Precise Determination of Selenium Forms and Contents in Selenium-Enriched Rapeseed Seedlings and Flowering Stalks by HPLC-ICP-MS.

Rapeseed (Brassica napus L.) has the ability of selenium (Se) enrichment. Identification of selenides in Se-rich rapeseed products will promote the development and utilization of high value. By optimizing the Se species extraction process (protease type, extraction reagent, enzyme sample ratio, extraction time, etc.) and chromatographic column, an efficient, stable, and accurate method was established for the identification of Se species and content in rapeseed seedlings and flowering stalks, which were cultured by inorganic Se hydroponics. Five Se compounds, including selenocystine (SeCys2), methylselenocysteine (MeSeCys), selenomethionine (SeMet), selenite (SeIV), and selenate (SeVI) were qualitatively and quantitatively identified. Organoselenium was absolutely dominant in both seedlings and flowering stalks among the detected rapeseed varieties, with 64.18-90.20% and 94.38-98.47%, respectively. Further, MeSeCys, a highly active selenide, predominated in rapeseed flowering stalks with a proportion of 56.36-72.93% and a content of 1707.3-5030.3 µg/kg. This study provides a new source of MeSeCys supplementation for human Se fortification.

Increasing Sufu gene dosage reveals its unorthodox role in promoting polydactyly and medulloblastoma tumorigenesis.

Suppressor of fused (SUFU) is widely regarded as a key negative regulator of the sonic hedgehog (SHH) morphogenic pathway and a known tumor suppressor of medulloblastoma (MB). However, we report here that SUFU expression was markedly increased in 75% of specimens compiled in a tissue array comprising 49 unstratified MBs. The SUFU and GLI1 expression levels in this MB array showed strong positive correlation, which was also identified in a large public data set containing 736 MBs. We further report that increasing Sufu gene dosage in mice caused preaxial polydactyly, which was associated with the expansion of the Gli3 domain in the anterior limb bud and heightened Shh signaling responses during embryonic development. Increasing Sufu gene dosage also led to accelerated cerebellar development and, when combined with ablation of the Shh receptor encoded by Patched1 (Ptch1), promoted MB tumorigenesis. These data reveal multifaceted roles of SUFU in promoting MB tumorigenesis by enhancing SHH signaling. This revelation clarifies potentially counterintuitive clinical observation of high SUFU expression in MBs and may pave way for novel strategies to reduce or reverse MB progression.

An integrated QTL mapping and transcriptome sequencing provides further molecular insights and candidate genes for stem strength in rapeseed (Brassica napus L.).

KEY MESSAGE: We detected the major QTL- qSR.A07, which regulated stem strength and was fine-mapped to 490 kb. BnaA07G0302800ZS and BnaA07G0305700ZS as the candidate functional genes were identified at qSR.A07 locus. The stem's mechanical properties reflect its ability to resist lodging. In rapeseed (Brassica napus L.), although stem lodging negatively affects yield and generates harvesting difficulties, the molecular regulation of stem strength remains elusive. Hence, this study aimed to unravel the main loci and molecular mechanisms governing rapeseed stem strength. A mapping population consisting of 267 RILs (recombinant inbred lines) was developed from the crossed between ZS11 (high stem strength) and 4D122 (low stem strength), and two mechanical properties of stems including stem breaking strength and stem rind penetrometer resistance were phenotyped in four different environments. Four pleiotropic QTLs that were stable in at least two environments were detected. qSR.A07, the major one, was fine-mapped to a 490 kb interval between markers SA7-2711 and SA7-2760 on chromosome 7. It displayed epistatic interaction with qRPR.A09-2. Comparative transcriptome sequencing and analysis unveiled methionine/S-adenosylmethionine cycle (Met/SAM cycle), cytoskeleton organization, sulfur metabolism and phenylpropanoid biosynthesis as the main pathways associated with high stem strength. Further, we identified two candidate genes, BnaA07G0302800ZS and BnaA07G0305700ZS, at qSR.A07 locus. Gene sequence alignment identified a number of InDels, SNPs and amino acid variants in sequences of these genes between ZS11 and 4D122. Finally, based on these genetic variants, we developed three SNP markers of these genes to facilitate future genetic selection and functional studies. These findings offer important genetic resources for the molecular-assisted breeding of novel rapeseed stem lodging-resistant varieties.

