Timp1, Sparc, Spp1, Tgfb1, Decr1, Vim, Serpine1, Serpina3n, Thbs2, and Vcan) were identified by the construction of a protein–protein interaction network from 135 differentially expressed genes identified through comprehensive bioinformatics analysis and their reliability was verified using GSE119857. In addition, the 10 hub genes were found to influence the ventricular remodeling of non-infarcted tissue by modulating the extracellular matrix (ECM)-mediated myocardial fibrosis, macrophage-driven inflammation, and fatty acid metabolism. (4) Conclusions: Ten hub genes were identified, which may provide novel potential targets for the improvement and treatment of AMI and its complications.(1) Background: There are few diagnostic and therapeutic targets for myocardial remodeling in the salvageable non-infarcted myocardium. (2) Methods: Hub genes were identified through comprehensive bioinformatics analysis  database) and the biological functions of hub genes were examined by gene ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Furthermore, the differential expression of hub genes in various cell populations between the acute myocardial infarction (AMI) and sham-operation groups was analyzed by processing scRNA data (E-MTAB-7376 from the ArrayExpress database) and RNA-seq data (GSE183168). (3) Results: Ten strongly interlinked hub genes ( As early as the Global Burden of Disease report from 1998 (GBD 1998), acute myocardial infarction (AMI) has been recognized as the most frequent potentially fatal cardiac event worldwide ,3. In AMSeveral biomarkers have been identified for AMI diagnosis, including cardiac troponin (cTn) isoforms I and T . HoweverCcr1, Cxcl2, Ptgs 2, and Mmp8 as potentially critical genes for cardiac remodeling following AMI [With advances in gene chips, high-throughput sequencing, and bioinformatics technologies, it has become possible to identify genes differentially expressed between various physiological and pathological conditions that could serve as diagnostic biomarkers or treatment targets. Park et al. identified mRNAs and miRNAs differentially expressed among AMI stages in mice and suggested that ferroptosis during AMI inhibited the production of the cytoprotective antioxidant glutathione peroxidase 4 (GPX4), leading to oxidative stress, cardiomyocyte death, and loss of cardiac function . In addiIn addition to genes differentially expressed within infarcted regions, several studies have reported transcriptional differences between the infarcted myocardium and the adjacent non-infarcted myocardium , which sIn the current study, we screened two microarray datasets (GSE775 and GSE19322) from the GEO database and one RNA-seq dataset (GSE110209) for DEGs between non-infarcted myocardia in C57BL/6J, MRL/MpJ, and FVB/N mice following AMI or sham treatment. We then identified DEGs uniformly altered across strains as potential diagnostic biomarkers or AMI treatment targets. A protein–protein interaction (PPI) network was constructed to identify hub genes most strongly associated with cardiac remodeling in non-infarcted myocardia post-AMI. Hub genes were then subjected to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to reveal enriched biological functions and pathways. Finally, scRNA data analysis was conducted to examine the contribution of each hub gene to myocardial remodeling.https://www.ncbi.nlm.nih.gov/gds/ (accessed on 2 June 2022)) [The GEO (e 2022))  is a pub2FC| > 1.0 and p < 0.05 used as the criteria for statistical significance. Subsequently, these DEGs that were consistently and significantly up-regulated or down-regulated in all 4 groups  were identified using the “RobustRankAggreg” package, with |log2FC| > 1.0 and p < 0.05  as the criteria for significance.The DEGs between AMI and sham-operation samples were analyzed using the “Limma” package of R 4.0.3 , with |lhttps://string-db.org/ (accessed on 2 June 2022)) and Cytoscape (version 3.7.1). Based on this PPI network, the Cytoscape plug-in MCODE was used to identify PPI modules with a score > 4.5. The DEGs were ranked according to their degree values and the top 10 DEGs were defined as hub genes.A protein-protein interaction (PPI) network was constructed using String version 11.0b ).Bioinformatics processing and clustering of the scRNA-seq data was performed in R using the “Seurat” package  with tSN2FC| > 1.0 and p < 0.05. Screening yielded 4183 DEGs in total, including 3110 up-regulated and 1073 down-regulated genes , which identified 110 genes that were uniformly up-regulated and 25 that were down-regulated in all strains , cellular component (CC), and molecular function (MF) . The topCkap4, Col1a2, Col3a1, and Mmp2), macrophage , endothelial cell , mural cell , B cell , T cell , and natural killer cell . Furthermore, the expression of hub genes was extracted and used to perform differential analysis for different cell populations  and single-cell sequencing (E-MTAB-7376) data. From the RNA-seq data, we extracted the expression data of hub genes in cardiomyocytes from non-infarcted myocardia to compare to the sham-operation group . In addiulations B,C. CombTimp1, Sparc, Spp1, Tgfb1, Vim, and Serpina3n were significantly increased in fibroblasts, and in macrophages, the expression levels of Timp1, Spp1, Tgfb1, and Vim were significantly increased; in contrast, Sparc, Serpine1, Serpina3n, and Thbs2 were significantly down-regulated. This result demonstrates that Timp1, Sparc, Spp1, Tgfb1, Vim, Serpina3n, Serpine1, and Thbs2 are involved in the regulation of cardiac remodeling by fibroblasts and macrophages. Notably, Sparc was significantly differentially expressed in all cell types except natural killer cells after infarction, while Spp1 was significantly differentially expressed in all cell types except cardiomyocytes, which also indicates that Sparc and Spp1 are involved in many cellular regulatory processes during cardiac remodeling as a crucial role.It has been shown that cardiac fibroblasts, which account for approximately 10% of all cardiac cells, are involved in inflammation and phagocytosis and play a major role in cardiac repair ,18,19. MDespite major advances in treatment , AMI is still the main cause of premature mortality worldwide ,6. RecenTimp1, Sparc, Spp1, Tgfb1, Decr1, Vim, Serpine1, Serpina3n, Thbs2, and Vcan) were identified by the construction of a PPI network from these DEGs. Among them, the expression of Timp1, Sparc, Spp1, Tgfb1, Vim, Vcan, Serpina3n, Serpine1, and Thbs2 was up-regulated and Decr1 expression was down-regulated in remote non-infarcted myocardia after AMI. Finally, the differential expression of the 10 hub genes in additional GEO datasets (GSE119857), which performed high-throughput RNA-seq of the remote myocardium 7 days after infarction, was consistent with our initial results  were identified through comprehensive bioinformatics analysis and 10 strongly interlinked hub genes -receptor interaction pathway and were closely associated with fibroblast and macrophage regulation of cardiac remodeling processes. It is shown that activated fibroblasts are the main source of structural ECM proteins in fibrotic hearts . In additabolism , which ptabolism . The baltabolism . TherefoThe cardiac ECM facilitates molecular and electrical signaling among cardiomyocytes and provides mechanical support to the myocardium ,29. The Vcan) [Thbs2), Secreted acidic cysteine-rich glycoprotein (Sparc), Osteopontin (Spp1), Serine (or cysteine) peptidase inhibitor I (Serpine1) [Serpine3n) [Tgfb1), and Tissue inhibitor of metalloproteinase 1 (Timp1) [Many of the identified hub genes were expressed in cardiac fibroblasts and implicated in the formation or regulation of the ECM, including Versican (Vcan) , Thromboerpine1) , Serine rpine3n) , Transfo (Timp1) . Neutrop (Timp1) ,36. To m (Timp1) ,32. In f (Timp1) ,38.Spp1 [Thbs2 [Spp1 up-regulates tissue inhibitors of MMPs and collagen, and conversely down-regulates MMP-1 expression in cardiac fibroblasts [Spp1, acting via β3 integrins, inhibits interleukin-1beta (IL-1β)-induced activation of MMP-2 and MMP-9, thereby increasing the deposition of collagen after AMI [Thbs2 in cardiac fibrosis induced by pressure overload has been widely studied. Following angiotensin II therapy, Thbs2 null mice demonstrated substantial interstitial edema and cardiomyocyte injury, both of which were linked to elevated MMP-2 and MMP-9 activity. Thus, the primary function of Thbs2 in myocardial remodeling appears to be the conservation of ECM integrity through the inhibition of MMP activity [Thbs2-KO mice exhibited increased expression of miR-29 in the skin, accompanied by reduced fibrous collagen and LOX-mediated fibrous collagen cross-linking, resulting in a markedly altered ECM structure [Spp1  and Thbs1 [Thbs2 ,40 are aroblasts ,41. It hfter AMI . Furtherfter AMI . The funtructure .Tgfb1 increases ECM protein production and heart hypertrophy in response to Ang II [Spp1 [Serpine1 [Sparc [Serpine1 is a known downstream transcription target of TGF-β, in the Ang II infusion model of post-AMI remodeling, Serpine1 deficiency resulted in a dramatic up-regulation of TGF-β, integrin-β, and ECM-associated protein transcripts [TGF-β is a critical modulator of inflammation, fibrotic healing, and other cellular reparative processes post-infarction ,46. In to Ang II ,48,49,50II [Spp1 ,52, SerpSerpine1 ,54, and 1 [Sparc ,56. Serp1 [Sparc . In addi1 [Sparc ,57. Althnscripts .Following AMI, signals from damaged myocardia attract circulating monocytes, which then develop into macrophages ,59. The Vcan may be involved in activating macrophages and inducing inflammatory cytokine release [Vim suppresses ROS production [vimentin deficiency caused poor endocytosis, increased oxidative stress, and elevated CD36 expression in macrophages [Sparc-null mice exhibited decreased macrophage numbers in the remote region after AMI, suggesting that SPARC may modulate macrophage viability and chronic immunological responses [Spp1, whose expression was significantly up-regulated  oxidation, which can be partially compensated by increased glucose metabolism . This mety acids ,73. Our  disease ,74,75, wTimp1, Sparc, Spp1, Tgfb1, Decr1, Vim, Serpine1, Serpina3n, Thbs2 and Vcan), that may directly or indirectly regulate myocardial remodeling in the non-infarcted zone after AMI by altering ECM composition, macrophage activity, and fatty acid metabolism. This study thus provides many novel potential biomarkers for the improvement and treatment targets for AMI and associated complications.In summary, we identified 10 hub genes (


