Development of polymorphic EST-SSR markers and characterization of the autotetraploid genome of sainfoin (Onobrychis viciifolia)

Background Sainfoin (Onobrychis viciifolia) is a highly nutritious, tannin-containing, and tetraploid forage legume. Due to the lack of detailed transcriptomic and genomic information on this species, genetic and breeding projects for sainfoin improvement have been significantly hindered. Methods In this study, a total of 24,630,711 clean reads were generated from 14 different sainfoin tissues using Illumina paired-end sequencing technology and deposited in the NCBI SRA database (SRX3763386). From these clean reads, 77,764 unigene sequences were obtained and 6,752 EST-SSRs were identified using de novo assembly. A total of 2,469 primer pairs were designed, and 200 primer pairs were randomly selected to analyze the polymorphism in five sainfoin wild accessions. Results Further analysis of 40 sainfoin individuals from the five wild populations using 61 EST-SSR loci showed that the number of alleles per locus ranged from 4 to 15, and the expected heterozygosity varied from 0.55 to 0.91. Additionally, by counting the EST-SSR band number and sequencing the three or four bands in one sainfoin individual, sainfoin was confirmed to be autotetraploid. This finding provides a high level of information about this plant. Discussion Through this study, 61 EST-SSR markers were successfully developed and shown to be useful for genetic studies and investigations of population genetic structures and variabilities among different sainfoin accessions

Enhanced Hygrothermal Stability of In-Situ-Grown MAPbBr₃ Nanocrystals in Polymer with Suppressed Desorption of Ligands

Currently, the intrinsic instability of organic-inorganic hybrid perovskite nanocrystals (PNCs) at high temperature and high humidity still stands as a big barrier to hinder their potential applications in optoelectronic devices. Herein, we report the controllable in-situ-grown PNCs in polyvinylidene fluoride (PVDF) polymer with profoundly enhanced hygrothermal stability. It is found that the introduced tetradecylphosphonic acid (TDPA) ligand enables significantly improved binding to the surface of PNCs via a strong covalently coordinated P-O-Pb bond, as evidenced by density functional theory calculations and X-ray photoelectron spectroscopy analyses. Accordingly, such enhanced binding could not only make efficient passivation of the surface defects of PNCs but also enable the remarkably suppressed desorption of the ligand from the PNCs under high-temperature environments. Consequently, the photoluminescence quantum yield (PL QY) of the as-fabricated MAPbBr3-PNCs@PVDF film exhibits almost no decay after exposure to air at 333 K over 1800 h. Once the temperatures are increased from 293 to 353 K, their PL intensity can be kept as 88.6% of the initial value, much higher than that without the TDPA ligand (i.e., 42.4%). Moreover, their PL QY can be maintained above 50% over 1560 h (65 days) under harsh working conditions of 333 K and 90% humidity. As a proof of concept, the as-assembled white light-emitting diodes display a large color gamut of 125% National Television System Committee standard, suggesting their promising applications in backlight devices.</p

The oxidative aging model integrated various risk factors in type 2 diabetes mellitus at system level

BackgroundType 2 diabetes mellitus (T2DM) is a chronic endocrine metabolic disease caused by insulin dysregulation. Studies have shown that aging-related oxidative stress (as “oxidative aging”) play a critical role in the onset and progression of T2DM, by leading to an energy metabolism imbalance. However, the precise mechanisms through which oxidative aging lead to T2DM are yet to be fully comprehended. Thus, it is urgent to integrate the underlying mechanisms between oxidative aging and T2DM, where meaningful prediction models based on relative profiles are needed.MethodsFirst, machine learning was used to build the aging model and disease model. Next, an integrated oxidative aging model was employed to identify crucial oxidative aging risk factors. Finally, a series of bioinformatic analyses (including network, enrichment, sensitivity, and pan-cancer analyses) were used to explore potential mechanisms underlying oxidative aging and T2DM.ResultsThe study revealed a close relationship between oxidative aging and T2DM. Our results indicate that nutritional metabolism, inflammation response, mitochondrial function, and protein homeostasis are key factors involved in the interplay between oxidative aging and T2DM, even indicating key indices across different cancer types. Therefore, various risk factors in T2DM were integrated, and the theories of oxi-inflamm-aging and cellular senescence were also confirmed.ConclusionIn sum, our study successfully integrated the underlying mechanisms linking oxidative aging and T2DM through a series of computational methodologies

