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Abstract Ovarian cancer is high recurrence and mortality malignant tumor. The most common ovarian cancer was High‐Grade Serous Ovarian Cancer. However, High‐Grade Serous Ovarian Cancer organoid is rare, which organoid with patient immune microenvironment and blood vessels even absence. Here, we report a novel High‐Grade Serous Ovarian Cancer organoid system derived from patient ovarian cancer samples. These organoids recapitulate High‐Grade Serous Ovarian Cancer organoids' histological and molecular heterogeneity while preserving the critical immune microenvironment and blood vessels, as evidenced by the presence of CD34+ endothelial cells. Whole exome sequencing identifies key mutations (CSMD3, TP53, GABRA6). Organoids show promise in testing cisplatin sensitivity for patients resistant to carboplatin and paclitaxel, with notable responses in cancer proteoglycans and p53 (TP53) signaling, like ACTG/ACTB1/AKT2 genes and BBC3/MDM2/PERP. Integration of immune microenvironment and blood vessels enhances potential for novel therapies like immunotherapies and angiogenesis inhibitors. Our work may provide a new detection system and theoretical basis for ovarian cancer research and individual therapy.

ObjectiveTubo-ovarian carcinosarcomas are rare, extremely aggressive malignant tumors that contain both carcinomatous and sarcomatous components. Due to the disease’s rarity, developing an effective treatment strategy for ovarian carcinosarcomas has been challenging. A study was conducted to investigate the clinicopathologic and molecular features of this rare disease.MethodsWe enrolled all patients diagnosed with tubo-ovarian carcinosarcomas from January 2007 to December 2022. The clinical and pathological data were gathered from medical records. Kaplan–Meier curves were plotted to calculate OS and PFS. The Log-rank test and Cox regression model were utilized to explore the relationship between clinicopathological parameters and survival. Patients with cancer tissues available had sequencing with a 242-gene panel done to investigate the mutational landscape and signature of the disease.ResultsIn total, 65% of the patients were diagnosed with advanced-stage cancer. The median PFS and OS of this cohort were 27 and 40 months, respectively, and there was no significant difference in survival between the homologous and heterologous components of sarcoma. Unexpectedly, staging did not have effects on prognosis. All patients had surgical attempts, and suboptimal debulking status was correlated with poorer PFS and OS. MSI was identified in 0% with low Tumor mutation burden (TMB) indicating a poor response to immunotherapy. Low HER2 expression is controversial, according to previous reports, and gives us limited choices with this rare and aggressive disease. We surprisingly found the homologous recombination deficiency (HRD)-positive status was identified in 64% of OCS, which is significantly higher than UCS and other types of epithelial ovarian cancer. The fact that all patients in our cohort who received olaparib as maintenance therapy had survived over 30 months and two had no evidence of recurrence at the latest follow-up might further validate the role of poly (ADP-ribose) polymerase inhibitors (PARPi) in the management of OCS.ConclusionOCS patients seemed to respond to carboplatin/paclitaxel with optimal PFS and OS. Cytoreduction with no residuals proved to be the sole independent prognostic factor. WES should be done to assess the prognosis and assist with the targeted therapy, especially the HRD test, which might help select potential patients who benefit from PARPi.

Epoxide hydrolases (EHs) catalyze the conversion of epoxides into vicinal diols. The epoxide hydrolase gene from P. chrysosporium was previously cloned and subjected to site-directed mutation to study its enzyme activity, but the results were unsatisfactory. This study used error prone PCR and DNA shuffling to construct a PchEHA mutation library. We performed mutation-site combinations on PchEHA based on enzyme activity measurement results combined with directed evolution technology. More than 15,000 mutants were randomly selected for the preliminary screening of PchEHA enzyme activity alongside 38 mutant strains with increased enzyme activity or enantioselectivity. Protein expression and purification were conducted to determine the hydrolytic activity of PchEHA, and three mutants increased their activity by more than 95% compared with that of the wt. After multiple rounds of screening and site-specific mutagenesis, we found that F3 offers the best enzyme activity and enantioselectivity; furthermore, the molecular docking results confirmed this result. Overall, this study uncovered novel mutants with potential value as industrial biocatalysts.