New Insights into the TIFY Gene Family of Brassica napus and Its Involvement in the Regulation of Shoot Branching.

As plant-specific transcription factors, the TIFY family genes are involved in the responses to a series of biotic and abiotic stresses and the regulation of the development of multiple organs. To explore the potential roles of the TIFY gene family in shoot branching, which can shape plant architecture and finally determine seed yield, we conducted comprehensive genome-wide analyses of the TIFY gene family in Brassica napus. Here, HMMER search and BLASTp were used to identify the TIFY members. A total of 70 TIFY members were identified and divided into four subfamilies based on the conserved domains and motifs. These TIFY genes were distributed across 19 chromosomes. The predicted subcellular localizations revealed that most TIFY proteins were located in the nucleus. The tissue expression profile analyses indicated that TIFY genes were highly expressed in the stem, flower bud, and silique at the transcriptional level. High-proportioned activation of the dormant axillary buds on stems determined the branch numbers of rapeseed plants. Here, transcriptome analyses were conducted on axillary buds in four sequential developing stages, that is, dormant, temporarily dormant, being activated, and elongating (already activated). Surprisingly, the transcription of the majority of TIFY genes (65 of the 70) significantly decreased on the activation of buds. GO enrichment analysis and hormone treatments indicated that the transcription of TIFY family genes can be strongly induced by jasmonic acid, implying that the TIFY family genes may be involved in the regulation of jasmonic acid-mediated branch development. These results shed light on the roles of TIFY family genes in plant architecture.

Research Progress of Selenium-Enriched Foods.

Selenium is an essential micronutrient that plays a crucial role in maintaining human health. Selenium deficiency is seriously associated with various diseases such as Keshan disease, Kashin-Beck disease, cataracts, and others. Conversely, selenium supplementation has been found to have multiple effects, including antioxidant, anti-inflammatory, and anticancer functions. Compared with inorganic selenium, organic selenium exhibits higher bioactivities and a wider range of safe concentrations. Consequently, there has been a significant development of selenium-enriched foods which contain large amounts of organic selenium in order to improve human health. This review summarizes the physiological role and metabolism of selenium, the development of selenium-enriched foods, the physiological functions of selenium-enriched foods, and provides an analysis of total selenium and its species in selenium-enriched foods, with a view to laying the foundation for selenium-enriched food development.

Integrating genome-wide association study with transcriptomic data to predict candidate genes influencing Brassica napus root and biomass-related traits under low phosphorus conditions.

BACKGROUND: Rapeseed (Brassica napus L.) is an essential source of edible oil and livestock feed, as well as a promising source of biofuel. Breeding crops with an ideal root system architecture (RSA) for high phosphorus use efficiency (PUE) is an effective way to reduce the use of phosphate fertilizers. However, the genetic mechanisms that underpin PUE in rapeseed remain elusive. To address this, we conducted a genome-wide association study (GWAS) in 327 rapeseed accessions to elucidate the genetic variability of 13 root and biomass traits under low phosphorus (LP; 0.01 mM P +). Furthermore, RNA-sequencing was performed in root among high/low phosphorus efficient groups (HP1/LP1) and high/low phosphorus stress tolerance groups (HP2/LP2) at two-time points under control and P-stress conditions. RESULTS: Significant variations were observed in all measured traits, with heritabilities ranging from 0.47 to 0.72, and significant correlations were found between most of the traits. There were 39 significant trait-SNP associations and 31 suggestive associations, which integrated into 11 valid quantitative trait loci (QTL) clusters, explaining 4.24-24.43% of the phenotypic variance observed. In total, RNA-seq identified 692, 1076, 648, and 934 differentially expressed genes (DEGs) specific to HP1/LP1 and HP2/LP2 under P-stress and control conditions, respectively, while 761 and 860 DEGs common for HP1/LP1 and HP2/LP2 under both conditions. An integrated approach of GWAS, weighted co-expression network, and differential expression analysis identified 12 genes associated with root growth and development under LP stress. In this study, six genes (BnaA04g23490D, BnaA09g08440D, BnaA09g04320D, BnaA09g04350D, BnaA09g04930D, BnaA09g09290D) that showed differential expression were identified as promising candidate genes for the target traits. CONCLUSION: 11 QTL clusters and 12 candidate genes associated with root and development under LP stress were identified in this study. Our study's phenotypic and genetic information may be exploited for genetic improvement of root traits to increase PUE in rapeseed.