Background: Previous studies revealed that colonic cancer-associated fibroblasts (CAFs) are associated with the modulation of the colon tumor microenvironment (TME). However, identification of key transcriptomes and their correlations with the survival prognosis, immunosuppression, tumor progression, and metastasis in colon cancer remains lacking.Methods: We used the GSE46824, GSE70468, GSE17536, GSE35602, and the cancer genome atlas (TCGA) colon adenocarcinoma (COAD) datasets for this study. We identified the differentially expressed genes (DEGs), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, hub genes, and survival-associated genes in colon cancer. Finally, we investigated the correlation of key genes with the survival prognosis, immunosuppression, and metastasis.Results: We identified 246 common DEGs between the GSE46824 and GSE70468 datasets of colonic CAFs, which included 72 upregulated and 174 downregulated genes. The upregulated pathways are mainly involved with cancers and cellular signaling, and downregulated pathways are involved with immune regulation and cellular metabolism. The search tool for the retrieval of interacting genes (STRING)-based analysis identified 15 hub genes and 9 significant clusters in colonic CAFs. The upregulation of CTHRC1, PDGFC, PDLIM3, NTM, and SLC16A3 and downregulation of FBN2 are correlated with a shorter survival time in colon cancer. The CTHRC1, PDGFC, PDLIM3, and NTM genes are positively correlated with the infiltration of tumor-associated macrophages (TAM), macrophages, M2 macrophages, the regulatory T cells (Tregs), T cell exhaustion, and myeloid-derived suppressor cells (MDSCs), indicating the immunosuppressive roles of these transcriptomes in colon cancer. Moreover, the CTHRC1, PDGFC, PDLIM3, NTM, and SLC16A3 genes are gradually increased from normal tissue to the tumor and tumor to the metastatic tumor, and FBN2 showed the reverse pattern. Furthermore, the CTHRC1, FBN2, PDGFC, PDLIM3, and NTM genes are positively correlated with the metastatic scores in colon cancer. Then, we revealed that the expression value of CTHRC1, FBN2, PDGFC, PDLIM3, NTM, and SLC16A3 showed the diagnostic efficacy in colonic CAFs. Finally, the expression level of CTHRC1, PDGFC, and NTM genes are consistently altered in colon tumor stroma as well as in the higher CAFs-group of TCGA COAD patients.Conclusion: The identified colonic CAFs-derived key genes are positively correlated with survival prognosis, immunosuppression, tumor progression, and metastasis. Cancer is a complex ecosystem comprising several cellular components including stromal cancer-associated fibroblasts (CAFs) . CAFs arCAFs are predominantly associated with the secretion of several inflammatory mediators which included chemokines, cytokines, transcription factors, proteases, and growth factors, thereby promoting the immunosuppressive TME . These iHerein, we identified the deregulated transcriptional signatures of human colonic CAFs. Then we analyzed the association of CAFs-derived DEGs with the enrichment of pathways. Moreover, we identified the key hub genes and significant clusters from the protein-protein interaction (PPI) network. Furthermore, we investigated the correlation of key genes with survival prognosis, immunosuppression, tumor progression, and metastasis.https://www.ncbi.nlm.nih.gov/geo/) using the keywords “colon cancer fibroblast,” “cancer-associated fibroblast,” “CAFs” “stroma cells,” “colon tumor stroma cells” and “tumor stroma,” and identified two cancer-associated fibroblasts gene expression datasets GSE46824 (n = 34) [n = 14) [2-base transformation  [https://gdc-portal.nci.nih.gov/), we used the gene expression profiling interactive analysis (GEPIA) [http://gepia2.cancer-pku.cn/#index). Furthermore, we used PrognoScan-based [n = 177) [We searched the NCBI gene expression omnibus (GEO) database ((n = 34)  and GSE7[n = 14)  of colonih.gov/) . For ana (GEPIA)  tool (htan-based  colon can = 177) , for valhttp://www.ncbi.nlm.nih.gov/geo/geo2r), which is an interactive web tool to identify the DEGs. GEO2R tool identified the significant DEGs by utilizing the GEOquery [http://www.bioconductor.org/). The R package “limma” was employed for identifying the significant DEGs between CAFs and normal colonic fibroblasts (NCFs) [p-value ≤0.05 [http://bioinformatics.psb.ugent.be/webtools/Venn/) for identifying common DEGs in both datasets.The differential expression was screened by using GEO2R (GEOquery  and limmGEOquery  from thes (NCFs) . We idenue ≤0.05 , 28. Finp-value <0.05 was considered significant when separating the pathways.We performed a gene-set enrichment analysis of the DEGs by using the gene-set enrichment analysis (GSEA) . We inpuTo better know the relationship among these identified DEGs, the PPI network was established using the STRING-based analysis . To idenn = 177) [p-value <0.05 was considered as significant when comparing the survival between the two groups.We compared the overall survival (OS) and the DFS of colon cancer patients. Kaplan-Meier survival curves were used to show the survival differences between the high expression group and low expression groups. The survival significance of all DEGs in the TCGA COAD cohort was analysed using GEPIA  databasen = 177)  for valip-value is not less than 0.001 (Spearman’s correlation test).ESTIMATE is an algorithmic tool based on the R package for predicting tumor purity, immune score (predicting the infiltrations of immune cells), and stromal score  which uses the gene expression profiles of 141 immune genes and 141 stromal genes . The pre+ T cells, CD4+ regulatory T cells, NK cells, TAM, macrophages, M2 macrophages, Tregs, T cell exhaustion, myeloid-derived suppressor cells (MDSCs), and CAFs. Moreover, we used the metastasis-promoting gene set for identifying the ssGSEA scores of metastasis-promoting genes [p-value less than 0.001.One of the extension packages of GSEA, single-sample gene-set enrichment analysis (ssGSEA) was used to identify the enrichment scores of immune cells for each pairing of a sample and gene set in the tumor samples . We collng genes , 41. AllTo assess diagnostic values of the survival-associated genes, the receiver operating characteristic (ROC) curve was plotted and the area under the ROC curve (AUC) was calculated using the “pROC” R package  to evalup < 0.05 was considered statistically significant for survival analysis. To investigate the correlation of survival-associated genes, Spearman’s correlation between the ssGSEA scores and specific survival-associated genes was performed (p < 0.001). We used Welch’s t-test for identifying the significance of specific genes between the two groups of samples (p ≤ 0.05). We utilized the R package ggplot2 for the graphical presentation of the Heatmap and correlation graph.We used the R software version 4.0.1 for all statistical analysis. In the Log-rank test, CDH13, DSP, EFNB2, IL7R, KIAA1217, KRT19, NTM, PDLIM3, SRGN, SYNPO2L, TGFB2, and TNFSF4 were the most significantly upregulated genes in colon CAFs  between the GSE46827 and GSE70468 datasets. The principal component analysis (PCA) plot of samples is shown in lon CAFs , while Adatasets .The enriched upregulated and downregulated biological pathways were identified by using the GSEA tool , 3. GSEABesides, we identified the 54 KEGG pathways that are significantly linked with commonly found downregulated 174 DEGs . The patPLAUR, RAC2, and TGFB2) and 12 downregulated hub genes   which included 3 upregulated hub genes (and VTN) .p < 0.05). Gene set of cluster 1 is associated with the enrichment of complement and coagulation cascades (p = 1.67e-7). Gene set of cluster 2 is mainly involved with immune regulation and cellular signaling  in TCGA COAD data. Our analysis revealed that the upregulated group of CAFs-derived upregulated genes included d TNFSF4  and the nd TIMP4  are signnd TIMP4 . MoreoveGSE17536 . In contGSE17536 , indicatCTHRC1, NTM, PDGFC, PDLIM3, and SLC16A3 and the downregulated group of FBN2 genes are consistently correlated with the shorter survival time in TCGA and GEO datasets, we investigated the association of these genes with immune score and stromal scores in colon cancer. Interestingly, we found that the expression levels (log2 transformation) of CTHRC1, NTM, PDGFC, and PDLIM3 are moderately correlated with immune scores   . This indicated that the expression levels of CTHRC1, FBN2, NTM, PDGFC, and PDLIM3 genes are associated with the modulation of immune and stromal activity in the colon cancer tumor microenvironment.Since the upregulated group of < 0.001) . In addi< 0.001) . In contCTHRC1, NTM, PDGFC, PDLIM3, SLC16A3, and FBN2) with the several immune stimulatory and inhibitory signatures including CD8+ T cells, CD4+ regulatory T cells, NK cells, TAM, macrophages, M2 macrophages, Tregs, T cell exhaustion, and MDSCs. We found that the expression levels of upregulated CTHRC1, NTM, PDGFC, and PDLIM3 are positively correlated with ssGSEA scores of TAMs, macrophages, M2 macrophages, Tregs, T cell exhaustion, and MDSCs   . Interestingly, the CD8+ T cells, CD4+ regulatory T cells, and NK cells are not significantly correlated with the expression levels of CTHRC1, NTM, PDGFC, PDLIM3, SLC16A3, and FBN2.Since survival time of patients is correlated with immunological responses in human cancers , we inve< 0.001) . Besides< 0.001) . In addiCTHRC1, NTM, PDGFC, PDLIM3, and SLC16A3) and one longer survival-associated gene (FBN2) among the normal fibroblast (n = 9), primary tumor fibroblast (n = 14), and metastatic tumor fibroblast (n = 11) samples of GSE46824 [CTHRC1, NTM, PDGFC, PDLIM3, and SLC16A3 are gradually upregulated from normal to a metastatic tumor, indicating the association of these genes in tumor progression    . Besides < 0.05) . Since tp < 0.001). We found that the expression levels of CTHRC1, FBN2, NTM, PDGFC, and PDLIM3 are positively correlated with the ssGSEA scores of metastasis-promoting genes in the TCGA COAD cohort  have diagnostic value in colonic CAFs. We used the GSE46824 dataset to validate our hypothesis, and the results showed that the ROC curve of the expression levels of these six genes  showed excellent diagnostic value for colonic CAFs and normal colonic fibroblast (p < 0.05)  . In addir stroma . MoreoveFs group . HoweverTNFSF4 gene is associated with epigenetic regulation in colon cancer [SRGN can stimulate the metastasis of CRC as a key downstream target of HIF1-A [TGFB2 is frequently mutated in colon cancer and associated with carcinogenesis [SEPP1 is correlated with M2 macrophage polarization and its downregulation is linked with stemness and proliferation of cells [AOC3, another downregulated gene in CAFs, is associated with the enrichment of pathways in colon cancer [Since CAFs are associated with tumor initiation, invasion, migration, metastasis, and inhibiting immunotherapy response –11, idenn cancer . Xu et af HIF1-A . TGFB2 iogenesis . The redof cells . AOC3, an cancer . AltogetThen, we investigated the deregulated pathways which are associated with CAFs-derived DEGs. We found that the upregulated DEGs are associated with the enrichment of KEGG pathways that are mainly involved with cancer and cellular signaling and development . In cont−/− mice, a marked reduction in regional colonic lymph node metastasis was found, suggesting a substantial role for Rac2 in controlling spontaneous lymph node metastasis [CLU could represent a diagnostic marker for colon cancer screening [Since CAFs-derived transcriptomes  are cructastasis . TGFB2, tastasis . P Mazzacreening . Also, wcreening . The checreening . AltogetCTHRC1 correlated with poor prognosis in patients with CRC [SLC16A3 is correlated with prognosis in pancreatic cancer [CTHRC1, NTM, PDGFC, PDLIM3, and SLC16A3, and downregulated FBN2) for finding the correlations  with various immune signatures    and the expression level of FBN2 showed the opposite trend in the high-CAFs group  . Finally< 0.001) . Shujuann of CRC . PDGFC in of CRC . In CRC ’s serum . In summbroblast . It indir stroma . Also, CD cohort . It indiFs group . As far assembly . It has assembly , 71. Bes cancers . Previou cancers . Further cancers . Althoug cancers . FBN2 an cancers . In cont cancers , 77. In ne cells , indicatCTHRC1, NTM, and PDGFC) is associated with poor survival prognosis, immunosuppression, tumor progression, and metastasis in human colon cancer. Numerous evidence indicated that immunohistochemistry is a highly effective substantial tool to predict survival prognosis in patients with various cancer types [Altogether, these results indicate the expression of CAFs-derived key transcriptomes (er types . Since ler types , measuriThe identification of colonic CAFs-derived key transcriptomes may provide insight into the association of these key genes with survival prognosis, immunosuppression, tumor progression, and metastasis.


