Inhibition of HDAC6 with CAY10603 alleviates acute and chronic kidney injury by suppressing the ATF6 branch of UPR.

BACKGROUND: Histone deacetylase 6 (HDAC6) inhibitor CAY10603 has been identified as a potential therapeutic agent for the treatment of diabetic kidney disease (DKD). The objective of this study was to investigate the therapeutic effects of CAY10603 in mice with acute kidney injury (AKI) and chronic kidney diseases (CKD). METHODS: Renal immunohistology was performed to assess the expression levels of HDAC6 in both human and mouse kidney samples. C57BL/6J mice were intraperitoneal injected with lipopolysaccharide (LPS) to induce AKI; CD-1 mice were fed with adenine diet to induce adenine-nephropathy as CKD model. Serum creatinine, blood urea nitrogen and uric acid were measured to reflect renal function; renal histology was applied to assess kidney damage. Western blot and immunohistology were used to analyze the unfolded protein response (UPR) level. RESULTS: HDAC6 was significantly upregulated in renal tubular epithelial cells (RTECs) of both AKI and CKD patients as well as mice. In the murine models of AKI induced by LPS and adenine-induced nephropathy, CAY10603 exhibited notable protective effects, including improvement in biochemical indices and pathological changes. In vivo and in vitro studies revealed that CAY10603 effectively suppressed the activation of activating transcription factor 6 (ATF6) branch of UPR triggered by thapsigargin (Tg), a commonly employed endoplasmic reticulum (ER) stressor. Consistent with these findings, CAY10603 also displayed substantial inhibition of ATF6 activation in RTECs from both murine models of LPS-induced AKI and adenine-induced nephropathy. CONCLUSIONS: Collectively, these results suggest that CAY10603 holds promise as a potential therapeutic agent for both acute and chronic kidney injury.

Integrating trans-omics, cellular experiments and clinical validation to identify ILF2 as a diagnostic serum biomarker and therapeutic target in gastric cancer.

BACKGROUND: Gastric cancer (GC) lacks serum biomarkers with clinical diagnostic value. Multi-omics analysis is an important approach to discovering cancer biomarkers. This study aimed to identify and validate serum biomarkers for GC diagnosis by cross-analysis of proteomics and transcriptomics datasets. METHODS: A cross-omics analysis was performed to identify overlapping differentially expressed genes (DEGs) between our previous aptamer-based GC serum proteomics dataset and the GC tissue RNA-Seq dataset in The Cancer Genome Atlas (TCGA) database, followed by lasso regression and random forest analysis to select key overlapping DEGs as candidate biomarkers for GC. The mRNA levels and diagnostic performance of these candidate biomarkers were analyzed in the original and independent GC datasets to select valuable candidate biomarkers. The valuable candidate biomarkers were subjected to bioinformatics analysis to select those closely associated with the biological behaviors of GC as potential biomarkers. The clinical diagnostic value of the potential biomarkers was validated using serum samples, and their expression levels and functions in GC cells were validated using in vitro cell experiments. RESULTS: Four candidate biomarkers (ILF2, PGM2L1, CHD7, and JCHAIN) were selected. Their mRNA levels differed significantly between tumor and normal tissues and showed different diagnostic performances for GC, with areas under the receiver operating characteristic curve (AUROCs) of 0.629-0.950 in the TCGA dataset and 0.736-0.840 in the Gene Expression Omnibus (GEO) dataset. In the bioinformatics analysis, only ILF2 (interleukin enhancer-binding factor 2) gene levels were associated with immune cell infiltration, some checkpoint gene expression, chemotherapy sensitivity, and immunotherapy response. Serum levels of ILF2 were higher in GC patients than in controls, with an AUROC of 0.944 for the diagnosis of GC, and it was also detected in the supernatants of GC cells. Knockdown of ILF2 by siRNA significantly reduced the proliferation and colony formation of GC cells. Overexpression of ILF2 significantly promotes the proliferation and colony formation of gastric cancer cells. CONCLUSIONS: Trans-omics analysis of proteomics and transcriptomics is an efficient approach for discovering serum biomarkers, and ILF2 is a potential diagnostic biomarker and therapeutic target of gastric cancer.

Ubiquitin-specific peptidase 24 accelerates aerobic glycolysis and tumor progression in gastric carcinoma through stabilizing PLK1 to activate NOTCH1.

