Browsing by Author "Zhao J"

Now showing 1 - 4 of 4
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    Antagonistic systemin receptors integrate the activation and attenuation of systemic wound signaling in tomato.
    (Elsevier B.V., 2024-12-03) Zhou K; Wu F; Deng L; Xiao Y; Yang W; Zhao J; Wang Q; Chang Z; Zhai H; Sun C; Han H; Du M; Chen Q; Yan J; Xin P; Chu J; Han Z; Chai J; Howe GA; Li C-B; Li C
    Pattern recognition receptor (PRR)-mediated perception of damage-associated molecular patterns (DAMPs) triggers the first line of inducible defenses in both plants and animals. Compared with animals, plants are sessile and regularly encounter physical damage by biotic and abiotic factors. A longstanding problem concerns how plants achieve a balance between wound defense response and normal growth, avoiding overcommitment to catastrophic defense. Here, we report that two antagonistic systemin receptors, SYR1 and SYR2, of the wound peptide hormone systemin in tomato act in a ligand-concentration-dependent manner to regulate immune homeostasis. Whereas SYR1 acts as a high-affinity receptor to initiate systemin signaling, SYR2 functions as a low-affinity receptor to attenuate systemin signaling. The expression of systemin and SYR2, but not SYR1, is upregulated upon SYR1 activation. Our findings provide a mechanistic explanation for how plants appropriately respond to tissue damage based on PRR-mediated perception of DAMP concentrations and have implications for uncoupling defense-growth trade-offs.
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    Effect of Berberine on Cardiovascular Disease Risk Factors: A Mechanistic Randomized Controlled Trial.
    (MDPI (Basel, Switzerland), 2021-07-26) Zhao JV; Yeung W-F; Chan Y-H; Vackova D; Leung JYY; Ip DKM; Zhao J; Ho W-K; Tse H-F; Schooling CM
    Cardiovascular disease (CVD) is a major contributor to the global burden of disease. Berberine, a long-standing, widely used, traditional Chinese medicine, is thought to have beneficial effects on CVD risk factors and in women with polycystic ovary syndrome. The mechanisms and effects, specifically in men, possibly via testosterone, have not been examined previously. To assess the effect of berberine on CVD risk factors and any potential pathway via testosterone in men, we conducted a randomized, double-blind, placebo-controlled, parallel trial in Hong Kong. In total, 84 eligible Chinese men with hyperlipidemia were randomized to berberine (500 mg orally, twice a day) or placebo for 12 weeks. CVD risk factors (lipids, thromboxane A2, blood pressure, body mass index and waist-hip ratio) and testosterone were assessed at baseline, and 8 and 12 weeks after intervention. We compared changes in CVD risk factors and testosterone after 12 weeks of intervention using analysis of variance, and after 8 and 12 weeks using generalized estimating equations (GEE). Of the 84 men randomized, 80 men completed the trial. Men randomized to berberine had larger reductions in total cholesterol (-0.39 mmol/L, 95% confidence interval (CI) -0.70 to -0.08) and high-density lipoprotein cholesterol (-0.07 mmol/L, 95% CI -0.13 to -0.01) after 12 weeks. Considering changes after 8 and 12 weeks together, berberine lowered total cholesterol and possibly low-density lipoprotein-cholesterol (LDL-c), and possibly increased testosterone. Changes in triglycerides, thromboxane A2, blood pressure, body mass index and waist-hip ratio after the intervention did not differ between the berberine and placebo groups. No serious adverse event was reported. Berberine is a promising treatment for lowering cholesterol. Berberine did not lower testosterone but instead may increase testosterone in men, suggesting sex-specific effects of berberine. Exploring other pathways and assessing sex differences would be worthwhile, with relevance to drug repositioning and healthcare.
