Structural variants (SVs) represent a major source of genetic diversity and are related to numerous agronomic traits and evolutionary events; however, their comprehensive identification and ...characterization in cucumber (Cucumis sativus L.) have been hindered by the lack of a high-quality pan-genome. Here, we report a graph-based cucumber pan-genome by analyzing twelve chromosome-scale genome assemblies. Genotyping of seven large chromosomal rearrangements based on the pan-genome provides useful information for use of wild accessions in breeding and genetic studies. A total of ~4.3 million genetic variants including 56,214 SVs are identified leveraging the chromosome-level assemblies. The pan-genome graph integrating both variant information and reference genome sequences aids the identification of SVs associated with agronomic traits, including warty fruits, flowering times and root growth, and enhances the understanding of cucumber trait evolution. The graph-based cucumber pan-genome and the identified genetic variants provide rich resources for future biological research and genomics-assisted breeding.
Cucurbitacins are triterpenoids that confer a bitter taste in cucurbits such as cucumber, melon, watermelon, squash, and pumpkin. These compounds discourage most pests on the plant and have also been ...shown to have antitumor properties. With genomics and biochemistry, we identified nine cucumber genes in the pathway for biosynthesis of cucurbitacin C and elucidated four catalytic steps. We discovered transcription factors Bl (Bitter leaf) and Bt (Bitter fruit) that regulate this pathway in leaves and fruits, respectively. Traces in genomic signatures indicated that selection imposed on Bt during domestication led to derivation of nonbitter cucurbits from their bitter ancestors.
The efficacy of government interventions in epidemic has become a hot subject since the onset of COVID-19. There is however much variation in the results quantifying the effects of interventions, ...which is partly related to the varying modelling approaches employed by existing studies. Among the many factors affecting the modelling results, people's voluntary behavior change is less examined yet likely to be widespread. This paper therefore aims to analyze how the choice of modelling approach, in particular how voluntary behavior change is accounted for, would affect the intervention effect estimation. We conduct the analysis by experimenting different modelling methods on a same data set composed of the 500 most infected U.S. counties. We compare the most frequently used methods from the two classes of modelling approaches, which are Bayesian hierarchical model from the class of computational approach and difference-in-difference from the class of natural experimental approach. We find that computational methods that do not account for voluntary behavior changes are likely to produce larger estimates of intervention effects as assumed. In contrast, natural experimental methods are more likely to extract the true effect of interventions by ruling out simultaneous behavior change. Among different difference-in-difference estimators, the two-way fixed effect estimator seems to be an efficient one. Our work can inform the methodological choice of future research on this topic, as well as more robust re-interpretation of existing works, to facilitate both future epidemic response plans and the science of public health.
GOALS:The goal of this study was to observe the bacterial colonization in the intestinal mucosa in the patients with diarrhea predominant irritable bowel syndrome (IBS-D) and ulcerative colitis (UC), ...and compare the mucosa-associated microbiota among the IBS-D patients, UC patients and the healthy control, and explore the correlation of the mucosa-associated microbiota with clinical manifestations.
STUDY:A total of 20 IBS-D patients, 28 patients with UC (16 active, 12 inactive) and 16 healthy subjects were enrolled in the study. They all underwent colonoscopies in the Gastrointestinal Endoscopy Center in the Second Affiliated Hospital of Xi’an Jiaotong University from June 2016 to October 2016. The mucosa specimens were taken at the junction of rectum and sigmoid colon for fluorescent in situ hybridization (FISH). Then the observed mucosa-associated microbiota was counted and compared.
RESULTS:(1) In the IBS-D patients, the mucosa-associated bacteria were found to colonize in the surface of mucosa and the adjacent mucin layer. And in active UC, Escherichia coli, and Bacteroides were found in the lamina propria, in addition to bacterial colonization in the above-mentioned areas. (2) The total count of mucosa-associated bacteria and the individual counts of E. coli, Clostridium, and Bacteroides were significantly increased, and Bifidobacteria significantly decreased (P<0.05) in the IBS-D patients and UC patients. Counts of Lactobacillus were decreased only in UC patients compared with the healthy control. And a significantly larger variation of the above-mentioned bacterial counts was found in the patients with UC, particularly in those with active UC, compared with those with IBS-D (P<0.05); the counts in the UC group were 1.3 to 5.3 times more or less than those in the IBS-D group. (3) Compared with healthy controls and IBS-D, the total count of bacteria and the individual counts of E. coli and Bacteroides in the lamina propria in active UC were significantly increased (P<0.05). (4) A significant negative correlation of the counts of Lactobacillus and Bifidobacteria with the defecation frequency and fecal characteristics (P<0.05) was found in the IBS-D patients; in those with UC, both the total count of bacteria and the individual counts of E. coli, Clostridium, Bacteroides, Lactobacillus, and Bifidobacteria were significantly correlated, positively or negatively, with the related clinical manifestations and the activity of the disease (P<0.05).
CONCLUSIONS:Compared with the healthy control, intestinal microecology was changed most obviously in UC with much smaller differences though in the same direction in IBS-D. The translocation of some bacteria into the lamina propria was found in UC, particularly in active UC. The changes of mucosa-associated microbiota were related more or less to some clinical manifestations in IBS-D and UC.
TRIM15 is a member of tripartite motif-containing protein (TRIM) protein family, which plays important roles in several cancers. The aim of the present study was to evaluate the role of TRIM15 in ...esophageal squamous cell carcinoma (ESCC). Our results showed that TRIM15 was upregulated in human ESCC tissues and cell lines.