Distinction and Recognition of the 'Black Pearl' Fresh Corn Origin Based on Electronic Nose and BP Neural Network

: 'Black pearl' fresh corns from different regions were analyzed using an electronic nose to capture the aroma profile. Principal component analysis (PCA) and discriminant function analysis (DFA) were used for multivariate statistical analysis of 200 data from two regions. Based on this, the judgment model of samples from Heilongjiang production area was built using a soft independent modeling class analysis (SIMCA) algorithm, and a back propagation neural network model was established by Pytorch software to identify and differentiate samples from different regions. The results illustrated that, although the volatile flavor of 'black pearl' fresh corns from different origins were similar, it also showed obvious origin characteristics. SIMCA model could effectively distinguish whether unknown samples come from Heilongjiang (the accuracy rate was 97%), while BP neural network model could predict and identify the origin of 'black pearl' fresh corns from unknown production areas, and the average accuracy rate was 99.44%. The combination of electronic nose technology and BP neural network model could accurately distinguish and identify the origin of 'black pearl' fresh corns

Enhancer trapping and annotation in Zebrafish mediated with Sleeping Beauty, piggyBac and Tol2 transposons

Although transposon-mediated enhancer trapping (ET) is successfully applied in diverse models, the efficiency of various transposon systems varies significantly, and little information is available regarding efficiency of enhancer trapping by various transposons in zebrafish. Most potential enhancers (Ens) still lack evidence of actual En activity. Here, we compared the differences in ET efficiency between sleeping beauty (SB), piggyBac (PB) and Tol2 transposons. Tol2 represented the highest germline transfer efficiencies at 55.56% (NF0 = 165), followed by SB (38.36%, NF0 = 151) and PB (32.65%, NF0 = 149). ET lines generated by the Tol2 transposon tended to produce offspring with a single expression pattern per line, while PB and SB tended to generate embryos with multiple expression patterns. In our tests, 10 putative Ens (En1&#8315;10) were identified by splinkerette PCR and comparative genomic analysis. Combining the GFP expression profiles and mRNA expression patterns revealed that En1 and En2 may be involved in regulation of the expression of dlx1a and dlx2a, while En6 may be involved in regulation of the expression of line TK4 transgene and rps26, and En7 may be involved in the regulation of the expression of wnt1 and wnt10b. Most identified Ens were found to be transcribed in zebrafish embryos, and their regulatory function may involve eRNAs

Anthropogenic influences on extremely persistent seasonal precipitation in Southern China during May–June 2022

Precipitation in southern China during April–June 2022 was the highest since 1961. Anthropogenic forcing has reduced the probability of 2022-like Rx30day precipitation by about 45% based on CMIP6 simulations

Inhomogeneous d-wave superconducting state of a doped Mott insulator

Recent scanning tunneling microscope (STM) measurements discovered remarkable electronic inhomogeneity, i.e. nano-scale spatial variations of the local density of states (LDOS) and the superconducting energy gap, in the high-Tc superconductor BSCCO. Based on the experimental findings we conjectured that the inhomogeneity arises from variations in local oxygen doping level and may be generic of doped Mott insulators which behave rather unconventionally in screening the dopant ionic potentials at atomic scales comparable to the short coherence length. Here, we provide theoretical support for this picture. We study a doped Mott insulator within a generalized t-J model, where doping is accompanied by ionic Coulomb potentials centered in the BiO plane. We calculate the LDOS spectrum, the integrated LDOS, and the local superconducting gap, make detailed comparisons to experiments, and find remarkable agreement with the experimental data. We emphasize the unconventional screening in a doped Mott insulator and show that nonlinear screening dominates at nano-meter scales which is the origin of the electronic inhomogeneity. It leads to strong inhomogeneous redistribution of the local hole density and promotes the notion of a local doping concentration. We find that the inhomogeneity structure manifests itself at all energy scales in the STM tunneling differential conductance, and elucidate the similarity and the differences between the data obtained in the constant tunneling current mode and the same data normalized to reflect constant tip-to-sample distance. We also discuss the underdoped case where nonlinear screening of the ionic potential turns the spatial electronic structure into a percolative mixture of patches with smaller pairing gaps embedded in a background with larger gaps to single particle excitations.Comment: 19 pages, final versio