaves and stems) (D1); untreated A. halimus plus 4 g/animal/day ZADO® (Z) (enzyme preparation in powder form) (D2); A. halimus ensiled with Z1 and barley plus 4 g/animal/day Z (D3); A. halimus ensiled with Z2 and barley (D3) plus 4 g/animal/day Z (D4); A. halimus ensiled with a combination of Z1 and Z2 (1 :1) and barley plus 4 g/head/day Z (D5). For all trials, ad libitum A. halimus was offered twice a day at 9:00 and 16:00 h while barley grain was given once a day at 10:00 h. Both D1 and D2 diets increased (P <0.001) dry matter intake of A. halimus and total dry matter intake. Addition of 4 g/day of Z to Z1 and/or Z2 ensiled diets improved (P < 0.0001) organic matter, crude protein, crude fibre, and neutral detergent fibre digestibilities. Diets D1 and D2 increased (P < 0.001) N intake, whereas the direct addition of Z to D3, D4, and D5 decreased (P < 0.001) N balance and N balance/N absorption ratio. Sheep fed on Z in addition to Z2 ensiled A. halimus showed higher improvements for total volatile fatty acids (P < 0.001), ammonia N (P = 0.007), and microbial protein production (P = 0.003). It can be concluded that feeding sheep on A. halimus ensiled with Z1 and Z2 with direct feeding of Z enzyme preparation improved intake, digestibility, nitrogen balance and utilization, as well as rumen fermentation

Logic shrinkage: learned connectivity sparsification for LUT-based neural networks

FPGA-specific DNN architectures using the native LUTs as independently trainable inference operators have been shown to achieve favorable area-accuracy and energy-accuracy tradeoffs. The first work in this area, LUTNet, exhibited state-of-the-art performance for standard DNN benchmarks. In this article, we propose the learned optimization of such LUT-based topologies, resulting in higher-efficiency designs than via the direct use of off-the-shelf, hand-designed networks. Existing implementations of this class of architecture require the manual specification of the number of inputs per LUT, K. Choosing appropriate K a priori is challenging, and doing so at even high granularity, e.g. per layer, is a time-consuming and error-prone process that leaves FPGAs’ spatial flexibility underexploited. Furthermore, prior works see LUT inputs connected randomly, which does not guarantee a good choice of network topology. To address these issues, we propose logic shrinkage, a fine-grained netlist pruning methodology enabling K to be automatically learned for every LUT in a neural network targeted for FPGA inference. By removing LUT inputs determined to be of low importance, our method increases the efficiency of the resultant accelerators. Our GPU-friendly solution to LUT input removal is capable of processing large topologies during their training with negligible slowdown. With logic shrinkage, we better the area and energy efficiency of the best-performing LUTNet implementation of the CNV network classifying CIFAR-10 by 1.54 × and 1.31 ×, respectively, while matching its accuracy. This implementation also reaches 2.71 × the area efficiency of an equally accurate, heavily pruned BNN. On ImageNet with the Bi-Real Net architecture, employment of logic shrinkage results in a post-synthesis area reduction of 2.67 × vs LUTNet, allowing for implementation that was previously impossible on today’s largest FPGAs. We validate the benefits of logic shrinkage in the context of real application deployment by implementing a face mask detection DNN using BNN, LUTNet and logic-shrunk layers. Our results show that logic shrinkage results in area gains versus LUTNet (up to 1.20 ×) and equally pruned BNNs (up to 1.08 ×), along with accuracy improvements

Optimal Nitrogen Fertilization to Reach the Maximum Grain and Stover Yields of Maize (Zea mays L.): Tendency Modeling

Utilization of maize stover to the production of meat and milk and saving the grains for human consumption would be one strategy for the optimal usage of resources. Variance and tendency analyses were applied to find the optimal nitrogen (N) fertilization dose (0, 100, 145, 190, 240, and 290 kg/ha) for forage (F), stover (S), cob (C), and grain (G) yields, as well as the optimal grain-to-forage, cob-to-forage, and cob-to-stover ratios (G:F, C:F, and C:S, respectively). The study was performed in central Mexico (20.691389° N and −101.259722° W, 1740 m a.m.s.l.; Cwa (Köppen), 699 mm annual precipitation; alluvial soils). N-190 and N-240 improved the individual yields and ratios the most. Linear and quadratic models for CDM, GDM, and G:F ratio had coefficients of determination (R2) of 0.20–0.46 (p < 0.03). Cubic showed R2 = 0.30–0.72 (p < 0.02), and the best models were for CDM, GDM, and the G:F, C:F, and C:S DM ratios (R2 = 0.60–0.72; p < 0.0002). Neither SHB nor SDM negatively correlated with CDM or GDM (r = 0.23–0.48; p < 0.0001). Excess of N had negative effects on forage, stover, cobs, and grains yields, but optimal N fertilization increased the proportion of the G:F, C:F, and C:S ratios, as well as the SHB and SDM yields, without negative effects on grain production