Previous studies have demonstrated that electrical stimulation of the cerebellar fastigial nucleus (FNS) can considerably decrease infarction volume and improve neurofunction restoration following cerebral ischemia. Nevertheless, the molecular mechanism of the neuroprotective effect of FNS is still vague.In this study, we developed a rat model of ischemia/reperfusion that included 1 h FNS followed by reperfusion for 3, 6, 12, 24, and 72 h. The expression profile of molecular alterations in brain tissues was obtained by transcriptome sequencing at five different time points. The function and pathway of miRNA expression pattern and core genes were annotated by Allen Brain Atlas, STRING database and Cytoscape software, so as to explore the mechanism of FNS-mediated neuroprotection.The results indicated that FNS is associated with the neurotransmitter cycle pathway. FNS may regulate the release of monoamine neurotransmitters in synaptic vesicles by targeting the corresponding miRNAs through core Dlg4 gene, stimulate the Alternative polyadenylation (APA) incident’s anti -apoptosis effect on the brain, and stimulate the interaction activation of neurons in cerebellum, cortex/thalamus and other brain regions, regulate neurovascular coupling, and reduce cerebral damage.FNS may activate neuronal and neurovascular coupling by regulating the release of neurotransmitters in synaptic vesicles through the methylation of core Dlg4 gene and the corresponding transcription factors and protein kinases, inducing the anti-apoptotic mechanism of APA events. The findings from our investigation offer a new perspective on the way brain tissue responds to FNS-driven neuroprotection.The online version contains supplementary material available at 10.1186/s12868-023-00811-6. Ischemic stroke is one of the main causes of permanent disability; however, the available treatment options are limited . Energy Despite the wide array of protective benefits FNS contributes, its most distinct advantage involves the immediate activation of neural pathways between disparate brain regions through electrical stimulation, setting it apart from numerous other neuroprotective therapies , 12. SysNeurons in the cerebellum, like other brain regions, are known to interact by changing their firing rates and firing at different rhythms . By seleThe study included two steps. The first step included the development of an experimental model, and the second step included the acquisition of the brain tissue samples for transcriptome sequencing. In the experimental modeling stage, we used an electrical stimulation device to stimulate the rats for 1 h and then generated a rat model of ischemia/reperfusion. Ischemia/reperfusion was performed for 3, 6, 12, 24, or 72 h (5 rats at each time point), and the animals of the control groups (5 rats at each time point) were not subjected to FNS. Then, brain tissues were collected during the second step for sequencing analysis. Finally, the sequencing results were comprehensively assessed and visually analyzed  the I/R control group  and (2) I/R + FNS group . Animals were handled according to the guidelines of the Council of the International Organization for Animal Experimental Medicine . The Animal Care and use Committee of Guangxi Medical University approved the animal protocol .Before the procedure, the rats were subjected to an 8–12 h fasting period. The rats were anesthetized with isoflurane gas inhalation and placed on a brain stereotaxic instrument. A median incision at the top of the skull exposed the skull, and the periosteum was removed. The location of the cerebellar fastigial nucleus was determined according to the stereotaxic map of the brain of Wistar rats. The position 11.1 mm posterior of the posterior edge of the anterior fontanelle was used as stereotaxic zero, and the midline was opened 1.1 mm to the left. A hole was drilled into the skull, and a stimulation needle was inserted to a depth of approximately 5.6 mm. A software-controlled YC-2 stimulator (Chengdu Instrument Factory) was used for electrical stimulation, the range of stimulus parameters reported in the previous literature was used for setting –25: currRat model of cerebral ischemia/reperfusion (I/R) was generated based on the method of Longa. The rats were anesthetized with isoflurane gas inhalation and fixed in the supine position on an operating table. After disinfection, an incision was made from the middle of the neck, and the anterior cervical muscle was bluntly separated to expose the right common carotid artery, external carotid artery, and internal carotid artery. The proximal end of the common carotid artery and the proximal end of the external carotid artery were ligated with an arterial clamp to temporarily block the blood flow of the internal carotid artery. A small opening at the junction of the external carotid artery near the common carotid artery was cut to insert a nylon thread bolt, and the artery clamps were released. The nylon line was gently pushed into the right middle cerebral artery to the depth of (18.5 ± 0.5) mm at the bifurcation to block the blood flow of the right middle cerebral artery. After operation, the skin was sutured to leave 1 cm of the nylon thread on the outside. After 2 h of ischemia, the rats were reperfused by gently lifting the outside end of the nylon thread leading to the stump of the external carotid artery to restore the blood flow. The rats were reperfused for 3, 6, 12, 24, and 72 h.The volume of cerebral infarction was determined by the triphenyltetrazolium chloride (TTC) staining. After 3, 6, 12, 24, and 72 h of ischemia/reperfusion, the rats were anesthetized with 2% sodium pentobarbital (0.3 mL/100 g) i.p and then underwent quick decapitation; the brain was carefully removed from the skull and kept at -20 °C for 30 min. The frozen brain was cut into continuous 2 mm coronal sections and immersed in 2% TTC solution at 37 °C for 30 min. The infarct volume of each brain section was analyzed by a Luxex-F image analyzer.After ischemia/reperfusion, the brain was dissected to harvest the tissue from the ipsilateral cortex beyond optic nerve chiasm. RNA was extracted with TRIzol, and the RNA concentration was detected by using a NanoDrop spectrophotometer . The expression levels of various microRNAs were determined by using an Illumina HiSeq 2500 platform by LC-BIO . The cDNA ends were repaired by agarose gel purification, and adenine was added to the 3’-ends of the cDNA followed by ligation. PCR was used to determine the size and amplify the fragments. Finally, single-end sequencing was performed by using an Illumina Truseq SmallRNA preparation kit .2fold change| > 1)  using DESeq (P < 0.05 and |log1) Table .http://mirwalk.umm.uniheidelberg.de/) and DIANA software [http://diana.imis.athena-innovation.gr/DianaTools/index.php) to predict the target genes of the sequenced miRNAs and selected the targets predicted by both databases. These genes were defined as important target genes. Furthermore, we utilized the web-based gene set analysis toolkit  database [http://www.webgestalt.org/) and STRING database [https://string-db.org/) to perform GO and KEGG pathway enrichment analyses on these targets, determining important pathophysiological genes and pathways.The gene regulation functions of miRNAs primarily involve complementary sequencing with target gene transcripts. Therefore, it is crucial to understand the detailed function of the miRNA target genes (MTGs). We used miRWalk  (http://software  (http://database  (http://database  (https:/http://amp.pharm.mssm.edu/Harmonizome/), which is a collection of genes, proteins, and their functions.eXpression2Kinases  (X2K) ishttps://epigenetics.essex.ac.uk/bloodbrain/) was used to perform methylation analysis of the core genes. We analyzed the methylation of the core Dlg4 gene using samples from blood and four brain regions .Then, the PhenoGen database [https://phenogen.org/), which can be used to investigate the qualitative characteristics of a single gene, was used to perform the expression quantitative trait loci (eQTL) analysis to identify the chromosomal regions corresponding to the location of the gene expression trait locus. Finally, the Harmonizome database was used to perform the ontology analysis of the core genes, and receiver operating characteristic (ROC) curve analysis was used to evaluate the accuracy of the results.In this study, the STRING database of gene interactions was used to construct a gene interaction network. We selected the targets, which have been validated by experimental evidence and have a high degree of confidence in their relationships, as inputs for Cytoscape v3.7.0. Then, the CytoHubba plug-in  was useddatabase  (https:/Alternative polyadenylation (APA) is a molecular mechanism during pre-mRNA processing that involves the use of multiple polyadenylation sites (PA sites) to generate transcripts of lengths from a single gene, expanding the mRNA transcript subtype diversity. Dysregulation of APA can disturb gene expression and induce protein dysfunction, which is associated with many diseases including neuronal degeneration in the brain . APA is P < 0.05 was considered statistically significant.Statistical analysis was performed using SPSS21.0 software. The data are expressed as the mean ± standard deviation (SD). T-test was used for comparison of two groups. P < 0.05)  Fig. .According to the experimental grouping, a visual volcano map Fig.  was consTo predict target genes that were expressed at the same time point, we selected miRNAs with the same co-expression to predict target genes expressed trend. Then, target genes and functional pathways associated with these microRNAs and differentially regulated by FNS were identified. DIANA and miRWalk databases were used to predict target genes. Select overlapping target genes to increase prediction reliability. Ultimately, we screened a total of 2,187 target genes, indicating that miRNAs differentially regulated by FNS have broad impacts on gene regulation.To investigate the details of the biological mechanisms of the influence of differentially expressed MTGs, Webgestalt was used to analyze MTGs, including biological process (BP), cellular component (CC), and molecular function (MF) Fig. A. The reWe identified the transcription factors and kinases of genes that play a role in neuronal regulation. The top 10 transcription factors were UBTF, NFE2L2, TCF3, SALL4, AR, CREB1, SOX2, ZNF384, KLF4, and GATA1 Fig. A, with UThe following core genes were identified by the analysis of the PPI network: Dlg4, Mapk3, Grb2, Ap2b1, Arid4a, Arid4b, Ubl4a, Ap1b1, Oas1b, and Sf3b1 Fig. A. The maAlthough specific DNA sequences that affect Dlg4 methylation have not been described, we utilized the PhenoGen database, a rat brain-wide gene expression database that analyzes the correlations between a phenotype and a central nervous system function and uses behavioral and expression QTL data to identify the core genes. This approach was employed to identify the chromosomal region corresponding to the location of the expression trait locus. The results indicated that Dlg4 is mainly located on chromosome 10 in