Using Machine Learning Methods Combined with Vegetation Indices and Growth Indicators to Predict Seed Yield of Bromus inermis.

Smooth bromegrass (Bromus inermis) is a perennial, high-quality forage grass. However, its seed yield is influenced by agronomic practices, climatic conditions, and the growing year. The rapid and effective prediction of seed yield can assist growers in making informed production decisions and reducing agricultural risks. Our field trial design followed a completely randomized block design with four blocks and three nitrogen levels (0, 100, and 200 kg·N·ha-1) during 2022 and 2023. Data on the remote vegetation index (RVI), the normalized difference vegetation index (NDVI), the leaf nitrogen content (LNC), and the leaf area index (LAI) were collected at heading, anthesis, and milk stages. Multiple linear regression (MLR), support vector machine (SVM), and random forest (RF) regression models were utilized to predict seed yield. In 2022, the results indicated that nitrogen application provided a sufficiently large range of variation of seed yield (ranging from 45.79 to 379.45 kg ha⁻¹). Correlation analysis showed that the indices of the RVI, the NDVI, the LNC, and the LAI in 2022 presented significant positive correlation with seed yield, and the highest correlation coefficient was observed at the heading stage. The data from 2022 were utilized to formulate a predictive model for seed yield. The results suggested that utilizing data from the heading stage produced the best prediction performance. SVM and RF outperformed MLR in prediction, with RF demonstrating the highest performance (R2 = 0.75, RMSE = 51.93 kg ha-1, MAE = 29.43 kg ha-1, and MAPE = 0.17). Notably, the accuracy of predicting seed yield for the year 2023 using this model had decreased. Feature importance analysis of the RF model revealed that LNC was a crucial indicator for predicting smooth bromegrass seed yield. Further studies with an expanded dataset and integration of weather data are needed to improve the accuracy and generalizability of the model and adaptability for the growing year.

Potential diagnostic markers and therapeutic targets for periodontitis and Alzheimer's disease based on bioinformatics analysis.

BACKGROUND AND OBJECTIVE: As a chronic inflammatory disease, periodontitis threatens oral health and is a risk factor for Alzheimer's disease (AD). There is growing evidence that these two diseases are closely related. However, current research is still incomplete in understanding the common genes and common mechanisms between periodontitis and AD. In this study, we aimed to identify common genes in periodontitis and AD and analyze the relationship between crucial genes and immune cells to provide new therapeutic targets for clinical treatment. MATERIALS AND METHODS: We evaluated differentially expressed genes (DEGs) specific to periodontitis and AD. Co-expressed genes were identified by obtaining gene expression profile data from the Gene Expression Omnibus (GEO) database. Using the STRING database, protein-protein interaction (PPI) networks were constructed, and essential genes were identified. We also used four algorithms to identify critical genes and constructed regulatory networks. The association of crucial genes with immune cells and potential therapeutic effects was also assessed. RESULTS: PDGFRB, VCAN, TIMP1, CHL1, EFEMP2, and IGFBP5 were obtained as crucial common genes. Immune infiltration analysis showed that Natural killer cells and Myeloid-derived suppressor cells were significantly differentially expressed in patients with PD and AD compared with the normal group. FOXC1 and GATA2 are important TFs for PD and AD. MiR-23a, miR-23b, miR-23a, and miR-23b were associated with AD and PD. Finally, the hub genes retrieved from the DSigDB database indicate multiple drug molecule and drug-target interactions. CONCLUSION: This study reveals commonalities in common hub genes and immune infiltration between periodontitis and AD, and the analysis of six hub genes and immune cells may provide new insights into potential therapeutic directions for the pathogenesis of periodontitis complicated by AD.

Tanshinone â ¡A participates in the treatment of endometriosis by regulating adhesion, invasion, angiogenesis and inhibition of PI3K/Akt/mTOR signaling pathway.

