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This study investigated the use of bi-exponential diffusion-weighted imaging (DWI) combined with structural features to differentiate high-grade glioma (HGG) from solitary brain metastasis (SBM). A total of 57 patients (31 HGG, 26 SBM) who underwent pre-surgical multi-b DWI and structural MRI (T1W, T2W, T1W + C) were included. Volumes of interest (VOI) in the peritumoral edema area (PTEA) and enhanced tumor area (ETA) were selected for analysis. Histogram features of slow diffusion coefficient (D slow ), fast diffusion coefficient (D fast ), and perfusion fraction (frac) were extracted. Results showed that HGG patients had higher skewness of D fast (P = 0.022) and frac (P = 0.077), higher kurtosis of D slow (P = 0.019) and frac (P = 0.025), and lower entropy of D slow (P = 0.005) and frac (P = 0.001) within the ETA. Additionally, HGG exhibited lower mean frac in both ETA (P = 0.007) and PTEA (P = 0.017). Combining skewness of frac in ETA with clear tumor margin enhanced diagnostic performance, achieving an optimal AUC of 0.79. These findings suggest that histogram analysis of diffusion and perfusion characteristics in ETA and structural features can effectively differentiate HGG from SBM., Competing Interests: Declarations. Competing interests: J. Guo is an employee of GE Healthcare. The other authors have no conflicts of interest to declare. Ethics approval: The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The protocol was reviewed and approved by the Ethics Committee of Shanxi Provincial People’s Hospital/Fifth Hospital of Shanxi Medical University (2022 Research Review No. 153). Consent to participate: The informed consent was waived by the Ethics Committee of Shanxi Provincial People’s Hospital /Fifth Hospital of Shanxi Medical University (2022 Research Review No. 153). Consent to publish: Not applicable., (© 2024. The Author(s).)

The plant-specific IDD transcription factors (TFs) are vital for regulating plant growth and developmental processes. However, the characteristics and biological roles of the IDD gene family in tomato ( Solanum lycopersicum ) are still largely unexplored. In this study, 17 SlIDD genes were identified in the tomato genome and classified into seven subgroups according to the evolutionary relationships of IDD proteins. Analysis of exon-intron structures and conserved motifs reflected the evolutionary conservation of SlIDDs in tomato. Collinearity analysis revealed that segmental duplication promoted the expansion of the SlIDD family. Ka/Ks analysis indicated that SlIDD gene orthologs experienced predominantly purifying selection throughout evolution. The analysis of cis -acting elements revealed that the promoters of SlIDD genes contain numerous elements associated with light, plant hormones, and abiotic stresses. The RNA-seq data and qRT-PCR experimental results showed that the SlIDD genes exhibited tissue-specific expression. Additionally, Group A members from Arabidopsis thaliana and rice are known to play a role in regulating plant shoot gravitropism. QRT-PCR analysis confirmed that the expression level of SlIDD15 in Group A was high in the hypocotyls and stems. Subcellular localization demonstrated that the SlIDD15 protein was localized in the nucleus. Surprisingly, the loss-of-function of SlIDD15 by CRISPR/Cas9 gene editing technology did not display obvious gravitropic response defects, implying the existence of functional redundant factors within SlIDD15 . Taken together, this study offers foundational insights into the tomato IDD gene family and serves as a valuable guide for exploring their molecular mechanisms in greater detail.

Background: Differentiation of glioma and solitary brain metastasis (SBM), which requires biopsy or multi-disciplinary diagnosis, remains sophisticated clinically. Histogram analysis of MR diffusion or molecular imaging hasn't been fully investigated for the differentiation and may have the potential to improve it., Methods: A total of 65 patients with newly diagnosed glioma or metastases were enrolled. All patients underwent DWI, IVIM, and APTW, as well as the T1W, T2W, T2FLAIR, and contrast-enhanced T1W imaging. The histogram features of apparent diffusion coefficient (ADC) from DWI, slow diffusion coefficient (Dslow), perfusion fraction (frac), fast diffusion coefficient (Dfast) from IVIM, and MTRasym@3.5ppm from APTWI were extracted from the tumor parenchyma and compared between glioma and SBM. Parameters with significant differences were analyzed with the logistics regression and receiver operator curves to explore the optimal model and compare the differentiation performance., Results: Higher ADC kurtosis (P = 0.022), frac kurtosis (P<0.001),and frac skewness (P<0.001) were found for glioma, while higher (MTRasym@3.5ppm) 10 (P = 0.045), frac 10 (P<0.001),frac 90 (P = 0.001), frac mean (P<0.001), and frac entropy (P<0.001) were observed for SBM. frac kurtosis (OR = 0.431, 95%CI 0.256-0.723, P = 0.002) was independent factor for SBM differentiation. The model combining (MTRasym@3.5ppm) 10 , frac 10 , and frac kurtosis showed an AUC of 0.857 (sensitivity: 0.857, specificity: 0.750), while the model combined with frac 10 and frac kurtosis had an AUC of 0.824 (sensitivity: 0.952, specificity: 0.591). There was no statistically significant difference between AUCs from the two models. (Z = -1.14, P = 0.25)., Conclusions: The frac 10 and frac kurtosis in enhanced tumor region could be used to differentiate glioma and SBM and (MTRasym@3.5ppm) 10 helps improving the differentiation specificity., (© 2024. The Author(s).)