Transcriptome analysis reveals key regulatory genes for root growth related to potassium utilization efficiency in rapeseed (Brassica napus L.).

Root system architecture (RSA) is the primary predictor of nutrient intake and significantly influences potassium utilization efficiency (KUE). Uncertainty persists regarding the genetic factors governing root growth in rapeseed. The root transcriptome analysis reveals the genetic basis driving crop root growth. In this study, RNA-seq was used to profile the overall transcriptome in the root tissue of 20 Brassica napus accessions with high and low KUE. 71,437 genes in the roots displayed variable expression profiles between the two contrasting genotype groups. The 212 genes that had varied expression levels between the high and low KUE lines were found using a pairwise comparison approach. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional classification analysis revealed that the DEGs implicated in hormone and signaling pathways, as well as glucose, lipid, and amino acid metabolism, were all differently regulated in the rapeseed root system. Additionally, we discovered 33 transcription factors (TFs) that control root development were differentially expressed. By combining differential expression analysis, weighted gene co-expression network analysis (WGCNA), and recent genome-wide association study (GWAS) results, four candidate genes were identified as essential hub genes. These potential genes were located fewer than 100 kb from the peak SNPs of QTL clusters, and it was hypothesized that they regulated the formation of the root system. Three of the four hub genes' homologs-BnaC04G0560400ZS, BnaC04G0560400ZS, and BnaA03G0073500ZS-have been shown to control root development in earlier research. The information produced by our transcriptome profiling could be useful in revealing the molecular processes involved in the growth of rapeseed roots in response to KUE.

A dataset of pomegranate growth stages for machine learning-based monitoring and analysis.

Machine learning and deep learning have grown very rapidly in recent years and are widely used in agriculture. Neat and clean datasets are a major requirement for building accurate and robust machine learning models and minimizing misclassification in real-time environments. To achieve this goal, we created a dataset of images of pomegranate growth stages. These images of pomegranate growth stages were taken from May to September from an orchard inside the Henan Institute of Science and Technology in China. The dataset contains 5857 images of pomegranates at different growth stages, which are labeled and classified into five periods: bud, flower, early-fruit, mid-growth and ripe. The dataset consists of four folders, which respectively store the images, two formats of annotation files, and the record files for the division of training, validation, and test sets. The authors have confirmed the usability of this dataset through previous research. The dataset may help researchers develop computer applications using machine learning and computer vision algorithms.

A dataset of tomato fruits images for object detection in the complex lighting environment of plant factories.

Plant factories are an advanced form of facility agriculture that enable efficient plant cultivation through controllable environmental conditions, making them highly suitable for the automation and intelligent application of machinery. Tomato cultivation in plant factories has significant economic and agricultural value and can be utilized for various applications such as seedling cultivation, breeding, and genetic engineering. However, manual completion is still required for operations such as detection, counting, and classification of tomato fruits, and the application of machine detection is currently inefficient. Furthermore, research on the automation of tomato harvesting in plant factory environments is limited due to the lack of a suitable dataset. To address this issue, a tomato fruit dataset was constructed for plant factory environments, named as TomatoPlantfactoryDataset, which can be quickly applied to multiple tasks, including the detection of control systems, harvesting robots, yield estimation, and rapid classification and statistics. This dataset features a micro tomato variety and was captured under different artificial lighting conditions, including changes in tomato fruit, complex lighting environment changes, distance changes, occlusion, and blurring. By facilitating the intelligent application of plant factories and the widespread adoption of tomato planting machinery, this dataset can contribute to the detection of intelligent control systems, operation robots, and fruit maturity and yield estimation. The dataset is publicly available for free and can be utilized for research and communication purposes.