The TZX protocol combined 2.2 mg kg-1 tiletamine, 2.2 mg kg-1 zolazepam, and 1.4 mg kg-1 xylazine. After treatment, the mean arterial pressure, systolic arterial pressure, diastolic arterial pressure, heart rate, respiratory rate, peripheral hemoglobin oxygen saturation, rectal temperature, and anesthesia quality were recorded. In phase 2, the feasibility of KMXS and TZX as general anesthetics were evaluated for pig castration. In phase 1, both drug combinations provided smooth induction with similar anesthetic effects. The KMXS protocol provided moderate anesthesia for 60–70 minutes in pigs, while the TZX protocol provided 30–45 minutes. In phase 2, castration was completed smoothly in all pigs with little fluctuation in physiological variables. The KMXS protocol is better for medium-term anesthesia, while the TZX protocol is preferable for short-term anesthesia in pigs.Effective and adequate anesthesia is conducive to better restrain for pigs during surgical or diagnostic procedures This study aimed to evaluate cardiorespiratory and anesthetic effects of ketamine-midazolam-xylazine-sufentanil or tiletamine-zolazepam-xylazine as general anesthetics in miniature pigs. In phase 1, one of the combinations was administered intramuscularly to miniature pigs. The KMXS protocol combined 10 mg kg Pigs are frequently used animal models for medical research because pig cardiorespiratory anatomy and physiology are similar to humans . Pigs arTiletamine is a competitive N-methyl-D-aspartic acid (NMDA) receptor antagonist that exerts analgesia and immobilization, while zolazepam is a benzodiazepine drug for muscle relaxation and sedation –13. XylaTherefore, ketamine, a non-competitive NMDA receptor antagonist  and midaNonetheless, opioids are another widely used analgesic. Sufentanil is a μ-opioid agonist with a 5–10 times higher analgesic effect than its parent drug, fentanyl. Thus, sufentanil is clinically used in general anesthesia and analgesia for dogs –21.However, there are no published manuscripts of veterinary medicine on the use of ketamine, midazolam, xylazine plus sufentanil (KMXS) drug combination for pig anesthesia. We hypothesized that KMXS provides adequate medium-term general anesthesia for pigs with few side effects that could be used for surgical procedures in clinical veterinary practice. Thus, this study evaluated the KMXS combination to provide knowledge on KMXS used for pig anesthesia. The study was performed in two phases to determine the KMXS efficacy in pigs using physiological parameters and evaluating the level of anesthesia (phase 1). Phase 2 evaluated the feasibility of combining KMXS as a general anesthetic for pig castration. All the results of the KMXS treatment were compared with the corresponding effects of TZX.The Laboratory Animal Welfare and Ethics Committee of Northeast Agricultural University  approved the study, performed following the guidelines for Animal Experiments at the Northeast Agricultural University. The study included 36 healthy, eight-month-old Chinese experimental miniature pigs  weighing 36.2 ± 4.8 kg. Pigs were ear tagged for proper identification. The pigs were placed in individual rooms maintained at 23±0.5°C temperature and 55%±15% humidity in an animal research facility at the Northeast Agricultural University of Life Sciences. The room lights were on/off at 7:00 am/ 9:00 pm, and individual room windows provided additional natural light. Pigs were provided a combination of a commercial pig diet and hay with water ad libitum. A physical examination and complete blood count revealed that all the miniature pigs were healthy. Phase 1 included 16 pigs , while phase 2 had 20 male pigs.Sixteen male pigs were allocated into two equal groups , using a random number table, namely KMXS group (ketamine-midazolam-xylazine-sufentanil) or TZX group (tiletamine-zolazepam-xylazine). The pigs fasted overnight with ad libitum access to water. All the investigators involved in both experiments were unaware of the treatment administered to individual animals.-1, midazolam 0.5 mg kg-1, xylazine 2 mg kg-1, and sufentanil 2 μg kg-1), or TZX , administered IM in the neck muscles to the base of the ear. Each combination of drugs was mixed in the same syringe immediately before injection. The recumbent pigs were positioned in the right lateral recumbency and allowed to breathe freely.Food, but not water, was withheld for 12 hours before drug treatments, and all pigs were acclimatized for at least 30 minutes in a room set at 25°C. All pigs are considered healthy following clinical examination and complete blood count before each anesthesia, and each animal was weighed on the day of the experiment. Anesthesia was induced with either KMXS (a combination of ketamine 10 mg kg2) were recorded before treatment (baseline), and at 0, 5, 10, 20, 30, 45, 60, 75 and 90 minutes after treatment. The HR, noninvasive blood pressure , SpO2 and RT, were monitored with the iMCE8 Vet physiological multi-parameters monitor . However, the HR, SPO2, and RT were measured using electrocardiograph (ECG) clips, SpO2 tongue, and temperature probes. For each pig, the NIBP was measured by oscillometry using a blood pressure cuff on the right thoracic limb, slightly distal to the elbow. The RR was recorded by observing thoracic movements for one minute or physiological multi-parameters. The baseline HR was measured manually using a stethoscope placed at the lower-left lateral thoracic wall. All physiological values were recorded by the same investigator who monitored each pig until after recovery.Physiological values, including heart rate (HR), respiratory rate (RR), mean arterial pressure (MAP), systolic arterial pressure (SAP), diastolic arterial pressure (DAP), rectal temperature (RT), and peripheral hemoglobin oxygen saturation , hypoxemia (SpO2 < 90%), bradycardia (HR < 60 beats minute-1), hypotension (MAP < 60 mmHg), or hypothermia (T < 36.6°C). Any pig showing adverse events during the experiment was excluded from the study and treated appropriately.The occurrence of adverse events was recorded, including myoclonus, regurgitation, cardiac arrest, hypoventilation , using a random number table. The pigs fasted overnight with ad libitum access to water. The KMXS or TZX anesthesia protocol was administered by IM injection into the neck muscles (ten pigs per group). Once anesthetized, each pig was positioned in the dorsal recumbency to prepare for surgery using 100% oxygen supplied by the mask. The caudal ventral abdomen and/or perineum was clipped, aseptically prepared, and 2% lidocaine was injected into the testes. All pigs were castrated following the pre-scrotal approach , in whic2, and anesthesia scores were recorded 0, 5, 10, 20, 30, 45, 60, 75, and 90 minutes after administration of KMXS or TZX. The start time of surgery, duration of surgery (minutes) from incision to completion, and the time from completion of surgery until the pig was standing, was recorded. Adverse reactions  were recorded during the surgery.The HR, RR, MAP, SAP, DAP, T, SpOThe sample size was estimated from preliminary data with 80% power to detect a 15% difference in anesthesia score between different treatment groups. The alpha was set at 5%; thus, a minimum of eight pigs was required per group.2, and RT). Time, treatment, and their interactions were fixed effects, and individual pigs were random effects. Post-hoc multiple comparisons were performed using student’s t-test to compare treatment groups at the same time points. Anesthesia scores were not normally distributed (nonparametric variables). Thus, a generalized linear mixed-effects model assuming a Poisson family with a logarithmic link function was used. Simultaneously, Mann-Whitney U tests compared scores at different treatment groups and the 5-minutes time point. Values with p < 0.05 were considered significantly different.The Shapiro-Wilk test determined the normality of data distribution. Data are presented as means ± standard deviation for parametric variables and medians (min-max) for nonparametric variables. The student’s t-test assessed differences between normally distributed groups for induction time, anesthesia duration, recovery time, the time to onset of sternal recumbency, and standing and walking in phase 1. The t-test also assessed the start time of surgery, duration of surgery from incision to completion, and the time from completion of surgery until the pig was standing in phase 2. The general linear mixed model analyzed the normally distributed physiological values .2 and RR were significantly higher in the TZX than in the KMXS group (p = 0.036 and 0.001), but the baseline RR and SPO2 were not significantly different from TZX. In the KMXS group, both SpO2 and RR were consistently below the baseline at 5~ 90 minutes, and some pigs developed mild hypoxemia. The RT decreased relative to the baseline after KMXS or TZX treatments but was non-significant. The rectal temperature of all pigs was 38.0 ± 0.5°C. No hypotension, bradycardia, or bradypnea was observed in phase 1, except for mild hypoxemia in the KXMS group.The SpO2 and RR were not statistically different over the time course and the interaction between time and treatment groups. Nevertheless, SpOIn phase 2, all twenty pigs underwent castration smoothly with no apparent movement or pain during surgery. The anesthesia score  was signThe results of physiological parameters in phase 2 are shown in In this study, cardiorespiratory and anesthetic effects were evaluated after IM administration of KMXS (phase 1), and the feasibility of KMXS as a general anesthetic in pig castration was subsequently evaluated (phase 2). The KMXS combination had not previously been tested in pigs, and all the results were compared with TZX. In phase 1, KMXS caused rapid and smooth induction in anesthetized pigs. The TZX group also reported rapid and smooth anesthetic induction with some adverse events, consistent with previous studies , 9.-1 ketamine (K20MX) or 10 mg kg-1 ketamine (K10MX) in combination with midazolam (0.25 mg kg-1) and xylazine (2 mg kg-1) was compared in pigs [10XM lacked analgesic effects with shorter recumbency and recovery duration. The K20XM group can provide analgesia within 40 minutes, but the duration of anesthesia is significantly longer (approximately 90 minutes) [-1 ketamine, 0.5 mg kg-1 midazolam and 2 mg kg-1 xylazine, and 2 μg kg-1 sufentanil.In another study, the anesthesia effects of 20 mg kg in pigs . K10XM lminutes) . We hypoIn phase 1, The anesthesia score increased gradually (5~20 minutes) and then reduced (60~90 minutes) over time in both KMXS and TZX, but the KMXS score significantly increased compared with TZX over the time course, treatment, and their interaction. Moderate anesthesia was defined as the total anesthesia score > 11 , 26, and-1 vs TZX group 1.4mg kg-1) caused the difference in arterial blood pressure and heart rate between the two treatment groups in stage one.Xylazine is associated with bradycardia, respiratory depression, and hypotension , 30, pro2 were higher in the TZX than in the KMXS group. The KMXS group showed mild hypoxemia and respiratory depression at phase 1. The RT in the two treatment groups was not significantly different and remained within the normal range. Therefore, we believe that the KMXS protocol has a relatively small effect on the physiological variables of pigs, except for mild hypoxemia, which may require additional oxygen supplementation and monitoring.Nevertheless, the RR and SpOCastration is one of the most commonly surgical procedures in domestic and pet pigs , 33, 34.In contrast, the TZX group provided 30~40 minutes  in phase 2. The MAP, SAP, DAP, and HR in the TZX group were higher than the KMXS group, and the changes were within the acceptable range. Similarly, all values of SpO2 and RR in the KMXS protocol were within the normal range. No hypoxemia and respiratory depression were observed, possibly due to additional supplemental oxygen.This study had some limitations. First, the study monitored the non-invasive blood pressure, but the more reliable method of invasive blood pressure or doppler blood pressure was not monitored due to lack of equipment. Secondly, the study sample size was small. Future studies will evaluate more clinical applications on the KMXS protocol.-1 ketamine, 0.5 mg kg-1 midazolam, and 2 mg kg-1 xylazine with 2 μg kg-1 sufentanil administered intramuscularly for medium-term anesthesia. Tiletamine-zolazepam-xylazine is preferred for short-term anesthesia on pigs in clinical veterinary practice.In conclusion, these results support the combination of 10 mg kgS1 Data(XLSX)Click here for additional data file.