The plant homeodomain finger (PHD finger) protein, a type of zinc finger protein extensively distributed in eukaryotes, plays diverse roles in regulating plant growth and development. While PHD finger proteins have been identified in various species, their functions remain largely unexplored in pea ( Pisum sativum ). In this study, we identified 84 members of the PHD finger gene family in pea, which displayed an uneven distribution across seven chromosomes. Through a comprehensive analysis using data from Arabidopsis thaliana and Medicago truncatula , we categorized the PHD finger proteins into 20 subfamilies via phylogenetic tree analysis. Each subfamily exhibited distinct variations in terms of quantity, genetic structure, conserved domains, and physical and chemical properties. Collinearity analysis revealed conserved evolutionary relationships among the PHD finger genes across the three different species. Furthermore, we identified the conserved and important roles of the subfamily M members in anther development. RT-qPCR and in situ hybridization revealed high expression of the pea subfamily M members PsPHD11 and PsPHD16 in microspores and the tapetum layer. In conclusion, this analysis of the PHD finger family in pea provides valuable guidance for future research on the biological roles of PHD finger proteins in pea and other leguminous plants.

Semi-leafless represents an advantageous plant architecture in pea breeding due to its ability to enhance resistance to lodging and potentially to powdery mildew. The introduction of semi-leafless pea varieties is considered a seminal advancement in pea breeding over the past half-century. The afila (af) mutation leads to the replacement of lateral leaflets by highly branched tendrils; combined with the semi-dwarfing le mutation, it forms the semi-leafless cultivated variety. In this study, we identified that mutations in two tandemly-arrayed genes encoding Cys(2)His(2) zinc finger transcription factors, PsPALM1a and PsPALM1b, were closely associated with the afila phenotype. These two genes may be deleted in the af mutant. In situ hybridization showed that both genes exhibit specific expression in early leaflet primordia. Furthermore, suppression of PsPALM1a/PsPALM1b resulted in a high frequency of conversion of lateral leaflets into tendrils. In conclusion, our study provides genetic evidence demonstrating that mutations in PsPALM1a and PsPALM1b are responsible for the af locus, contributing to a better understanding of compound leaf formation in peas and offering new insights for breeding applications related to afila., (© 2024 Scandinavian Plant Physiology Society.)

Individuals typically spend most of their lives indoors, predominantly in spaces like offices and residences. Consequently, prolonged indoor exposure underscores the critical significance of maintaining optimal indoor air quality (IAQ) to safeguard one's health. The primary impediment to attaining efficient regulation of Indoor Air Quality (IAQ) is the challenge of monitoring the IAQ parameters, particularly within the immediate vicinity of an individual's breathing space. Current heating, ventilation, and air conditioning systems lack the ability to rapidly predict and optimize the quality of indoor air. The objective of this study is to acquire the distribution features of indoor pollutants and precise indoor environment data in order to efficiently forecast and enhance the IAQ. To achieve this objective, a proposed surrogate model was developed using computational fluid dynamics (CFD). Notably, the Kriging surrogate model can rapidly predict IAQ while using a limited number of CFD runs. CFD are widely used as numerical simulation methods to obtain the accurate information. Surrogate models can rapidly forecast indoor environmental conditions using CFD simulation data simultaneously. Optimization algorithms can efficiently achieve desirable indoor ambient conditions, offering highly effective and intelligent control techniques for indoor atmospheric ventilation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Plant lateral organs are often elaborated through repetitive formation of developmental units, which progress robustly in predetermined patterns along their axes. Leaflets in compound leaves provide an example of such units that are generated sequentially along the longitudinal axis, in species-specific patterns. In this context, we explored the molecular mechanisms underlying an acropetal mode of leaflet initiation in chickpea pinnate compound leaf patterning. By analyzing naturally occurring mutants multi-pinnate leaf1 (mpl1) that develop higher-ordered pinnate leaves with more than forty leaflets, we show that MPL1 encoding a C2H2-zinc finger protein sculpts a morphogenetic gradient along the proximodistal axis of the early leaf primordium, thereby conferring the acropetal leaflet formation. This is achieved by defining the spatiotemporal expression pattern of CaLEAFY, a key regulator of leaflet initiation, and also perhaps by modulating the auxin signaling pathway. Our work provides novel molecular insights into the sequential progression of leaflet formation., (© 2023. The Author(s).)

