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Patients with large artery occlusion-acute ischemic stroke (LAO-AIS) can experience adverse outcomes, such as brain herniation due to complications. This study aimed to construct a nomogram prediction model for prognosis in patients with LAO-AIS in order to maximize the benefits for clinical patients.Retrospective analysis of 243 LAO-AIS patients from January 2019 to January 2022 with medical history data and blood examination at admission. Univariate and multivariate analyses were conducted through binary logistic regression equation analysis, and a nomogram prediction model was constructed.Results of this study showed that hyperlipidemia (odds ratio (OR)=2.849, 95% confidence interval (CI)=1.100-7.375, P=0.031), right cerebral infarction (OR=2.144, 95%CI=1.106-4.156, P=0.024), D-Dimer500 ng/mL (OR=2.891, 95%CI=1.398-5.980, P=0.004), and neutrophil-lymphocyte ratio (NLR)7.8 (OR=2.149, 95%CI=1.093-4.225, P=0.027) were independent risk factors for poor early prognosis in patients with LAO-AIS. In addition, hypertension (OR=1.947, 95%CI=1.114-3.405, P=0.019), hyperlipidemia (OR=2.594, 95%CI=1.281-5.252, P=0.008), smoking (OR=2.414, 95%CI=1.368-4.261, P=0.002), D-dimer500 ng/mL (OR=3.170, 95%CI=1.533-6.553, P=0.002), and NLR7.8 (OR=2.144, 95%CI=1.231-3.735, P=0.007) were independent risk factors for poor long-term prognosis. The early prognosis nomogram receiver operating characteristic (ROC) curve area under the curve (AUC) value was 0.688 for the training set and 0.805 for the validation set, which was highly differentiated. The mean error was 0.025 for the training set calibration curve and 0.016 for the validation set calibration curve. Both the training and validation set decision curve analyses (DCAs) indicated that the clinical benefit of the nomogram was significant. The long-term prognosis nomogram ROC curve AUC values was 0.697 for the training set and 0.735 for the validation set, showing high differentiation. The mean error was 0.041 for the training set calibration curve and 0.021 for the validation set calibration curve. Both of the training and validation set DCAs demonstrated a substantial clinical benefit of the nomogram.The nomogram prediction model based on admission history data and blood examination are easy-to-use tools that provide an accurate individualized prediction for LAO-AIS patients and can assist in early clinical decisions and in obtaining an early prognosis.

Additional file 1: Table S1. Yield in field trials of XL22 and XL17 under the WW and WD conditions.

Additional file 7: Fig. S1. Consumed water analysis of XL22 and XL17 under the WW and WD conditions. A. Plant phenotyping of XL22 and XL17 at bud stage under the WW and WD conditions. B. Consumed water content of XL22 and XL17 under the WW and WD conditions. WW, well-watered; WD, water deficit. The scales bars are indicated with white lines. Error bars are standard errors. Values represent the means ± SE, n = 3. Different letters above the bars indicate statistically different from each other as determined by the Student’s t test: p < 0.05. Fig. S2. SEM observation of the leaves surface wax of XL22 and XL17 under the WW and WD conditions. a and b. XL22 leaf at the seedling stage under WW and WD condition, respectively. c and d. XL22 leaf at the bud stage under WW and WD condition, respectively. e and f. XL17 leaf