Nonlinear dynamics of an interband cascade laser with optical injection.

This work reports the nonlinear dynamics of a mid-infrared interband cascade laser (ICL) subject to optical injection. It is shown that the stable locking regime is asymmetric and broadens with increasing injection strength. Outside the locking regime, the ICL mostly produces period-one oscillations. However, three categories of periodic pulse oscillations are observed in the vicinity of the Hopf bifurcation and the saddle-node bifurcation. In particular, it is found that the ICL generates broadband chaos at a near-threshold pump current, and the chaos bandwidth is over 300 MHz.

Broadband chaos of an interband cascade laser with a 6-GHz bandwidth.

Near-infrared semiconductor lasers subject to optical feedback usually produce chaos with a broad bandwidth of a few GHz. However, the reported mid-infrared interband cascade lasers (ICLs) only show chaos with a limited bandwidth below 1 GHz. Here we show that an ICL with optical feedback is able to generate broadband chaos as well. The mid-infrared chaos exhibits a remarkable bandwidth of about 6 GHz, which is comparable to that of the near-infrared counterpart. In addition, the spectral coverage in the electrical domain reaches as high as 17.7 GHz. It is found that the chaos bandwidth generally broadens with increasing feedback ratio and/or increasing pump current of the laser, while it is insensitive to the feedback length.

Multi-omics characterization of esophageal squamous cell carcinoma identifies molecular subtypes and therapeutic targets.

Esophageal squamous cell carcinoma (ESCC) is the predominant form of esophageal cancer and is characterized by an unfavorable prognosis. To elucidate the distinct molecular alterations in ESCC and investigate therapeutic targets, we performed a comprehensive analysis of transcriptomics, proteomics, and phosphoproteomics data derived from 60 paired treatment-naive ESCC and adjacent nontumor tissue samples. Additionally, we conducted a correlation analysis to describe the regulatory relationship between transcriptomic and proteomic processes, revealing alterations in key metabolic pathways. Unsupervised clustering analysis of the proteomics data stratified patients with ESCC into 3 subtypes with different molecular characteristics and clinical outcomes. Notably, subtype III exhibited the worst prognosis and enrichment in proteins associated with malignant processes, including glycolysis and DNA repair pathways. Furthermore, translocase of inner mitochondrial membrane domain containing 1 (TIMMDC1) was validated as a potential prognostic molecule for ESCC. Moreover, integrated kinase-substrate network analysis using the phosphoproteome nominated candidate kinases as potential targets. In vitro and in vivo experiments further confirmed casein kinase II subunit α (CSNK2A1) as a potential kinase target for ESCC. These underlying data represent a valuable resource for researchers that may provide better insights into the biology and treatment of ESCC.

Efficacy and safety of caspofungin for the treatment of invasive pulmonary aspergillosis in patients with chronic obstructive pulmonary disease.

OBJECTIVES: We assessed the efficacy of a 3-week primary or salvage caspofungin regimen in patients with chronic obstructive pulmonary disease (COPD) and concomitant proven or suspected invasive pulmonary aspergillosis (IPA). METHODS: Forty-four patients were treated with an initial loading caspofungin dose of 70 mg, followed by a daily dose of 50 mg for 20 days. The main efficacy endpoint was clinical effectiveness. Secondary endpoints included the clinical efficacy of caspofungin after 1 week, therapeutic efficacy based on the European Organization for Research and Treatment of Cancer and Mycoses Study Group Education and Research Consortium (EORTC/MSG) criteria, the sensitivity of different Aspergillus strains to caspofungin in vitro, and the safety of caspofungin. RESULTS: An assessment of 42 patients in the intention-to-treat group revealed efficacy rates of 33.33% within 1 week and 38.10% within 3 weeks. According to the EORTC/MSG criteria, the treatment success rate was 38.10%. The success rate of first-line treatment was 54.76%, whereas salvage treatment had a success rate of 45.24%. No adverse events were reported among the participants. CONCLUSIONS: Caspofungin is effective and safe as an initial or salvage treatment for patients with IPA and COPD.