the rat and that there is a significant correlation between the DNA sequences of chromosomes 3, 5, 11, 15, and 20 and the X chromosome of the rat and the Dlg4 gene Fig. C. Thus, Analysis of the core Dlg4 gene indicated that the functions of Dlg4 include short-term regulation of synaptic plasticity, maturation of synaptic vesicles, and positive regulation of calcium-dependent exocytosis, which are mainly involved in the regulation of synaptic vesicles released by neurotransmitters Table . AdditioThe untranslated regions (UTRs) of mRNAs are critical sites for regulatory control, as they can affect mRNA stability, localization and translation. To gain a better understanding of transcriptional regulation, we explore how alternative cleavage and polyadenylation alter the fate of mRNAs by altering the length of their 3’UTRs . We begaWe quantified APA using the DaPars algorithm and found that the APA site of the Dlg4 gene was located at chr17:7093469-7093932 in the first exon of the 3’-UTR Fig. A. MeanwhRecent research has demonstrated the neuroprotective effects of FNS and suggested that FNS preconditioning can significantly enhance resistance to ischemic brain injury. miRNAs are the general regulators of gene expression at the posttranslational level, and many miRNAs respond to preconditioning stimuli , 47. BraTo explore whether continuous time-series data can provide a better understanding of complex regulatory interactions, we collected a dataset of time-series miRNAs representing changes in electrical stimulation, and analyzed the data sets at different time points after transcriptional activation. We identified miRNAs differentially regulated by FNS and analyzed the neural circuits activated by electrical stimulation of the parietal nucleus, revealing how it confers neuroprotection by modulating neurotransmitter release. Our investigation also identified UBTF as the predominant transcription factor, while MAPK1 was determined to be the most pertinent kinase involved in this process due to its ability to regulate apoptosis. Network topology analysis identified Dlg4, which regulates synaptic vesicles, as the central gene and determined that chromosomes 3, 5, 11, 15, and 20 and the X chromosome of rat may have a profound influence on hypomethylation of Dlg4 in the cerebellum.The Dlg4 gene encodes postsynaptic density protein 95 (PSD95), a major synaptic protein that aggregates glutamate receptors and plays a key role in regulating glutamate receptor density and activity because it acts as the backbone of protein complexes that mediate signaling between membrane glutamate receptors and intracellular pathways –51. TherTranscription factors and kinases play a crucial role in various upstream regulatory pathways, affecting differentiation, proliferation, and apoptosis . UBTF trThe present study’s data suggest that FNS significantly affects gene expression across multiple neuroprotective pathways in various brain regions, including those involved in neurotransmission such as glutamate, serotonin, and dopamine neurotransmitter pathways. Notably, the distribution of several neurotransmitter cycle pathways was highly coincident, and this effect may be related to the metabolic release of neurotransmitters in the neuronal system induced by FNS. The information obtained by integrating time series miRNA data may represent an important step in understanding the principle of FNS regulation. Our findings highlight a unique pattern of miRNA-associated pathways involved in FNS-induced protection against brain injury, underscoring their potential clinical applicability.Both excitatory neurotransmitter glutamate and monoamines, such as dopamine and serotonin, have been shown to regulate neuronal excitability and affect the concentration of glutamate in brain regions like the cortex and hypothalamus. Moreover, neurotransmitters can protect marginally damaged neurons by reducing neuronal activity and ion flow or increasing local metabolism around the injury . TherefoDNA methylation of specific genomic sites in the brain has a significant association with DNA methylation levels in blood samples . NotablyAlternative polyadenylation (APA) has a significant impact on the transformation of biological processes, with many biological processes, such as B cell activation, tumorigenesis, and proliferation, intricately linked to global APA events in the mRNA 3’ UTR. Advances in sequencing and transcriptome analysis techniques have paved the way for groundbreaking discoveries that continue to shed light on disease complexity. Transcription plays a critical role in shaping the functional diversity of cells .Analysis of Dlg4 revealed that brain tissue had the highest frequency of APA events. The likelihood of APA events gradually increased during the early period of ischemia and then stabilized. Furthermore, the probability of APA events was greater under hypoxic conditions, prompting us to investigate the susceptibility of Dlg4 gene to trigger APA events during ischemia and hypoxia. When we correlated gene expression, we discovered that Dlg4 exhibited a positive correlation with the expression of anti-apoptotic genes, but negatively correlated with the expression of apoptotic factors, indicating that Dlg4 played a protective role in regulating the body’s stress response during APA events.The present study has some limitations that should be acknowledged. These include the model’s limited clinical relevance to human stroke patients, possible variability of results due to differences in surgical techniques and anesthesia, unclear mechanisms by which Dlg4 provides neuroprotection, and a lack of evaluation of potential effects beyond the brain. Our study may have the following limitations:(1) Specificity of the model: Although the model aims to simulate ischemic brain injury, it is still an artificial manipulation that does not exactly mimic human stroke situations. (2) Reproducibility of results: Variations in surgical techniques, duration, frequency, or intensity of electrical stimulation, and anesthesia could lead to inconsistent outcomes across different experiments from various labs, challenging the reproducibility of any observed neuroprotective effect or associating benefits with Dlg4 . (3) AttFurther research is necessary to address these limitations and refine the model. One avenue of research could involve exploring alternative models for simulating ischemia/reperfusion injury with greater clinical relevance to human stroke situations. Moreover, studies focused on elucidating the underlying molecular mechanisms by which Dlg4 confers neuroprotection may help refine approaches for stimulating the fastigial nucleus. Conducting larger animal studies with greater anatomical similarity to humans, such as primate models , can alsIn the nervous system, Dlg4 regulates the release probability of synaptic transmitter vesicles, alters short-term presynaptic plasticity , and enhThis study provides the first description of the effect of FNS on miRNA expression profile after cerebral ischemia/reperfusion, including timepoints of 3, 6, 12, 24, and 72 h. Furthermore, the study expands on the enrichment analysis of upstream transcription factors and kinases, explores hypomethylation and regulation of APA events of the core gene Dlg4 (PSD95) in the cerebellum, and investigates its effect on the downstream pathway in neurotransmitter release. Our study reveals that FNS may activate neuronal and neurovascular coupling by regulating the release of neurotransmitters in synaptic vesicles through the methylation of core Dlg4 gene and the corresponding transcription factors and protein kinases, inducing the anti-apoptotic mechanism of APA events, thereby protecting neurons from ischemic injury.Below is the link to the electronic supplementary material.Supplementary Material 1: Table S1: Differentially expressed miRNA in fastigial nucleus stimulation (FNS) group at 3 h, 6 h, 12 h, 24 h and 72 h


Using Cytometry by time of flight (CyTOF), we identified subpopulations with high HLA-DR expression that were associated with indolent behavior. In the RNA sequencing (RNA-seq) dataset, pathways related to immune response were associated with indolent behavior, while pathways associated with cell cycle and proliferation were associated with aggressive behavior. We extracted quantitative radiomics features from the CT scans of the patients. Integrating these datasets, we identified four feature signatures and four patient clusters that were associated with survival. Using single-cell RNA-seq, we found that indolent tumors had significantly more T cells and less B cells than aggressive tumors, and that the latter had a higher abundance of regulatory T cells and Th cells. In conclusion, we were able to uncover a correspondence between radiomics and tumor biology, which could improve the discrimination between indolent and aggressive LUAD tumors, enhance our knowledge in the biology of these tumors, and offer novel and personalized avenues for intervention.Lung adenocarcinoma (LUAD) is a heterogeneous group of tumors associated with different survival rates, even when detected at an early stage. Here, we aim to investigate the biological determinants of early LUAD indolence or aggressiveness using radiomics as a surrogate of behavior. We present a set of 92 patients with LUAD with data collected across different methodologies. Patients were risk-stratified using the CT-based Score Indicative of Lung cancer Aggression (SILA) tool . We grouped the patients as indolent (This study provides a comprehensive profiling of LUAD indolence and aggressiveness at the biological bulk and single-cell levels, as well as at the clinical and radiomics levels. This hypothesis generating study uncovers several potential future research avenues. It also highlights the importance and power of data integration to improve our systemic understanding of LUAD and to help reduce the gap between basic science research and clinical practice. Lung cancer has the highest mortality rate among cancers worldwide, causing more deaths than breast, cervical, prostate, and colorectal cancers, each of which have established population-based screening programs . The 5-yTumor tissues samples were collected from patients undergoing lung resection surgery following an Institutional Review Board–approved protocol 000616 at the Vanderbilt University Medical Center . Written informed consent was obtained from all subjects. Samples were obtained from 92 patients with LUAD, from which 43 were males and 49 were females. The ages from these patients ranged from 48 to 90 with a median of 66.5. See All tissue samples were processed within 1 hour of surgery. For single-cell suspension analyses, lung tissues were minced and digested with Collagenase and DNase I for 1 hour at 37°C. Single-cell suspension was sequentially filtered (70 and 40 μm) and cryopreserved for long-term storage as described previously . Cell viScore Indicative of Lung Cancer Aggression (SILA) is a cumulative aggregate of normalized distributions of the ordered CANARY exemplars  and provHealthMyne platform allows semiautomatic lesion segmentation of the