To investigate the ecological impacts of macroalgae in the framework of shifting global CO2 concentrations, we conducted a study utilizing Ulva fasciata and Sargassum horneri specimens sourced from the Ma’an Archipelago in Zhejiang Province on how ocean acidification (OA) and temperature changes interact to affect the photosynthetic physiological responses of macroalgae. The results of the study showed that OA reduced the tolerance of U. fasciata to bright light at 20 °C, resulting in more pronounced photoinhibition, while 15 °C caused significant inhibition of U. fasciata, reducing its growth and photosynthetic activity, but OA alleviated the inhibition and promoted the growth of the alga to a certain extent. The tolerance of S. horneri to bright light was also reduced at 20 °C; the inhibition was relieved at 15 °C, and the OA further improved the algal growth. The Relative Growth Rate (RGR), photosynthetic pigment content, and the release of the dissolved organic carbon (DOC) of U. fasciata were mainly affected by the change in temperature; the growth of the alga and the synthesis of metabolites were more favored by 20 °C. A similar temperature dependence was observed for S. horneri, with faster growth and high metabolism at 15 °C. Our results suggest that OA reduces the tolerance of macroalgae to high light at suitable growth temperatures; however, at unsuitable growth temperatures, OA effectively mitigates this inhibitory effect and promotes algal growth.

Abstract A growing body of epidemiological evidence suggests that nonalcoholic fatty liver disease (NAFLD) is an independent risk factor for chronic kidney disease (CKD), but the regulatory mechanism linking NAFLD and CKD remains unclear. Our previous studies have shown that overexpression of PDE4D in mouse liver is sufficient for NAFLD, but little is known about its role in kidney injury. Here, liver-specific PDE4D conditional knockout (LKO) mice, adeno-associated virus 8 (AAV8)-mediated gene transfer of PDE4D and the PDE4 inhibitor roflumilast were used to assess the involvement of hepatic PDE4D in NAFLD-associated renal injury. We found that mice fed a high-fat diet (HFD) for 16 weeks developed hepatic steatosis and kidney injury, with an associated increase in hepatic PDE4D but no changes in renal PDE4D. Furthermore, liver-specific knockout of PDE4D or pharmacological inhibition of PDE4 with roflumilast ameliorated hepatic steatosis and kidney injury in HFD-fed diabetic mice. Correspondingly, overexpression of hepatic PDE4D resulted in significant renal damage. Mechanistically, highly expressed PDE4D in fatty liver promoted the production and secretion of TGF-β1 into blood, which triggered kidney injury by activating SMADs and subsequent collagen deposition. Our findings revealed PDE4D might act as a critical mediator between NAFLD and associated kidney injury and indicated PDE4 inhibitor roflumilast as a potential therapeutic strategy for NAFLD-associated CKD.

Ovarian cancer (OC), particularly high-grade serous cancer (HGSC), is the leading cause of mortality among gynecological cancers owing to the treatment difficulty and high recurrence probability. As therapeutic drugs approved for OC, poly ADP-ribose polymerase inhibitors (PARPi) lead to synthetic lethality by inhibiting single-strand DNA repair, particularly in homologous recombination-deficient cancers. However, even PARPi have distinct efficacies and are prone to have drug resistance, the molecular mechanisms underlying the PARPi resistance in OC remain unclear. A patient-derived organoid platform was generated and treated with a PARPi to understand the factors associated with PARPi resistance. PARPi significantly inhibits organoid growth. After 72 h of treatment, both the size of organoids and the numbers of adherent cells decreased. Moreover, immunofluorescence results showed that the proportion of Ki67 positive cells significantly reduced. When the PARPi concentration reached 200 nM, the percentage of Ki67 + /4′,6-diamidino-2-phenylindole (DAPI) cells decreased approximately 50%. PARPi treatment also affected the expression of genes involved in base excision repair and cell cycle. Functional assays revealed that PARPi inhibits cell growth by upregulating early apoptosis. The expression levels of several key genes were validated. In addition to previously reported genes, some promising genes FEN1 and POLA2 , were also be founded. The results demonstrate the complex effects of PARPi treatment on changes in potential genes relevant to PARPi resistance, and provide perspectives for further research on the PARPi resistance mechanisms.