In vitro
studies showed that knockdown of TRIM15 significantly inhibited the proliferation, migration, and invasion of ESCC cells. Knockdown of TRIM15 caused a significant increase in E-cadherin expression, as well as decreases in expression of N-cadherin and Vimentin proteins. Moreover,
in vivo
assay proved that tumor growth was suppressed by knockdown of TRIM15. Furthermore, the protein expression levels of β-catenin, C-myc, and CyclinD1 were markedly decreased in sh-TRIM15-infected ESCC cells. Additionally, treatment with LiCl reversed the inhibitory effects of TRIM15 knockdown on ESCC cells. In conclusion, these findings indicated that knockdown of TRIM15 blocked the growth and metastasis of ESCC in part through inhibiting the Wnt/β-catenin signaling pathway. Thus, TRIM15 might serve as a promising therapeutic target for ESCC.
Key message
A novel dwarf cucumber mutant,
scp
-
2
,
displays a typical BR biosynthesis-deficient phenotype, which is due to a mutation in
CsDET2
for a steroid 5-alpha-reductase.
Brassinosteroids ...(BRs) are a group of plant hormones that play important roles in the development of plant architecture, and extreme dwarfism is a typical outcome of BR-deficiency. Most cucumber (
Cucumis sativus
L.) varieties have an indeterminate growth habit, and dwarfism may have its value in manipulation of plant architecture and improve production in certain production systems. In this study, we identified a spontaneous dwarf mutant,
super compact
-
2
(
scp
-
2
), that also has dark green, wrinkle leaves. Genetic analyses indicated that
scp
-
2
was different from two previously reported dwarf mutants:
compact
(
cp
) and
super compact
-
1
(
scp
-
1
). Map-based cloning revealed that the mutant phenotype was due to two single nucleotide polymorphism and a single-base insertion in the
CsDET2
gene that resulted in a missense mutation in a conserved amino acid and thus a truncated protein lacking the conserved catalytic domains in the predicted steroid 5
α
-reductase protein. Measurement of endogenous hormone levels indicated a reduced level of brassinolide (BL, a bioactive BR) in
scp
-
2
, and the mutant phenotype could be partially rescued by the application of epibrassinolide (EBR). In addition,
scp
-
2
mutant seedlings exhibited dark-grown de-etiolation, and defects in cell elongation and vascular development. These data support that
scp
-
2
is a BR biosynthesis-deficient mutant, and that the
CsDET2
gene plays a key role in BR biosynthesis in cucumber. We also described the systemic BR responses and discussed the specific BR-related phenotypes in cucumber plants.
Due to the increasing importance of food quality/safety control, there is an imminent need to develop efficient methods for the rapid detection of pesticide residues in agricultural products. Herein, ...we proposed a simple and rapid detection approach to the in situ detection of residual pesticides on fruit/vegetable using surface-enhanced Raman spectroscopy (SERS). Flexible and transparent SERS substrates were fabricated by transferring Au@Ag core-shell nanorods (Au@Ag NRs) arrays to silicone membranes, with the single-layer Au@Ag NRs arrays prepared by the liquid–liquid interface self-assembly method. The as-prepared SERS sensor showed excellent SERS activity and repeatability, and it could be readily pasted onto the surface of fruit and vegetables for residual pesticide detection. For the inspection of thiram in contaminated strawberries, apples, and mushrooms, the limit of detection (LOD) could reach 2 ng/cm2 with high measurement recovery and reproducibility. In general, this work provides an effective way for the preparation and application of flexible and transparent SERS substrates in food-safety control.
In this paper, a theory is developed for analysis of steel-concrete composite beams with interfacial slip and shear deformation in steel considered. Closed-form solutions are derived for simply ...supported composite beam under uniform and mid-span concentrated load respectively. Examples are given to compute various quantities of beams. Comparing the results calculated by closed-form solutions with those by ANSYS, good agreements are found. Finally, an explicit formula for the equivalent bending stiffness of the composite beams is found by which the deflections of the composite beams can be calculated as if they were common Bernoulli beams.
•A theory is developed for composite beams with slip and shear deformation of steel.•Closed-form solutions are derived and verified by ANSYS.•An equivalent bending stiffness is found to simply calculate deflections.
Short-term demand forecasting for on-demand ride-hailing services is a fundamental issue in intelligent transportation systems. However, previous research predominantly focused on improving ...prediction accuracy, ignoring fairness issues such as systematic underestimations of travel demand in disadvantaged neighborhoods. This study investigates how to measure, evaluate, and enhance prediction fairness between disadvantaged and privileged communities in spatial-temporal demand forecasting of ride-hailing services. We developed a socially-aware neural network (SA-Net) that integrates socio-demographics and ridership information for fair demand prediction, and introduced a bias-mitigation regularization to reduce the prediction error gap between black and non-black, and low-income and high-income communities. The experimental results, using Chicago Transportation Network Company (TNC) data, demonstrate that our de-biasing SA-Net model outperforms other models in both prediction accuracy and fairness. Notably, the SA-Net exhibits a significant improvement in prediction accuracy, reducing 2.3% in Mean Absolute Error (MAE) compared to state-of-the-art models. When coupled with the bias-mitigation regularization, the de-biasing SA-Net effectively bridges the mean percentage prediction error (MPE) gap between the disadvantaged and privileged groups, and protects the disadvantaged regions against systematic underestimation of TNC demand. Specifically, our approach reduces the MPE gap between black and non-black communities by 67% without compromising overall prediction accuracy.