Integrating biochemical and anatomical characterizations with transcriptome analysis to dissect superior stem strength of ZS11 (Brassica napus).

Stem lodging resistance is a serious problem impairing crop yield and quality. ZS11 is an adaptable and stable yielding rapeseed variety with excellent resistance to lodging. However, the mechanism regulating lodging resistance in ZS11 remains unclear. Here, we observed that high stem mechanical strength is the main factor determining the superior lodging resistance of ZS11 through a comparative biology study. Compared with 4D122, ZS11 has higher rind penetrometer resistance (RPR) and stem breaking strength (SBS) at flowering and silique stages. Anatomical analysis shows that ZS11 exhibits thicker xylem layers and denser interfascicular fibrocytes. Analysis of cell wall components suggests that ZS11 possessed more lignin and cellulose during stem secondary development. By comparative transcriptome analysis, we reveal a relatively higher expression of genes required for S-adenosylmethionine (SAM) synthesis, and several key genes (4-COUMATATE-CoA LIGASE, CINNAMOYL-CoA REDUCTASE, CAFFEATE O-METHYLTRANSFERASE, PEROXIDASE) involved in lignin synthesis pathway in ZS11, which support an enhanced lignin biosynthesis ability in the ZS11 stem. Moreover, the difference in cellulose may relate to the significant enrichment of DEGs associated with microtubule-related process and cytoskeleton organization at the flowering stage. Protein interaction network analysis indicate that the preferential expression of several genes, such as LONESOME HIGHWAY (LHW), DNA BINDING WITH ONE FINGERS (DOFs), WUSCHEL HOMEOBOX RELATED 4 (WOX4), are related to vascular development and contribute to denser and thicker lignified cell layers in ZS11. Taken together, our results provide insights into the physiological and molecular regulatory basis for the formation of stem lodging resistance in ZS11, which will greatly promote the application of this superior trait in rapeseed breeding.

Oncogenic role and drug sensitivity of ETV4 in human tumors: a pan-cancer analysis.

Background: Increasing evidence supports a relationship between E twenty-six variant transcription factor 4 (ETV4) and several cancers, but no pan-cancer analysis has been reported. Methods: The present study surveyed the effects of ETV4 on cancer using RNA sequencing data obtained from The Cancer Genome Atlas and GTEx, and further explored its role in drug sensitivity using data from Cellminer. Differential expression analyses were conducted for multiple cancers using R software. Cox regression and survival analysis were employed to calculate correlations between ETV4 levels and survival outcomes in multiple cancers using the online tool Sangerbox. ETV4 expression was also compared with immunity, heterogeneity, stemness, mismatch repair genes, and DNA methylation among different cancers. Results: ETV4 was found to be significantly upregulated in 28 tumors. Upregulation of ETV4 was associated with poor overall survival, progression free interval, disease-free-interval, and disease specific survival in several cancer types. Expression of ETV4 was also remarkably correlated with immune cell infiltration, tumor heterogeneity, mismatch repair gene expression, DNA methylation, and tumor stemness. Furthermore, ETV4 expression seemed to affect sensitivity to a number of anticancer drugs. Conclusions: These results suggest that ETV4 may be useful as a prognostic factor and therapeutic target.

A systematic dissection in oilseed rape provides insights into the genetic architecture and molecular mechanism of yield heterosis.

Heterosis refers to the better performance of cross progeny compared with inbred parents, and its utilization contributes greatly to agricultural production. Several hypotheses have been proposed to explain heterosis mainly including dominance, over-dominance (or pseudo-overdominance) and epistasis. However, systematic dissection and verification of these hypotheses are rarely documented. Here, comparison of heterosis level across different traits showed that the strong heterosis of composite traits (such as yield) could be attributed to the multiplicative effects of moderate heterosis of component traits, whether at the genome or locus level. Yield heterosis was regulated by a complex trait-QTL network that was characterized by obvious centre-periphery structure, hub QTL, complex up/downstream and positive/negative feedback relationships. More importantly, we showed that better-parent heterosis on yield could be produced in a cross of two near-isogenic lines by the pyramiding and complementation of two major heterotic QTL showing partial-dominance on yield components. The causal gene (BnaA9.CYP78A9) of QC14 was identified, and its heterotic effect results from the heterozygous status of a CACTA-like transposable element in its upstream regulatory region, which led to partial dominance at expression and auxin levels, thus resulting in non-additive expression of downstream responsive genes involved in cell cycle and proliferation, eventually leading to the heterosis of cell number. Taken together, the results at the phenotypic, genetic and molecular levels were highly consistent, which demonstrated that the pyramiding effect of heterotic QTL and the multiplicative effect of individual component traits could well explain substantial parts of yield heterosis in oilseed rape. These results provide in-depth insights into the genetic architecture and molecular mechanism of yield heterosis.

