Characterization and stress-responsive regulation of CmPHT1 genes involved in phosphate uptake and transport in Melon (Cucumis melo L.).

BACKGROUND: Phosphorus (P) deficiency, a major nutrient stress, greatly hinders plant growth. Phosphate (Pi) uptake in plant roots relies on PHT1 family transporters. However, melon (Cucumis melo L.) lacks comprehensive identification and characterization of PHT1 genes, particularly their response patterns under diverse stresses. RESULTS: This study identified and analyzed seven putative CmPHT1 genes on chromosomes 3, 4, 5, 6, and 7 using the melon genome. Phylogenetic analysis revealed shared motifs, domain compositions, and evolutionary relationships among genes with close histories. Exon number varied from 1 to 3. Collinearity analysis suggested segmental and tandem duplications as the primary mechanisms for CmPHT1 gene family expansion. CmPHT1;4 and CmPHT1;5 emerged as a tandemly duplicated pair. Analysis of cis-elements in CmPHT1 promoters identified 14 functional categories, including putative PHR1-binding sites (P1BS) in CmPHT1;4, CmPHT1;6, and CmPHT1;7. We identified that three WRKY transcription factors regulated CmPHT1;5 expression by binding to its W-box element. Notably, CmPHT1 promoters harbored cis-elements responsive to hormones and abiotic factors. Different stresses regulated CmPHT1 expression differently, suggesting that the adjusted expression patterns might contribute to plant adaptation. CONCLUSIONS: This study unveils the characteristics, evolutionary diversity, and stress responsiveness of CmPHT1 genes in melon. These findings lay the foundation for in-depth investigations into their functional mechanisms in Cucurbitaceae crops.

MRI Assessment of Brain Frailty and Clinical Outcome in Patients With Acute Posterior Perforating Artery Infarction.

BACKGROUND: Global brain health has gained increasing attention recently. Imaging markers of brain frailty have been related to functional outcomes in previous studies on anterior circulation; however, little data are available on imaging markers and posterior circulation. PURPOSE: To investigate the impact of brain frailty on functional outcomes in patients with acute perforating artery infarction (PAI) of the posterior circulation. STUDY TYPE: Prospective. POPULATION: One hundred patients (60.78 ± 9.51 years, 72% men) with acute posterior circulation PAI (determined by diffusion-weighted magnetic resonance imaging (MRI)/time-of-flight MR angiography). FIELD STRENGTH/SEQUENCE: T1- and T2-weighted fast spin echo, T2-weighted fluid-attenuated inversion recovery, diffusion-weighted echo planar, gradient echo (susceptibility-weight imaging), and 3D time-of-flight MR angiography sequences at 3.0 T. ASSESSMENT: Periventricular and deep white matter hyperintensities (WMH), enlarged perivascular spaces (EPVS) in the basal ganglia and centrum semiovale area, lacunes, cerebral microbleeds (CMB), and total brain frailty score by calculating the above imaging characters were rated visually by three radiologists with 9, 10, and 11 years of experience and one neuroradiologist with 12. Infarction volume was assessed using baseline diffusion-weighted imaging (DWI) data obtained within 24 hours of symptom onset. A modified Rankin Scale (mRS) score >1 on day 90 defined an adverse functional outcome. Associations between the imaging markers of brain frailty and functional outcomes were assessed. STATISTICAL TESTS: Fisher's exact test, Mann-Whitney U test, and multivariable binary logistic regression. A P value <0.05 was considered statistically significant. RESULTS: Adverse prognoses (mRS > 1) were observed in 34 (34%) patients. Infarction volume, periventricular WMH, deep WMH, basal ganglia EPVS, CMB, and the brain frailty score were significantly associated with adverse functional outcomes. An increased brain frailty score was significantly associated with unfavorable mRS score on day 90 (odds ratio 1.773, 95% confidence interval 1.237-2.541). DATA CONCLUSION: Advanced MRI imaging markers of brain frailty, individually or combined as a total brain frailty score, were associated with worse functional outcomes after acute posterior circulation PAI. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 3.

Deep medullary vein damage correlates with small vessel disease in small vessel occlusion acute ischemic stroke.