Deposit accumulation is one of the predominant causes of sewer blockage and overflow. Nevertheless, the traditional detection methods are costly and time-consuming, and the accuracy of the mathematical models for deposit prediction is usually affected by some uncertain factors (e.g., pipe properties and flow velocity of water). This paper proposes a framework of global sensitivity analysis (GSA) to identify the most sensitive indicators for sewer deposit prediction by (i) developing a data-driven bilevel (i.e., catchment level and segment level) model to map the relation between input and output indicators and (ii) employing three different GSA methods, namely, the Morris method, Sobol method, and Borgonovo index method to identify the indicators as important or unimportant (insensitive). The results show that the likelihood of combined sewer overflow occurrences (LCSOO), pipe age (PA), and pipe material (PM) are influential parameters for the thickness of deposits. Here, we pay close attention to the most influential parameters, which can help improve forecast prediction accuracy., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Objective: To evaluate the diagnostic value of multimodal MRI radiomics based on T2-weighted fluid attenuated inversion recovery imaging (T2WI-FLAIR) combined with T1-weighted contrast enhanced imaging (T1WI-CE) in the early differentiation of high-grade glioma recurrence from pseudoprogression., Methods: A total of one hundred eighteen patients with brain gliomas who were diagnosed from March 2014 to April 2020 were retrospectively analyzed. According to the clinical characteristics, the patients were randomly split into a training group ( n = 83) and a test group ( n = 35) at a 7 : 3 ratio. The region of interest (ROI) was delineated, and 2632 radiomic features were extracted. We used multiple logistic regression to establish a classification model, including the T 1 model, T 2 model, and T 1 + T 2 model, to differentiate recurrence from pseudoprogression. The diagnostic efficiency of the model was evaluated by calculating the area under the receiver operating characteristic curve (AUC) and accuracy (ACC) and by analyzing the calibration curve of the nomogram and decision curve., Results: There were 75 cases of recurrence and 43 cases of pseudoprogression. The diagnostic efficacies of the multimodal MRI-based radiomic model were relatively high. The AUC values and ACC of the training group were 0.831 and 77.11%, respectively, and the AUC values and ACC of the test group were 0.829 and 88.57%, respectively. The calibration curve of the nomogram showed that the discrimination probability was consistent with the actual occurrence in the training group, and the discrimination probability was roughly the same as the actual occurrence in the test group. In the decision curve analysis, the T 1 + T 2 model showed greater overall net efficiency., Conclusion: The multimodal MRI radiomic model has relatively high efficiency in the early differentiation of recurrence from pseudoprogression, and it could be helpful for clinicians in devising correct treatment plans so that patients can be treated in a timely and accurate manner., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this article., (Copyright © 2022 Hui Jing et al.)

Purpose: We aimed to explore whether multiparametric magnetic resonance imaging (MRI)-based radiomics combined with selected blood inflammatory markers could effectively predict the grade and proliferation in glioma patients., Methods: This retrospective study included 152 patients histopathologically diagnosed with glioma. Stratified sampling was used to divide all patients into a training cohort (n=107) and a validation cohort (n=45) according to a ratio of 7:3, and five-fold repeat cross-validation was adopted in the training cohort. Multiparametric MRI and clinical parameters, including age, the neutrophil-lymphocyte ratio and red cell distribution width, were assessed. During image processing, image registration and gray normalization were conducted. A radiomics analysis was performed by extracting 1584 multiparametric MRI-based features, and the least absolute shrinkage and selection operator (LASSO) was applied to generate a radiomics signature for predicting grade and Ki-67 index in both training and validation cohorts. Statistical analysis included analysis of variance, Pearson correlation, intraclass correlation coefficient, multivariate logistic regression, Hosmer-Lemeshow test, and receiver operating characteristic (ROC) curve., Results: The radiomics signature demonstrated good performance in both the training and validation cohorts, with areas under the ROC curve (AUCs) of 0.92, 0.91, and 0.94 and 0.94, 0.75, and 0.82 for differentiating between low and high grade gliomas, grade III and grade IV gliomas, and low Ki-67 and high Ki-67, respectively, and was better than the clinical model; the AUCs of the combined model were 0.93, 0.91, and 0.95 and 0.94, 0.76, and 0.80, respectively., Conclusion: Both the radiomics signature and combined model showed high diagnostic efficacy and outperformed the clinical model. The clinical factors did not provide additional improvement in the prediction of the grade and proliferation index in glioma patients, but the stability was improved.