Endometriosis (EMs) is a common gynecological disorder characterized by abnormal growth of the endometrial stroma and glands outside the uterus. Tanshinone IIA, the active component of Chinese medicine Danshen (Salvia miltiorrhiza Bge.), has a number of pharmacological effects such as anti­inflammation and anti­oxidation and serves a significant role in the treatment of EMs. In the present study, network pharmacology and experimental validation were used to elucidate the potential mechanism of tanshinone IIA for treating EMs. Several databases were used to collect information on EMs and tanshinone IIA and cross­targets for tanshinone IIA and EMs finally obtained. A total of 64 common targets were found between tanshinone IIA and EMs. Subsequently, a protein­protein interaction network was constructed, a total of 14 core targets were screened for enrichment analysis. Furthermore, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed. The network pharmacology showed that intercellular adhesion molecule (ICAM)­1, MMP­9 and VEGF are the core targets while PI3K/AKT pathway and mTOR pathway are the main signaling pathways through which tanshinone IIA regulates relevant biological processes to intervene in EMs. Finally, the therapeutic role and mechanism of tanshinone IIA on EMs was verified in vivo. Female Sprague­Dawley rats were treated by autologous transplantation to establish EMs. Serum inflammatory factors were detected by enzyme­linked immunosorbent assay (ELISA). The expression of ICAM­1, MMP­9 and VEGF in ectopic endometrial tissues of rats was determined by immunohistochemical. The expression of PI3K/Akt/mTOR pathway­related proteins and genes was detected by western blotting and quantitative PCR. It was found that tanshinone IIA treatment significantly decreased the formation of ectopic endometrium by reducing serum levels of TNF­α and IL­1ß, and down regulating the levels of ICAM­1, MMP­9 and VEGF in ectopic uterine tissue. In addition, tanshinone IIA can also block the activation of PI3K/Akt/mTOR signaling pathway by reducing the expression of related proteins and genes. In conclusion, tanshinone IIA can regulate adhesion, invasion and angiogenesis, thereby improving the pathological morphology of ectopic endometrium and inhibiting the formation of ectopic lesions. The PI3K/Akt/mTOR signaling pathway may play a key role in controlling this process.

Genomic Identification and Expression Profiling of Lesion Simulating Disease Genes in Alfalfa (Medicago sativa) Elucidate Their Responsiveness to Seed Vigor.

Seed aging, a common physiological phenomenon during forage seed storage, is a crucial factor contributing to a loss of vigor, resulting in delayed seed germination and seedling growth, as well as limiting the production of hay. Extensive bodies of research are dedicated to the study of seed aging, with a particular focus on the role of the production and accumulation of reactive oxygen species (ROS) and the ensuing oxidative damage during storage as a primary cause of decreases in seed vigor. To preserve optimal seed vigor, ROS levels must be regulated. The excessive accumulation of ROS can trigger programmed cell death (PCD), which causes the seed to lose vigor permanently. LESION SIMULATING DISEASE (LSD) is one of the proteins that regulate PCD, encodes a small C2C2 zinc finger protein, and plays a molecular function as a transcriptional regulator and scaffold protein. However, genome-wide analysis of LSD genes has not been performed for alfalfa (Medicago sativa), as one of the most important crop species, and, presently, the molecular regulation mechanism of seed aging is not clear enough. Numerous studies have also been unable to explain the essence of seed aging for LSD gene regulating PCD and affecting seed vigor. In this study, we obtained six MsLSD genes in total from the alfalfa (cultivar Zhongmu No. 1) genome. Phylogenetic analysis demonstrated that the MsLSD genes could be classified into three subgroups. In addition, six MsLSD genes were unevenly mapped on three chromosomes in alfalfa. Gene duplication analysis demonstrated that segmental duplication was the key driving force for the expansion of this gene family during evolution. Expression analysis of six MsLSD genes in various tissues and germinating seeds presented their different expressions. RT-qPCR analysis revealed that the expression of three MsLSD genes, including MsLSD2, MsLSD5, and MsLSD6, was significantly induced by seed aging treatment, suggesting that they might play an important role in maintaining seed vigor. Although this finding will provide valuable insights into unveiling the molecular mechanism involved in losing vigor and new strategies to improve alfalfa seed germinability, additional research must comprehensively elucidate the precise pathways through which the MsLSD genes regulate seed vigor.