delineated volumes of interest, followed by extraction of radiomics features. The user initializes the lesion segmentation by drawing a long axis on region of interest in an axial plane of the multiplanar reconstruction (MPR). A two-dimensional (2D) segmentation is updated in real time with interactive feedback of the lesion boundary and 2D segmentations on the other MPR planes are immediately proposed. If the contour on a MPR plane seems unsatisfactory, the user can update the segmentation by either drawing long axes on the other MPR views or using a 2D brush tool. When the segmentation is satisfactory, the user can confirm to initiate the three-dimensional (3D) segmentation computation. On the basis of these initial user interactions, the reads per million (RPM) algorithms combined statistical sampling methods together with deep learning strategies to delineate the target volume and provide an automatic 3D segmentation. The 3D segmentation is reviewed by scrolling through slices on the MPR views. Interactive editing tools including 2D and 3D brushes can be used to reduce/enlarge or add details to the proposed volume segmentation. As the 3D segmentation is confirmed by the user, the measure of the long and short lesion axes is automatically determined by leveraging the volume delineation. Many radiomics features are extracted from the segmented volume. Redundant features or features with high interuser/intrauser variability were removed. The radiomics risk score is derived from regression shrinkage and subset selection via Least Absolute Shrinkage and Selection Operator (LASSO) method.We have developed a comprehensive antibody panel that comprises a total of 34 antibodies, including markers for cellular lineage , cancer markers, and signaling pathways. Metal-conjugated antibodies were purchased from Fluidigm and customized conjugations were performed using Maxpar Multi-Metal labeling Kits (Fluidigm) with purified antibodies from different sources see .× 105 cells/mL. Cells were filtered using FACS tubes with filter caps  and collected using a standard/narrow bore on a Helios CyTOF system at the Mass Cytometry Center of Excellence at Vanderbilt University.Cryopreserved samples were thawed and stained with our antibody panel  as descrhttps://github.com/ParkerICI/premessa, version 0.2.4), an R implementation of the MATLAB bead normalization software ]. The optimal number of clusters was determined by calculating the within cluster sum of squares (WSS) for different k values, plotting k versus WSS and choosing the k in which we see a pronounced bend or “elbow” (k = 10). The clusters were annotated on the basis of protein expression and clusters with similar characteristics were merged. Final cell types were annotated as epithelial cancer cells , endothelial cells (CD45−/CD31+), fibroblasts/mesenchymal cells (vimentin+/CD45−/CD31−/EpCAM−/cytokeratin−/cytokeratin7−), and immune cells (CD45+). We performed a second clustering round for immune cells only using immune cell markers CD8, CD4, CD3, CD11b, and CD56. Clusters were annotated into myeloid cells (CD45+/CD3−/CD11b+), CD8+ T cells (CD45+/CD3+/CD8+), CD4+ T cells (CD45+/CD3+/CD4+), double-negative T cells (CD45+/CD3+/CD4−/CD8−), and other immune as the remaining CD45+ cells. Each identified cell subset, including the nonimmune cells, underwent an independent round of clustering using the protein markers showed in their corresponding heat map  following the kit protocol. A quantitation and integrity assessment were completed using the whole-genomic DNA. An aliquot of each sample was analyzed on the Agilent TapeStation and quantified using a Picogreen assay. The samples were normalized and plated using the BioMek FX liquid handler. Libraries were prepared using 12–50 ng of DNA and the Twist Biosciences library preparation kit (P/N 104207) per manufacturer's instructions. Libraries were then captured using the Twist Comprehensive Exome panel (P/N 102031). Individual libraries were assessed for quality using the Agilent 2100 Bioanalyzer and quantified with a Qubit Fluorometer. The adapter ligated material was evaluated using qPCR prior to normalization and pooling for sequencing on the QuantStudio 12K Flex. The libraries were sequenced using the NovaSeq 6000 instrument with 150 bp paired end reads. RTA  was used for base calling and data quality control (QC) was completed using MultiQC v1.7. Each sample was analyzed using the DRAGEN Enrichment Pipeline v3.7.5 to calculate alignment and capture metrics.Sequence data from genomic DNA were aligned to the reference human genome (GRCh38) by Burrows-Wheeler Aligner aligner . For QC The resulting processed file  was analyzed using the R package maftools . We usedRNA was extracted using the RNeasy Plus Mini Kit (Qiagen) following the kit protocol. RNA-seq libraries were prepared using 300 ng of RNA and the NEBNext Ultra II Directional RNA Library Prep kit . Fragmentation, cDNA synthesis, end repair/dA-tailing, adaptor ligation and PCR enrichment were performed per manufacturer's instructions. Individual libraries were assessed for quality using the Agilent 2100 Bioanalyzer and quantified with a Qubit Fluorometer. The adapter ligated material was evaluated using qPCR prior to normalization and pooling for sequencing. The libraries were sequenced using the NovaSeq 6000 with 150 bp paired end reads. RTA  was used for base calling and data QC was completed using MultiQC v1.7 by the Vanderbilt Technologies for Advanced Genomics (VANTAGE) core .QC analysis was performed on all sequencing reads using FastQC package developed by the Babraham Institute bioinformatics group. Reads with poor quality were trimmed and adapter sequences were removed by cutadapt g. Reads were then aligned to human genome (hg38) using STAR  and quanStarting from the raw counts, we removed low variance genes and filtered out genes from chromosomes X and Y. We used the package DESeq2 to perform differential gene expression analysis  and the After dead cell removal with MACS Dead Cell Removal Kit, (Miltenyi Biotec), cells  were submitted for processing using the 10X Genomics platform. Libraries were prepared using P/N 1000006, 1000080, and 1000020 following the manufacturer's protocol. The libraries were sequenced using the NovaSeq 6000 with 150 bp paired end reads. RTA  was used for base calling and analysis was completed using 10X Genomics Cell Ranger software v4.0.0.https://scanpy-tutorials.readthedocs.io/en/latest/pbmc3k.html.We used 10x Genomics Cell Ranger 4.0.0 software to obtain the feature barcode matrices per sample. For further preprocessing steps, we used the scanpy tool . For morWe first computed a principal component analysis (PCA) to reduce the dimensionality of the data and then computed a neighborhood graph on the first 40 principal components. We then used the Leiden graph-clustering method  and obtaPadjusted value < 0.05, and a normalized enrichment score >1.5. We then used the GSVA package to calculate individual expression scores of these pathways for each patient. For the HealthMyne radiomics features dataset, we performed a Spearman pairwise correlation against the SILA score and selected only those significantly correlated . Only patients with complete data were selected, all the matrices concatenated, and the features were scaled and centered. Patients and features were clustered independently using k means . Cluster IDs for each patient and feature can be found in For the data integration effort, we selected only the features that were significantly associated with tumor behavior. From the CyTOF dataset, we included the cell type cluster proportions and the bulk protein expression per patient. In the latter, for a protein marker to be considered, the median of at least one patient group  should be above 1.44, which in raw values (before the arcsinh transform) correspond to 10 “pushes” which is the default lower limit of the Helios . From thP values for multiple hypothesis using the Benjamini and Hochberg method . All methods were carried out in accordance with relevant guidelines and regulations.All the code used to analyze the data and generate the visualizations and tables can be accessed at To characterize the biological landscape of LUAD in association with their radiomics-based predicted behavior , we designed a multi-omic profiling study of surgically removed primary tumors. We present a comprehensive set of 92 patients with LUAD who were treatment naïve at the time of surgery and were representative of the LUAD distribution across age, sex, mutational status, and smoking status . In addiData were collected using different assays . Surgicax ≤ 0.4, n = 14), intermediate , and aggressive , intermediate (n = 21), and aggressive (n = 39) were stained with our previously validated antibody panel , CD8+ T cells (CD3+/CD8+/CD4−), double-negative T cells (CD3+/CD8−/CD4−), myeloid cells (CD11b+/CD3−), and the remainder CD45+ cells were annotated as “Other Immune.” The relative abundance (frequencies) of these main cell types was not significantly different between patient groups , and PD-L1 expression was also correlated with the first two , followed by p-STAT3 and MDM2 (r = 0.47), and HLA-DR and PD-L1 . Although our CyTOF panel did not include sufficient markers to further annotate the identified immune cell types, we also performed reclustering on these with the aim of uncovering some degree of heterogeneity if present , as was the expression of Ki67, TTF1, and MDM2 . In addition, as HLA-DR (an isotype of MHC-II) is known to be involved in antigen presentation, we wanted to see whether the relative abundance of the above-mentioned subsets were significantly correlated with enrichment or depletion of CD8+ and CD4+ T cells and myeloid cells  was processed and the RNA was extracted and sequenced. A subset of those were also used to obtain WES  for genomic analysis. The mutational landscape of our LUAD cohort was very similar to what is expected for this cancer type (KRAS being the top mutated gene (41%) followed by RYR2 (34%) and MUC16  and EGFR (21%) were also among the top 15 mutated genes, and the latter was exclusive from KRAS alterations, as expected. We computed the mutational load for all 56 samples and found that it was mildly but significantly correlated with the SILA score , suggesting that genomic instability increases with the degree of predicted aggressiveness of the tumor  is presented in 2–M checkpoint, E2F targets, DNA replication, and elongation, etc. This suggests that the tumors predicted to be aggressive, share a strong proliferative signal compared with tumors with lower SILA scores. On the other hand, when comparing indolent versus aggressive or indolent versus intermediate, pathways related with immune response were upregulated, such as Inflammatory response, Complement, TGF-beta signaling, TNF-alpha signaling via NFkB, Leishmania infection, IL3, IL5, and GMCSF, Innate immune system, etc. Even though we saw the “Allograft rejection” pathway (a pathway associated with the expression of MHC classes I and II genes) present when comparing indolent or intermediate versus aggressive tumors, the pathways “Antigen