Cognitive decline, memory impairment and circadian rhythm disturbance are iconic manifestations of Alzheimer's disease (AD). APPswe/PS1dE9 (APP/PS1) mice, a model of AD, show deficits in multiple learning and memory abilities, synaptic plasticity, and behavioral circadian rhythm, but whether circadian differences in cognitive performance and synaptic plasticity could be affected in AD remain unclear. Here, the cognitive behaviors of 6-month-old APP/PS1 mice were assessed by multiple behavior tests in the rest phase (light period) or active phase (dark period) of the day. The possible electrophysiological mechanism was subsequently investigated by in vivo hippocampal long-term potentiation (LTP) recording, and the locomotor activity rhythm of the mice was detected using wheel-running activities. Compared to wild-type (WT) mice, APP/PS1 mice exhibited long-term spatial memory impairment and in vivo hippocampal LTP suppression. In addition, in APP/PS1 mice, circadian differences in new object recognition memory and LTP were lost, and the circadian difference in long-term spatial memory was decreased, accompanied by a less robust locomotor activity rhythm. These results indicate that the loss of circadian differences in new object recognition memory and the decrease in the circadian difference in long-term spatial memory in APP/PS1 mice, which are closely associated with the loss of the circadian difference in LTP and less robust locomotor activity, might occur early in the course of AD.

Apolipoprotein E4 (APOE4) allele located on chromosome 19 is a major genetic risk factor for developing Alzheimer's disease (AD). However, the direct effects of ApoE4 on the cognitive function and long-term synaptic plasticity have not fully investigated. At the same time, although amyloid beta protein (Aβ)-ApoE complexes are principal components of AD-associated brain damage, there is still lack of in vivo study on the effects of co-existed Aβ1-40 and ApoE4. In the present study, we examined the effects of ApoE4 on the spatial memory and hippocampal long term potentiation (LTP) by using Morris water maze test and in vivo field potential recording, compared the neurotoxicity of Aβ1-40 and ApoE4, and investigated the effects of co-application of Aβ1-40 and ApoE4 on cognitive behavior and synaptic plasticity. The results showed that intracerebrovenrticular (i.c.v.) injection of Aβ1-40 or ApoE4 significantly and similarly impaired spatial learning and memory, and depressed the high-frequency stimulus (HFS) induced LTP. Importantly, compared to the effects of Aβ1-40 or ApoE4 alone, co-injection of Aβ1-40 and ApoE4 produced much heavier damages in cognitive behaviors and long term synaptic plasticity. These results demonstrated that ApoE4 not only exerted direct neurotoxicity but also enhanced the neurotoxicity of Aβ1-40 on spatial cognitive function and hippocampal LTP, which maybe partly elucidates the mechanism by which APOE4 allele exerted negative effects as a major genetic risk factor for developing AD., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Alzheimer's disease (AD) is the most common cause of dementia, and effective therapeutics are lacking. Colivelin (CLN), a novel, strong humanin derivative, is effective in vitro in preventing cell death induced by AD-causative genes and amyloid-β protein (Aβ) even at a low concentration. We recently demonstrated that intrahippocampal injection of CLN prevents Aβ25-35-induced deficits in spatial memory and synaptic plasticity in normal rats. Here, we further observed the effects of chronically intranasally (i.n.) administered CLN on cognitive behaviors and pathological hallmarks in 9-month-old APPswe/PS1dE9 (APP/PS1) AD mice using multiple behavioral tests and immunochemistry. The electrophysiological mechanism of CLN neuroprotection was also investigated by recording in vivo hippocampal long-term potentiation (LTP). CLN pretreatment effectively prevented impairments in new object recognition, working memory, and long-term spatial memory and reversed the depression of in vivo hippocampal LTP in APP/PS1 mice. Additionally, chronic application of CLN obviously reduced Aβ deposition in the hippocampus in APP/PS1 mice. These results indicate that CLN has strong neuroprotective effects on learning and memory behaviors in APP/PS1 mice and that this behavioral improvement is closely associated with the reduction of Aβ deposition and alleviation of LTP suppression in the hippocampus, supporting the potential of CLN for the prevention and treatment of AD.