Transcriptomic profiling of human granulosa cells between women with advanced maternal age with different ovarian reserve.

BACKGROUND: Age-related diminished ovarian reserve (DOR) is not absolute. Some advanced maternal age (AMA) still have normal ovarian reserve (NOR) and often show better pregnancy outcomes. Exploring the transcriptomic profile of granulosa cells (GCs) in AMA could lead to new ideas for mitigating age-related diminished ovarian reserve. AIM: This study aimed to analyze the transcriptomic profile of GCs in AMA with different ovarian reserve. RESULTS: In total, 6273 statistically significant differential expression genes (DEGs) (|log2fc|> 1, q < 0.05) were screened from the two groups, among which 3436 genes were upregulated, and 2837 genes were downregulated in the DOR group. Through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, the potential functions of dysregulated genes in AMA with DOR or NOR were predicted. The GO enrichment analysis revealed that the DEGs were mainly enriched in obsolete oxidation-reduction process, mitochondrion, metal ion binding, ATP binding, etc. The KEGG pathway enrichment analysis revealed that the above-mentioned DEGs were mainly enriched in ferroptosis, regulation of actin cytoskeleton, oxidative phosphorylation, etc. Meanwhile, verification of the mRNA expression levels of DEGs revealed the possible involvement of "ferroptosis" in age-related diminished ovarian reserve. CONCLUSIONS: From a new clinical perspective, we presented the first data showing the transcriptomic profile in GCs between AMA with different ovarian reserve. At the same time, we identified the role of ferroptosis in the GCs of AMA, providing a new biological basis for studying ovarian aging and improving pregnancy outcomes of AMA.

Genome-wide analysis and expression profiling of glyoxalase gene families in oat (Avena sativa) indicate their responses to abiotic stress during seed germination.

Abiotic stresses have deleterious effects on seed germination and seedling establishment, leading to significant crop yield losses. Adverse environmental conditions can cause the accumulation of methylglyoxal (MG) within plant cells, which can negatively impact plant growth and development. The glyoxalase system, which consists of the glutathione (GSH)-dependent enzymes glyoxalase I (GLX1) and glyoxalase II (GLX2), as well as the GSH-independent glyoxalase III (GLX3 or DJ-1), plays a crucial role in detoxifying MG. However, genome-wide analysis of glyoxalase genes has not been performed for one of the agricultural important species, oat (Avena sativa). This study identified a total of 26 AsGLX1 genes, including 8 genes encoding Ni2+-dependent GLX1s and 2 genes encoding Zn2+-dependent GLX1s. Additionally, 14 AsGLX2 genes were identified, of which 3 genes encoded proteins with both lactamase B and hydroxyacylglutathione hydrolase C-terminal domains and potential catalytic activity, and 15 AsGLX3 genes encoding proteins containing double DJ-1 domains. The domain architecture of the three gene families strongly correlates with the clades observed in the phylogenetic trees. The AsGLX1, AsGLX2, and AsGLX3 genes were evenly distributed in the A, C, and D subgenomes, and gene duplication of AsGLX1 and AsGLX3 genes resulted from tandem duplications. Besides the core cis-elements, hormone responsive elements dominated the promoter regions of the glyoxalase genes, and stress responsive elements were also frequently observed. The subcellular localization of glyoxalases was predicted to be primarily in the cytoplasm, chloroplasts, and mitochondria, with a few presents in the nucleus, which is consistent with their tissue-specific expression. The highest expression levels were observed in leaves and seeds, indicating that these genes may play important roles in maintaining leaf function and ensuring seed vigor. Moreover, based on in silico predication and expression pattern analysis, AsGLX1-7A, AsGLX2-5D, AsDJ-1-5D, AsGLX1-3D2, and AsGLX1-2A were suggested as promising candidate genes for improving stress resistance or seed vigor in oat. Overall, the identification and analysis of the glyoxalase gene families in this study can provide new strategies for improving oat stress resistance and seed vigor.