Ubiquitin-specific peptidase 24 (USP24), a member of the deubiquitinase family, plays an important role in tumor regulation. However, the role of USP24 in gastric cancer (GC) is unknown. The aim of our study was to explore the role of USP24 in GC to seek new therapeutic targets for GC. TCGA analysis showed that USP24 was upregulated in GC patients, and its high expression levels were associated with poor prognosis. It was found that overexpressed USP24 promoted GC cell proliferation and abnormal glycolysis. Further analysis and study showed that USP24 could promote the stability and increase the expression of oncogene PLK1. Knocking down USP24 can reduce the stability of PLK1 to reduce Notch 1 activity, thus inhibiting GC glycolysis, proliferation, and other processes and alleviating tumor progression. Knocking down USP24 can inhibit GC progression. In conclusion, USP24 was upregulated in GC and promoted the growth and glycolysis of GC cells, the mechanism of which was related to the deubiquitination of PLK1 and the increase of its stability. Silencing USP24 inhibited the GC process. This study suggests that the USP24/PLK1/Notch 1 axis may be a novel therapeutic target for gastric cancer.

Transcriptomics-proteomics Integration reveals alternative polyadenylation driving inflammation-related protein translation in patients with diabetic nephropathy.

BACKGROUND: Diabetic nephropathy (DN) is a complex disease involving the upregulation of many inflammation-related proteins. Alternative polyadenylation (APA), a crucial post-transcriptional regulatory mechanism, has been proven to play vital roles in many inflammatory diseases. However, it is largely unknown whether and how APA exerts function in DN. METHODS: We performed transcriptomics and proteomics analysis of glomeruli samples isolated from 50 biopsy-proven DN patients and 25 control subjects. DaPars and QAPA algorithms were adopted to identify APA events from RNA-seq data. The qRT-PCR analysis was conducted to verify 3'UTR length alteration. Short and long 3'UTRs isoforms were also overexpressed in podocytes under hyperglycemia condition for examining protein expression. RESULTS: We detected transcriptome-wide 3'UTR APA events in DN, and found that APA-mediated 3'UTR lengthening of genes (APA genes) increased their expression at protein but not mRNA level. Increased protein level of 3'UTR lengthening gene was validated in podocytes under hyperglycemia condition. Pathway enrichment analysis showed that APA genes were enriched in inflammation-related biological processes including endoplasmic reticulum stress pathways, NF-κB signaling and autophagy. Further bioinformatics analysis demonstrated that 3'UTR APA of genes probably altered the binding sites for RNA-binding proteins, thus enhancing protein translation. CONCLUSION: This study revealed for the first time that 3'UTR lengthening of APA genes contributed to the progression of DN by elevating the translation of corresponding proteins, providing new insight and a rich resource for investigating DN mechanisms.

Many-Body Description of STM-Induced Fluorescence of Charged Molecules.

A scanning tunneling microscope is used to study the fluorescence of a model charged molecule (quinacridone) adsorbed on a sodium chloride (NaCl)-covered metallic sample. Fluorescence from the neutral and positively charged species is reported and imaged using hyperresolved fluorescence microscopy. A many-body model is established based on a detailed analysis of voltage, current, and spatial dependences of the fluorescence and electron transport features. This model reveals that quinacridone adopts a palette of charge states, transient or not, depending on the voltage used and the nature of the underlying substrate. This model has a universal character and clarifies the transport and fluorescence mechanisms of molecules adsorbed on thin insulators.

TYRO3 protects podocyte via JNK/c-jun-P53 pathway.

Podocyte injury plays a critical role in diabetic kidney disease (DKD). Our previous work demonstrated a protective role of tyrosine-protein kinase receptor TYRO3 in glomerular disease; However, the downstream signaling of TYRO3 remains unclear. Our data showed that genetic ablation of tyro3 in zebrafish recapitulated a nephrotic syndrome phenotype. TYRO3 expression was suppressed by high glucose and TGF-ß, which may contribute to the decreased TYRO3 expression in progressive DKD. Moreover, knockdown of TYRO3 expression with siRNA induced podocytes apoptosis and cytoskeleton rearrangement. Further study revealed that TYRO3 conferred antiapoptotic effects through the activation of JNK/c-jun-P53 in podocytes. Our results revealed a novel signaling module of TYRO3 in podocyte homeostasis, which provides a new molecular insight of TYRO3 effect in podocyte protection.