at the seedling stage under WW and WD condition, respectively. g and h. XL17 leaf at the bud stage under WW and WD condition, respectively. i, j, k and l, the adaxial surface of XL22 leaf corresponds to a, b, c and d. m, n, o and p, the adaxial surface of XL17 leaf corresponds to e, f, g and h. The waxy crystals as indicated by the arrows. WW, well-watered; WD, water deficit. SS-22, XL22 leaves at seedling stage; SS-17, XL17 leaves at seedling stage; BS-22, XL22 leaves at bud stage; BS-17, XL17 leaves at bud stage. Fig. S3. Total wax content of cotton leaves of XL22 and XL17 under WW and WD conditions. WW, well-watered; WD, water deficit. SS, the seedling stage; BS, the bud stage. Error bars are standard errors. Values represent the means ± SE, n = 3. Different letters above the bars indicate statistically different from each other as determined by the Student’s t test: p < 0.05. Fig. S4. Heatmap showing the relative expression levels of the 9 selected genes in the two cotton varieties determined by RNA-seq analysis (A) and qRT-PCR (B). Of the selected genes, 4 genes are involved in fatty acid synthesis and 5 genes are related to wax and cutin biosynthesis. The enzymes encoded by these genes are: Very-long-chain enoyl-CoA reductase (GH_D10G2517), Very-long-chain 3-oxoacyl-CoA reductase 1 (GH_D03G1424), 3-oxoacyl-acyl-carrier-protein synthase II (GH_A13G2186), Stearoyl-acyl-carrier-protein 9-desaturase (GH_D10G1329), Delta(12)-fatty-acid desaturase (GH_A11G3588), Probable peroxygenase 4 (GH_A12G1707), Cytochrome P450 86A22 (GH_A08G2095), Very-long-chain -3-hydroxyacyl-CoA dehydratase (GH_D11G2259), Very-long-chain-3-hydroxyacyl-CoA dehydratase 2 (GH_A03G0493). S/W: well-watered plants at the seedling stage, S/D: water deficit plants at the seedling stage, B/W: well-watered plants at the bud stage, B/D: water deficit plants at the bud stage. GhUBI was used as a reference gene. All qRT–PCR reactions were performed in triplicate. Fig. S5. KEGG analysis of DEGs at the seedling stage of XL22 and XL17. A. KEGG categories of DEGs at the seedling stage of XL22. B. KEGG categories of DEGs at the seedling stage of XL17. Fig. S6. Heatmap comparison of DEGs associated with two cotton varieties. A. Venn diagram showing the different KEGGs at the two stages of XL22 and XL17. B and C show the DEGs at the seedling stage of XL22. D and E show the DEGs at the seedling stage of XL17. Red represents high expression, and blue represents low expression. Each row represents a DEG. S/W-22: well-watered XL22 at the seedling stage; S/D-22: water deficit XL22 at the seedling stage; S/W-17: well-watered XL17 at the seedling stage; S/D-17: water deficit XL17 at the seedling stage; B/W-22: well-watered XL22 at the bud stage; B/D-22: water deficit XL22 at the bud stage; B/W-17: well-watered XL17 at the bud stage; B/D-17: water deficit XL17 at the bud stage. Fig. S7. GO analysis and KEGG pathways of the black module and turquoise module genes. A. Analysis of GO enrichment of the black module genes, B. Analysis of GO enrichment of the turquoise module genes, C. KEGG categories of DEGs of the black module, D. KEGG categories of DEGs of the turquoise module. The horizontal axis represents rich factor, the vertical axis represents statistics of the enriched pathways. Circle size represents the number of genes. Red represents high KEGG enrichment, and blue represents low KEGG enrichment.