Targeting CRAF kinase in anti-cancer therapy: progress and opportunities.

The RAS/mitogen-activated protein kinase (MAPK) signaling cascade is commonly dysregulated in human malignancies by processes driven by RAS or RAF oncogenes. Among the members of the RAF kinase family, CRAF plays an important role in the RAS-MAPK signaling pathway, as well as in the progression of cancer. Recent research has provided evidence implicating the role of CRAF in the physiological regulation and the resistance to BRAF inhibitors through MAPK-dependent and MAPK-independent mechanisms. Nevertheless, the effectiveness of solely targeting CRAF kinase activity remains controversial. Moreover, the kinase-independent function of CRAF may be essential for lung cancers with KRAS mutations. It is imperative to develop strategies to enhance efficacy and minimize toxicity in tumors driven by RAS or RAF oncogenes. The review investigates CRAF alterations observed in cancers and unravels the distinct roles of CRAF in cancers propelled by diverse oncogenes. This review also seeks to summarize CRAF-interacting proteins and delineate CRAF's regulation across various cancer hallmarks. Additionally, we discuss recent advances in pan-RAF inhibitors and their combination with other therapeutic approaches to improve treatment outcomes and minimize adverse effects in patients with RAF/RAS-mutant tumors. By providing a comprehensive understanding of the multifaceted role of CRAF in cancers and highlighting the latest developments in RAF inhibitor therapies, we endeavor to identify synergistic targets and elucidate resistance pathways, setting the stage for more robust and safer combination strategies for cancer treatment.

Rescue analgesia with serratus anterior plane block improved pain relief after thoracic surgery.

BACKGROUND: Video-assisted thoracic surgery (VATS) is frequently associated with substantial postoperative pain, which may lead to hypopnea. Rescue analgesia using opioids has adverse effects. We aimed to evaluate the effects of rescue analgesia with serratus anterior plane block (SAPB) on moderate-to-severe pain and oxygenation in patients undergoing VATS. METHODS: Eighty patients undergoing VATS and reporting a numeric rating scale (NRS, ranging from 0-10) score of cough pain ≥4 on the first postoperative day were randomized to receive either sufentanil or SAPB for rescue analgesia. The primary outcome was the degree of relief in cough pain 30 min after rescue analgesia. Arterial oxygen pressure (PaO2), opioid consumption after rescue analgesia and the incidence of chronic pain were also assessed. RESULTS: The NRS scores were significantly reduced after rescue analgesia in both groups (Ppaired <0.001). Notably, the degree of relief in cough pain was significantly higher in the SAPB group than that in the sufentanil group (medians [interquartiles]: -3 [-4, -2] vs. -2 [-3, -1], P<0.001). Moreover, patients receiving SAPB exhibited significantly higher PaO2 than those before receiving rescue analgesia (Ppaired=0.007). However, there were no significant differences in the PaO2 before and after receiving rescue analgesia in the sufentanil group. No significant differences in opioid consumption or the incidence of chronic pain were observed between groups. CONCLUSIONS: Rescue analgesia with SAPB on the first postoperative day had a greater effect on pain relief and oxygenation after VATS. However, its long-term effect on chronic pain requires further research.

Multi-View and Multi-Order Structured Graph Learning.

Recently, graph-based multi-view clustering (GMC) has attracted extensive attention from researchers, in which multi-view clustering based on structured graph learning (SGL) can be considered as one of the most interesting branches, achieving promising performance. However, most of the existing SGL methods suffer from sparse graphs lacking useful information, which normally appears in practice. To alleviate this problem, we propose a novel multi-view and multi-order SGL (M 2 SGL) model which introduces multiple different orders (multi-order) graphs into the SGL procedure reasonably. To be more specific, M 2 SGL designs a two-layer weighted-learning mechanism, in which the first layer truncatedly selects part of views in different orders to retain the most useful information, and the second layer assigns smooth weights into retained multi-order graphs to fuse them attentively. Moreover, an iterative optimization algorithm is derived to solve the optimization problem involved in M 2 SGL, and the corresponding theoretical analyses are provided. In experiments, extensive empirical results demonstrate that the proposed M 2 SGL model achieves the state-of-the-art performance in several benchmarks.