Abstract Background Considering the unique biological behavior of cervical adenocarcinoma (AC) compared to squamous cell carcinoma, we now lack a distinct method to assess prognosis for AC patients, especially for intermediate-risk patients. Thus, we sought to establish a Silva-based model to predict recurrence specific for the intermediate-risk AC patients and guide adjuvant therapy. Methods 345 AC patients were classified according to Silva pattern, their clinicopathological data and survival outcomes were assessed. Among them, 254 patients with only intermediate-risk factors were identified. The significant cutoff values of four factors (tumor size, lymphovascular space invasion (LVSI), depth of stromal invasion (DSI) and Silva pattern) were determined by univariate and multivariate Cox analyses. Subsequently, a series of four-, three- and two-factor Silva-based models were developed via various combinations of the above factors. Results (1) We confirmed the prognostic value of Silva pattern using a cohort of 345 AC patients. (2) We established Silva-based models with potential recurrence prediction value in 254 intermediate-risk AC patients, including 12 four-factor models, 30 three-factor models and 16 two-factor models. (3) Notably, the four-factor model, which includes any three of four intermediate-risk factors (Silva C, ≥ 3 cm, DSI > 2/3, and > mild LVSI), exhibited the best recurrence prediction performance and surpassed the Sedlis criteria. Conclusions Our study established a Silva-based four-factor model specific for intermediate-risk AC patients, which has superior recurrence prediction performance than Sedlis criteria and may better guide postoperative adjuvant therapy.

Abstract The β2-adrenergic receptor (β2AR) is a G protein-coupled receptor (GPCR) that mediates the majority of cellular responses to external stimuli. Aberrant expression of β2AR results in various pathophysiological disorders, including tumorigenesis, but little is known about its role in liver regeneration. This study aims to investigate the impact and the underlying mechanism of β2AR in liver regeneration. Here, we found that β2AR was upregulated during liver regeneration induced by 70% PH. Deletion of β2AR in mice resulted in 62% mortality 2 days post-PH, decreased proliferative marker expression and impaired liver function throughout regeneration. Moreover, AAV8-mediated overexpression of β2AR in hepatocytes accelerated the regeneration process and increased target gene expression. Mechanistically, β2AR recruited G-protein-coupled receptor kinase 2 (GRK2) to the membrane and then formed a complex with c-met to transactivate c-met signaling, which triggered downstream extracellular regulated protein kinase (ERK) signaling activation and nuclear translocation. Inhibition of c-met with SU11274 or ERK with U0126 decreased β2AR overexpression-induced hepatocyte proliferation. Our findings revealed that β2AR might act as a critical mediator regulating liver regeneration by crosstalk with c-met and activation of ERK signaling.

This paper aims to assess the efficacy of the Harris Hawk Optimization (HHO) algorithm within the domain of photovoltaic (PV) power-generation systems. The focus lies in elucidating how the HHO algorithm optimizes maximum-power-point tracking (MPPT) and augments the performance of grid-connected PV systems. Initially, in the MATLAB/Simulink environment, a comparison is made between the HHO algorithm and two other extensively utilized methods for maximum-power-point tracking (MPPT): Perturb and Observe (P&O) and Particle Swarm Optimization (PSO). Preliminary findings indicate the HHO algorithm’s notable advantages in efficiency and speed over the other algorithms. Furthermore, by establishing a practical experimental platform and synchronously verifying outcomes through simulation, we conducted a comprehensive assessment of the HHO algorithm on a single-phase full-bridge-inverter grid-connected system. Results show the HHO algorithm’s exceptional optimization capabilities, which displays superior adaptability and ability to adjust to varying external conditions.

Abstract Acyl-CoA oxidase 2 (Acox2) is an enzyme involved in peroxisomal bile acid synthesis and branched-chain fatty acid degradation. Acox2 knockout (−/−) mice spontaneously developed liver cancer with marked lymphocytic infiltrate. Tandem-affinity purification coupled with mass spectrometry analysis revealed that Acox2 interacted with methylcrotonoyl-CoA carboxylase followed by co-immunoprecipitation confirmation. Here we reported that non-histone lysine crotonylation (Kcr) levels were downregulated in Acox2 −/− mice livers. Interestingly, Kcr signals were concentrated in the nucleus of tumor cells but mostly located in the cytoplasm of adjacent normal liver cells of Acox2 −/− mice. Quantitative analysis of the global crotonylome further revealed that 54% (27/50) of downregulated non-histone Kcr sites were located in mitochondrial (11/50) and peroxisomal (17/50) enzymes including Ehhadh, Scp2, Hsd17b4, Crot, Etfa, Cpt1a, Eci1/2, Hadha, Etfdh, and Idh2. Subsequent site-directed mutagenesis and transcriptome analysis revealed that Ehhadh K572cr might have site-specific regulatory roles by downregulating TOP3B expression that lead to increased DNA damage in vitro. Our findings suggested Acox2 is a regulator of Kcr that might play critical role on hepatic metabolic homeostasis.