First transcriptome profiling in gill and hepatopancrease tissues of Metapenaeus ensis in response to acute ammonia-N stress.

The greasyback shrimp, Metapenaeus ensis, suffers from ammonia-N stress during intensive factory aquaculture. Optimizing ammonia-N stress tolerance has become an important issue in M. ensis breeding. The metabolic and adaptive mechanisms of ammonia-N toxicity in M. ensis have not been comprehensively understood yet. In this study, a large number of potential simple sequence repeats (SSRs) in the transcriptome of M. ensis were identified. Differentially expressed genes (DEGs) in the gill and hepatopancreas at 24 h post-challenges under high concentrations of ammonia-N treatment were detected. We obtained 20,108,851-27,681,918 clean reads from the control and high groups, assembled and clustered a total of 103,174 unigenes with an average of 876 bp and an N50 of 1189 bp. Comparative transcriptome analyses identified 2000 different expressed genes in the gill and 2010 different expressed genes in the hepatopancreas, a large number of which were related to immune function, oxidative stress, metabolic regulation, and apoptosis. The results suggest that M. ensis may counteract ammonia-N toxicity at the transcriptome level by increasing the expression of genes related to immune stress and detoxification metabolism, and that selected genes may serve as molecular indicators of ammonia-N. By exploring the genetic basis of M. ensis' ammonia-N stress adaptation, we constructed the genetic networks for ammonia-N adaptation. These findings will accelerate the understanding of M. ensis' ammonia-N adaptation, contribute to the research of future breeding, and promote the level of factory aquaculture of M. ensis.

Bibliometric analysis of aptamer-conjugated nanoparticles for diagnosis in the last two decades.

Objective.Aptamer-conjugated nanoparticles for diagnosis have recently gained increasing attention. Here, we performed a bibliometric analysis to provide an overview of this field over the past two decades.Methods. The terms 'aptamer, nanoparticles and diagnosis' were used to search for relevant original articles published in English from 2003 to 2022 in the Web of Science database. VOSviewer and CiteSpace software were employed to analyze the development process, knowledge structure, research hotspots, and potential trends in the field of aptamer-conjugated nanoparticles for diagnosis.Results. A total of 1076 original articles were retrieved, with a rapid increase in the annual output and citation. The journal 'Biosensors and Bioelectronics' has contributed the most in this field, and the most influential researcher, institution and country were Weihong Tan, the Chinese Academy of Sciences, China, respectively. Gold nanoparticles and quantum dots were the most used, but in the past three years, research hotspots focused on carbon dots and graphene quantum dots. Diagnostic directions primarily focused on cancer. The most used strategy was label-free electrochemical detection, but in the past two years, colorimetric analysis and fluorescence imaging emerged as hot topics.Conclusion.The bibliometric analysis reveals a rapid increase in the research on aptamer-conjugated nanoparticles for diagnosis, major contributors at the levels of journals, authors, institutions, and countries, and research preferences in diagnostic objects, nanoparticle types, and detection methods, as well as the evolution of research hotspots and future trends.

Identifying acute kidney injury subphenotypes using an outcome-driven deep-learning approach.

OBJECTIVE: Acute kidney injury (AKI), a common condition on the intensive-care unit (ICU), is characterized by an abrupt decrease in kidney function within a few hours or days, leading to kidney failure or damage. Although AKI is associated with poor outcomes, current guidelines overlook the heterogeneity among patients with this condition. Identification of AKI subphenotypes could enable targeted interventions and a deeper understanding of the injury's pathophysiology. While previous approaches based on unsupervised representation learning have been used to identify AKI subphenotypes, these methods cannot assess time series or disease severity. METHODS: In this study, we developed a data- and outcome-driven deep-learning (DL) approach to identify and analyze AKI subphenotypes with prognostic and therapeutic implications. Specifically, we developed a supervised long short-term memory (LSTM) autoencoder (AE) with the aim of extracting representation from time-series EHR data that were intricately correlated with mortality. Then, subphenotypes were identified via application of K-means. RESULTS: In two publicly available datasets, three distinct clusters were identified, characterized by mortality rates of 11.3%, 17.3%, and 96.2% in one dataset and 4.6%, 12.1%, and 54.6% in the other. Further analysis demonstrated that AKI subphenotypes identified by our proposed approach were statistically significant on several clinical characteristics and outcomes. CONCLUSION: In this study, our proposed approach could successfully cluster the AKI population in ICU settings into 3 distinct subphenotypes. Thus, such approach could potentially improve outcomes of AKI patients in the ICU, with better risk assessment and potentially better personalized treatment.