Identification of hypoxia-related genes and exploration of their relationship with immune cells in ischemic stroke.

Ischemic stroke (IS) is a major threat to human health, and it is the second leading cause of long-term disability and death in the world. Impaired cerebral perfusion leads to acute hypoxia and glucose deficiency, which in turn induces a stroke cascade response that ultimately leads to cell death. Screening and identifying hypoxia-related genes (HRGs) and therapeutic targets is important for neuroprotection before and during brain recanalization to protect against injury and extend the time window to further improve functional outcomes before pharmacological and mechanical thrombolysis. First, we downloaded the GSE16561 and GSE58294 datasets from the NCBI GEO database. Bioinformatics analysis of the GSE16561 dataset using the limma package identified differentially expressed genes (DEGs) in ischemic stroke using adj. p. values < 0.05 and a fold change of 0.5 as thresholds. The Molecular Signature database and Genecards database were pooled to obtain hypoxia-related genes. 19 HRGs associated with ischemic stroke were obtained after taking the intersection. LASSO regression and multivariate logistic regression were applied to identify critical biomarkers with independent diagnostic values. ROC curves were constructed to validate their diagnostic efficacy. We used CIBERSORT to analyze the differences in the immune microenvironment between IS patients and controls. Finally, we investigated the correlation between HRGs and infiltrating immune cells to understand molecular immune mechanisms better. Our study analyzed the role of HRGs in ischemic stroke. Nineteen hypoxia-related genes were obtained. Enrichment analysis showed that 19 HRGs were involved in response to hypoxia, HIF-1 signaling pathway, autophagy, autophagy of mitochondrion, and AMPK signaling pathway. Because of the good diagnostic properties of SLC2A3, we further investigated the function of SLC2A3 and found that it is closely related to immunity. We have also explored the relevance of other critical genes to immune cells. Our findings suggest that hypoxia-related genes play a crucial role in the diversity and complexity of the IS immune microenvironment. Exploring the association between hypoxia-related critical genes and immune cells provides innovative insights into the therapeutic targets for ischemic stroke.

Integrating optical imaging techniques for a novel approach to evaluate Siberian wild rye seed maturity.

Advances in optical imaging technology using rapid and non-destructive methods have led to improvements in the efficiency of seed quality detection. Accurately timing the harvest is crucial for maximizing the yield of higher-quality Siberian wild rye seeds by minimizing excessive shattering during harvesting. This research applied integrated optical imaging techniques and machine learning algorithms to develop different models for classifying Siberian wild rye seeds based on different maturity stages and grain positions. The multi-source fusion of morphological, multispectral, and autofluorescence data provided more comprehensive information but also increases the performance requirements of the equipment. Therefore, we employed three filtering algorithms, namely minimal joint mutual information maximization (JMIM), information gain, and Gini impurity, and set up two control methods (feature union and no-filtering) to assess the impact of retaining only 20% of the features on the model performance. Both JMIM and information gain revealed autofluorescence and morphological features (CIELab A, CIELab B, hue and saturation), with these two filtering algorithms showing shorter run times. Furthermore, a strong correlation was observed between shoot length and morphological and autofluorescence spectral features. Machine learning models based on linear discriminant analysis (LDA), random forests (RF) and support vector machines (SVM) showed high performance (>0.78 accuracies) in classifying seeds at different maturity stages. Furthermore, it was found that there was considerable variation in the different grain positions at the maturity stage, and the K-means approach was used to improve the model performance by 5.8%-9.24%. In conclusion, our study demonstrated that feature filtering algorithms combined with machine learning algorithms offer high performance and low cost in identifying seed maturity stages and that the application of k-means techniques for inconsistent maturity improves classification accuracy. Therefore, this technique could be employed classification of seed maturity and superior physiological quality for Siberian wild rye seeds.