ObjectivesWe investigated HPV genotypes in a large cohort of patients with definitive cervical histologic diagnosis.MethodsHPV testing was performed by real-time PCR assay, including 18 high-risk HPV (hrHPV) and 3 low-risk HPV (lrHPV). Totally 61,422 patients with documented HPV genotyping results within 6 months before cervical histologic diagnoses were included.ResultsHrHPV positive rate was 55.1% among all tested cases with the highest in adenosquamous carcinoma (94.1%), followed by squamous cell carcinoma (SCC) (93.7%), cervical intraepithelial neoplasia 2/3 (CIN2/3) (92.8%). HrHPV positive rates were significantly higher in high-grade squamous lesions than in those in glandular lesions. HPV16 was the most common genotype followed by HPV52 and HPV58 in CIN2/3. The most frequent hrHPV genotype in adenocarcinoma in situ (AIS) was HPV18, followed by HPV16, HPV45 and HPV52. In SCC cases, HPV16 was the most common type followed by HPV58, HPV52, HPV18 and HPV33. However, HPV18 showed significantly higher prevalence in adenocarcinoma and adenosquamous carcinoma than in that in SCC. Theoretically, the protective rates of 2/4-valent and 9-valent vaccine were 69.1% and 85.8% for cervical cancers.ConclusionsThe prevalence of HPV genotypes in Chinese population was different from that in Western population. Some hrHPV types were identified in cervical precancerous lesions and cancers, which are not included in current HPV vaccines. These data provide baseline knowledge for future HPV vaccine development.

IntroductionThe diagnosis and treatment of ankylosing spondylitis (AS) is a difficult task, especially in less developed countries without access to experts. To address this issue, a comprehensive artificial intelligence (AI) tool was created to help diagnose and predict the course of AS.MethodsIn this retrospective study, a dataset of 5389 pelvic radiographs (PXRs) from patients treated at a single medical center between March 2014 and April 2022 was used to create an ensemble deep learning (DL) model for diagnosing AS. The model was then tested on an additional 583 images from three other medical centers, and its performance was evaluated using the area under the receiver operating characteristic curve analysis, accuracy, precision, recall, and F1 scores. Furthermore, clinical prediction models for identifying high-risk patients and triaging patients were developed and validated using clinical data from 356 patients.ResultsThe ensemble DL model demonstrated impressive performance in a multicenter external test set, with precision, recall, and area under the receiver operating characteristic curve values of 0.90, 0.89, and 0.96, respectively. This performance surpassed that of human experts, and the model also significantly improved the experts' diagnostic accuracy. Furthermore, the model's diagnosis results based on smartphone-captured images were comparable to those of human experts. Additionally, a clinical prediction model was established that accurately categorizes patients with AS into high-and low-risk groups with distinct clinical trajectories. This provides a strong foundation for individualized care.DiscussionIn this study, an exceptionally comprehensive AI tool was developed for the diagnosis and management of AS in complex clinical scenarios, especially in underdeveloped or rural areas that lack access to experts. This tool is highly beneficial in providing an efficient and effective system of diagnosis and management.