Toosendanin targeting eEF2 impedes Topoisomerase I & II protein translation to suppress esophageal squamous cell carcinoma growth.

BACKGROUND: Although molecular targets such as HER2, TP53 and PIK3CA have been widely studied in esophageal cancer, few of them were successfully applied for clinical treatment. Therefore, it is urgent to discover novel actionable targets and inhibitors. Eukaryotic translational elongation factor 2 (eEF2) is reported to be highly expressed in various cancers. However, its contribution to the maintenance and progression of cancer has not been fully clarified. METHODS: In the present study, we utilized tissue array to evaluate eEF2 protein expression and clinical significance in esophageal squamous cell carcinoma (ESCC). Next, we performed knockdown, overexpression, RNA-binding protein immunoprecipitation (RIP) sequence, and nascent protein synthesis assays to explore the molecular function of eEF2. Furthermore, we utilized compound screening, Surface Plasmon Resonance (SPR), Isothermal Titration Calorimetry (ITC) assay, cell proliferation and Patient derived xenograft (PDX) mouse model assays to discover an eEF2 inhibitor and assess its effects on ESCC growth. RESULTS: We found that eEF2 were highly expressed in ESCC and negatively associated with the prognosis of ESCC patients. Knocking down of eEF2 suppressed the cell proliferation and colony formation of ESCC. eEF2 bond with the mRNA of Topoisomerase II (TOP1) and Topoisomerase II (TOP2) and enhanced the protein biosynthesis of TOP1 and TOP2. We also identified Toosendanin was a novel inhibitor of eEF2 and Toosendanin inhibited the growth of ESCC in vitro and in vivo. CONCLUSIONS: Our findings show that Toosendanin treatment suppresses ESCC growth through targeting eEF2 and regulating downstream TOP1 and TOP2 biosynthesis. eEF2 could be supplied as a potential therapeutic target in the further clinical studies.

Erianin suppresses constitutive activation of MAPK signaling pathway by inhibition of CRAF and MEK1/2.

Constitutive activation of RAS-RAF-MEK-ERK signaling pathway (MAPK pathway) frequently occurs in many cancers harboring RAS or RAF oncogenic mutations. Because of the paradoxical activation induced by a single use of BRAF or MEK inhibitors, dual-target RAF and MEK treatment is thought to be a promising strategy. In this work, we evaluated erianin is a novel inhibitor of CRAF and MEK1/2 kinases, thus suppressing constitutive activation of the MAPK signaling pathway induced by BRAF V600E or RAS mutations. KinaseProfiler enzyme profiling, surface plasmon resonance (SPR), isothermal titration calorimetry (ITC), cellular thermal shift assay, computational docking, and molecular dynamics simulations were utilized to screen and identify erianin binding to CRAF and MEK1/2. Kinase assay, luminescent ADP detection assay, and enzyme kinetics assay were investigated to identify the efficiency of erianin in CRAF and MEK1/2 kinase activity. Notably, erianin suppressed BRAF V600E or RAS mutant melanoma and colorectal cancer cell by inhibiting MEK1/2 and CRAF but not BRAF kinase activity. Moreover, erianin attenuated melanoma and colorectal cancer in vivo. Overall, we provide a promising leading compound for BRAF V600E or RAS mutant melanoma and colorectal cancer through dual targeting of CRAF and MEK1/2.

Effect of esketamine on opioid consumption and postoperative pain in thyroidectomy: A randomized controlled trial.