Uterine leiomyomas are the most common benign tumors of the female reproductive system. Obese individuals have a higher burden of uterine leiomyoma, yet the mechanism relating obesity and leiomyoma development remains unknown. In this study, we observe the effect of adipocyte coculture and leptin treatment on human myometrium and leiomyoma cells. We isolated primary leiomyoma and myometrium cells from hysterectomy or myomectomy patients. Protein expression levels of phosphorylated ERK1/2/total ERK1/2, phosphorylated STAT3/total STAT3, and phosphorylated AKT1/2/3/total AKT1/2/3 were quantified using immunoblotting in immortalized and primary leiomyoma and myometrial cells cocultured with human adipocytes and treated with leptin. An enzyme-linked immunosorbent assay (ELISA) was used to assess pro-inflammatory, fibrotic, and angiogenic factors in immortalized human myometrium and leiomyoma cells treated with leptin. The effects of STAT3, ERK, and AKT inhibitors were assessed in leiomyoma cell lines additionally cultured with adipocytes. Adipocyte coculture and leptin treatment increases the expression of JAK2/STAT3, MAPK/ERK, and PI3K/AKT signaling while inhibitors suppressed this effect. Leptin induces a tumor-friendly microenvironment through upregulation of pro-inflammatory , fibrotic , and angiogenic  factors in human leiomyoma cells. Furthermore, adipocyte coculture and leptin treatment increases leiomyoma cells growth through activation of MAPK/ERK, JAK2/STAT3, and PI3k/AKT signaling pathways. Finally, STAT3, ERK, and AKT inhibitor treatment suppressed PCNA, TNF-α, TGF-β3, and VEGF-A intracellular staining intensity in both adipocyte coculture and leptin treated leiomyoma cells. These findings suggest that, in obese women, adipocyte secreted hormone or adipocytes may contribute to leiomyoma development and growth by activating leptin receptor signaling pathways. Uterine leiomyoma, the leading cause for hysterectomies in the United States, are the most common benign neoplasm of the female reproductive system . UterineIn recent years, epidemiological studies have determined an association between obesity and the development of uterine leiomyoma, though the underlying mechanism remains unknown ,4,5,6,7.In this study, we aim to further investigate the pathophysiological association between obesity and uterine leiomyoma development. To do this, we sought to investigate the influence of adipocyte coculture on leptin receptor pathways in human uterine myometrium and leiomyoma cells. We further investigated the potential role of leptin in the inflammation, angiogenesis, and fibrosis in human uterine leiomyoma and myometrium cells.2 at 37 °C. Human uterine smooth muscle (UtSM) and leiomyoma (HuLM) cells, previously utilized by us and others, were gifted to us by Dr. Darlene Dixon [2 at 37 °C. To model mature adipocytes, we used the human liposarcoma SW872 cell line [2 at 37 °C to maintain the cell line.As previously done, primary myometrium and leiomyoma cells were isolated from five different human patients who underwent hysterectomy or myomectomy at the Department of Gynecology and Obstetrics at Johns Hopkins University Hospital ,12. All ne Dixon ,12,13,14ell line . We obtaThe primary myometrium and leiomyoma cells were treated with 100 ng/mL leptin for 48 h. Human adipocyte (SW872) cells were used to coculture with human primary or immortalized myometrium and leiomyoma cells [The medium was gathered from various experiments, centrifuged, and stored at −80 °C. For analysis, we then shipped the media to Eve Technologies Corporation . We used a Multiplex Immunoassay  to measure pro-inflammatory, fibrosis, and angiogenesis factors. The sensitivity threshold for an ELISA is 2.2 pg/mL, and coefficient of variation for intra- and inter-assays were 6.3% and 8.1%, respectively.Following coculture and leptin treatment, we harvested and lysed the primary and immortalized myometrium and leiomyoma cells in an ice-cold lysis buffer . The buffer was composed of a phosphatase and protease inhibitor cocktail (MilliporeSigma). We combined the same amounts of protein lysates with 4–12% Bis-Tris gradient gels (Thermo Fisher Scientific) and transferred them onto nitrocellulose membranes (Thermo Fisher Scientific). For 1 h at room temperature, we blocked the membranes by soaking them in Tris-buffered saline with 0.1% Tween-20  in 5% nonfat milk. The membranes were then incubated for 24 h with the following specific primary antibodies: anti-total STAT3 , anti-phosphorylated STAT3 , anti-phosphorylated AKT1/2/3 , anti-total AKT1/2/3 , anti-phosphorylated ERK1/2 , and anti-total ERK1/2 . These membranes were left overnight at 4 °C on a rocker, diluted in 5% BSA (1:1000). We then washed the membranes with TBST and incubated the membranes with the corresponding horseradish peroxidase (HRP)-conjugated secondary antibodies for 1 h at room temperature. Using an Azure Imager c300 , we visualized the membranes. The protein band signals were quantified using the NIH ImageJ software (version 1.52r) .A formaldehyde solution of 4% was used to fix immortalized leiomyoma cells following coculture and leptin treatment. Next, the cells were incubated at room temperature for 1 h with a blocking solution containing 1% PBS, 5% normal goat serum , and 0.3% Triton X-100 . They were then incubated for a period of overnight at 4 °C with primary antibodies against PCNA , TNF-α , TGF-β3 , and VEGF-A . A secondary antibody conjugated with antirabbit Alexa 488  and antimouse Alexa 546  was then added to the cells and incubated for 1 h in the dark at room temperature. DAPI with ProLong Gold Antifade Mountant (Thermo Fisher Scientific) were used to fix the slide overnight at room temperature. Using a Zeiss AxioPlan 2 microscope , pictures were taken at 20X magnification. Using ImageJ , we analyzed the staining intensity.p < 0.05 considered statistically significant.We used GraphPad Prism 6.01 for statistical analysis of all the experiments. Each experiment was conducted three times. The results were expressed as the mean ± standard error of the mean (SEM). To compare two groups, we used a Student’s t-test, with differences at Activation of Stat3 occurs when Thy705 is phosphorylated and activated by kinases upstream, such as Janus Kinase 2 (JAK2). In our previous publication we have demonstrated that leptin treatment increased pSTAT3/STAT3 signaling in immortalized leiomyoma cells . To furtA number of extracellular stimuli, including mitogens, growth factors, and cytokines, can activate the p44/42 MAPK (ERK1/2) signaling pathway. In order to activate p44 and p42, MEK1 and MEK2 phosphorylate and Thr202/Tyr204 and Thr185/Tyr187, respectively, are in the activation loop. The MAPK/ERK is another marker in leptin receptor signaling pathways and it was observed previously that leptin treatment increases MAPK/ERK signaling in immortalized leiomyoma cells . Next, wSeveral members of the serine/threonine kinase AKT family exist, including AKT1, AKT2, and AKT3. The activation of AKT1 and AKT2 is dependent on the phosphatidylinositol 3-kinase complex (PI3K) subunits Thy740 and Thy751. However, both Thr 308 and Ser 473 of Akt1 are phosphorylated by insulin or insulin-growth factor-1 (IGF-1). The AKT3 protein is phosphorylated on a serine residue in response to insulin. Cells stimulated by Insulin/IGF-1 undergo phosphorylation and activation of AKT proteins. Activation of the PI3K/AKT pathway has been observed as promoting uterine leiomyoma growth . In primIt is known that obesity affects the tumor microenvironment through the release of several inflammatory mediators . ChronicAdipocytes are known to secrete leptin, pro-fibrotic factors, and angiogenic factors . TherefoLeptin treatment has previously been shown to augment the effect of STAT3 and ERK inhibitors in leiomyoma cells . We sougAdipocyte coculture and leptin treatment has previously been shown to increase PCNA expression in leiomyoma cells . ElevatePrevious studies have shown that coculture of adipocytes increases TNF-α, TGF-β3, and VEGF-A levels in medium, and TGF-β3 and VEGF-A expression in obese individuals . The purIn this study, we focused on the impact of adipocyte coculture on leiomyoma and myometrium cells. We found increased activation of MAPK/ERK, JAK2/STAT3, and PI3k/AKT signaling pathways in human leiomyoma cells as a result of adipocyte coculture, outlining the pathophysiological link between adipocyte hypertrophy in obesity and the development of uterine leiomyoma. Additionally, inhibitors of MAPK/ERK, JAK2/STAT3, and PI3k/AKT leptin receptor pathways are more effective in leiomyoma cells cocultured with adipocytes. These findings suggest that therapeutics for uterine leiomyomas should consider the role of adipocytes in cell proliferation and growth. Finally, we found a direct impact of leptin treatment on pro-inflammatory, angiogenic, and fibrotic factors in the tumor microenvironment.Several epidemiological studies have proven an association between obesity and uterine leiomyoma. However, the complex pathophysiology underlying this association remains unclear.Activation of JAK2/STAT3, MAPK/ERK, and PI3k/Akt pathways have previously been linked to the binding of leptin, an adipocyte derived hormone, to Ob-R ; howeverOur study found that leptin treatment of leiomyoma cells increased pro-inflammatory factors, MCP-1, IFNγ, IL-8, GM-CSF, IL-6, and TNF-a. Increasing evidence is demonstrating the association between leptin, an adipocyte-secreted hormone, and cancer progression ,24,25,26This study complements the body of epidemiological literature linking obesity and uterine leiomyoma growth by further elucidating the pathophysiology. Obesity has grown as an epidemic in the United States, and strategies aiming to reduce adipose tissue in individuals may help to reduce the large burden of disease of uterine leiomyomas.