BackgroundTuberculosis (TB) is a chronic infectious disease. Bone and joint TB is a common type of extrapulmonary TB and often occurs secondary to TB infection. In this study, we aimed to find the difference in the blood examination results of patients with bone and joint TB and patients with TB by using machine learning (ML) and establish a diagnostic model to help clinicians better diagnose the disease and allow patients to receive timely treatment.MethodsA total of 1,667 patients were finally enrolled in the study. Patients were randomly assigned to the training and validation cohorts. The training cohort included 1,268 patients: 158 patients with bone and joint TB and 1,110 patients with TB. The validation cohort included 399 patients: 48 patients with bone and joint TB and 351 patients with TB. We used three ML methods, namely logistic regression, LASSO regression, and random forest, to screen the differential variables, obtained the most representative variables by intersection to construct the prediction model, and verified the performance of the proposed prediction model in the validation group.ResultsThe results revealed a great difference in the blood examination results of patients with bone and joint TB and those with TB. Infectious markers such as hs-CRP, ESR, WBC, and NEUT were increased in patients with bone and joint TB. Patients with bone and joint TB were found to have higher liver function burden and poorer nutritional status. The factors screened using ML were PDW, LYM, AST/ALT, BUN, and Na, and the nomogram diagnostic model was constructed using these five factors. In the training cohort, the area under the curve (AUC) value of the model was 0.71182, and the C value was 0.712. In the validation cohort, the AUC value of the model was 0.6435779, and the C value was 0.644.ConclusionWe used ML methods to screen out the blood-specific factors—PDW, LYM, AST/ALT, BUN, and Na+—of bone and joint TB and constructed a diagnostic model to help clinicians better diagnose the disease in the future.

Uterine endometrial cancer (UEC) is an estrogen-related tumor. Succinate and heme metabolism play important roles in the progression of multiple tumors. However, the relationship between estrogen, succinate, and heme metabolism and related regulatory mechanisms remain largely unknown. In this study, we observed that the expression of aminolevulinate delta synthase 1 (ALAS1) and solute carrier family member 38 (SLC25A38) in UEC tissues is significantly higher than that in normal tissues. Further analysis showed that estrogen and succinate increased the expression of ALAS1 and SLC25A38 in uterine endometrial cancer cells (UECC), and the administration of succinate upregulated the level of the estrogen receptor (ER). Silencing nuclear receptor coactivator 1 (NCOA1) reversed the effects of estrogen and succinate via downregulation of ALAS1 expression. Additionally, exposure of UECC to heme increased cell viability and invasiveness, while silencing the NCOA1 gene weakened this effect. These findings revealed that estrogen and succinate can synergistically increase the expression of ALAS1 and SLC25A38 via the ERβ/NCOA1 axis, promoting heme accumulation and increasing the proliferative and invasive potential of UECC.

Drought restricts the growth of alpine grassland vegetation. This study aimed to explore a new technical system to improve the drought resistance of forage grass. Qinghai cold-land Poa pratensis seedlings were used in the drought stress experiment. A combination of abscisic acid (ABA) and polyacrylamide (PAM) were used to affect the growth, leaf physiology, soil enzyme activity, and rhizosphere microbial diversity of P. pratensis. The fresh leaf weight and root surface area were significantly increased after ABA-PAM combined treatment, while root length was significantly reduced. Besides, the leaf catalase (CAT) and superoxide dismutase (SOD) enzyme activity, proline and chlorophyll content, increased after the treatment, while malondialdehyde (MDA) content decreased. The treatment also increased sucrase, urease, and alkaline protease activities in rhizosphere soil, while decreasing acid phosphatase and neutral phosphatase enzyme activities. ABA-PAM combined treatment enhanced the rhizosphere microbial community and forage drought resistance by altering the abundance of various dominant microorganisms in the rhizosphere soil. The relative abundances of Actinobacteria, Chloroflexi, and Acidobacteria decreased, while Proteobacteria, Firmicutes, and Ascomycota increased. Unlike the relative abundance of Gibberella that decreased significantly, Komagataeibacter, Lactobacillus, Pichia, and Dekkera were significantly increased. Single-factor collinearity network analysis revealed a close relationship between the different rhizosphere microbial communities of forage grass, after ABA-PAM treatment. This study implies that ABA-PAM combined treatment can improve the drought resistance of forages. Therefore, it provides a theoretical and practical basis for restoring drought-induced grassland degradation.