Lightweight saliency detection method for real-time localization of livestock meat bones.

Existing salient object detection networks are large, have many parameters, are bulky and take up a lot of computational resources. Seriously hinder its application and promotion in boning robot. To solve this problem, this paper proposes a lightweight saliency detection algorithm for real-time localization of livestock meat bones. First, a lightweight feature extraction network based on multi-scale attention is constructed in the encoding stage. To ensure that more adequate salient object features are extracted with fewer parameters. Second, the fusion of jump connections is introduced in the decoding phase. Used to capture fine-grained semantics and coarse-grained semantics at full scale. Finally, we added a residual refinement module at the end of the backbone network. For optimizing salient target regions and boundaries. Experimental results on both publicly available datasets and self-made Pig leg X-ray (PLX) datasets show that. The proposed method is capable of ensuring first-class detection accuracy with 40 times less parameters than the conventional model. In the most challenging SOD dataset. The proposed algorithm in this paper achieves a value of Fωß of 0.699. And the segmentation of livestock bones can be effectively performed on the homemade PLX dataset. Our model has a detection speed of 5fps on industrial control equipment.

Lightweight SM-YOLOv5 Tomato Fruit Detection Algorithm for Plant Factory.

Due to their rapid development and wide application in modern agriculture, robots, mobile terminals, and intelligent devices have become vital technologies and fundamental research topics for the development of intelligent and precision agriculture. Accurate and efficient target detection technology is required for mobile inspection terminals, picking robots, and intelligent sorting equipment in tomato production and management in plant factories. However, due to the limitations of computer power, storage capacity, and the complexity of the plant factory (PF) environment, the precision of small-target detection for tomatoes in real-world applications is inadequate. Therefore, we propose an improved Small MobileNet YOLOv5 (SM-YOLOv5) detection algorithm and model based on YOLOv5 for target detection by tomato-picking robots in plant factories. Firstly, MobileNetV3-Large was used as the backbone network to make the model structure lightweight and improve its running performance. Secondly, a small-target detection layer was added to improve the accuracy of small-target detection for tomatoes. The constructed PF tomato dataset was used for training. Compared with the YOLOv5 baseline model, the mAP of the improved SM-YOLOv5 model was increased by 1.4%, reaching 98.8%. The model size was only 6.33 MB, which was 42.48% that of YOLOv5, and it required only 7.6 GFLOPs, which was half that required by YOLOv5. The experiment showed that the improved SM-YOLOv5 model had a precision of 97.8% and a recall rate of 96.7%. The model is lightweight and has excellent detection performance, and so it can meet the real-time detection requirements of tomato-picking robots in plant factories.

Spontaneous fracture of a titanium mesh cranioplasty implant in a child: A case report.

BACKGROUND: Titanium mesh cranioplasty is often performed after decompressive craniectomy. Spontaneous fracture of the titanium prosthesis is an extremely rare postoperative complication. Here, we report a 10-year-old boy who presented with a spontaneous fracture of titanium mesh without antecedent head trauma. CASE SUMMARY: A 10-year-old boy presented with a 1-wk history of a tender bulge over the left temporo-parieto-occipital scalp. He had undergone a temporo-parieto-occipital titanium mesh cranioplasty 26 mo previously. He denied antecedent head trauma. Computerized tomography disclosed a perpendicular fissure in the titanium mesh, suggesting a diagnosis of spontaneous titanium mesh fracture. He underwent a second temporo-parieto-occipital cranioplasty and made an uneventful recovery. Three-dimensional modeling and finite element analyses were used to explore potential risk factors of titanium mesh fracture. CONCLUSION: We report a case of spontaneous fracture of a titanium mesh cranioplasty implant. The current case and literature review indicate that titanium mesh implants should be well-anchored to the base of bony defects to prevent fatigue-induced fractures.