OsHDZIP genes from the rice genome database. The evolutionary relationship, gene structure, conserved motifs, and chemical properties highlight the key aspects of OsHDZIP genes in rice. The OsHDZIP family is divided into a further four subfamilies . Moreover, the protein–protein interaction and Gene Ontology (GO) analysis showed that OsHDZIP genes regulate plant growth and response to various environmental stimuli. Various microRNA (miRNA) families targeted HDZIP III subfamily genes. The microarray data analysis showed that OsHDZIP was expressed in almost all tested tissues. Additionally, the differential expression patterns of the OsHDZIP genes were found under salinity stress and hormonal treatments, whereas under brown planthopper (BPH), striped stem borer (SSB), and rice leaf folder (RLF), only OsHDZIP3, OsHDZIP4, OsHDZIP40, OsHDZIP10, and OsHDZIP20 displayed expression. The qRT-PCR analysis further validated the expression of OsHDZIP20, OsHDZIP40, and OsHDZIP10 under BPH, small brown planthopper (SBPH) infestations, and jinggangmycin (JGM) spraying applications. Our results provide detailed knowledge of the OsHDZIP gene family resistance in rice plants and will facilitate the development of stress-resilient cultivars, particularly against chewing and sucking insect pests.The homeodomain-leucine zipper (HDZIP) is an important transcription factor family, instrumental not only in growth but in finetuning plant responses to environmental adversaries. Despite the plethora of literature available, the role of HDZIP genes under chewing and sucking insects remains elusive. Herein, we identified 40  The homeodomain–leucine zipper (HDZIP) is a transcription factor family that plays a vital role in plant growth, developmental processes, and stress response [Plantae is different than in other organisms [The static nature of plants entails the frequent endurance of various environmental stresses. In response, plants have developed various mechanisms to adjust to the constantly changing environment . These dresponse . The HDZresponse ,4. Theserganisms . Based organisms ,7,8. The HDZIP subfamily I was found to be highly responsive in the developmental stages and regulates host plant resistance to several abiotic stresses ,10 and bNilaparvata lugens Stål and Laodelphax striatellus (Hemiptera: Delphacide), are recognized as key pests [Rhizoctonia solani) [In the recent decades, rice consumption has increased globally. A statistical analysis of rice consumption showed a high increase: in the 2008/2009 crop year, 437.18 million metric tons (MMTs) of rice was consumed; in comparison, in 2021/2022, 509.87 MMTs of rice was consumed worldwide. [ey pests ,20. Bothey pests . Host pley pests . Further solani) . However solani) ,27. Previously, the plant hormone jasmonic acid (JA) is reported to play the main role in host plant defense against numerous herbivores. Herbivore damage elicits a rapid and transient JA burst in the wounded leaves, and JA functions as a signal to mediate the accumulation of various secondary metabolites that confer resistance to herbivores . BrassinHDZIP gene family associated with growth and development, physiological and various defense responses, and the diversity of HDZIP gene family members in many plant species, it is critical to investigate the global status and evolution of the HDZIP gene family in rice [OsHDZIP gene family against BPH and SBPH infestations. Additionally, an expression analysis was also performed in rice plants treated with JGM fungicide. Comprehensive in silico analyses were also performed by exploring the rice genome and expression databases. We believe our results will facilitate future research work in the field of rice stress biology, particularly in response to BPH. Considering the potential role of the  in rice . Herein,OsHDZIP gene family regarding sequence analysis in Oryza sativa and their counterparts, we retrieved the OsHDZIP proteins from the Arabidopsis thaliana genome “TAIR” (https://www.arabidopsis.org/) (accessed on 18 February 2022) [Cucumis sativus genome (http://cucurbitgenomics.org/) (accessed on 20 February 2022) [http://rapdb.dna.affrc.go.jp/) (accessed on 20 February 2022) [http://www.ncbi.nlm.nih.gov/cdd/) (accessed on 20 February 2022), SMART database (http://smart.embl-heidelberg.de/) (accessed on 18 February 2022) [https://www.ebi.ac.uk/interpro/) (accessed on 21 February 2022), and Scan Prosite (https://prosite.expasy.org/scanprosite/) (accessed on 18 February 2022) were used to confirm the HDZIP family-specific leucine-zipper (LZ) domain. Additionally, the physiochemical properties of the HDZIP proteins in the studied plants were discovered using the ExPASy online server (http://web.expasy.org/protparam/) (accessed on 21 February 2022) [To obtain insightful knowledge of the ry 2022) , the Cucry 2022) , and thery 2022) . To avoiry 2022) , Inter Pry 2022) .http://www.genome.jp/tools/clustalw/) (accessed on 22 February 2022) following the default parameters to examine the evolutionary relationships among the sequences and construct the maximum likelihood phylogenetic tree using MEGA (version 7.0) [O. sativa were predicted using the MEME online server (Version 4.12.0) (http://meme-suite.org/) (accessed 10 March 2022) with the default settings. The details of the top 10 predicted motifs were obtained from the MEME suite. The conserved domains of the HDZIP gene family of O. sativa were predicted using the NCBI-CDD (http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi) (accessed 10 March 2022). The conserved domain and motif distribution were drawn via Microsoft PowerPoint 365 software. Finally, for the visualization of the heatmap, TBtools (Version 1.098765) was used, and the transcriptomic data were retrieved from the rice genome database and GEO dataset platform from the NCBI [To obtain detailed knowledge regarding the evolutionary relationship of the HDZIP gene family in rice with the developed genome species. Here, we investigated the phylogenetic relationships of the HDZIP gene family members of rice with model plants. Firstly, the HDZIP amino acid sequences were downloaded from their corresponding genome database and were then aligned through ClustalW software (version 2.1) (ion 7.0) . Furtherthe NCBI ,32.OsHDZIP gene, 1.5 kb of an upstream genomic DNA sequence with the starting codon (ATG) was obtained from the rice genome sequence database. Further, we used the plantCARE database (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/) (accessed on 26 February 2022) to identify the cis-elements in the promoter regions of 40 OsHDZIP genes of O. sativa. Furthermore, for the GO analysis, the OsHDZIP protein sequences were downloaded from the iTAK-Plant Transcription Factor and Protein Kinase Identifier and Classifier (http://itak.feilab.net/cgi-bin/itak/index.cgi) (accessed on 5 March 2022). The obtained OsHDZIP protein sequences were implied in the “CELLO2GO” online server to determine the predicted functions, such as molecular functions, biological processes, and cellular components, and finally, the GO classifications were recovered using Microsoft Excel 365 software.To determine the cis-regulatory elements in each https://string-db.org) (accessed on 8 February 2022) was used for the interactive protein network analysis (accessed on 8 March 2022), using the O. sativa OsHDZIP2 protein as a reference following the default advanced settings [The online server String  by the Institute for Systems Biology  following the same procedure by Rizwan et al. [To predict putative miRNA target sites in the n et al. .The insects  and the rice variety used in the study, Ninjing4, were initially obtained from the China National Rice Research Institute insect repository . The Ninjing4 rice variety, known to be resistanceless to these insect infestations, was used for insect rearing. Initially, the BPH and SBPH colonies were reared on the rice seedlings in cement tanks covered with fine mesh outdoors  for six months  and overwintered in lab-controlled conditions. First, we soaked the seeds for 24 h in a water dip plastic tray with a standard size of one-quarter (60 cm H_100 cm W_200 cm L) in standard conditions of 26 ± 2 °C with the 16 h L:8 h D in relative humidity of 80 ± 10% in the ecological laboratory of Yangzhou University. The germinated seeds were transferred to cement tanks covered with fine mesh in an outdoor natural environment and were grown until the six-leaf seedling stage. Secondly, the seedlings were then transferred into plastic pots (dimensions = R ¼ 16 cm). Finally, the stress treatments proceeded at the tillering stage .The JGM technical grade of 61.7% used in this study was obtained from the Qianjiang Biochemistry Co., Ltd. . Following the protocol of in a previous report by Ahmad et al. (2022), the two hundred parts per million (PPM) solution was Tween 20 obtained from the Sinopsin Group Chemical Reagent Company . The fungicide was then sprayed on the rice seedlings, following the procedure in a previous study ,38.Forty day-old (40 ± 2) rice plants were exposed to BPH and SBPH stress, and samples were collected at 2, 4, and 8 days after infestation. Similarly, JGM was sprayed on the rice plants, and samples were taken 2, 4, and 8 days after treatment. The samples were then stored at −80 °C degrees until further experiments. After that, the total RNA was extracted from the samples using kits . First, the DNA was removed using DNase I, the concentration and purity were measured with a NanoDrop 1000 spectrophotometer , and the integrity was checked using 1.5% agarose gel electrophoresis. Finally, the resulting cDNA was used as a template for qPCR  analysis using SYBR Green real-time PCR master mix . The qPCR assays were performed in triplicate using a real-time PCR system  following the manufacturer’s protocol . TM II . The cDNAs were amplified at 95 °C for 2 min, followed