Cymbidiumensifolium L. is a significant ornamental plant in Orchidaceae. Aside from its attractive flowers, its leaf coloration is also an important ornamental trait. However, there is an apparent lack of studies concerning the intricate mechanism of leaf coloration in C. ensifolium. In this study, we report a systematic evaluation of leaf coloration utilizing transcriptome and metabolome profiles of purple, yellow, and green leaves. In total, 40 anthocyanins and 67 flavonoids were quantified along with chlorophyll content. The tissue–transcriptome profile identified 26,499 differentially expressed genes (DEGs). The highest chlorophyll contents were identified in green leaves, followed by yellow and purple leaves. We identified key anthocyanins and flavonoids associated with leaf coloration, including cyanidin-3-O-sophoroside, naringenin-7-O-glucoside, delphinidin, cyanidin, petunidin, and quercetin, diosmetin, sinensetin, and naringenin chalcone. Moreover, genes encoding UDP-glucoronosyl, UDP-glucosyl transferase, chalcone synthesis, flavodoxin, cytochrome P450, and AMP-binding enzyme were identified as key structural genes affecting leaf coloration in C. ensifolium. In summary, copigmentation resulting from several key metabolites modulated by structural genes was identified as governing leaf coloration in C. ensifolium. Further functional verification of the identified DEGs and co-accumulation of metabolites can provide a tool to modify leaf color and improve the aesthetic value of C. ensifolium.

BackgroundGlia maturation factor-γ (GMFG) regulates actin cytoskeletal organization and promotes the invasion of cancer cells. However, its expression pattern and molecular function in gliomas have not been clearly defined.MethodsIn this study, public datasets comprising 2,518 gliomas samples were used to explore GMFG expression and its correlation with malignancy in gliomas. Immunohistochemistry (IHC) staining was performed to determine the expression of GMFG in gliomas using an in-house cohort that contained 120 gliomas samples. Gene ontology enrichment analysis was conducted using the DAVID tool. The correlation between GMFG expression and immune cell infiltration was evaluated using TIMER, Tumor Immune Single-Cell Hub (TISCH) database, and IHC staining assays. The Kaplan–Meier analysis was performed to determine the prognostic role of GMFG and its association with temozolomide (TMZ) response in gliomas.ResultsThe GMFG expression was higher in gliomas compared with non-tumor brain tissues both in public datasets and in-house cohort. High expression of GMFG was significantly associated with WHO grade IV, IDH 1/2 wild-type, and mesenchymal (ME) subtypes. Bioinformatic prediction and IHC analysis revealed that GMFG expression obviously correlated with the macrophage marker CD163 in gliomas. Moreover, both lower grade glioma (LGG) and glioblastoma multiforme (GBM) patients with high GMFG expression had shorter overall survival than those with low GMFG expression. These results indicate that GMFG may be a therapeutic target for the treatment of such patients. Patients with low GMFG expression who received chemotherapy had a longer survival time than those with high GMFG expression. For patients who received ion radiotherapy (IR) only, the GMFG expression level had no effect on the overall survival neither in CGGA and TCGA datasets.ConclusionThe GMFG is a novel prognostic biomarker for patients with both LGG and GBM. Increased GMFG expression is associated with tumor-associated macrophages (TAMs) infiltration and with a bad response to TMZ treatment.

Synchytrium endobioticum, the causal agent of potato wart disease, poses a major threat to commercial potato production. Understanding the roles of transcriptionally regulated genes following pathogen infection is necessary for understanding the system-level host response to pathogen. Although some understanding of defense mechanisms against S. endobioticum infection has been gained for incompatible interactions, the genes and signaling pathways involved in the compatible interaction remain unclear. Based on the collection of wart diseased tubers of a susceptible cultivar, we performed phenotypic and dual RNA-Seq analyses of wart lesions in seven stages of disease progression. We totally detected 5,052 differentially expressed genes (DEGs) by comparing the different stages of infection to uninfected controls. The tendency toward differential gene expression was active rather than suppressed under attack by the pathogen. The number of DEGs step-up along with the development of the disease and the first, third and seventh of the disease stages showed substantially increase of DEGs in comparison of the previous stage. The important functional groups identified via Gene ontology (GO) and KEGG enrichment were those responsible for plant-pathogen interaction, fatty acid elongation and phenylpropanoid biosynthesis. Gene coexpression networks, composed of 17 distinct gene modules that contained between 25 and 813 genes, revealed high interconnectivity of the induced response and led to the identification of a number of hub genes enriched at different stages of infection. These results provide a comprehensive perspective on the global response of potato to S. endobioticum infection and identify a potential transcriptional regulatory network underlying this susceptible response, which contribute to a better understanding of the potato–S. endobioticum pathosystem.