processing-Cross presentation” and “MHC class II antigen presentation” were only upregulated in aggressive when compared with intermediate, suggesting that the high HLA-DR protein expression we previously saw associated with indolent tumors , lung nodules were segmented from CT scans for feature extraction (P < 0.05). We then ended up with 61 features, and only five of them were negatively correlated with the SILA score  included mostly radiomics features positively correlated with SILA score, a CyTOF subpopulation (ECC5) enriched in aggressive tumors, and the pathways “O-linked glycosylation of mucins” and “KRAS signaling down.” Feature cluster III (FIII) included the radiomics feature “GLCM homogeneity” and then pathways associated with structural components such as collagen degradation and formation, ECM organization, angiogenesis, cell motility, and EMT. GLCM stands for gray-level co-occurrence matrix, also known as the gray-level spatial dependence matrix, and it is a statistical method of examining texture that considers the spatial relationship of pixels (>70% of variance explained), we observed that FI and FIV showed almost no overlap, whereas FIII mostly overlapped with FI, and FII overlapped mostly with FIV (>55% of variance explained), we observed that clusters P1, P2, and P4 were different from each other, while P3 overlapped with P1 and P2 , whereas cluster 6 showed high expression of CXCL13, a chemokine expressed by Th cells. Numerous CD8+ T cells also expressed GZMA, GZMB, GZMK, and GNLY, which encode the cytotoxic molecules granzymes A, B, and K and granulosyn, respectively. In addition to granzymes and other cytotoxic molecules, cluster 3 also expressed FCGR3A, a gene that encodes CD16, which presumably indicates that these are natural killer T cells , with 0 being CDC1+ DCs, 5 being LAMP3+ DCs, and 6 being plasmacytoid DCs expressing IL3A. Finally, cells from cluster 2 were identified as mast cells for their unique expression of MS4A2. Aggressive tumors as well as P4 tumors were enriched in cluster 1, while the mast cell subset (cluster 2) was dominated by one particular indolent tumor , and cluster 3 is characterized by the expression of KLF4 and MGP, genes associated with mesenchymal cells and regulation of SMC. Indolent and P2 are slightly enriched in cluster 3 cells while aggressive tumors appear to be enriched in cluster 0 cells  and as high cutoff >60%, and found that when using the latter an association with poor prognosis was significant. In a recent study of ours (in vitro studies show that T cells migrate slower through collagen gels of high density compared with low density (in vitro studies have also demonstrated that T cells preferentially migrate along the collagen fibers, indicating that the collagen orientation could control the migration of T cells (+ T cells were skewed toward a Th2 phenotype. We then integrated biological and radiomics features that were significantly associated with tumor behavior (Understanding the biology of LUADs in the context of tumor behavior is crucial to improving the current clinical standards of diagnosis and treatment, particularly in early stages of the disease. In this study, we presented a comprehensive set of patients with early-stage LUAD risk-stratified into predicted indolent, intermediate or aggressive behavior groups based on radiomics, with data collected across different biological layers. First, we used our previously validated CyTOF panel  to assesparadox” , a phenoparadox” . In the paradox” . In a reparadox” , the autifically . Also, aifically . Howeverifically . When cosumption . KIF1A at cancer  and the t cancer . In the t cancer , a gene  hypoxia . One posmstances . In that of ours  using th of ours , we foun of ours . Some in density . Other i T cells . The ove T cells , we see  T cells . We also T cells . In thatbehavior . Howeverbehavior . SimilarOur results show a potential novel bridge between tumor biology and the developing field of radiomics. However, our work also has its limitations. In the clinic, there are fewer patients that come with indolent tumors than aggressive ones, therefore our cohort has a reduced number of these samples which limits the study of intrapatient heterogeneity in this subset and introduces some degree of bias as we have an overrepresentation of aggressive tumors. In the same line, aggressive tumors are, for the most part, bigger than indolent tumors, which inherently influences the total number of cells and thus our ability to capture intracellular heterogeneity. These tissues are also less affected by cell loss during tissue processing. As for clinical limitations, the approach to define the aggressiveness or indolence of LUAD is still at the discretion of the researcher as there is no gold standard. The behavior of LUADs is confounded by the heterogeneous treatments patients undergo and we do not know the true natural history of early LUAD, as prospective studies to simply observe the natural history of the tumor without intervention would be unethical. In this study, all patients had resection of their primary lung nodule and an accompanying CT scan of that nodule obtained a few weeks or days before surgery. We decided to use SILA, a CT-based tool that predicts the degree of histologic tissue invasion and patient survival specifically design for LUAD. We acknowledge that this, as any other predictive tool, is not flawless but it has been thoroughly validated to accurately correlate with histopathologic assessment . Even thIn conclusion, we presented a unique and comprehensive collection of datasets in LUAD from which we were able to elucidate previously unknown insights in the biology of the tumors related to their predicted behavior, and data integration provided an evident and unprecedented link between tumor biology and structural radiomics. We also showed the important role of the TME, both in the immune compartment and the stromal compartment, in defining the indolence or aggressiveness of the tumors. Finally, experimental and mechanistic validations are needed to further understand these relationships. This is a rich data collection with huge potential that could be further explored in the future to answer multiple other research questions regarding LUAD. We believe that this work contributes to the knowledge and characterization of LUAD tumor biology in relation with its indolence or aggressiveness and further research can potentially integrate this evidence into the clinical settings to improve current management of early LUADs.Supplementary Tables S1-S12Supplementary tablesClick here for additional data file.Supplementary Figures S1-S21Supplementary figuresClick here for additional data file.


To investigate the value of MRI texture analysis in evaluating the effect of gestational diabetes mellitus (GDM) on neonatal brain microstructure development, we retrospectively collected images of neonates undergoing head MRI scans, including a GDM group (N1 = 37) and a healthy control group (N2 = 34). MaZda texture analysis software was used to extract the texture features from different sequence images and perform dimensionality reduction, and then the texture features selected by the lowest misjudgement rate method were imported into SPSS software for statistical analysis. In our study, we found that GDM affects the development of the microstructure of the neonatal brain, and different combinations of texture features have different recognition performances, such as different sequences and different brain regions. As a consequence, texture analysis combining multiple conventional MRI sequences has a high recognition performance in revealing the abnormal development of the brain microstructure of neonates born of mothers with GDM. GDM is the most common complication of pregnancy, with prevalence rates ranging from 1 to 20% and increasing yearly worldwide. GDM has been identified as one of the major barriers to improving maternal and child health5. Previous studies have found that 1 in 7 newborns is born to mothers with GDM7. Such offspring are at increased risk of multiple direct complications, including macrosomia, preterm birth, labor injury, shoulder dystocia, neonatal hypoglycemia, respiratory distress, hyperbilirubinemia and low Apgar scores10. In terms of long-term effects, GDM offspring are also at increased risk for diabetes and cardiovascular disease14.Gestational diabetes mellitus (GDM) refers to any degree of glucose intolerance that develops or is first diagnosed in the mother during pregnancy2. Another possible mechanism linking GDM to abnormal brain development in neonates is iron deficiency caused by the rapid addition of red blood cells. Iron is involved in oxygen transport and organogenesis. Low iron promotes specific apoptosis and immature oligodendrocytes, resulting in hypomyelination and a profound influence on neural development5. In addition, learning and memory deficits are strongly associated with changes in insulin signaling within the brains of GDM offspring12.Infant brain development is particularly sensitive to the health conditions of the mother. Maternal hyperglycemia leads to excessive production of proinflammatory cytokines in the placenta and directly affects the fetus, and neonatal hyperglycemia also promotes the production of interleukin 1β (IL-1β), tumor necrosis factor α (TNF-α) and toll-like receptor activity in spleen cells. The abnormal alterations lead to chronic low-grade systemic inflammation and induce the proinflammatory response of activated microglia to increase the sensitivity of inflammatory responses of the central nervous system and ultimately affect fetal and neonatal brain development15. Few studies have used neuroimaging examinations to explore the effects of GDM on offspring brain development. One study using diffusion tensor imaging found that fasting glucose concentration during pregnancy in nonobese mothers was negatively correlated with the fractional anisotropy (FA) in the right amygdala of newborns16. Another neuroimaging study on GDM offspring showed that the FA of the corporis callosi splenium, posterior limb of the internal capsule, and thalamus of the GDM group were significantly lower than those of the control group, suggesting that the offspring of GDM may present abnormal white matter microstructure related to hypomyelination5. A study using an animal model reported that maternal hyperglycemia tended to cause fetal hyperglycemia and iron deficiency, affecting the neural development of several fetal brain regions, such as the striatum and hippocampus12. Magnetic resonance imaging (MRI) is widely used to acquire images and diagnose diseases in clinical practice and can provide multiparameter images such as T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted imaging (DWI)17. Currently, MRI is considered an effective tool for accurately evaluating changes in the neonatal brain and the relationship between these changes and cognitive outcomes. However, previous studies mainly used conventional MRI or diffusion imaging but did not further mine the information contained in the imaging data of GDM offspring. Furthermore, neurological