Unveiling breast cancer risk profiles: a survival clustering analysis empowered by an online web application.

Aim: To develop a shiny app for doctors to investigate breast cancer treatments through a new approach by incorporating unsupervised clustering and survival information. Materials & methods: Analysis is based on the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset, which contains 1726 subjects and 22 variables. Cox regression was used to identify survival risk factors for K-means clustering. Logrank tests and C-statistics were compared across different cluster numbers and Kaplan-Meier plots were presented. Results & conclusion: Our study fills an existing void by introducing a unique combination of unsupervised learning techniques and survival information on the clinician side, demonstrating the potential of survival clustering as a valuable tool in uncovering hidden structures based on distinct risk profiles.

Data-driven decision-making for precision diagnosis of digestive diseases.

Modern omics technologies can generate massive amounts of biomedical data, providing unprecedented opportunities for individualized precision medicine. However, traditional statistical methods cannot effectively process and utilize such big data. To meet this new challenge, machine learning algorithms have been developed and applied rapidly in recent years, which are capable of reducing dimensionality, extracting features, organizing data and forming automatable data-driven clinical decision systems. Data-driven clinical decision-making have promising applications in precision medicine and has been studied in digestive diseases, including early diagnosis and screening, molecular typing, staging and stratification of digestive malignancies, as well as precise diagnosis of Crohn's disease, auxiliary diagnosis of imaging and endoscopy, differential diagnosis of cystic lesions, etiology discrimination of acute abdominal pain, stratification of upper gastrointestinal bleeding (UGIB), and real-time diagnosis of esophageal motility function, showing good application prospects. Herein, we reviewed the recent progress of data-driven clinical decision making in precision diagnosis of digestive diseases and discussed the limitations of data-driven decision making after a brief introduction of methods for data-driven decision making.

Design, synthesis and anti-tumor efficacy evaluation of novel 1,3-diaryl propane-based polyphenols obtained from Claisen rearrangement reaction.

Polyphenols such as resveratrol, honokiol and nordihydroguaiaretic acid are widely existing in nature products or synthetic compounds with interesting biological activities. Inspired by their structural feature, a total of 49 1,3-diaryl propane-based polyphenols were designed and synthesized through Claisen rearrangement reaction. New compounds were initially assessed for their anti-proliferative activities against various cancer cell lines (PC-3, U87MG, U251, HCT116) at a concentration of 50 µM, and the results guided the SAR of this series of compounds. Further screening of selected compounds against seven cancer cell lines (three additional colon cancer cell lines namely COLO205, HT29 and SW480 were chosen) led to the identification of two advanced leads 2t and 3t with IC50 values ranging from 8.2 ± 0.1 to 19.3 ± 1.9 µM. Both compounds also showed promising anti-proliferative activities against COLO205 in dose- and time-dependent manners. Furthermore, 2t and 3t exhibited good anti-tumor efficacy in COLO205 xenografted mice model with TGI values ranging from 38% to 58%. These results warrant the further investigation of this series of compounds.

A generalizable and interpretable model for mortality risk stratification of sepsis patients in intensive care unit.

PURPOSE: This study aimed to construct a mortality model for the risk stratification of intensive care unit (ICU) patients with sepsis by applying a machine learning algorithm. METHODS: Adult patients who were diagnosed with sepsis during admission to ICU were extracted from MIMIC-III, MIMIC-IV, eICU, and Zigong databases. MIMIC-III was used for model development and internal validation. The other three databases were used for external validation. Our proposed model was developed based on the Extreme Gradient Boosting (XGBoost) algorithm. The generalizability, discrimination, and validation of our model were evaluated. The Shapley Additive Explanation values were used to interpret our model and analyze the contribution of individual features. RESULTS: A total of 16,741, 15,532, 22,617, and 1,198 sepsis patients were extracted from the MIMIC-III, MIMIC-IV, eICU, and Zigong databases, respectively. The proposed model had an area under the receiver operating characteristic curve (AUROC) of 0.84 in the internal validation, which outperformed all the traditional scoring systems. In the external validations, the AUROC was 0.87 in the MIMIC-IV database, better than all the traditional scoring systems; the AUROC was 0.83 in the eICU database, higher than the Simplified Acute Physiology Score III and Sequential Organ Failure Assessment (SOFA),equal to 0.83 of the Acute Physiology and Chronic Health Evaluation IV (APACHE-IV), and the AUROC was 0.68 in the Zigong database, higher than those from the systemic inflammatory response syndrome and SOFA. Furthermore, the proposed model showed the best discriminatory and calibrated capabilities and had the best net benefit in each validation. CONCLUSIONS: The proposed algorithm based on XGBoost and SHAP-value feature selection had high performance in predicting the mortality of sepsis patients within 24 h of ICU admission.

