Abstract Background Grain number (GN) is one of the key yield contributing factors in modern wheat (Triticum aestivum) varieties. Fruiting efficiency (FE) is a key trait for increasing GN by making more spike assimilates available to reproductive structures. Thousand grain weight (TGW) is also an important component of grain yield. To understand the genetic architecture of FE and TGW, we performed a genome-wide association study (GWAS) in a panel of 236 US soft facultative wheats that were phenotyped in three experiments at two locations in Florida and genotyped with 20,706 single nucleotide polymorphisms (SNPs) generated from genotyping-by-sequencing (GBS). Results FE showed significant positive associations with GN, grain yield (GY), and harvest index (HI). Likewise, TGW mostly had a positive correlation with GY and HI, but a negative correlation with GN. Eighteen marker-trait associations (MTAs) for FE and TGW were identified on 11 chromosomes, with nine MTAs within genes. Several MTAs associated with other traits were found within genes with different biological and metabolic functions including nuclear pore complex protein, F-box protein, oligopeptide transporter, and glycoside vacuolar protein. Two KASP markers showed significant mean differences for FE and TGW traits in a validation population. Conclusions KASP marker development and validation demonstrated the utility of these markers for improving FE and TGW in breeding programs. The results suggest that optimizing intra-spike partitioning and utilizing marker-assisted selection (MAS) can enhance GY and HI.

• Book : 25(1)
• Pub. Date : 2025
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Accurate measurement of chlorophyll content in plant leaves is crucial for evaluating plant health. Leaf radiation transfer models are commonly used to estimate chlorophyll content from remote sensing data. However, current methods often show limited accuracy in certain scenarios. This study addresses these challenges by developing a more precise method for chlorophyll content retrieval. First, the PROSPECT model, which does not fully account for optical reflection on leaf surfaces, results in lower spectral simulation accuracy. To overcome this limitation, a surface geometric feature factor (σ) is introduced, leading to the PROSPECT-LSROGF model. This enhanced model incorporates the optical reflection characteristics of the leaf surface, expands the range of light source incident angles, and more accurately describes radiative transfer within the leaf. As a result, the PROSPECT-LSROGF model shows superior spectral simulation accuracy to the traditional PROSPECT and PIOSL models. Next, to improve the retrieval accuracy of traditional BP neural networks for chlorophyll content, the Beetle Antennae Search (BAS) algorithm is used to optimize the weights and thresholds of the BP neural network, forming the BAS-BP model. By combining the PROSPECT-LSROGF model with the BAS-BP network, the PROSPECT-LSROGF-BAS-BP model is developed for accurate chlorophyll content retrieval. The performance of this model is compared with that of the gradient boosting machine retrieval and the PROSPECT-BAS-BP model. Validation is conducted using the LOPEX93, CABO, and ANGERS datasets. The PROSPECT-LSROGF-BAS-BP model achieves root mean square errors (RMSEs) of 4.186, 4.258, and 3.894 g/cm2, with determination coefficients (R2) of 0.876, 0.862, and 0.903, respectively—outperforming the other methods in terms of accuracy. These results demonstrate that the proposed method significantly improves the model’s ability to accurately estimate chlorophyll content from spectral data.

• Book : 15(1)
• Pub. Date : 2025
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Abstract Phytochemical variability in plants is driven by a complex interplay of ecological and environmental factors, including genetics, climate, and soil characteristics. Understanding these determinants is increasingly important as phytochemicals are vital in mediating plant interactions with herbivores, pathogens, and their broader ecosystem. Recent research shows the s that both abiotic factors—such as temperature fluctuations, ultraviolet radiation, and nutrient availability—and biotic factors, including herbivory and competition, have significant impacts on phytochemical profiles. Seasonal and spatial variations also influence the concentration of secondary metabolites, which are key to plant defenses and overall ecosystem health. For example, environmental stressors like drought or elevated temperatures can induce higher production of protective phytochemicals, while the developmental stage of the plant and the type of organ (leaf, root, flower) further dictate metabolite expression. This variability holds profound implications for forest conservation and climate resilience. As forests face increasing pressures from climate change, understanding the role of phytochemicals in maintaining ecosystem stability becomes critical. Phytochemicals contribute to plant fitness, species diversity, and ecological interactions, all of which are crucial for the resilience of forest ecosystems. The integration of phytochemical knowledge into forest management can promote biodiversity, enhance ecosystem services, and lead to more sustainable practices in conservation. This paper advocates for interdisciplinary research that connects ecology, chemistry, and conservation biology. Such collaboration is essential to unravel the complex relationships between phytochemical variability and environmental factors, ultimately fostering more informed conservation strategies that can safeguard forest ecosystems in the face of environmental change.