by 35 cycles of 10 s at 95 °C, then for 30 s, and at 72 °C for 30 s, with a final extension step of 72 °C for 10 min in a CFX96 real-time PCR system . The mRNA amounts of all genes were separately quantified with the stable expression of the constitutive reference gene, actin. The specific primers are listed in . The data were analyzed and are expressed as the mean ± standard deviation (SD) of three biologically independent replicates in all measured parameters, and finally, GraphPad Prism (Version 8.0.2)  was used for graphical representation [The data presented in this paper were analyzed using the SPSS software  for statistical analysis (ANOVA), statistical significance, and a 95% confidence interval , and tabulated. We retrieved 40 rice  OsHDZ40 . Among tOsHDZIP genes in Oryza sativa are shown in The HDZIP gene family consisted of two functional domains: homeodomain (HD) and leucine zipper (LZ). Based on their sequence conservation and functional properties, the HDZIP gene family was divided into four subfamilies . The HDZIP I subfamily contains the HD and LZ domains among the four subfamilies; HDZIP II contains a similar HD and LZ domain with an additional CPSCE motif; HDZIP III and HDZIP IV contain HD and LZ with an additional START and SAD domain. Only HDZIP III possesses the highly conserved MEKHLA domain . The domArabidopsis thaliana [Cucumis sativus [O. sativa [A. thaliana (47 AtHDZIP) [After alignment, a maximum likelihood phylogenetic tree was constructed to gain insightful knowledge regarding the evolutionary relationship of the homeodomain-leucine zipper in thaliana , Cucumis sativus , and O. . sativa   , and cucAtHDZIP)  were dowAtHDZIP) . AdditioThe protein interaction analysis revealed various other proteins interacting with the OsHDZIP orthologous gene OsHDZIP2 . The OsHOsHDZIP genes, 56 putative miRNAs targeting four OsHDZIP genes were identified, as shown in the network illustration . This was followed by OsHDZIP13, which was targeted by 11 miRNAs families, including osa-miR414, osa-miR1429-3p, osa-miR164a, osa-miR164b, osa-miR164d, osa-miR164e, osa-miR169r-3p, osa-miR2877, osa-miR2927, osa-miR2794, and osa-miR164f. Furthermore, the same subfamily member, OsHDZIP37, was targeted by five miRNAs families , and OsHDZIP40 was targeted by only four miRNA families . However, from the OsHDZIP subfamily III, four members were targeted in combination by 21 miRNAs families including osa-miR5075, osa-miR1865-3p, osa-miR5075, osa-miR166f, osa-miR2275d, osa-miR444c.1, osa-miR444b.1, osa-miR166e-3p, osa-miR1661-3p, osa-miR166k-3p, osa-miR166i-3p, osa-miRg-33p, osa-miR166h-3p, osa-miR166j-3p, osa-miR444e, osa-miR444d.2, osa-miR444a-3p.2, osa-miR5508, osa-miR166a-3p, osa-miR166b-3p, and osa-miR444d.2. Noticeably, the miRNA165/166 family targeted all the genes in the OsHDZIP subfamily III and could be involved in the post-transcriptional regulation of these genes in rice plants. The schematic diagrams indicating the ented in . DetaileOsHDZIP genes in Oryza sativa. Three functional predictions were analyzed into biological, molecular, and cellular processes [OsHDZIP genes play a crucial role in growth-related activities via hormonal and metabolic modulation  enrichment pathway analysis showed various key functions of the rocesses . Accordidulation . AdditioOsHDZIP in silico analysis revealed that the upstream region of HDZIP genes possesses various stress, hormonal, and growth receptive cis-regulatory elements. Here, we identified twenty-two cis-regulatory elements. Among these 22 cis-elements, 13 were related to stress and growth changes, and 9 were responsive to hormonal changes , the GCTCZ-motif (MeJA responsive), and the TCA-salicylic acid element, were responsive. Moreover, ABRE (abscisic acid responsive) was found in most of the OsHDZIP genes; meanwhile, the GARE-motif and P-box (a gibberellin-responsive cis-element) were identified in several gene’s upstream regions. Following a drought, the anaerobic induction-responsive cis-elements, MYB and ARE, and the light-responsive cis-elements, such as the ZTCT-motif, G-box, and ACE, were also found in the majority of OsHDZIP genes. In addition, various stress- and growth-responsive cis-elements, such as CAT-box (involved in meristem expression), TC-rich repeats (stress- and defense-responsive cis-regulatory elements), MBS1 (regulates flavonoid biosynthesis gene expression), and LTR (low-temperature responsive), were observed in the promoter region of OsHDZIP genes. These clustering cis-regulatory elements in the promoter region of OsHDZIP genes imply their role in regulating gene expression during different growth stages and under environmental stimuli; the same results were reported in [The  changes . Furtherorted in .OsHDZIP genes. The OsHDZIP family genes contain multiple exons and have varied intron lengths  had 20 exons and 17 introns; followed by subfamily IV in which the OsHDZIP3 and OsHDZIP17 had 13 exons and 10 introns; OsHDZIP16, OsHDZIP20, OsHDZIP32, and OsHDZIP39 had 11 exons and 8 introns in total. However, OsHDZIP2 had 10 exons and 9 introns, and with OsHDZIP24, 10 exons and 7 introns were observed. Furthermore, the third-highest number of exons and introns was recorded in subfamily II, in which the OsHDZIP1, OsHDZIP15, OsHDZIP25, OsHDZIP27, and OsHDZIP30 had six exons and three introns, followed by OsHDZIP34 and OsHDZIP38 with five exons and two introns; meanwhile, OsHDZIP18, OsHDZIP19, and OsHDZIP30 had four exons and two introns; OsHDZIP21 had three exons and two introns; only OsHDZIP4 had the least number with two exons and a single intron. Additionally, the OsHDZIP subfamily I was counted as having the least number of introns and exons distributed in which OsHDZIP11, OsHDZIP25, OsHDZIP26, OsHDZIP28, OsHDZIP29, and OsHDZIP31 accounted for five exons and two introns; followed by OsHDZIP6, OsHDZIP10, OsHDZIP14, OsHDZIP33, OsHDZIP35, and OsHDZIP36 with four exons and a single intron; a single gene OsHDZIP8 was observed with six exons and three introns. We identified the exons–introns distribution using the CDS and genomic sequence of  lengths . Among tHDZIPs gene’s structure  counted has having three motifs in total. A total of 40 conserved motifs were discovered using the MEME online server (Version 5.4.1) (accessed on 10 April 2022) , and thetructure . Among tOsHDZIP genes in plant growth and development based on a set of microarray data obtained from the RiceXPro expression database (version 3.0) (accessed on 13 April 2022) [OsHDZIP genes family is presented as a heatmap, with blue to red colors reflecting the expression pattern. In twelve tissues , the OsHDZIP gene family members showed moderate to high expressions, respectively  . The micectively . Among tHDZIP genes’ responsiveness to high salinity, the transcriptomic expression data were obtained from the publicly available in the NCBI (GSE102152) (accessed on 17 April 2022) [OsHDZIP genes, the dominant transcription was rescored under SWR-NaCl of OsHDZIP7, OsHDZIP10, OsHDZIP16, OsHDZIP18, OsHDZIP19, OsHDZIP20, OsHDZIP22, OsHDZIP27, OsHDZIP30, OsHDZIP32, OsHDZIP36 OsHDZIP37, OsHDZIP38, and OsHDZIP40. In addition, OsHDZIP1, OsHDZIP3, OsHDZIP11, OsHDZIP12, OsHDZIP24, OsHDZIP28, OsHDZIP31, OsHDZIP35, and OsHDZIP39 were found to have moderate expression, and the rest of the genes did not show a response. Meanwhile, under SWR-CK, various OsHDZIP genes  had high expression and moderate expression  in comparison to CK. This expression analysis suggests that OsHDZIP genes play a crucial role in the rice plant’s defense against high salinity. Salinity is an important stress that hinders plant growth and yield. The injurious effects of salinity can be noted over the whole plant. To obtain insightful knowledge regarding il 2022) . In the OsHDZIP genes involved in rice plant defense against brown planthopper (BPH), rice striped stem borer (SSB), Chilo suppressalis, and combined SSB_BPH stresses  (accessed on 11 May 2022) . The anastresses B. HoweveOsHDZIP gene’s role in rice plant defense against rice leaf folder (RLF) Cnaphalocrocis medinalis Guenée (Lepidoptera: Crambidae) , and the rest of the genes did not show transcription. This expression analysis suggests that the HDZIP gene family plays a role in the rice defense system against biotic stress.The transcriptomic expression data were taken from the NCBI (GSE159259) (accessed on 15 May 2022) . The anaambidae) C. FurtheOsHDZIP genes family under Jasmonic acid (JA) and brassinosteroids (BRs) were obtained from the RiceXPro expression database (version 3.0) (accessed on 25 May 2022) [HDZIP genes family is presented as a heatmap, with blue to red colors reflecting the expression percentage. Under JA, the expression analysis of OsHDZIP genes at the 12 h timepoint, OsHDZIP3, OsHDZIP10 and OsHDZIP28 and OsHDZIP11, OsHDZIP24, OsHDZIP25, OsHDZIP26, and OsHDZIP37 were found with high and moderate transcription, respectively  . The micectively . FolloweOsHDZIP genes showed moderate expressions at almost all time points, except OsHDZIP15 and OsHDZIP20, which had high dominant expressions ; OsHDZIP7 (1 h); OsHDZIP7, OsHDZIP10, OsHDZIP21, OsHDZIP27, OsHDZIP30, OsHDZIP32, and OsHDZIP36 (3 h); OsHDZIP7, OsHDZIP12, OsHDZIP22, OsHDZIP23, and OsHDZIP39 (12 h); OsHDZIP12, OsHDZIP18, OsHDZIP26, OsHDZIP36, and OsHDZIP39 (24 h) were found with moderate expressions. However, these findings suggest that OsHDZIP14 and OsHDZIP15 showed no response at all given time points. In addition, various genes, such as OsHDZIP1, OsHDZIP2, OsHDZIP3, OsHDZIP25, OsHDZIP30, OsHDZIP35, and OsHDZIP32, were found with the least transcriptions, and the remaining genes were not expressed. Under BRs, the ressions . FurtherOsHDZIP genes under BPH and SBPH infestations and botanical fungicide JGM applications, herein, we performed quantitative real-time polymerase chain reaction (qRT-PCR) to analyze the expression