AIMS: Thyroidectomy is frequently associated with substantial postoperative pain. Esketamine, an N-methyl-d-aspartate receptor antagonist, has been demonstrated to be effective in multiple analgesia scenarios. We hypothesized that intraoperative administration of esketamine may reduce perioperative opioid consumption and postoperative pain in patients undergoing thyroidectomy. METHODS: Sixty patients undergoing thyroidectomy were randomly assigned to two groups. Patients in the esketamine group received a pre-incisional intravenous bolus of esketamine (0.5 mg kg-1 ) followed by a continuous infusion of 0.24 mg kg-1  h-1 until the beginning of wound closure. Patients in the placebo group received 0.9% NaCl (bolus and infusion). The primary outcome was perioperative sufentanil consumption. The postoperative pain, sleep quality and adverse events during the first postoperative 24 h were also evaluated. RESULTS: Patients in the esketamine group consumed significantly less sufentanil than those in the saline group (24.6 ± 3.1 µg vs. 33.7 ± 5.1 µg, mean difference, 9.1; 95% confidence interval [CI], 6.9-11.3, P < .001). Postoperative pain scores were significantly lower in the esketamine group than those in the saline group during the first 24 h postoperatively (P < .05). Patients receiving esketamine experienced higher sleep quality than those in the saline group during surgical night (P = .043). There were no significant differences in adverse events between the two groups. CONCLUSIONS: Intraoperative administration of esketamine reduces perioperative sufentanil consumption and postoperative pain without increasing psychotomimetic side effects in patients undergoing thyroidectomy. The development of combined anaesthesia regimens, including esketamine, may foster strategies for pain management during thyroidectomy.

In vitro characterization and molecular epidemiology of Cryptococcus spp. isolates from non-HIV patients in Guangdong, China.

Background: The burden of cryptococcosis in mainland China is enormous. However, the in vitro characterization and molecular epidemiology in Guangdong, a key region with a high incidence of fungal infection in China, are not clear. Methods: From January 1, 2010, to March 31, 2019, clinical strains of Cryptococcus were collected from six medical centres in Guangdong. The clinical information and characteristics of the strains were analysed. Furthermore, molecular types were determined. Results: A total of 84 strains were collected, mostly from male and young or middle-aged adult patients. Pulmonary and cerebral infections (82.1%) were most common. All strains were Cryptococcus neoformans, grew well at 37°C and had capsules around their cells. One melanin- and urea- and one melanin+ and urea- variants were found. Although most strains exhibited a low minimum inhibitory concentration (MIC) value for voriconazole (mean: 0.04 µg/mL) and posaconazole (mean: 0.12 µg/mL), the results for these isolates showed a high degree of variation in the MIC values of fluconazole and 5-fluorocytosine, and resistance was observed for 4 out of 6 drugs. A significant proportion of these strains had MIC values near the ECV values, particularly in the case of amphotericin B. The proportion of strains near the clinical breakpoints was as follows: fluconazole: 3.66%; voriconazole: 3.66%; itraconazole: 6.10%; posaconazole: 13.41%; amphotericin B: 84.15%; 5-fluorocytosine: 2.44%. These strains were highly homogeneous and were dominated by the Grubii variant (95.2%), VNI (94.0%), α mating (100%), and ST5 (89.3%) genotypes. Other rare types, including ST4, 31, 278, 7, 57 and 106, were also found. Conclusion: Phenotypically variant and non-wild-type strains were found in Guangdong, and a significant proportion of these strains had MIC values near the ECV values towards the 6 antifungal drugs, and resistance was observed for 4 out of 6 drugs. The molecular type was highly homogeneous but compositionally diverse, with rare types found. Enhanced surveillance of the aetiology and evolution and continuous monitoring of antifungal susceptibility are needed to provide references for decision-making in the health sector and optimization of disease prevention and control.

Structure-Aware Multimodal Deep Learning for Drug-Protein Interaction Prediction.