Automatic counting of rapeseed inflorescences using deep learning method and UAV RGB imagery.

Flowering is a crucial developing stage for rapeseed (Brassica napus L.) plants. Flowers develop on the main and branch inflorescences of rapeseed plants and then grow into siliques. The seed yield of rapeseed heavily depends on the total flower numbers per area throughout the whole flowering period. The number of rapeseed inflorescences can reflect the richness of rapeseed flowers and provide useful information for yield prediction. To count rapeseed inflorescences automatically, we transferred the counting problem to a detection task. Then, we developed a low-cost approach for counting rapeseed inflorescences using YOLOv5 with the Convolutional Block Attention Module (CBAM) based on unmanned aerial vehicle (UAV) Red-Green-Blue (RGB) imagery. Moreover, we constructed a Rapeseed Inflorescence Benchmark (RIB) to verify the effectiveness of our model. The RIB dataset captured by DJI Phantom 4 Pro V2.0, including 165 plot images and 60,000 manual labels, is to be released. Experimental results showed that indicators R2 for counting and the mean Average Precision (mAP) for location were over 0.96 and 92%, respectively. Compared with Faster R-CNN, YOLOv4, CenterNet, and TasselNetV2+, the proposed method achieved state-of-the-art counting performance on RIB and had advantages in location accuracy. The counting results revealed a quantitative dynamic change in the number of rapeseed inflorescences in the time dimension. Furthermore, a significant positive correlation between the actual crop yield and the automatically obtained rapeseed inflorescence total number on a field plot level was identified. Thus, a set of UAV- assisted methods for better determination of the flower richness was developed, which can greatly support the breeding of high-yield rapeseed varieties.

Long noncoding RNA TPTEP1 suppresses diabetic retinopathy by reducing oxidative stress and targeting the miR-489-3p/NRF2 axis.

BACKGROUND: Diabetic retinopathy (DR) is a diabetic complication with complex etiology and severe visual impairment. Dysregulated long noncoding RNAs (lncRNAs) are closely associated with DR. This article focused on the impact of lncRNA transmembrane phosphatase with tensin homology pseudogene 1 (TPTEP1) in DR. METHODS: First, sera were collected from DR patients and healthy control. Human retinal vascular endothelial cells (HRVECs) were exposed to high glucose (HG) to construct a DR model in vitro. A real-time quantitative polymerase chain reaction (RT-qPCR) was carried out to detect TPTEP1. Targeting relationships were predicted using StarBase and TargetScan, and confirmed by the Dual-Luciferase Reporter Assay. Cell Counting Kit 8 (CCK-8) and EdU staining were applied to measure cell viability and proliferation, respectively. Protein expression was determined by a western blotting assay. RESULTS: lncRNA TPTEP1 expression was significantly decreased in the serum of DR patients and HG-stimulated HRVECs. Overexpression of TPTEP1 reduced cell viability and proliferation induced by HG and oxidative stress. In addition, overexpression of miR-489-3p impaired the effects of TPTEP1. Nrf2, which was targeted by miR-489-3p, was down-regulated in HG-treatment HRVECs. Knockdown of Nrf2 enhanced the influence of miR-489-3p and antagonized the effects of TPTEP1. CONCLUSION: This study demonstrated that a TPTEP1/miR-489-3p/NRF2 axis affects the development of DR by regulating oxidative stress.

Suppression of innate and acquired immunity in severe hand foot and mouth disease caused by EV71 infections in children.