OBJECTIVES: We aim to investigate whether cerebral small vessel disease (cSVD) imaging markers correlate with deep medullary vein (DMV) damage in small vessel occlusion acute ischemic stroke (SVO-AIS) patients. METHODS: The DMV was divided into six segments according to the regional anatomy. The total DMV score (0-18) was calculated based on segmental continuity and visibility. The damage of DMV was grouped according to the quartiles of the total DMV score. Neuroimaging biomarkers of cSVD including white matter hyperintensity (WMH), cerebral microbleed (CMB), perivascular space (PVS), and lacune were identified. The cSVD score were further analyzed. RESULTS: We included 229 SVO-AIS patients, the mean age was 63.7 ± 23.1 years, the median NIHSS score was 3 (IQR, 2-6). In the severe DMV burden group (the 4th quartile), the NIHSS score grade (6 (3-9)) was significantly higher than other groups (p < 0.01). The grade scores for basal ganglia PVS (BG-PVS) were positively correlated with the degree of DMV (R = 0.67, p < 0.01), rather than centrum semivole PVS (CS-PVS) (R = 0.17, p = 0.1). In multivariate analysis, high CMB burden (adjusted odds ratio [aOR], 25.38; 95% confidence interval [CI], 1.87-345.23) was associated with severe DMV scores. In addition, BG-PVS was related to severe DMV burden in a dose-dependent manner: when BG-PVS score was 3 and 4, the aORs of severe DMV burden were 18.5 and 12.19, respectively. CONCLUSION: The DMV impairment was associated with the severity of cSVD, which suggests that DMV burden may be used for risk stratification in SVO-AIS patients. CLINICAL RELEVANCE STATEMENT: The DMV damage score, based on the association between small vessel disease and the deep medullary veins impairment, is a potential new imaging biomarker for the prognosis of small vessel occlusion acute ischemic stroke, with clinical management implications. KEY POINTS: • The damage to the deep medullary vein may be one mechanism of cerebral small vessel disease. • Severe burden of the basal ganglia perivascular space and cerebral microbleed is closely associated with significant impairment to the deep medullary vein. • The deep medullary vein damage score may reflect a risk of added vascular damage in small vessel occlusion acute ischemic stroke patients.

A machine-learning approach based on multiparametric MRI to identify the risk of non-sentinel lymph node metastasis in patients with early-stage breast cancer.

BACKGROUND: It has been reported that patients with early breast cancer with 1-2 positive sentinel lymph nodes have a lower risk of non-sentinel lymph node (NSLN) metastasis and cannot benefit from axillary lymph node dissection. PURPOSE: To develop the potential of machine learning based on multiparametric magnetic resonance imaging (MRI) and clinical factors for predicting the risk of NSLN metastasis in breast cancer. MATERIAL AND METHODS: This retrospective study included 144 patients with 1-2 positive sentinel lymph node breast cancer. Multiparametric MRI morphologic findings and the detailed demographical characteristics of the primary tumor and axillary lymph node were extracted. The logistic regression, support vector classification, extreme gradient boosting, and random forest algorithm models were established to predict the risk of NSLN metastasis. The prediction efficiency of a machine-learning-based model was evaluated. Finally, the relative importance of each input variable was analyzed for the best model. RESULTS: Of the 144 patients, 80 (55.6%) developed NSLN metastasis. A total of 24 imaging features and 14 clinicopathological features were analyzed. The extreme gradient boosting algorithm had the strongest prediction efficiency with an area under curve of 0.881 and 0.781 in the training set and test set, respectively. Five main factors for the metastasis of NSLN were found, including histological grade, cortical thickness, fatty hilum, short axis of lymph node, and age. CONCLUSION: The machine-learning model incorporating multiparametric MRI features and clinical factors can predict NSLN metastasis with high accuracy for breast cancer and provide predictive information for clinical protocol.

Comprehensive review: Effects of climate change and greenhouse gases emission relevance to environmental stress on horticultural crops and management.

Global climate change exerts a significant impact on sustainable horticultural crop production and quality. Rising Global temperatures have compelled the agricultural community to adjust planting and harvesting schedules, often necessitating earlier crop cultivation. Notably, climate change introduces a suite of ominous factors, such as greenhouse gas emissions (CGHs), including elevated temperature, increased carbon dioxide (CO2) concentrations, nitrous oxide (N2O) and methane (CH4) ozone depletion (O3), and deforestation, all of which intensify environmental stresses on crops. Consequently, climate change stands poised to adversely affect crop yields and livestock production. Therefore, the primary objective of the review article is to furnish a comprehensive overview of the multifaceted factors influencing horticulture production, encompassing fruits, vegetables, and plantation crops with a particular emphasis on greenhouse gas emissions and environmental stressors such as high temperature, drought, salinity, and emission of CO2. Additionally, this review will explore the implementation of novel horticultural crop varieties and greenhouse technology that can contribute to mitigating the adverse impact of climate change on agricultural crops.