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    Optimizing nitrogen and phosphorus application to improve soil organic carbon and alfalfa hay yield in alfalfa fields
    (Frontiers Media South Africa, 2023) Wei K; Zhao J; Sun Y; López IF; Ma C; Zhang Q; Wang LI
    Soil organic carbon (SOC) is the principal factor contributing to enhanced soil fertility and also functions as the major carbon sink within terrestrial ecosystems. Applying fertilizer is a crucial agricultural practice that enhances SOC and promotes crop yields. Nevertheless, the response of SOC, active organic carbon fraction and hay yield to nitrogen and phosphorus application is still unclear. The objective of this study was to investigate the impact of nitrogen-phosphorus interactions on SOC, active organic carbon fractions and hay yield in alfalfa fields. A two-factor randomized group design was employed in this study, with two nitrogen levels of 0 kg·ha-1 (N0) and 120 kg·ha-1 (N1) and four phosphorus levels of 0 kg·ha-1 (P0), 50 kg·ha-1 (P1), 100 kg·ha-1 (P2) and 150 kg·ha-1 (P3). The results showed that the nitrogen and phosphorus treatments increased SOC, easily oxidized organic carbon (EOC), dissolved organic carbon (DOC), particulate organic carbon (POC), microbial biomass carbon (MBC) and hay yield in alfalfa fields, and increased with the duration of fertilizer application, reaching a maximum under N1P2 or N1P3 treatments. The increases in SOC, EOC, DOC, POC, MBC content and hay yield in the 0-60 cm soil layer of the alfalfa field were 9.11%-21.85%, 1.07%-25.01%, 6.94%-22.03%, 10.36%-44.15%, 26.46%-62.61% and 5.51%-23.25% for the nitrogen and phosphorus treatments, respectively. The vertical distribution of SOC, EOC, DOC and POC contents under all nitrogen and phosphorus treatments was highest in the 0-20 cm soil layer and tended to decrease with increasing depth of the soil layer. The MBC content was highest in the 10-30 cm soil layer. DOC/SOC, MBC/SOC (excluding N0P1 treatment) and POC/SOC were all higher in the 0-40 cm soil layer of the alfalfa field compared to the N0P0 treatment, indicating that the nitrogen and phosphorus treatments effectively improved soil fertility, while EOC/SOC and DOC/SOC were both lower in the 40-60 cm soil layer than in the N0P0 treatment, indicating that the nitrogen and phosphorus treatments improved soil carbon sequestration potential. The soil layer between 0-30 cm exhibited the highest sensitivity index for MBC, whereas the soil layer between 30-60 cm had the highest sensitivity index for POC. This suggests that the indication for changes in SOC due to nitrogen and phosphorus treatment shifted from MBC to POC as the soil depth increased. Meanwhile, except the 20-30 cm layer of soil in the N0P1 treatment and the 20-50 cm layer in the N1P0 treatment, all fertilizers enhanced the soil Carbon management index (CMI) to varying degrees. Structural equation modeling shows that nitrogen and phosphorus indirectly affect SOC content by changing the content of the active organic carbon fraction, and that SOC is primarily impacted by POC and MBC. The comprehensive assessment indicated that the N1P2 treatment was the optimal fertilizer application pattern. In summary, the nitrogen and phosphorus treatments improved soil fertility in the 0-40 cm soil layer and soil carbon sequestration potential in the 40-60 cm soil layer of alfalfa fields. In agroecosystems, a recommended application rate of 120 kg·ha-1 for nitrogen and 100 kg·ha-1 for phosphorus is the most effective in increasing SOC content, soil carbon pool potential and alfalfa hay yield
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    Potential rapid intraoperative cancer diagnosis using dynamic full-field optical coherence tomography and deep learning: A prospective cohort study in breast cancer patients
    (Elsevier B V on behalf of the Science China Press, 2024-06-15) Zhang S; Yang B; Yang H; Zhao J; Zhang Y; Gao Y; Monteiro O; Zhang K; Liu B; Wang S
    An intraoperative diagnosis is critical for precise cancer surgery. However, traditional intraoperative assessments based on hematoxylin and eosin (H&E) histology, such as frozen section, are time-, resource-, and labor-intensive, and involve specimen-consuming concerns. Here, we report a near-real-time automated cancer diagnosis workflow for breast cancer that combines dynamic full-field optical coherence tomography (D-FFOCT), a label-free optical imaging method, and deep learning for bedside tumor diagnosis during surgery. To classify the benign and malignant breast tissues, we conducted a prospective cohort trial. In the modeling group (n = 182), D-FFOCT images were captured from April 26 to June 20, 2018, encompassing 48 benign lesions, 114 invasive ductal carcinoma (IDC), 10 invasive lobular carcinoma, 4 ductal carcinoma in situ (DCIS), and 6 rare tumors. Deep learning model was built up and fine-tuned in 10,357 D-FFOCT patches. Subsequently, from June 22 to August 17, 2018, independent tests (n = 42) were conducted on 10 benign lesions, 29 IDC, 1 DCIS, and 2 rare tumors. The model yielded excellent performance, with an accuracy of 97.62%, sensitivity of 96.88% and specificity of 100%; only one IDC was misclassified. Meanwhile, the acquisition of the D-FFOCT images was non-destructive and did not require any tissue preparation or staining procedures. In the simulated intraoperative margin evaluation procedure, the time required for our novel workflow (approximately 3 min) was significantly shorter than that required for traditional procedures (approximately 30 min). These findings indicate that the combination of D-FFOCT and deep learning algorithms can streamline intraoperative cancer diagnosis independently of traditional pathology laboratory procedures.