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• Pub. Date : 2025
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• Pub. Date : 2025
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Background: Multiparametric MRI (mpMRI) as a non-invasive imaging tool is important in prostate cancer (PCa) detection and localization. Combined with radiomics analysis, features extracted from mpMRI have been utilized to predict PCa aggressiveness. T2 mapping provides quantitative information in PCa diagnoses but is not routinely available in clinical practice. Previous work from our group developed a deep learning-based method to estimate T2 maps from clinically acquired T1- and T2-weighted images. This study aims to evaluate the added value of the estimated T2 map by combining it with conventional T2-weighted images for detecting clinically significant PCa (csPCa). Methods: An amount of 76 peripheral zone prostate lesions, including clinically significant and insignificant cases, were retrospectively analyzed. Radiomic features were extracted from conventional T2-weighted images and deep learning-estimated T2 maps, followed by feature selection and model development using five-fold cross-validation. Logistic regression and Gaussian Process classifiers were employed to develop the prediction models, with performance evaluated by area under the curve (AUC) and accuracy metrics. Results: The model incorporating features from both T2-weighted images and estimated T2 maps achieved an AUC of 0.803, significantly outperforming the model based solely on T2-weighted image features (AUC of 0.700, p = 0.048). Conclusions: Radiomics features extracted from deep learning-estimated T2 maps provide additional quantitative information that improves the prediction of peripheral zone csPCa aggressiveness, potentially enhancing risk stratification in non-invasive PCa diagnostics.

• Book : 17(3)
• Pub. Date : 2025
• Page : pp.381-381
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Autophagy-related gene 6 (ATG6) plays a crucial role in plant immunity. Nonexpressor of pathogenesis-related genes1 (NPR1) acts as a signaling hub of plant immunity. However, the relationship between ATG6 and NPR1 is unclear. Here, we find that ATG6 directly interacts with NPR1. ATG6 overexpression significantly increased nuclear accumulation of NPR1. Furthermore, we demonstrate that ATG6 increases NPR1 protein levels and improves its stability. Interestingly, ATG6 promotes the formation of SINCs (SA-induced NPR1 condensates)-like condensates. Additionally, ATG6 and NPR1 synergistically promote the expression of pathogenesis-related genes. Further results showed that silencing ATG6 in NPR1-GFP exacerbates Pst DC3000/ avrRps4 infection, while double overexpression of ATG6 and NPR1 synergistically inhibits Pst DC3000/ avrRps4 infection. In summary, our findings unveil an interplay of NPR1 with ATG6 and elucidate important molecular mechanisms for enhancing plant immunity.

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• Pub. Date : 2025
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Abstract Prostate cancer treatment-related erectile dysfunction and stress urinary incontinence are commonly treated with inflatable penile prosthesis (IPP) or artificial urinary sphincter (AUS). Given the association with androgens and penile/urethral health, we aim to evaluate whether patients on androgen deprivation therapy (ADT) undergoing IPP or AUS surgery are at increased risk for reintervention, complication, or infection. We queried the TriNetX database for adult males receiving IPP or AUS. The ADT cohort included those on ADT 3 months before or any time after surgery. We performed sub-analysis for leuprolide and bicalutamide. Cohorts and outcomes were defined by Current Procedural Terminology and International Classification of Diseases codes. Propensity score matching was performed using age, prostate cancer, history of prostatectomy, and history of radiation. Outcomes were reintervention (revision, removal, or replacement), infection, and complication. Analytics were performed in March 2024. 13,432 patients received an IPP and 5676 received an AUS, 465 and 745 of whom were on ADT, respectively. The only significant AUS analysis was for patients on abiraterone having fewer reinterventions (10.5% vs 20.8%, RR = 0.50 [0.29, 0.88]). Patients receiving an IPP with ADT had fewer reinterventions (7.2% vs 12%, RR = 0.60 [0.39, 0.92]) and complications (12.7% vs 18.5%, RR = 0.68 [0.49, 0.95]). Those on a GnRH agonist had fewer reinterventions (7.4% vs 11.7%, RR = 0.63 [0.41, 0.98]) for IPP. Patients receiving an IPP on bicalutamide had fewer reinterventions ( <5.2%* vs 10.8%, RR = 0.48 [0.23, 0.99]) and on leuprolide had fewer complications (12.2% vs 19.3%, RR = 0.63 [0.43, 0.91]). The remainder of analyses showed no significant differences. Patients with IPP or AUS do not fare worse on ADT. Further evaluation into the duration of ADT may provide clinical context, but based on these results, ADT should not limit implant surgery.

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• Pub. Date : 2025
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The development of molecular methods to detect Mytilus hybrids is important for food authentication, conservation, and the sustainable management of shellfish aquaculture as accurate food labeling is a legal requirement, and because introgression may promote undesirable phenotypes or displace native species. However, nuclear and mitochondrial markers can segregate independently, compromising diagnostic congruence between these markers. This study aimed to detect hybrids in the Mytilus edulis species complex using a multi-locus approach, including RFLP-PCR assays for Me 15/16, 16S rRNA, and COIxba, in samples collected from five continents. We used a model-based Bayesian method for hybrid and pure species detection to analyze the diagnostic potential of nuclear and mitochondrial markers in mussel samples from South America, North America, Africa, Oceania, and Europe. Our results showed that the combined use of markers can differentiate between M. trossulus, M. edulis, M. galloprovincialis, and M. chilensis. The combined use of nuclear and mitochondrial molecular markers also improves hybrid detection and allows us to identify introgression using Bayesian analysis.

• Book : 17(2)
• Pub. Date : 2025
• Page : pp.82-82
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• Pub. Date : 2025
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• Pub. Date : 2025
• Page : pp.1-1
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