Identifying drug-protein interactions (DPIs) is crucial in drug discovery, and a number of machine learning methods have been developed to predict DPIs. Existing methods usually use unrealistic data sets with hidden bias, which will limit the accuracy of virtual screening methods. Meanwhile, most DPI prediction methods pay more attention to molecular representation but lack effective research on protein representation and high-level associations between different instances. To this end, we present the novel structure-aware multimodal deep DPI prediction model, STAMP-DPI, which was trained on a curated industry-scale benchmark data set. We built a high-quality benchmark data set named GalaxyDB for DPI prediction. This industry-scale data set along with an unbiased training procedure resulted in a more robust benchmark study. For informative protein representation, we constructed a structure-aware graph neural network method from the protein sequence by combining predicted contact maps and graph neural networks. Through further integration of structure-based representation and high-level pretrained embeddings for molecules and proteins, our model effectively captures the feature representation of the interactions between them. As a result, STAMP-DPI outperformed state-of-the-art DPI prediction methods by decreasing 7.00% mean square error (MSE) in the Davis data set and improving 8.89% area under the curve (AUC) in the GalaxyDB data set. Moreover, our model is an interpretable model with the transformer-based interaction mechanism, which can accurately reveal the binding sites between molecules and proteins.

Genome and systems biology of Melilotus albus provides insights into coumarins biosynthesis.

Melilotus species are used as green manure and rotation crops worldwide and contain abundant pharmacologically active coumarins. However, there is a paucity of information on its genome and coumarin production and function. Here, we reported a chromosome-scale assembly of Melilotus albus genome with 1.04 Gb in eight chromosomes, containing 71.42% repetitive elements. Long terminal repeat retrotransposon bursts coincided with declining of population sizes during the Quaternary glaciation. Resequencing of 94 accessions enabled insights into genetic diversity, population structure, and introgression. Melilotus officinalis had relatively larger genetic diversity than that of M. albus. The introgression existed between M. officinalis group and M. albus group, and gene flows was from M. albus to M. officinalis. Selection sweep analysis identified candidate genes associated with flower colour and coumarin biosynthesis. Combining genomics, BSA, transcriptomics, metabolomics, and biochemistry, we identified a ß-glucosidase (BGLU) gene cluster contributing to coumarin biosynthesis. MaBGLU1 function was verified by overexpression in M. albus, heterologous expression in Escherichia coli, and substrate feeding, revealing its role in scopoletin (coumarin derivative) production and showing that nonsynonymous variation drives BGLU enzyme activity divergence in Melilotus. Our work will accelerate the understanding of biologically active coumarins and their biosynthetic pathways, and contribute to genomics-enabled Melilotus breeding.

Enhanced Rotated Mask R-CNN for Chromosome Segmentation.

Karyotyping is an important process for finding chromosome abnormalities that could cause genetic disorders. This process first requires cytogeneticists to arrange each chromosome from the metaphase image to generate the karyogram. In this process, chromosome segmentation plays an important role and it is directly related to whether the karyotyping can be achieved. The key to achieving accurate chromosome segmentation is to effectively segment the multiple touching and overlapping chromosomes at the same time identify the isolated chromosomes. This paper proposes a method named Enhanced Rotated Mask R-CNN for automatic chromosome segmentation and classification. The Enhanced Rotated Mask R-CNN method can not only accurately segment and classify the isolated chromosomes in metaphase images but also effectively alleviate the problem of inaccurate segmentation for touching and overlapping chromosomes. Experiments show that the proposed approach achieves competitive performances with 49.52 AP on multi-class evaluation and 69.96 AP on binary-class evaluation for chromosome segmentation.

Functionalized Activated Carbon for Competing Adsorption of Volatile Organic Compounds and Water.