Modulating plant-soil microcosm with green synthesized ZnONPs in arsenic contaminated soil.

Biogenic nanoparticle (NP), derived from plant sources, is gaining prominence as a viable, cost-effective, sustainable, and biocompatible alternative for mitigating the extensive environmental impact of arsenic on the interplay between plant-soil system. Herein, the impact of green synthesized zinc oxide nanoparticles (ZnONPs) was assessed on Catharanthus roseus root system-associated enzymes and their possible impact on microbiome niches (rhizocompartments) and overall plant performance under arsenic (As) gradients. The application of ZnONPs at different concentrations successfully modified the arsenic uptake in various plant parts, with the root arsenic levels increasing 1.5 and 1.4-fold after 25 and 50 days, respectively, at medium concentration compared to the control. Moreover, ZnONPs gradients regulated the various soil enzyme activities. Notably, urease and catalase activities showed an increase when exposed to low concentrations of ZnONPs, whereas saccharase and acid phosphatase displayed the opposite pattern, showing increased activities under medium concentration which possibly in turn influence the plant root system associated microflora. The use of nonmetric multidimensional scaling ordination revealed a significant differentiation (with a significance level of p < 0.05) in the structure of both bacterial and fungal communities under different treatment conditions across root associated niches. Bacterial and fungal phyla level analysis showed that Proteobacteria and Basidiomycota displayed a significant increase in relative abundance under medium ZnONPs concentration, as opposed to low and high concentrations, respectively. Similarly, in depth genera level analysis revealed that Burkholderia, Halomonas, Thelephora and Sebacina exhibited a notably high relative abundance in both the rhizosphere and rhizoplane (the former refers to the soil region influenced by root exudates, while the latter is the root surface itself) under medium concentrations of ZnONPs, respectively. These adjustments to the plant root-associated microcosm likely play a role in protecting the plant from oxidative stress by regulating the plant's antioxidant system and overall biomass.

Impact of the Alberta Stroke Program CT Score subregions on long-term functional outcomes in acute ischemic stroke: Results from two multicenter studies in China.

Background and Objectives: The Alberta Stroke Program CT Score (ASPECTS) is a widely used rating system for assessing infarct extent and location. We aimed to investigate the prognostic value of ASPECTS subregions' involvement in the long-term functional outcomes of acute ischemic stroke (AIS). Materials and Methods: Consecutive patients with AIS and anterior circulation large-vessel stenosis and occlusion between January 2019 and December 2020 were included. The ASPECTS score and subregion involvement for each patient was assessed using posttreatment magnetic resonance diffusion-weighted imaging. Univariate and multivariable regression analyses were conducted to identify subregions related to 3-month poor functional outcome (modified Rankin Scale scores, 3-6) in the reperfusion and medical therapy cohorts, respectively. In addition, prognostic efficiency between the region-based ASPECTS and ASPECTS score methods were compared using receiver operating characteristic curves and DeLong's test. Results: A total of 365 patients (median age, 64 years; 70% men) were included, of whom 169 had poor outcomes. In the reperfusion therapy cohort, multivariable regression analyses revealed that the involvement of the left M4 cortical region in left-hemisphere stroke (adjusted odds ratio [aOR] 5.39, 95% confidence interval [CI] 1.53-19.02) and the involvement of the right M3 cortical region in right-hemisphere stroke (aOR 4.21, 95% CI 1.05-16.78) were independently associated with poor functional outcomes. In the medical therapy cohort, left-hemisphere stroke with left M5 cortical region (aOR 2.87, 95% CI 1.08-7.59) and caudate nucleus (aOR 3.14, 95% CI 1.00-9.85) involved and right-hemisphere stroke with right M3 cortical region (aOR 4.15, 95% CI 1.29-8.18) and internal capsule (aOR 3.94, 95% CI 1.22-12.78) affected were related to the increased risks of poststroke disability. In addition, region-based ASPECTS significantly improved the prognostic efficiency compared with the conventional ASPECTS score method. Conclusion: The involvement of specific ASPECTS subregions depending on the affected hemisphere was associated with worse functional outcomes 3 months after stroke, and the critical subregion distribution varied by clinical management. Therefore, region-based ASPECTS could provide additional value in guiding individual decision making and neurological recovery in patients with AIS.