Hand, foot, and mouth disease (HFMD) is a common children infectious disease caused by human enteroviruses. Most of the cases have minimal symptoms, however, some patients may develop serious neurological, cardiac complications, or even death. The pathological mechanism leading to severe HFMD is not clearly understood, and the immunological status of the individual patient may play an important role. Transcriptomes of peripheral blood mononuclear cells from EV71-infected patients (n = 45) and healthy controls (n = 36) were examined. Immune pathways were up-regulated in patients with mild disease symptoms (n = 11, M) compared to the healthy controls (n = 36, H), demonstrating an effective anti-viral response upon EV71 infection. However, in patients with severe symptoms (n = 23, S) as well as severe patients following treatment (n = 11, A), their innate and acquired immune pathways were down-regulated, indicating a global immunity suppression. Such immune suppression characteristics could thus provide an opportunity for early EV-71 infection prognosis prediction. Based on our cohort, an SVM model using RNA-seq expression levels of five genes (MCL1, ZBTB37, PLEKHM1P, IFNAR2 and YEATS2) was developed and achieved a high ROC-AUC (91·3%) in predicting severe HFMD. Meanwhile, qPCR fold-changes method was performed based three genes (MCL1, IFNAR2 and YEATS2) on additional cohort. This qPCR method achieved a ROC-AUC of 78.6% in predicting severe HFMD, which the patients could be distinguished in 2-3 h. Therefore, our models demonstrate the possibility of HFMD severity prediction based on the selected biomarkers that predict severe HFMD effectively.

AMPK attenuates SHH subgroup medulloblastoma growth and metastasis by inhibiting NF-κB activation.

BACKGROUND: Medulloblastoma (MB) is one of the most common malignant pediatric brain tumors. Metastasis and relapse are the leading causes of death in MB patients. The initiation of the SHH subgroup of MB (SHH-MB) is due to the aberrant activation of Sonic Hedgehog (Shh) signaling. However, the mechanisms for its metastasis are still unknown. RESULTS: AMP-dependent protein kinase (AMPK) restrains the activation of Shh signaling pathway, thereby impeding the proliferation of SHH-MB cells. More importantly, AMPK also hinders the growth and metastasis of SHH-MB cells by regulating NF-κB signaling pathway. Furthermore, Vismodegib and TPCA-1, which block the Shh and NF-κB pathways, respectively, synergistically restrained the growth, migration, and invasion of SHH-MB cells. CONCLUSIONS: This work demonstrates that AMPK functions through two signaling pathways, SHH-GLI1 and NF-κB. AMPK-NF-κB axis is a potential target for molecular therapy of SHH-MB, and the combinational blockade of NF-κB and Shh pathways confers synergy for SHH-MB therapy.

Genetic dissection of branch architecture in oilseed rape (Brassica napus L.) germplasm.

Branch architecture is an important factor influencing rapeseed planting density, mechanized harvest, and yield. However, its related genes and regulatory mechanisms remain largely unknown. In this study, branch angle (BA) and branch dispersion degree (BD) were used to evaluate branch architecture. Branch angle exhibited a dynamic change from an increase in the early stage to a gradual decrease until reaching a stable state. Cytological analysis showed that BA variation was mainly due to xylem size differences in the vascular bundle of the branch junction. The phenotypic analysis of 327 natural accessions revealed that BA in six environments ranged from 24.3° to 67.9°, and that BD in three environments varied from 4.20 cm to 21.4 cm, respectively. A total of 115 significant loci were detected through association mapping in three models (MLM, mrMLM, and FarmCPU), which explained 0.53%-19.4% of the phenotypic variations. Of them, 10 loci were repeatedly detected in different environments and models, one of which qBAD.A03-2 was verified as a stable QTL using a secondary segregation population. Totally, 1066 differentially expressed genes (DEGs) were identified between branch adaxial- and abaxial- sides from four extremely large or small BA/BD accessions through RNA sequencing. These DEGs were significantly enriched in the pathways related to auxin biosynthesis and transport as well as cell extension such as indole alkaloid biosynthesis, other glycan degradation, and fatty acid elongation. Four known candidate genes BnaA02g16500D (PIN1), BnaA03g10430D (PIN2), BnaC03g06250D (LAZY1), and BnaC06g20640D (ARF17) were identified by both GWAS and RNA-seq, all of which were involved in regulating the asymmetric distribution of auxins. Our identified association loci and candidate genes provide a theoretical basis for further study of gene cloning and genetic improvement of branch architecture.