The interfacial interaction of activated carbon with volatile organic compounds (VOCs) is seriously affected by water vapor. Therefore, it is vital to enhance the hydrophobic performance of activated carbon for expanding its application in industrial and environmental fields. Herein, a series of hydrophobic activated carbon was fabricated by tailored mixed siloxane and applied in dynamic competitive adsorption at 0, 50, and 90% humidity. Simultaneously, the diffusion molecular models and multicomponent adsorption experiments were used to study the adsorption and diffusion mechanisms. The hydrophobicity of activated carbon was significantly improved by loading of mixed siloxane, in which the equilibrium water absorption decreased from 21.9 to 7.2% and the contact angles increased by 70.10°. Meanwhile, dynamic competitive adsorption at different humidities indicated that the siloxane-functionalized activated carbons (SACs) showed much better competitive adsorption performances for VOCs than original activated carbon, which was further confirmed by the theoretical calculations of adsorption energy. In addition, a remarkable adsorption selectivity and reusability could be demonstrated to VOCs with different polarities on SACs. This study not only provides a new strategy for the hydrophobic modification of activated carbon materials but also offers theoretical guidance for the treatment of gas streams with significant water contents.

SWnet: a deep learning model for drug response prediction from cancer genomic signatures and compound chemical structures.

BACKGROUND: One of the major challenges in precision medicine is accurate prediction of individual patient's response to drugs. A great number of computational methods have been developed to predict compounds activity using genomic profiles or chemical structures, but more exploration is yet to be done to combine genetic mutation, gene expression, and cheminformatics in one machine learning model. RESULTS: We presented here a novel deep-learning model that integrates gene expression, genetic mutation, and chemical structure of compounds in a multi-task convolutional architecture. We applied our model to the Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE) datasets. We selected relevant cancer-related genes based on oncology genetics database and L1000 landmark genes, and used their expression and mutations as genomic features in model training. We obtain the cheminformatics features for compounds from PubChem or ChEMBL. Our finding is that combining gene expression, genetic mutation, and cheminformatics features greatly enhances the predictive performance. CONCLUSION: We implemented an extended Graph Neural Network for molecular graphs and Convolutional Neural Network for gene features. With the employment of multi-tasking and self-attention functions to monitor the similarity between compounds, our model outperforms recently published methods using the same training and testing datasets.

Periplogenin suppresses the growth of esophageal squamous cell carcinoma in vitro and in vivo by targeting STAT3.

The mortality rate of esophageal squamous cell carcinoma (ESCC) is higher than that of other cancers worldwide owing to a lack of therapeutic targets and related drugs. This study aimed to find new drugs by targeting an efficacious therapeutic target in ESCC patients. Signal transducer and activator of transcription 3 (STAT3) is hyperactive in ESCC. Herein, we identified a novel STAT3 inhibitor, periplogenin, which strongly inhibited phosphorylation of STAT3 at Tyr705. Docking models and pull-down assays revealed that periplogenin bound directly and specifically to STAT3, leading to significant suppression of subsequent dimerization, nuclear import, and transcription activities. In addition, STAT3 knockdown cell lines were insensitive to periplogenin, whereas in contrast, STAT3-overexpressing cells were more sensitive to periplogenin, indicating that STAT3 was a target of periplogenin. Intraperitoneally administered periplogenin exhibited efficacious therapeutic effects in ESCC patient-derived xenograft models and dramatically impaired the phosphorylation of STAT3 and expression levels of STAT3-mediated downstream genes. Thus, our study demonstrated that periplogenin acted as a new STAT3 inhibitor, suppressing the growth of ESCC in vitro and in vivo, providing a basis for its potential application in ESCC treatment and prevention.

Genome-Wide Analysis and Expression Profiles of the Dof Family in Cleistogenes songorica under Temperature, Salt and ABA Treatment.