Comparison of two different starting dose of rhFSH in GnRH antagonist protocol for patients with normal ovarian reserve.

Objective: To evaluate different starting doses of recombinant human follicle-stimulating hormone (rhFSH) on pregnancy outcomes for patients with normal ovarian reserve during gonadotropin- releasing hormone antagonist (GnRH-ant) protocol-controlled ovarian stimulation of in vitro fertilization (IVF) cycles. Methods: In this retrospective study, a total of 1138 patients undergoing IVF cycles following the GnRH-ant protocol were enrolled. Patients were divided into two groups according to the starting dose of rhFSH. 617 patients received a starting dose of rhFSH of 150 IU, and 521 patients received a starting dose of rhFSH of 225 IU. We compared demographic characteristics, ovarian stimulation and embryological characteristics, and pregnancy and birth outcomes between the two groups. Multivariate logistic regression analysis was performed to examine the possible effects of the known potential confounding factors on pregnancy outcomes. Results: The number of oocytes retrieved in the 150 IU rhFSH group was significantly lower than those in the 225 IU rhFSH group. There was no significant difference between the two groups referring to embryological characteristics. The proportion of fresh embryo transfer in the 150 IU rhFSH group was significantly higher than that in the 225 IU rhFSH group (48.30% vs. 40.90%), and there was no difference in the risk of ovarian hyperstimulation syndrome and pregnancy outcomes between the two groups. Conclusions: In conclusion, the starting dose of rhFSH of 150 IU for ovarian stimulation has a similar pregnancy outcome as starting dose of rhFSH of 225 IU in GnRH-ant protocol for patients with normal ovarian reserve. Considering the potential cost-effectiveness and shorter time to live birth, the starting dose of rhFSH of 150 IU may be more suitable than 225 IU.

Single Seed Identification in Three Medicago Species via Multispectral Imaging Combined with Stacking Ensemble Learning.

Multispectral imaging (MSI) has become a new fast and non-destructive detection method in seed identification. Previous research has usually focused on single models in MSI data analysis, which always employed all features and increased the risk to efficiency and that of system cost. In this study, we developed a stacking ensemble learning (SEL) model for successfully identifying a single seed of sickle alfalfa (Medicago falcata), hybrid alfalfa (M. varia), and alfalfa (M. sativa). SEL adopted a three-layer structure, i.e., level 0 with principal component analysis (PCA), linear discriminant analysis (LDA), and quadratic discriminant analysis (QDA) as models of dimensionality reduction and feature extraction (DRFE); level 1 with support vector machine (SVM), multiple logistic regression (MLR), generalized linear models with elastic net regularization (GLMNET), and eXtreme Gradient Boosting (XGBoost) as basic learners; and level 3 with XGBoost as meta-learner. We confirmed that the values of overall accuracy, kappa, precision, sensitivity, specificity, and sensitivity in the SEL model were all significantly higher than those in basic models alone, based on both spectral features and a combination of morphological and spectral features. Furthermore, we also developed a feature filtering process and successfully selected 5 optimal features out of 33 ones, which corresponded to the contents of chlorophyll, anthocyanin, fat, and moisture in seeds. Our SEL model in MSI data analysis provided a new way for seed identification, and the feature filter process potentially could be used widely for development of a low-cost and narrow-channel sensor.

Genome-Wide Analysis and Expression Profiling of Glutathione Reductase Gene Family in Oat (Avena sativa) Indicate Their Responses to Abiotic Stress during Seed Imbibition.