dysfunction has also been reported to occur in some neonates with normal conventional MRI findings19. Texture analysis, an image pattern extraction technique based on microstructural information representation, can extract data such as gray level intensity, pixel position, and the arrangement and relationship between voxel intensity from medical images, allowing quantification of the gray levels inside an image by measuring the spatial relationships through different quantitative values22. It is a well-known medical image processing approach widely used in neonatal acute bilirubin encephalopathy, perinatal asphyxia neonatal brain injury, Parkinson's disease and other brain diseases25.To date, understanding of the effects of gestational diabetes on brain development has been largely based on an assessment of the growth and development of GDM offspring, the determination of some specific biological factors, genetic testing and animal experimentsTo our knowledge, no studies have used MRI texture analysis to explore neural development in newborns of mothers with GDM. Therefore, our main study objective was to investigate the value of MRI image texture analysis in assessing the effect of GDM on the development of the neonatal brain microstructure and to identify the most valuable texture features with the best diagnostic performance, providing objective evidence for formulating early intervention strategies to reduce or avoid the occurrence of neurodevelopmental abnormalities in infants exposed to GDM.p = 0.35), gestational age (p = 0.93), days since birth (p = 0.92), body length (p = 0.48), weight (p = 0.45), head circumference (p = 0.99), neonatal blood glucose (p = 0.60), blood pH value (p = 0.22) or Apgar score (p = 0.53) between the two groups.A total of 71 participants were enrolled, including 37 neonates in the GDM group  and 34 neonates in the healthy control group . The demographic and clinical details are listed in Table P > 0.05), and the 203 texture features from the other 8 brain regions showed significant differences (P < 0.05) between the two groups. Finally, the 203 features with statistical differences were input into the binary logistic regression model, and the results showed that 29 features had a better fitting effect through the Hosmer‒Lemeshow test; that is, the prediction effect of each texture feature was better (P < 0.05).The results show that the combined MI + PA + F dimension reduction method and LDA method yielded the lowest misjudgment rate of 18.80%. Every ROI in a single sequence captured 30 texture features using the MI + PA + F dimension reduction method, and 330 texture features were obtained from the selected 11 ROIs in each sequence. A total of 1320 texture features from T1WI, T2WI, FLAIR and DWI sequences were imported into SPSS software. There were no significant differences in the texture features in the right caudate nucleus, right lenticular nucleus and right thalamus AngScMom and SEntropy) in the genu of the corpus callosum from the FLAIR sequence obtained high AUC values . Among the 29 texture features obtained from the T1WI, T2WI, FLAIR and DWI sequences, 11 texture features, mainly from the FLAIR and DWI sequences, had AUCs greater than 0.7, as shown in Table In this study, texture analysis of MR images became an effective tool for the quantitative identification of differences in brain microstructure development between GDM neonates and healthy controls. By extracting and analyzing the texture features of the studied brain regions from T1WI, T2WI, FLAIR and DWI sequences, we obtained 29 texture features with AUC values greater than 0.6. By synthesizing the statistically significant texture features extracted from each sequence, we found that the recognition performance of those from the different sequences was different. The results of this study indicated that the AUC value and sensitivity of the FLAIR sequence were the highest at 0.97 and 100.0%, respectively. Taken together, we concluded from these findings that the FLAIR sequence had the best recognition performance. It should be emphasized that the sequence with the highest specificity was T1WI, with a value of 91.9%. In addition, the results showed that the number of texture features with recognizable value in the T2WI sequence was the least, which may indicate that the value of the T2WI sequence in detecting brain microstructure abnormalities in offspring of GDM was relatively low.16 found microstructural abnormalities of the thalamus and right amygdala, which are consistent with the results of this study. Xuan et al. found that the abnormal microstructure of the splenium of the corpus callosum in GDM neonates5, together with the abnormal microstructure of the genu of the corpus callosum revealed by our study, is conducive to further demonstrating and integrating the influence of GDM on the neonatal corpus callosum microstructure. Combined with the results of animal experiments conducted by De et al.12 and the abnormal development of the hippocampus in the GDM group in this study, it is preliminarily concluded that the influence of GDM on the brain development of its offspring may last from the fetal to neonatal period. Although microstructural abnormalities in the genu of the corpus callosum, left caudate nucleus and left lenticular nucleus of GDM neonates were not mentioned in previous neuroimaging studies, our study used texture analysis to quantitatively detect subtle microstructural abnormalities in the above brain regions. These differences may be due to the different sensitivities of the imaging methods for subtle pathological alterations. Therefore, more research data are needed to further explore and confirm the above results.We identified some abnormal development of the deep gray matter and white matter microstructure in GDM neonates. The recognition performance of the texture features in different brain regions was also different; specifically, the genu of the corpus callosum, the right hippocampus, the left caudate nucleus and the right amygdala had the best combined recognition performance. Previous studies using the DTI sequence26. The results may be associated with the disrupted microstructural features of the neonatal brain, especially the genu of the corpus callosum in the GDM group. The potential pathophysiological mechanism of the findings is that neuroinflammation caused by GDM leads to abnormal neuron distribution and apoptosis in the neonatal brain16. In addition, iron deficiency in newborns of diabetic mothers promotes neuronal apoptosis and immature oligodendrocytes, resulting in hypomyelination and abnormal cortical connections12. Overall, these results suggest that the texture features based on conventional brain images of neonates, especially the texture features of the genu of the corpus callosum in FLAIR sequence images, are of great value in revealing the effects of GDM on neonatal brain development.Among the 29 texture features that were finally obtained, we found a total of 11 texture features with AUCs greater than 0.7. Combining the above 11 texture features was helpful in identifying the effects of GDM on the development of the neonatal brain microstructure. Notably, only the AUC values of the SAngScMom and SEntropy features in the genu of the corpus callosum in the FLAIR sequence are both greater than 0.8, indicating that these two texture features from a single brain region in a single sequence had good recognition performance. AngScMom reflects the uniformity of the gray distribution and texture thickness of the image, and entropy represents the degree of uncertainty (a measure of randomness). Both of these features are derived from the coocurrence matrix and reflect the spatial correlation characteristics of grayscale on the imageThe limitations of this study should be considered. First, the acquisition of brain images of neonates was relatively difficult, so the number of data samples was relatively small, and the possibility of occasionality in some results cannot be completely ruled out. Furthermore, because of the small sample size, subgroup analyses were not performed to exclude the effects of confounding factors such as the severity of GDM, duration of disease, and treatment scheme on the results. However, this study is the first to explore the neurodevelopmental abnormalities of GDM offspring by using MRI texture analysis, so a large amount of data is needed to further verify the results. Second, there may be some differences in the selected image levels and manual ROI segmentation in the study samples, and the extracted texture features of corresponding brain regions may not completely reflect the heterogeneity of the lesions. Thus, it is necessary to further verify the repeatability of the method in future studies. Third, this was a retrospective cross-sectional study, so some valuable clinical information was absent in the medical records, and the neurodevelopmental evolutional pattern of GDM offspring could not be explored. Prospective longitudinal studies investigating the long-term effects of GDM on neurodevelopment as well as relevant cognition and behavior in GDM offspring can be considered a future research direction.In conclusion, our study used quantitative texture analysis based on conventional MRI to demonstrate that GDM may affect the development of the neonatal brain microstructure. Furthermore, this approach has a high recognition performance in detecting the abnormal development of neonatal brain microstructure before visible morphological abnormalities appear, especially the texture features of the genu of the corpus callosum from the FLAIR sequence, which have good recognition performance and may be a potential biomarker for the early identification and monitoring of GDM-related brain abnormalities in neonates and provide objective evidence for intervention strategies. In addition, our study only required conventional brain MRI of neonates and avoided the increase in scanning time for acquiring additional sequences because of the difficulty of cooperation for neonates during scanning, conducing the possibility for clinical practice.Conventional plain head MR scan images of 71 neonates in the Affiliated Hospital of Southwest Medical University were retrospectively collected, including 37 patients in the GDM group and 34 patients in the healthy control group. Clinical data mainly included gestational age, days since birth, body length, weight, head circumference, neonatal blood glucose, blood pH and Apgar scores (1–5–10 min).27); (2) in addition to GDM, the mother of the neonate had no other diseases affecting fetal development during pregnancy and delivery, such as severe anemia, serious lung disease, hypertension, etc.; and (3) neonatal Apgar score (1–5–10 min) ≥ 7 after birth, and clinical data were complete. The inclusion criteria of the healthy control group were as follows: (1) the mother was healthy, and the neonate did not suffer from any diseases affecting brain development or developmental malformations; and (2) neonatal Apgar score (1–5–10 min) ≥ 7 after birth. The exclusion criteria were as follows: (1) any diseases