The DNA-binding with one zinc finger (Dof) family of plant-specific transcription factors has a variety of important functions in gene transcriptional regulation, development, and stress responses. However, the structure and expression patterns of Dof family have not been identified in Cleistogenes songorica, which is an important xerophytic and perennial gramineous grass in desert grassland. In this study, 50 Dof genes were identified in C. songorica and could be classified into four groups. According to genome-wide analysis, 46 of 50 Dof genes were located on 20 chromosomes, and the gene structure and conserved protein motif of these proteins were analyzed. In addition, phylogenetic analysis of Dof genes in C. songorica, Arabidopsis thaliana, Oryza sativa, and Brachypodium distachyon estimated the evolutionary relationships, and these genes were grouped into seven clusters. Moreover, the expression profiles of these Dof genes in C. songorica were analyzed in response to high/low temperature, salinity, and ABA treatments. These results will provide valuable information for future studies on gene classification, cloning, and functional characterization of this family in C. songorica.

Honokiol Inhibits Melanoma Growth by Targeting Keratin 18 in vitro and in vivo.

Honokiol, a natural compound, derived from Magnolia officinalis, has been shown to have anti-cancer effect in several cancer types. However, the underlying molecular mechanism associated with its anti-cancer properties has not been fully elucidated. In the current study, we showed that honokiol inhibited the growth of melanoma cells in a dose and time-dependent manner. Mechanistically, it directly interacts with keratin 18 (KRT18) protein and induces its degradation through ubiquitination. Furthermore, the expression of KRT18 was found to be higher in melanoma tissues compared to the normal skin tissues. In addition, KRT18 overexpression significantly promoted melanoma cell proliferation and growth. Our results showed that honokiol treatment significantly decreased KRT18 protein level and suppressed the tumor growth in melanoma cell-derived xenograft mice models. Hence, KRT18 plays an oncogenic role in melanoma and honokiol can be an inhibitor for KRT18.

Integrated analysis of co-expression, conserved genes and gene families reveal core regulatory network of heat stress response in Cleistogenes songorica, a xerophyte perennial desert plant.

BACKGROUND: As global warming continues, heat stress (HS) is becoming an increasingly significant factor limiting plant growth and reproduction, especially for cool-season grass species. The objective of this study was to determine the transcriptional regulatory network of Cleistogenes songorica under HS via transcriptome profiling, identify of gene families and comparative analysis across major Poaceae species. RESULTS: Physiological analysis revealed significantly decreased leaf relative water content (RWC) but increased proline (Pro) content in C. songorica under 24 h of HS. Transcriptome profiling indicated that 16,028 and 14,645 genes were differentially expressed in the shoots and roots of C. songorica under HS, respectively. Two subgenomes of C. songorica provide equal contribution under HS on the basis of the distribution and expression of differentially expressed genes (DEGs). Furthermore, 216 DEGs were identified as key evolutionarily conserved genes involved in the response to HS in C. songorica via comparative analysis with genes of four Poaceae species; these genes were involved in the 'response to heat' and 'heat acclimation'. Notably, most of the conserved DEGs belonged to the heat-shock protein (HSP) superfamily. Similar results were also obtained from co-expression analysis. Interestingly, hub-genes of co-expression analysis were found to overlap with conserved genes, especially heat-shock protein (HSP). In C. songorica, 84 HSP and 32 heat-shock transcription factor (HSF) genes were identified in the allotetraploid C. songorica genome, and might have undergone purifying selection during evolutionary history based on syntenic and phylogenetic analysis. By analysing the expression patterns of the CsHSPs and CsHSFs, we found that the transcript abundance of 72.7% of the CsHSP genes and of 62.5% of the CsHSF genes changed under heat stress in both the shoots and roots. Finally, a core regulatory network of HS was constructed on the basis of the CsHSP, CsHSF and other responsive genes in C. songorica. CONCLUSIONS: Regulatory network and key genes were comprehensively analysed and identified in C. songorica under HS. This study improves our knowledge of thermotolerance mechanisms in native grasses, and also provides candidate genes for potential applications in the genetic improvement of grasses.