patterns at three-time points over 2 days (2D), 4D, and 8D long treatments during BPH and SBPH infestations and JGM spraying (To further investigate the response of spraying . The resO. sativa HDZIP transcription factor through moderate and high expressions. Among the eight candidate genes (two genes from each subfamily) at three different time points , Cucumis sativus (40 CsHZIPs) [Arabidopsis thaliana (47 AtHDZIPs) [Arabidopsis thaliana and Cucumis sativus [OsHDZIP genes was analyzed, and the results stated that the HDZIP III and HDZIP IV subfamilies exhibited the highest number of motifs of the other two subfamilies  , and Ara sativus  CsHZIPs  sativus ,40. The  sativus ,55,56. Tfamilies . A motifOsHDZIP gene family members, including OsHDZIP18 and OsHDZIP27, displayed dominant expression in all tested organs of O. sativa in the developmental stages. Similar results were reported for the OsHDZIP18, OsHDZIP27 homologs CsHDZ02, and CsHDZ33, respectively. These results indicate the potential importance of OsHDZIP18, OsHDZIP27, and other subfamily members in regulating the growth and developmental activities of O. sativa [The HDZIP I TFs were documented for their involvement in plant developmental processes such as root growth and stem elongation, leaf morphology, flowering induction, and pollen hydration . The OsHOsHDZIP17 and OsHDZIP28 were expressed in all six tissues   . Members of the HDZIP III subfamily were shown to be important for appropriate morphogenesis, embryo development, giving support during the commencement of lateral organ development, control of the shoot apical meristem, and water and nutrient transport throughout the plant’s overall body ,8,59,60.OsHDZIP11 and OsHDZIP37 were expressed in all the tissues  to validate their expressions. The results revealed the potential role of OsHDZIP genes. Furthermore, among these eight candidate genes, OsHDZIP20 was observed with dominant expressions, and the rest of the genes  had moderate expressions, whereas OsHDZIP03, OsHDZIP28, and OsHDZIP40 had low transcription  and fungal infections [OsHDZIP gene showed a differential expression pattern where the candidate genes from each subfamily, including OsHDZIP40, OsHDZIP28, and OsHDZIP10, were dominantly expressed, whereas the OsHDZIP3, OsHDZIP4, OsHDZIP15, and OsHDZIP37 were moderately expressed  [Vigna unguiculata) [Glycine max) [Arachis hypogaea [OsHDZIP genes  , cowpea iculata) , soybeanine max) , pathogehypogaea , and richypogaea , and areIP genes . OsHDZIP genes, and miR166 has been reported to be involved in drought stress in maize [OsABP, OsDBH and OsDSHCT genes in rice enhanced the miRNAs response against salinity stress [OsHDZIP genes  were targeted by these miRNAs providing another aspect of these miRNAs’ potential role in regulating rice response under salinity (HDZIP genes in O. sativa. Among these 28 miRNAs families targeting the HDZIP gene family, several miRNAs predicted expression levels and functions have been identified, whereas various miRNAs targeting OsHDZIP genes that regulate biotic/abiotic stress responses and other important agronomic traits remain to be clarified.The osa-miR166 family targeted four in maize , cowpea in maize , soybeanin maize , peanut in maize , and plain maize . miR444 in maize . Previouy stress . Our ressalinity  and theisalinity . CollectOsHDZP3, OsHDZP9, and OsHDZP28 was enhanced, suggesting their possible involvement in JA-mediated rice resistance against BPH (JA is synthesized from linolenic acid through the action of several enzymes in plant chloroplast membranes, and the current evidence indicates that it induces resistance against necrotrophic pathogens and chewing herbivores ,81. In cinst BPH . OsHDZIP15 and OsHDZIP20 suggest the essential role of these genes and their possible participation in the immunity regulation of the rice plant; however, functional studies are required to unfold the underlying mechanism of these crucial hormones (BRs are a group of polyhydroxylated steroidal phytohormones that are mandatory for plant development, growth, and productivity . In addihormones .OsHDZIP family TFs were identified in the rice genome database and classified into four subfamilies based on their domain and structural properties. Furthermore, heatmap analysis revealed the expression of OsHDZIP TFs in distinct O. sativa tissues. The expression of OsHDZIP genes under salinity and hormone stress indicated that they might play a role in modulating O. sativa resistance. Furthermore, differential expression patterns were found under JA and BR treatments, indicating that OsHDZIP genes may be critical in hormonal-mediated rice immunity against BPH and SBPH. On the other hand, stress control is a complicated system, and our results suggested the potential application of HDZIP biomarkers in developing stress-resilient rice lines. These results provide the missing role of HDZIP genes in regulating rice immunity against SBPH and particularly BPH. Forty


Plants are constantly exposed to a variety of different environmental stresses, including drought, salinity, and elevated temperatures. These stress cues are assumed to intensify in the future driven by the global climate change scenario which we are currently experiencing. These stressors have largely detrimental effects on plant growth and development and, therefore, put global food security in jeopardy. For this reason, it is necessary to expand our understanding of the underlying mechanisms by which plants respond to abiotic stresses. Especially boosting our insight into the ways by which plants balance their growth and their defense programs appear to be of paramount importance, as this may lead to novel perspectives that can pave the way to increase agricultural productivity in a sustainable manner. In this review, our aim was to present a detailed overview of different facets of the crosstalk between the antagonistic plant hormones abscisic acid (ABA) and auxin, two phytohormones that are the main drivers of plant stress responses, on the one hand, and plant growth, on the other. Global warming and environmental pollution are among the major threats that humanity will face in the coming decades. Rising global temperatures and more frequent heat waves accompanied by unforeseeable torrential rains ,2 are asPlants perceive changes in their environment and, in turn, modulate the content and distribution of a small number of metabolites, referred to as plant hormones, which serve the integration and transmission of internal signals ,14,15. ‘Arabidopsis thaliana through the induction of YUCCA8 and YUCCA9 gene expression, involving the transcriptional control of target genes by transcription factors from the JA-specific basic helix loop helix family myelocytomatosis oncogene (MYC) [However, many recent studies indicated that the classification of plant hormones, according to their growth-promoting or -repressing effects, is all too simplistic and needs to be readdressed because many interactions between antagonistic plant hormones have been described in the past. Just to name some examples, wound induced formation of JA has been shown to trigger auxin biosynthesis in ne (MYC) ,23. Morene (MYC) ,25, and ne (MYC)  while aune (MYC) ,27. ThisThe class of auxins contains the most important phytohormones related to plant growth and development. Auxins are involved in processes ranging from cell expansion growth, control of cell division, vascular tissue differentiation, lateral and adventitious root initiation, tropistic responses (gravitropism and phototropism), maintenance of apical dominance, delay of leaf senescence, and contributions to the control of leaf and fruit abscission, as well as fruit ripening ,29.l-tryptophan (l-Trp), including the indole-3-pyruvic acid (IPyA) pathway [l-Trp-independent auxin biosynthesis pathway was introduced more than 30 years ago [l-Trp-independent auxin biosynthesis pathway [IAA is considered the most abundant and most important representative of the auxin class in the plant kingdom. Its occurrence in plants was first described nearly a century ago by Frits W. Went and Kenneth V. Thimann ,31, but  pathway ,34,35,36ears ago ,38, althears ago . However pathway .l-Trp, together with the IPyA pathway for IAA biosynthesis that involves the conversion of l-Trp to IPyA by means of two l-Trp aminotransferases, TRYPTOPHAN AMINOTRANSFERASE OF ARABIDOPSIS 1 (TAA1) and TRYPTOPHAN AMINOTRANSFERASE-RELATED 2 (TAR2) [aba3 mutant translated into altered IAA levels in Arabidopsis [Medicago truncatula [l-Trp into IAA [AMIDASE 1 (AMI1), was cloned and several other AMI1-like enzymes have been characterized from a multitude of other plant species since then [N-acylethanolamines [ami1 alleles that both showed significantly reduced IAA levels and elevated IAM contents under control conditions [Regarding the auxin biosynthesis pathways dependent on 2 (TAR2) ,41, and 2 (TAR2) ,35,42, t2 (TAR2) ,44,45. Wbidopsis , it mustbidopsis ,47. Receuncatula ,49,50. Iuncatula , but theuncatula . The IAMinto IAA . Nonethence then ,55,56. Aolamines ,58. Alonolamines . The latnditions . Along wFor proper plant growth and development, strict control of cellular auxin homeostasis and auxin fluxes along the plant body is imperative. Auxin gradients produced in plant tissues change dynamically due to developmental programs and in response to external stimuli ,62. In t−), preventing the passive efflux of the molecule from the cell [The acidic pH of the apoplast (pH~5.5) , in contthe cell . Auxin ethe cell ,72. HoweTIR1/AFB that either contains the F-box protein TRANSPORT INHIBITOR RESPONSE 1 (TIR1) or a TIR1 homolog auxin-related F-box protein (AFB) [Auxin signaling occurs both in the nucleus and in the plasma membrane. The core element that controls the signaling pathway is the E3 ubiquitin ligase complex SCFin (AFB) , the co-in (AFB) , and thein (AFB) . The recTIR1/AFB can recruit the Aux/IAA co-receptor proteins. Following binding, the Aux/IAA proteins are polyubiquitinated and thereby tagged for their subsequent proteolytic degradation by the 26S proteasome. The ARFs, in turn, are liberated from their repression and are free to mediate auxin-responsive transcriptional responses [In the absence of auxin, Aux/IAA repressor proteins heterooligomerize with the ARFs and the co-repressor TOPLESS (TPL), thereby inhibiting the transcriptional activity of the ARF transcription factors. However, in the presence of auxin, which binds at the bottom of an Aux/IAA protein-specific pocket of the F-box protein, the E3 ubiquitin ligase complex SCFesponses ,77. Howeesponses , but it esponses .15H20O4). ABA biosynthesis commences in plastids, while the final steps occur in the cytosol [β-carotene (C40) [C-methyl-d-erytritol (MEP) pathway, through multistep enzymatic catalysis. ABA received its name in 1968 [ABA is a sesquiterpene isoprenoid (C cytosol . It is one (C40) ,81,82, a in 1968 , after b in 1968 , in stud in 1968 , and pro in 1968 . For a m in 1968 .