or developmental malformations that may affect brain development, such as respiratory distress, bilirubin encephalopathy, and infection; (2) a neonatal Apgar score (1–5–10 min) < 7; and (3) a history of improper postpartum care.The inclusion criteria of the GDM group were as follows: (1) the mother of the neonate was diagnosed with GDM : turbo spin echo (TSE), repetition time/echo time (TR/TE) 1600/8.6 ms, slice thickness 4 mm, slice gap 0 mm, matrix 256 × 230, field of view (FOV) 200 mmx200 mm; ② T2-weighted imaging (T2WI): TSE, TR/TE 5140/120 ms, slice thickness 4 mm, slice gap 0 mm, matrix 320 × 210, FOV 170 mmx180 mm; ③ T2 blade fluid-attenuated inversion recovery (FLAIR) imaging: TSE/inversion recovery, TR/TE 6000/123 ms, TI 1966 ms, slice thickness 4 mm, slice gap 0 mm, matrix 256 × 256, FOV 180 mmx180 mm; ④ Diffusion-weighted imaging (DWI): TSE, TR/TE 4000/64 ms, slice thickness 4 mm, slice gap 0 mm, matrix 128 × 128, FOV 180 mmx180 mm, b = 1000 s/mmhttp://www.eletel.p.lodz.pl/mazda/). Using the principle of blinding, two radiologists mapped the ROIs of each patient. When there was disagreement about the delineation of the ROI, the ROI was adjusted after discussion between the two doctors and then verified by a senior radiologist. Finally, consistent results were obtained. We considered and investigated the alterations of texture features in the following structures: the hippocampus, amygdala, caudate nucleus, lenticular nucleus, thalamus and genu of the corpus callosum . All selected brain regions are related to GDM offspring or cognitive function according to previous studies30. All ROIs were manually delineated on the T2W images  workstation in DICOM format, and the two slices with the best visualization of the studied brain regions in the axial view of each sequence were selected. The obtained images were imported into MaZda texture analysis software ; finally, the sketched and normalized ROIs on the image were automatically analyzed, and the texture feature extraction reports of the ROIs were obtained by the software. The process of remaining images was successively repeated according to the above steps for feature extraction. The texture features extracted by MaZda software were classified into the following six categories: run-length matrix (RLM), coocurrence matrix (COM), absolute gradient (GRA), histogram, autoregressive model (AR) and wavelet transform (WAV)31. Thus, the feature reduction method corresponding to the lowest error rate is selected as the optimal dimensionality reduction method in the present study.After texture feature extraction, we imported all texture feature extraction reports into MaZda software and performed dimensionality reduction. Four feature reduction methods, namely, the Fisher coefficient method (Fisher), minimizing classification error probability and average correlation coefficient method (POE + ACC), mutual information coefficient method (MI), and the combination of the above three methods (MI + PA + F), will obtain 10, 10, 10, and 30 optimal texture features, respectively. The B11 program analysis module embedded in MaZda software is used to analyze the optimal texture features obtained by the above four feature reduction methods. The analysis methods included principal component analysis (PCA), linear discriminant analysis (LDA), nonlinear discriminant analysis (NDA), and raw data analysis (RDA), and the analysis results were expressed as the false error rate . The feature reduction method with the lowest error rate can screen out the features with higher distinguishing ability so that enough relevant information for texture discrimination can be obtained when the number of features is limitedχ2 test was used for comparing the distribution of sex. The two independent-sample t-test  or the Mann‒Whitney U test  was used to compare the differences in each measurement variable between the two groups of subjects, and P < 0.05 was considered statistically significant. A binary logistic regression model was used to analyze significantly different texture features between the groups, and the goodness of fit of the model was tested by the Hosmer‒Lemeshow method. The characteristic parameters finally included in the regression model were successively modeled according to different sequences, brain regions and combinations of the indexes. The receiver operating characteristic (ROC) curve was used to assess the performance of the model, and the area under the curve (AUC), sensitivity and specificity were obtained.SPSS 22.0 statistical analysis software was used. The normality of the distribution of measurement data was assessed with a normality test. Data conforming to a normal distribution are expressed as the mean ± standard deviation


To identify transcriptional changes that occur in zebrafish mutants undergoing progressive photoreceptor degeneration, RNA-seq transcriptional profiling was performed on cep290−/− and bbs2−/− retinas. The PANTHER Classification System was used to identify biological processes and signaling pathways that were differentially expressed between mutants and wild-type siblings during degeneration. As expected, genes associated with phototransduction were downregulated in cep290 and bbs2 mutants compared to wild-type siblings. Although both cep290 and bbs2 mutants undergo proliferation of rod precursors in response to retinal degeneration, the process of negatively regulating proliferation is enriched for upregulated genes, and this negative regulation may restrict proliferation of Müller glia and inhibit regeneration. A total of 815 differentially expressed genes (DEGs) were shared by cep290 and bbs2 retinas. Genes in pathways associated with inflammation, apoptosis, stress response, and PDGF signaling were overrepresented. Identifying the genes and biological pathways that are common in zebrafish models of inherited retinal degeneration provides a foundation for future studies on the mechanisms that regulate cell death as well as processes that prohibit Müller cell reprogramming or proliferation in a model capable of retinal regeneration. The pathways will provide targets for future interventions that may promote successful regeneration of lost photoreceptors.Acute injury to the adult zebrafish retina triggers the release of pro-inflammatory cytokines and growth factors that stimulate multiple gene regulatory networks, which ultimately stimulate Müller glia to proliferate and regenerate neurons. In contrast, zebrafish carrying mutations in  Ciliopathies are a collection of rare genetic disorders that result from defects in the genesis or function of primary cilia . Cilia aBBS1-BBS21) and more than 90% of BBS patients experience retinal degeneration by teens to early twenties  are a leading cause of LCA in Caucasians. LCA is initially characterized by nystagmus and visual impairment at birth or in the first few years of life and functional vision rapidly deteriorates  and to determine the common cellular pathways that were altered in the retinas of both bbs2 and cep290 mutants. Disruption to these ciliary genes led to elevated inflammatory signaling, increased expression of solute transporters, and a reduction in visual response gene function. The common pathways suggest that death of photoreceptors triggers an inflammatory response that contributes to photoreceptor death in bbs2 and cep290 models.Assessing changes in gene transcription during photoreceptor degeneration can reveal those cellular pathways and processes that are common between different ciliopathies. In this study, we used bulk RNA-seq and bioinformatics to assess the transcriptomic changes in the retinas of the zebrafish lization . The zebat 6 mpf . In zebrat 6 mpf , yet thecep290fh297  as previously described (Adult zebrafish were maintained and housed in an Aquatic Habitats recirculating system (Pentair) with a 14/10 h light/dark cycle with ambient room lighting. Zebrafish lines used in this study included the mutant lines 290fh297  and bbs297  were dark adapted overnight for 16–20 h and euthanized in the dark. Retinas were dissected from whole eyes with minimal inclusion of the RPE. Four independent samples, each of which contained two pooled retinas, were collected. RNA was purified using Trizol , with Glycoblue  used as a co-precipitant as previously described  or 100 bp (bbs2) reads. All library preparations, quality control, and next-generation sequencing was performed by the Lerner Research Institute (LRI) Genomics Core at the Cleveland Clinic.Fish at 6 months post-fertilization (mpf) of age  < 0.05 were considered differentially expressed genes (DEGs). DESeq2 v1.30.1  were used for the clustering analysis comparing cep290 samples to bbs2 samples to account for differences in sequencing depth between both samples and genes within each experiment. To adjust for the difference in total reads between the cep290 and bbs2 experiments, z-scores were calculated across the 8 samples  within each experiment. The mean count was set to 0 for each gene, with the sample score representing the number of standard deviations away from that mean. Log2 fold change was used for the clustering analysis to compare differential gene expression of both mutants to differential gene expression that occurs during the course of a 28-day retinal regeneration in zebrafish  and gene abundance estimated using the star aligner v2.7.5a . Transcr v1.30.1  was usedDanio rerio reference. In cep290, 16,873 were uniquely mapped to an ontology term, 116 had multiple mapping information, and 4818 were unmapped. In bbs2, 16,957 were uniquely mapped to an ontology term, 115 had multiple mapping information, and 4818 were unmapped. A binomial test was used to identify ontologies that were enriched for upregulated or downregulated DEGs. Ontologies were considered enriched if DEGs were two-fold or greater more common than expected with p < 0.05. The PANTHER over-representation test  was >0.5 or ~ 1.4-fold (n = 413). This was approximately the top 50% of DEGs in both experiments. Of these genes, 341 were uniquely mapped to the genome, 2 had multiple mapping information, and 72 were unmapped. Ontologies were considered overrepresented if they had a FDR < 0.05.PANTHER version 17.0  was usedion test  was perfDESeq2 analyses were performed using R v4.0.4. Python v3.9.13 was used to parse JSON results from PANTHER and perform the clustering analysis. The following packages were used: pandas v1.5.0, numpy v1.23.3 , statistcep290 mapped reads and pairwise comparisons can be found in bbs2 mapped reads and pairwise comparisons can be found in cep290 and bbs2 zebrafish models of retinal ciliopathies is characterized by the degeneration of photoreceptors, chronic inflammation, and increased proliferation of rod precursor cells (cep290 and bbs2 mutants and wild-type siblings at 6 months post fertilization (mpf) when degeneration was ongoing. Total RNA was extracted and purified from dark-adapted retinas (n = 4 per genotype), which had the retinal pigment epithelium (RPE) removed. Individual libraries were prepared from each retina sample and all libraries subjected to next-generation sequencing. The average number of