Aims Photorespiration and non-photochemical quenching of chlorophyll fluorescence in photosystem II (PSII) were studied in bracts and leaves of cotton (Gossypium hirsutum) plants, in order to investigate the photoprotective mechanisms and drought tolerance in cotton bracts under field conditions of water-saving drip irrigations. Methods Gas exchange and chlorophyll fluorescence parameters of PSII were analyzed in bracts and leaves of cotton plants after anthesis. The study was conducted with two treatments comprising normal drip irrigation (5 228.5 m 3 ·hm -2 ) and water-saving drip irrigation (3 874.1 m 3 ·hm -2 ) under field conditions. Important findings The actual photochemical efficiency of PSII (ΦPSII) decreased in both bracts and leaves of cotton plants after anthesis under water-saving drip irrigation, but the magnitude of decrease was less in bracts than in leaves. Results showed the bracts experienced less severe photoinhibition than leaves. The rate of net pho- tosynthesis (Pn), ΦPSII, net photorespiration (Pr), photochemical quenching (qP), and non-photochemical quench- ing (NPQ) decreased in the leaves of cotton plants under water-saving drip irrigation, but no significant difference was observed in the bracts. With decreasing water supply, the Pr/Pn in bracts was much higher than that in leaves and water deficit had no significant effect on the Pr/Pn in bracts. The results of chlorophyll fluorescence parame- ters showed that the quantum yield of regulated energy dissipation (Y(NPQ)) was higher in bracts than in leaves under high irradiance and temperature conditions, and that the thermal dissipation in bracts was not susceptible to water deficit, thus protecting the photosynthetic apparatus against photodamage. Overall, both photorespiration and energy dissipation in bracts were found to alleviate photoinhibition and played important roles in protecting

Cotton(Gossypium spp.),which is of tropical origin,is the most economically important textile fiber crop worldwide.Water and nitrogen are two major factors that limit the photosynthetic capacity and yield of cotton.The ability to absorb water and nutrients is closely related to the size and growing space of the root system.In Xinjiang province cotton is often cultivated at a high plant density with under-mulch drip irrigation,a method that saves both water and fertilizer application.In addition,the growing space of the root system is suppressed to a certain degree.The aim of this study was to evaluate the effects of nitrogen and water supply on photosynthesis and yield of cotton with a restricted root space grown with under-mulch drip irrigation.An improved understanding of the physiological mechanisms by which cotton acclimates to water,nitrogen supply and root restriction will be useful to improve the yield potential of cotton cultivated using this method.The experiment was conducted in Xinjiang in northwestern China from March to October,2011.Two upland cotton cultivars,Xinluzao13 and Xinluzao 33,were selected as the plant material.Plants of both cultivars were grown in soil columns to restrict the depth of the root system and regulate the supply of water and nitrogen.We measured net photosynthetic rate(Pn),stomatal conductance(Gs),maximum photochemical efficiency(Fv/Fm),photochemical efficiency of PSⅡ(ΦPSⅡ),PSⅡ photochemical quenching(qp),and the biomass of various organs at different growth stages.Under the same water and nitrogen supply from the flowering stage to the full boll opening stage,the values of qp,Gs,and Pn of root-restricted cotton plants were significantly lower compared with those of the control.This effect was greater at later growth stages.No differences in Fv/Fm and ΦPSⅡ were observed between root-restricted and control plants.The root weight of root-restricted plants at the full flowering stage and full boll opening stage was lower than that of the control.However,the dry matter accumulation in the shoot and boll and the seed cotton yield were greater in root-restricted plants than those of the control.From the flowering stage to the full boll opening stage,Pn,Gs,Fv/Fm,ΦPSⅡ,and qp of plants with the same root system volume but treated with different rates of water and nitrogen supply were ranked in the following order: W1N1(moderate water and nitrogen) W0N1(water deficiency) W1N0(nitrogen deficiency) W0N0(water and nitrogen deficiency).At the full flowering and full boll opening stages,the dry matter accumulation in the shoot and boll of root-restricted plants supplied with moderate water and nitrogen was significantly greater than that in the other treatments.Consequently,the boll number per plant,single boll weight,and seed cotton yield were markedly higher in this treatment than in the other treatments.The root system of plants grown with under-mulch drip irrigation is confined to a limited space.Therefore,effective methods to promote the yield of cotton cultivated with under-mulch drip irrigation include optimization of water and nitrogen supply at all growth stages.Moderate supply of water and nitrogen can strengthen photosynthetic ability,increase dry matter accumulation in the shoot,and increase the photosynthate distribution from shoot biomass to reproductive organs.In practice,given the small drip volume but high frequency of application to cotton plants grown with under-mulch drip irrigation,it is likely that the most effective approach to save water and increase yield simultaneously is to increase plant density and adjust the inter-and intra-row spacing among plants in order to moderately limit root growth.