β-carotene [trans-violaxanthin by the enzyme zeaxanthin epoxidase (ZEP), which is known as ABA1 in Arabidopsis, the only ZEP gene in this species. However, it should be noted that aba1 mutants contain some residual ABA, suggesting that there is an alternative minor biosynthesis pathway operative in Arabidopsis [trans-violaxanthin is converted into 9-cis-violaxanthin or (via trans-neoxanthin) into 9′-cis-neoxanthin. In Arabidopsis, ABA4 produces cis-neoxanthin and cis-violaxanthin [15) by 9-cis-epoxy carotenoid dioxygenases (NCEDs) by cleavage of 9-cis-violaxanthin or 9′-cis-neoxanthin. The NCED enzyme family has been found to require iron and oxygen to become catalytically active [NCED3 gene expression has recently been associated with IAM abundance in Arabidopsis [ABA3 or FLACCA present an ABA-deficient phenotype [The formation of ABA involves a complex multi-step enzymatic conversion of carotene ,89. The bidopsis . Then, aaxanthin ,92. Subsy active . In Araby active . Interesbidopsis . Xanthoxbidopsis , before bidopsis . To exerbidopsis  and FLACbidopsis , respecthenotype ,100.Classically, ABA was considered to show a root-to-shoot transport pattern, especially under drought stress. However, more recent studies have put this notion into question, and it is accepted today that ABA biosynthesis also takes place in aerial vascular tissues . SeveralABA perception and signaling are complex and involve the interaction of several proteins. For this reason, elucidation of ABA perception appeared to be very difficult and took considerable time and effort . As depiIn the presence of ABA, the hormone binds to its receptors. This facilitates the binding of the receptors to PP2Cs, causing their inactivation. Inactivation of PP2C, in turn, leads to the release of SnRK2s from repression. SnRK2s activate themselves through their autophosphorylation loop, which renders them capable of phosphorylating their downstream target proteins, most notably transcription factors from the ABA-responsive element binding protein/ABRE-binding factor (AREB/ABF) families . FurtherPlant hormones do not act in entirely isolated manners, but in regulatory networks in which they operate in synergistic or antagonistic ways with each other. Consequently, the final condition of growth and development represents the net effect of the total hormone balance . The terDEHYDRATION-RESPONSIVE ELEMENT BINDING 2 (DREB2), the transcription factor genes bZIP11, MYB14, MYB48, WRKY2, WRKY56, and RESPONSIVE TO DESICCATION 22 (RD22), along with some auxin responsive genes, such as the Gretchen Hagen 3 genes GH3.1 and GH3.9, as well as the Aux/IAA gene IAA8. At the same time, IAA treatment triggered the downregulation of leaf senescence-associated genes, such as SENESCENCE-ASSOCIATED GENE 101 (SAG101) and SAG102 [SAUR32 was dominantly expressed in roots and was highly induced by ABA and drought [SAUR32 interacts with the clade-A PP2C proteins HAI1 and AIP1 to regulate ABA sensitivity. A barley mutant, nec1, that is defective in an HLM gene that encodes the CYCLIC NUCLEOTIDE-GATED ION CHANNEL 4, has been reported to over accumulate IAA and exhibit changes in stomatal regulation in response to exogenous auxin. The Arabidopsis orthologous mutant dnd2 shows increased salt tolerance, over-accumulation of both IAA and ABA, and displays related phenotypic and physiological changes, such as reduced stomata size, higher stomatal density, and stomatal index [ami1 mutant leads to an induction of NCED3 expression and, consequently, to significantly elevated levels of ABA [ami1 mutants were shown to have altered osmotic stress responses. Thus, it must be concluded that IAM is an additional hub that links the biosynthesis pathways of IAA and ABA and, thus, contributes to the crosstalk between these two plant hormones. Furthermore, Ortiz-García et al. [MYB74, which is reported to be involved in osmotic stress responses, by IAM and ABA  in both seed germination and primary root growth [ABI3 expression [ABI3 by recruiting auxin response factors ARF10 and ARF16. In turn, ARF10 is negatively regulated by miRNA160 [ABI3 transcription, whose transcripts are high in dormant seeds and lowered after germination, regulating the seed dormancy in synergy with ABA [MIR160B, amongst other miRNA genes [ABI3 expression has been reported to be required for the formation of somatic embryogenesis, because it induces the expression of embryo identity genes through, at least, ARF10/16 activation [ABI3 has also been described to be negatively regulated by the auxin signaling repressor IAA8, whose accumulation promotes seed germination [ABI3 promoter through ARFs suppresses ABI3 transcription during seed germination, but the exact ARF proteins have not yet been identified. Interestingly, IAA8 has been shown to interact with ARF6 and ARF8 in modulating JA levels during flower development [ABI5, which acts by inducing degradation of PIN2 proteins [PIN1, PIN3, and PIN7 genes and promotes the stabilization of AUXIN RESISTANT 3 (AXR3)/IAA17 through nitric oxide (NO) [ABI5 expression and the biological half-life of the protein are tightly regulated [OsABI5 [PIN1, which plays a role in polar auxin transport necessary for root development [ABI4 is also regulated, for example, by WRKY46, which integrates ABA-dependent and ABA-independent abiotic stress responses and, thus, controls auxin-related gene expression [OsPIN2 mutant wavy root 1 (war1) is defective in auxin transport and auxin distribution at root tips, leading to loss of gravitropic perception, but also shows increased sensitivity to ABA in seed germination, increased ABA levels, and changes in ABA-associated gene expression in roots [PIN2 rather than accelerating the degradation of PIN2 [OsIAA20 is positively regulated by abiotic stress conditions and exogenous ABA treatment, and contributes positively to abiotic stress tolerance: reduces water loss, improves seed germination, decreases the Na+/K+ ratio, increases the proportion of closed stomata, and also enhances growth in different developmental stages [OsIAA18 also confers salt and drought tolerance, at least by increasing proline biosynthesis and reducing ROS accumulation, through an ABA-dependent pathway, therefore acting upstream of ABA-signaling pathways [VvIAA18 in tobacco enhances drought tolerance, as measured by upregulation of salt stress-responsive genes, including PYRROLINE-5-CARBOXYLATE SYNTHASE (P5CS), LATE EMBRYOGENESIS ABUNDANT PROTEIN 5 (LEA5), SUPEROXIDE DISMUTASE (SOD) and PEROXIDASE (POD) under drought stress, as well as higher SOD and POD activities [IAA5, IAA6, and IAA19 [The extensive interaction of ABA with other hormones in the regulation of stress responses, growth, and development is well documented . Nonethet growth . In factt growth . For exat growth . ABI3 wot growth ,145 and pression . Auxin amiRNA160 . ARF10/1with ABA , but notNA genes . Furthertivation . Regardimination . The autelopment . In anotelopment , but alselopment . In factelopment  and inhielopment . For exaelopment . ABA alsproteins . Complemide (NO) . Howeveride (NO) ,159 the egulated , and oth [OsABI5 ,162, whi [OsABI5 . ABI4 wo [OsABI5 , and is  [OsABI5 , at leas [OsABI5 , but its [OsABI5 . Interes [OsABI5 , since Aelopment , even ovelopment . In turnpression . ABI4 mapression ,172 and pression , althougin roots . A subse of PIN2 . In ricel stages . Remarkapathways , even thpathways , and hettivities . Howevernd IAA19 .YUC5, TAA1, and PIN1 to promote auxin biosynthesis and transport [YUC8 in rice, and genetic studies provided additional evidence that ABA uses auxin as a downstream signal to modify root elongation and radial expansion [ABI3 expression during seed dormancy, acting not downstream of ABA signaling, but probably in parallel [WRKY41 are not yet clear, and their elucidation might reveal new interactions. PIN3 expression is also directly inhibited by HAT2, an HD-Zip II transcription factor, whose expression is upregulated by osmotic stress, at least in roots, thus inhibiting meristem growth [PIN1/3/7 and auxin biosynthesis, a possible crosstalk node would be the ARABIDOPSIS RESPONSE REGULATOR 1 (ARR1) transcription factor [Despite recent discoveries that shed light on the intricacies of auxin-ABA crosstalk, there are remaining knowledge gaps that need to be closed. For example, the role of indeterminate domain (IDD) transcription factors in abiotic stress responses have recently been discovered. IDD14 can physically interact with ABF1-4, promoting their transcriptional activities by forming a protein complex that positively regulates drought-stress responses . Numerouransport , but it xpansion . One furparallel . Howeverm growth , and itsm growth , but them growth . Low temm growth , and parn factor , in whicn factor , but then factor .