total reads was 1.12×108 per cep290 library and 3.00×107 per bbs2 library. Differentially expressed genes (DEGs) were defined as those genes with p < 0.05 and a false discovery rate (FDR) < 0.05. This definition does not rely on a minimal fold-change criteria, but rather identifies those transcripts expressed in cep290 and bbs2 retinas that exhibit a statistically detectable difference in expression from wild-type across all samples. The cep290 dataset had 1379 DEGs, with 731 upregulated DEGs and 648 downregulated DEGs  was given a z-score by gene equal to the number of standard deviations away from the mean count for that dataset across the 8 samples. A heat map illustrating hierarchical clustering of the datasets using all DEGs in both mutants (n = 5522) revealed a strong similarity in expression patterns between the cep290 and bbs2 mutant samples and that differed from the wild-type samples  were upregulated in both, 390 (47.9%) were downregulated in both, 13 (1.6%) were upregulated in cep290 but downregulated in bbs2, and 9 (1.1%) were downregulated in cep290 but upregulated in bbs2 , indicating that photoreceptor degeneration in both models produced a common set of DEGs. The 50 DEGs found to be expressed most abundantly among these DEGs in common between the mutant retinas were also predominantly downregulated when compared to wild-type retinas , the alpha subunit of cone transducin (gnat2), cone cGMP phosphodiesterase (pde6c), and the solute carrier gene slc24a2, which encodes an ortholog of the potassium-dependent sodium-calcium exchanger found in cone photoreceptors. The 50 DEGs with the greatest fold-change in expression were predominantly upregulated in both mutants  change in expression  and used the PANTHER GO-Slim Molecular Function enrichment analysis to identify specific classes of molecules playing mechanistic role within a pathway. This analysis revealed an overabundance of genes functioning in guanylate cyclase activity, active ion transmembrane transporter activity, anion transmembrane transporter activity, cytokine binding and transcription . The IRFs are key mediators of the interferons (IFNs) to boost the innate immune response , two Fos genes (fosab and fosl1a), and two Jun genes (jun and junbb) were upregulated, suggesting that upregulation of inflammatory markers was mediated by AP-1 in these mutants. The Myc genes mych and myclb were also upregulated, with a role in cell proliferation, cell cycle progression, and apoptosis. Inhibition of TGFβ signaling is necessary for Müller glia proliferation  pathway and gonadotropin-releasing hormone receptor pathway . Knockdown of esrra impairs the expression of sox9 and sox5 in zebrafish  is a centrosomal protein critical to the asymmetric cell division, and its absence resulted in the depletion of radial glia progenitors in mice , but the qRT-PCR failed to reach statistical significance (p = 0.11) due to high variability between samples. The expression of junbb in cep290 mutants was only 0.5-fold higher by RNAseq. While the sensitivity of RNAseq data found this difference to be reproducible across the samples and statistically significant, we could not replicate this result using qRT-PCR. From these results, we concluded that the RNAseq data could be validated using qRT-PCR and that the RNAseq was often more sensitive and capable of detecting small, but reproducible changes in gene expression.To validate our RNAseq results, we utilized quantitative real-time PCR (qRT-PCR) to examine the expression of several genes involved in inflammation and apoptosis . RNA waspathways . In all cep290 and bbs2 mutants do not exhibit signs of regeneration but show evidence of inflammation, we asked how the gene expression patterns in cep290 and bbs2 mutants compared to the transcriptomes of wild-type animals at different stages of regeneration following acute light injury. A previous study provided detailed transcriptional profiling of wild-type retinas during early stages of regeneration at 24 h post lesion (hpl), 36 hpl, 72 hpl, and at ages of neuronal differentiation, such as 5 days post lesion (dpl) and 10 dpl, and at later points of functional recovery, such as 14 dpl and 28 dpl . In aggregate, expression in the two mutants most closely resembles those of zebrafish at later stages of regeneration when proliferation has largely ceased and photoreceptors are differentiating (n = 179), the expression profiles most closely resembles the profiles from later stages of degeneration  to provide higher resolution.Overall, this report provides a foundation for subsequent comparative analyses with other zebrafish models of retinal degeneration, as well as mouse models of retinitis pigmentosa, to identify gene expression changes that contribute to photoreceptor death and for the discovery of pathways that regulate regeneration.cep290 RNAseq data – NCBI BioProject, PRJNA787536.The datasets presented in this study can be found in online repositories. The names of the repositories and accession numbers can be found at: bbs2 RNAseq data – NCBI GEO, GSE223277. The animal study was reviewed and approved by the Cleveland Clinic Institutional Animal Care and Use Committee (IACUC).SG and BP conceived and designed the experiments, analyzed the data, and wrote and edited the manuscript and figures. SG, DP, and BP performed the experiments. All authors contributed to the article and approved the submitted version.This work was supported by NIH grants R01-EY017037 and R01-EY030574 and a Doris and Jules Stein Professorship Award from Research to Prevent Blindness BP. Additional support was provided by an NIH P30 core grant (P30-EY025585), a Foundation Fighting Blindness (FFB) Center Grant, and an Unrestricted Award from Research to Prevent Blindness to the Cole Eye Institute. The LRI Genomics Core is supported by an NIH P30 core grant (P30-CA043703). The funding agencies had no role in the design or execution of the research.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Chenopodium quinoa Willd.) is a plant of South American origin recently valorized for its nutritional and nutraceutical properties in human diet. Quinoa is cultivated in many parts of the world, with a selection of varieties with good adaptability to extreme climatic conditions and salt stress. The variety Red Faro, native to southern Chile but harvested in Tunisia, was considered for salt stress resistance, considering its seed germination and 10-day seedling growth at increasing doses of NaCl . Seedlings were spectrophotometrically analyzed for antioxidant secondary metabolites , antioxidant capacity , antioxidant enzyme activity (superoxide dismutase (SOD), guaiacol peroxidase (GPX), ascorbate peroxidase (APX) and catalase (CAT)) and mineral nutrient content in root and shoot tissues. Cytogenetic analysis of root tip was performed to check for meristematic activity and the possible presence of chromosomal abnormalities induced by salt stress. The results indicated a general increase in antioxidant molecules and antioxidant enzymes NaCl dose-dependent, no effects on seed germination but negative effects on seedling growth, and little effect on root meristems mitotic activity. These results indicated that stress conditions can induce an increase in biologically active molecules that could be used for nutraceutical purposes.Quinoa ( Chenopodium quinoa Willd.) is a dicotyledonous annual plant that belongs to the Chenopodiaceae family, native to the Andean highland region of Lake Titicaca in Perù and Bolivia, which was, for centuries, a basic food of ancient Andean populations [Quinoa  and antioxidant activity (AA) in quinoa plants grown under salinity was reported, suggesting a positive effect on the content of these important bioactive compounds . Other rThe aim of the present research was to investigate the effects of NaCl treatments  on quinoa var. Red Faro seedlings by analyzing seed physiological response in terms of germination percentage, seedling growth, cytological analysis of root meristems, changes in the total polyphenols, total flavonoids, flavonols, anthocyanins, antioxidant activity (DPPH* and ORAC), mineral nutrient content and antioxidant enzymes. This approach might give new insights into the resistance to salt stress and consequent modifications in nutritional value of the under-analyzed variety grown in Tunisia. Chenopodium quinoa Willd. seeds, Red Faro variety, native to southern Chile, were kindly provided by the Association of Environment and Development of Soliman . Seeds were sown in Petri dishes with two sheets of Whatman filter papers imbibed with distilled water for control and in the presence of NaCl 100, 200 and 300 mM for salt stress conditions. Seeds were germinated at 24 °C in the dark for 4 days, then exposed to daylight until the 10th day for the analysis of the earlier stages of germination and growth. Twenty seeds per dish, for a total of 100 seeds, were sown for each treatment. The germination percentage (G%) and the length of roots and shoots, as estimation of plant growth, were measured 10 days after sowing. v/v) to reach a final concentration of 10 mg mL−1. The suspension was shaken overnight in the dark and then centrifuged at 3000× g for 20 min at 4 °C. The supernatant was recovered and processed or stored at –20 °C for the different determinations. All the determinations were performed on seedlings that were carefully washed and separated in roots and shoots on the 10th day after sowing. For polyphenols, flavonoids and flavonols analyses extraction was carried out based on previous protocols . Briefly2CO3 were added; the solution was stirred and incubated for 1 h at room temperature (RT). The absorbance was determined spectrophotometrically at 760 nm against a blank using a UV/visible spectrophotometer apparatus . The TPC was estimated through the calibration curve of gallic acid and expressed as mg of gallic acid equivalents per gram of fresh weight (mg GAE g−1 FW) of each extract. The total polyphenols content (TPC) was determined following the protocol of Singleton and Rossi  with mod2 solution and 800 μL of distilled water and incubated at RT for 5 min. Then, 60 μL of AlCl3 10% in water was added and the solution incubated for 6 min. Next, 400 μL of 1 M NaOH and 480 μL of distilled water were added. After 5 min at RT the absorption was measured at 510 nm against a blank. The FC was determined through the calibration curve of quercetin and expressed as mg catechin equivalents (mg CE g−1 FW) of each extract.The total flavonoids content (FC) was determined by the protocol of Heimler et al. . Specifi−1 FW) of extract. The total flavonols content (FLC) was determined following the protocol of Romani et al. . A totalv/v) at room temperature, and their absorbance was measured at 535 nm. The absorbance values were converted into cyanidin-3-O-glucoside equivalents calculated on the basis of the molar extinction coefficient of this substance in the same solvent and expressed as mg cyanidin 3-glucoside eq/100 g FW.The total anthocyanin content was determined spectrophotometrically with the method of Landi et al.  with somAntioxidant activity by 2,2-diphenyl-1-picrylhydrazyl (DPPH*) assay was determined by the method of Boudjou et al. . A solutv/v) and added to a mixture of 1 mL final volume. The mixture contained 800 μL sodium phosphate buffer  with fluorescein sodium salt (0.05 μM) plus a 100 μL solution of 2,2′-azobis(2-amidinopropane) dihydrochloride (400 mM). The standard mixture consisted of 100 μL of 50 μM 6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid (Trolox); the control consisted of sodium phosphate buffer . The Perkin-Elmer Victor TM X3 apparatus  measured fluorescence every 5 min at 37 °C at 485 nm excitation; 520 nm emission for 60 cycles. The ORAC values were calculated by the formula (As − Ab/At − Ab) × KA, where As is the area subtended by the curve (AUC) of fluorescein in the sample; At and Ab are Trolox and control AUCs, respectively. K is the dilution factor and A is the Trolox concentration (μM). The ORAC unit was expressed in micromoles of Trolox equivalents per g−1 FW (μmol g−1 TE).The oxygen radical absorbance capacity (ORAC) assay was performed following the protocol of Ninfali et al.  with minFor antioxidant enzyme determination, superoxide dismutase (SOD), guaiacol peroxidase (GPX), ascorbate peroxidase (APX), catalase (CAT) and total protein analysis extractions were carried out in accordance with Pereira et al. .w/v) insoluble PVP in the ratio of 1:3 (w/v). The homogenate was filtered by cheesecloth, then centrifuged at 14,000× g for 30 min. The supernatant was collected and stored at −80 °C until use. Protein concentration in quinoa extracts was evaluated in accordance with the Bradford method [Quinoa roots and shoots were frozen and ground in liquid nitrogen, extracted in 100 mM potassium phosphate buffer (pH 7.5) added with 1 mM EDTA, 3 mM DTT and 5% .APX activity was evaluated in accordance with Nakano and Asada  by the dv/v) overnight) and Feulgen staining [Root meristems of quinoa seedlings from control and from each NaCl treatment were collected on the 3rd day after seed imbibition. Roots meristems were squashed on slides after fixation  was determined for mitotic activity and possible cytotoxic effects on root meristems under treatments. Cytological anomalies , consistent in c metaphases, chromosomal bridges and fragments, lagging chromosomes and disturbed anaphases were analyzed for genotoxic effect estimation. +, Ca++, Mg++, K+) using an Inductively Coupled Plasma Emission Spectroscopy . At the harvesting, seedlings were separated in roots and shoots tissues, washed in deionized water, oven-dried until constant weight and weighed for the biomass determination. The dried roots and shoots were powdered (<1 mm) and the acid was digested, then they were analyzed for the content of macronutrients  and microwave-assisted acidic digestion using a microwave Ethos 900 . A digestion method was performed following the protocol described in , with ovp ≤ 0.05. Data are the average of three separate experiments’ ± standard deviation (SD). Three separate experiments were conducted in triplicate and data were reported as mean ± SD. Analysis of variance (ANOVA) and a post hoc Tukey’s multiple range test was used to identify statistically significant differences between treatments using the Statistica package (StatSoft) 6.0 version. Different letters indicate significative differences at Pearson’s correlation and principle component analysis (PCA) were performed to visualize the response to salt stress both in quinoa roots and shoots.The percentage of germination of quinoa seeds exposed to saline stress with 100, 200 and 300 mM NaCl was not influenced by the treatments as no significant differences were observed with respect to the control seeds germinated in water A. On the+ and Cl− ions mainly in glycophytic plants [The germination process can be inhibited by salt stress for the decrease in water potential and the accumulation of toxic Nac plants . Moreovec plants ,30. Quinc plants ,32. The c plants , but datOn the contrary, data reported for other quinoa varieties  evidenced significant negative effects on the hypocotyl length already at 50 mM NaCl, with complete prevention of the growth at 300 mM for the Titicaca and Puno varieties . A previous cytogenetic study indicated that the quinoa genome is allotetraploid with a basic chromosome number x = 9 and 36 small size somatic chromosomes (2n = 36) ,35. In oCytogenetic analysis showed a significant reduction in the mitotic index induced by NaCl from the lowest to the highest concentrations of NaCl in the range of −28.8% −40% with respect to control A. ConsidThe frequency (%) of the different mitotic phases was reported in The main cytological aberrations observed in samples treated with NaCl are reported in Previous studies have demonstrated that salt stress can induce DNA fragmentation up to the induction of apoptotic phenomena with the consequent formation of chromosomal abnormalities . Among c−1 FW in control roots significantly increasing to 0.36, 0.39 and 0.55 mg GaE g−1 FW in 100, 200 and 300 mM NaCl treated roots, respectively  and a dose dependent significant increase in these metabolites under salt stress conditions in shoots. In particular, TPC was 0.24 mg GaE gectively A. In sho−1 FW in control and 0.1, 0.21 and 0.32 mg CE g−1 FW in 100, 200 and 300 mM NaCl-treated samples, respectively. The FC values in shoots were 0.23, 0.68, 0.75 and 0.79 mg CE g−1 FW in control, 100, 200 and 300 mM NaCl, respectively  generated by salt stress and the scavenging capacity of the antioxidant system in the detoxification of ROS in plants (18). In fact, recent works indicated that particularly flavonols and flavonoids, among polyphenols, were involved in plant protection being implicated in scavenging various forms of ROS . SecondaC. quinoa seedlings  of 0.9915 and 0.9896, respectively. Sodium and macronutrients composition in the roots and shoots of quinoa seedlings var. Red Faro were generally affected by the salt concentration in the growth media . Sodium +, Ca++ and Mg++) were significantly affected by the salt stress. In particular, K+ in the roots and shoots decreased significantly with the increase in NaCl treatment, reaching a reduction of more than 50% at 300 mM with respect to the control , and in the shoots, it was reduced in all treatments from −27 to −37% with respect to the control  were sequestered in the vacuoles or were subjected to a compartmentation mechanism, which will be responsible for the osmotic adjustment in plant cells/tissues, as already suggested for other quinoa varieties [+ uptake led to a general nutritional imbalance. Sodium uptake was associated with the reduction in K+ both in the roots and in the shoots, which could be one factor influencing plant growth and development, as the regulation of osmotic pressure, the maintenance of cell turgor and the activation of enzymes employed in the metabolism and synthesis of proteins and carbohydrates are K+-dependent [+ content in quinoa was also a reason for the increased Na+/K+ ratio, which could reflect a competitive process with increased influx of Na+ at the expenses of K+ uptake. It has been suggested that Na+ could be used in osmoregulation to avoid its toxic effect, where several halophytes and the so-called glycophytic includers can perform an effective cellular portioning and translocate Na+ to the shoots to improve both crop resistance and Na+ content as a functional nutrient [+ and K+ in hydrated forms could be partially causing the partial replacement of Na+ in some roles of K+ in plants [+ movement have also been considered, such as the involvement of HKT-type transporters (High-affinity Potassium Transporters) for the translocation of Na+ from the root to the shoot via its recall from the xylem [Our data suggested that the quinoa variety Red Faro has high capacity to uptake, translocate and accumulate high concentration of Naarieties . This exependent . The rednutrient . Moreoven plants . In addihe xylem ,42. ++ in the roots could be explained as a possible exchange of Na+ with Ca2+ from membranes and cell wall as a primary response to salt stress [2+. The less marked decrease observed at 300 mM NaCl could indicate a tentative maintenance of Ca2+ level or its translocation to shoot under the increase in ionic strength in the solution with high salinity. In fact, the level of Ca++ in the shoot at 300 mM NaCl is higher than in control and in 100 and 200 mM NaCl-treated seedlings. The Mg++ concentration remained almost constant in the roots at any treatment, suggesting a lower replacement of Na+ in its functions, while a decrease was observed in the shoots. Thus, the reduction in the macronutrient’s uptake observed in quinoa var. Red Faro under salinity stress may be correlated with the reduced growth observed, although NaCl in solution modulated nutrient levels in roots and shoots differently. The decrease detected for Cat stress ,44. The + content (r = 0.319). Shoot 300 mM had the highest significant and positive correlation with antioxidant compounds , DPPH* (r = 0.738) and ORAC activity (r = 0.533) and antioxidant enzymes , thus confirming the highest antioxidant response to NaCl treatments. It is noteworthy that only root 300 mM NaCl-treated samples strongly negatively correlated with length (r = −0.500), while the correlation of shoot 300 mM NaCl did not reach significance (r = −0.182), in accord with results reported in In order to highlight the antioxidant and biochemical responses of quinoa var. Red Faro roots and shoots to increasing concentrations of NaCl, a Pearson’s correlation  and a pr+ being translocated to the shoots as a functional nutrient and improving health-promoting molecules, such as antioxidants and bioactive compounds. In fact, antioxidant enzymes and bioactive molecules increased in NaCl treatments in a dose-dependent manner. Interestingly, the significant increase in antioxidant molecules, such as polyphenols, flavonoids and flavonols, which have nutraceutical properties, make the plant, in particular this variety, a good candidate as a functional food for animal and human nutrition.The present results on quinoa seedlings evidenced that the var. Red Faro is tolerant to salt stress up to 300 mM NaCl, showing that the percentage of germination and the mitotic activity of root meristems were slightly affected by salt treatments, although an increase in the chromosomal aberrations was noticed, maybe induced by ROS production. In addition, salt treatments affected the mineral nutrient content of the seedlings and sodium accumulation in the tissues, which in turn can act as a chemical eustressor, NaThis study can be the basis for evaluation of the best doses and times of exposure in salt stress experiments in order to have a good compromise between plant growth, its content of mineral elements and the production of biologically active molecules of nutraceutical interest with antioxidant activity and lower anti-nutritional compounds in comparison to seeds. For their nutritional properties, 10-day quinoa seedlings, which are sprouts and microgreens, can be considered superfoods in the food industry and used either fresh or in commercial powder as dietary supplements for human wellness.