Late blight is one of the main biological stresses limiting the potato yield; however, the biochemical mechanisms underlying the infection process of Phytophthora infestans remain unrevealed. In this study, the late blight-resistant potato cultivar Ziyun No.1 (R) and the susceptible cultivar Favorita (S) were inoculated with P. infestans. Untargeted metabolomics was used to study the changes of metabolites in the compatible and incompatible interactions of the two cultivars and the pathogen at 0, 48, and 96 h postinoculation (hpi). A total of 819 metabolites were identified, and the metabolic differences mainly emerged after 48 hpi. There were 198 and 115 differentially expressed metabolites (DEMs) in the compatible and incompatible interactions. These included 147 and 100 upregulated metabolites during the compatible and incompatible interactions, respectively. Among them, 73 metabolites were identified as the P. infestans-responsive DEMs. Furthermore, the comparisons between the two cultivars identified 57 resistance-related metabolites. Resistant potato cultivar had higher levels of salicylic acid and several upstream phenylpropanoid biosynthesis metabolites, triterpenoids, and hydroxycinnamic acids and their derivatives, such as sakuranetin, ferulic acid, ganoderic acid Mi, lucidenic acid D2, and caffeoylmalic acid. These metabolites play crucial roles in cell wall thickening and have antibacterial and antifungal activities. This study reports the time-course metabolomic responses of potatoes to P. infestans. The findings reveal the responses involved in the compatible and incompatible interactions of potatoes and P. infestans.

Late blight, caused by Phytophthora infestans (P. infestans), is a devastating plant disease. P. infestans genome encodes hundreds of effectors, complicating the interaction between the pathogen and its host and making it difficult to understand the interaction mechanisms. In this study, the late blight-resistant potato cultivar Ziyun No.1 and the susceptible potato cultivar Favorita were infected with P. infestans isolate SCPZ16-3-1 to investigate the global expression profiles during the compatible and incompatible interactions using dual RNA sequencing (RNA-seq). Most of the expressed Arg-X-Leu-Arg (RXLR) effector genes were suppressed during the first 24 h of infection, but upregulated after 24 h. Moreover, P. infestans induced more specifically expressed genes (SEGs), including RXLR effectors and cell wall-degrading enzymes (CWDEs)-encoding genes, in the compatible interaction. The resistant potato activated a set of biotic stimulus responses and phenylpropanoid biosynthesis SEGs, including kirola-like protein, nucleotide-binding site-leucine-rich repeat (NBS-LRR), disease resistance, and kinase genes. Conversely, the susceptible potato cultivar upregulated more kinase, pathogenesis-related genes than the resistant cultivar. This study is the first study to characterize the compatible and incompatible interactions between P. infestans and different potato cultivars and provides the genome-wide expression profiles for RXLR effector, CWDEs, NBS-LRR protein, and kinase-encoding genes.

EIF1A encodes a translation initiation factor in eukaryocyte and aberrant expression of EIF1A is deemed to be associated with dysfunctions in intracranial diseases. The goal of this research was to explore the impacts of EIF1A on progression of human pituitary adenoma (PA). We employed immunohistochemistry to assess the expression of EIF1A in PA and para-carcinoma tissues. After constructing EIF1A-knockdown cell models via lentivirus infection, we examined cell proliferation through CCK-8 assay and Celigo cell counting assay. Flow cytometry was utilized to detect cell apoptosis and the migration ability of experimental cells was estimated using wound-healing assay and Transwell assay. The activity of the apoptosis-related factor, Caspase 3, was also examined via Caspase 3 activity assay. Lastly, in vivo xenograft mouse models were established to verify findings derived from in vitro cell models. Our results affirmed upregulation of EIF1A in PA cells and revealed that depletion of EIF1A could seriously limit cell proliferation and weaken the capacity of cell migration, and also enhance apoptosis of tumor cells. Mechanistically, degradation in cell growth mediated by EIF1A knockdown may involve in activation of MAPK signaling but inactivation of PI3K/AKT signaling pathway. This study indicates EIF1A plays a prominent role in facilitating tumor cell proliferation and migration which may further contribute to PA progression.