Abiotic stress disturbs plant cellular redox homeostasis, inhibiting seed germination and plant growth. This is a crucial limitation to crop yield. Glutathione reductase (GR) is an important component of the ascorbate-glutathione (AsA-GSH) cycle which is involved in multiple plant metabolic processes. In the present study, GRs in A. sativa (AsGRs) were selected to explore their molecular characterization, phylogenetic relationship, and RNA expression changes during seed imbibition under abiotic stress. Seven AsGR genes were identified and mapped on six chromosomes of A, C, and D subgenomes. Phylogenetic analysis and subcellular localization of AsGR proteins divided them into two sub-families, AsGR1 and AsGR2, which were predicted to be mainly located in cytoplasm, mitochondrion, and chloroplast. Cis-elements relevant to stress and hormone responses are distributed in promoter regions of AsGRs. Tissue-specific expression profiling showed that AsGR1 genes were highly expressed in roots, leaves, and seeds, while AsGR2 genes were highly expressed in leaves and seeds. Both AsGR1 and AsGR2 genes showed a decreasing-increasing expression trend during seed germination under non-stress conditions. In addition, their responses to drought, salt, cold, copper, H2O2, and ageing treatments were quite different during seed imbibition. Among the seven AsGR genes, AsGR1-A, AsGR1-C, AsGR2-A, and AsGR2-D responded more significantly, especially under drought, ageing, and H2O2 stress. This study has laid the ground for the functional characterization of GR and the improvement of oat stress tolerance and seed vigor.

Dynamic Responses of Antioxidant and Glyoxalase Systems to Seed Aging Based on Full-Length Transcriptome in Oat (Avena sativa L.).

Seed aging is a major challenge for food security, agronomic production, and germplasm conservation, and reactive oxygen species (ROS) and methylglyoxal (MG) are highly involved in the aging process. However, the regulatory mechanisms controlling the abundance of ROS and MG are not well characterized. To characterize dynamic response of antioxidant and glyoxalase systems during seed aging, oat (Avena sativa L.) aged seeds with a range of germination percentages were used to explore physiological parameters, biochemical parameters and relevant gene expression. A reference transcriptome based on PacBio sequencing generated 67,184 non-redundant full-length transcripts, with 59,050 annotated. Subsequently, eleven seed samples were used to investigate the dynamic response of respiration, ROS and MG accumulation, antioxidant enzymes and glyoxalase activity, and associated genes expression. The 48 indicators with high correlation coefficients were divided into six major response patterns, and were used for placing eleven seed samples into four groups, i.e., non-aged (Group N), higher vigor (Group H), medium vigor (Group M), and lower vigor (Group L). Finally, we proposed a putative model for aging response and self-detoxification mechanisms based on the four groups representing different aging levels. In addition, the outcomes of the study suggested the dysfunction of antioxidant and glyoxalase system, and the accumulation of ROS and MG definitely contribute to oat seed aging.

Determination of the energy contents and nutrient digestibility of corn, waxy corn and steam-flaked corn fed to growing pigs.

Objective: The research was conducted to determine the DE and ME contents as well as the apparent total tract digestibility (ATTD) of nutrients in corn, waxy corn and steam-flaked corn fed to growing pigs. Methods: Eighteen growing pigs with initial body weight of 15.42 ± 1.41 kg were randomly allotted to three diets including a corn diet, a waxy corn diet and a steam-flaked corn diet in a completely randomized design. Each treatment contained six replicates. The experiment lasted for 12 days, which comprised 7-d adaptation to diets followed by a 5-d total collection of feces and urine. The energy contents and the nutrient digestibility in three ingredients were calculated using direct method. Results: Compared to normal corn, both the amylose and dietary fiber contents in waxy corn were numerically lower, but the starch gelatinization degree was numerically greater. Moreover, the DE and ME contents as well as the ATTD of NDF and ADF in waxy corn were significantly greater (p < 0.05) than those in normal corn when fed to growing pigs. Furthermore, the steam-flaked corn had greater (p < 0.05) DE and ME contents, and ATTD of ether extract (EE) and ADF compared to normal corn. Conclusion: Both variety and processing procedure have influence on chemical compositions, energy contents and nutrient digestibility of corn. The waxy corn and steam-flaked corn had greater starch gelatinization degree and DE and ME contents compared to normal corn when fed to growing pigs.