Azaphilones from the Fungus Penicillium multicolor LZUC-S2 and Their Antibacterial Activity.

Two new azaphilones, penimultiones A and B, together with seven known analogs were isolated from the culture of Penicillium multicolor LZUC-S2. Their structures were elucidated by detailed spectroscopic data analysis and chemical transformation. Penimultiones A and B belong to a rare class of azaphilones possessing a 1,3-dioxolane moiety. In addition, all compounds were evaluated for their antibacterial activity against five clinically bacterial strains in vitro, and three compounds showed potent antibacterial activity with minimum inhibitory concentration (MIC) values ranging from 12.5 to 50.0 µg/mL.

Comparative transcriptome analysis of differentially expressed genes and pathways in Procambarus clarkii (Louisiana crawfish) at different acute temperature stress.

Procambarus clarkii is an important economic species in China, and exhibit heat and cold tolerance in the main culture regions. To understand the mechanisms, we analyzed the hepatopancreas transcriptome of P. clarkii treated at 10 °C, 25 °C, and 30 °C, then 2092 DEGs and 6929 DEGs were found in 30 °C stress group and 10 °C stress group, respectively. KEGG pathway enrichment results showed that immune pathway is the main stress pathway for 10 °C treatment and metabolic pathway is the main response pathway for 30 °C treatment, which implies low temperature stress induces the damage of the immune system and increases the susceptibility of bacteria while the body response to high temperature stress through metabolic adjustment. In addition, flow cytometry proved that both high and low temperature stress caused different degrees of apoptosis of hemocytes, and dynamic transcription heat map analysis also identified the differential expression of HSPs family genes and apoptosis pathway genes under different heat stresses. This indicates that preventing damaged protein misfolding and accelerating cell apoptosis are necessary mechanisms for P. clarkii to cope with high and low temperature stress. Our research has deepened our understanding of the complex molecular mechanisms of P. clarkii in response to acute temperature stress, and provided a potential strategy for aquatic animals to relieve environmental duress.

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Objective: To investigate the role of histone deacetylase 6 (HDAC6) in podocyte injury in diabetic kidney disease (DKD) in mice. Methods: 1) The 8-week-old male CD-1 mice were selected to construct the model of DKD with streptozocin (STZ). After the model was established, the mice were intraperitoneally injected with HDAC6 inhibitor CAY10603 (5mg/kg/daily) or same volume vehicle as control. The mice were divided into four groups, control (CTL)+vehicle (Veh) (n=5), CLT+CAY10603 (n=3), STZ+Veh (n=9), and STZ+CAY10603 (n=7). Mice in STZ+Veh and STZ+CAY10603 groups developed DKD, while mice in the CTL+Veh and CTL+CAY10603 groups were served as normal controls. The therapeutic effect was evaluated through urine albumin-to-creatinine ratio (uACR) and renal pathology after the 2-week treatment with CAY10603. 2) Human podocytes were cultured in vitro and were divided into four groups as follows: CTL, transforming growth factor-ß (TGFß), TGFß+CAY10603 (250 nmol/L), and TGFß+CAY10603 (500 nmol/L) groups. The control group did not receive any treatment, the last three groups were given 36-h TGFß treatment at 5 ng/µL, with or without CAY10603 as indicated for an additional 12 h. Western blot was performed to determine the inhibitory effect of CAY10603 on NLRP3 inflammasome. 3) HDAC6 knockout (KO) mice were generated and used to create STZ-induced model of DKD. The mice were divided into four groups: C57BL/6J wild type (WT) (n=6), HDAC6 KO (n=6), WT+STZ (n=10), and HDAC6 KO+STZ (n=9). Samples were collected 16 weeks after successful modeling and changes in uACR and renal pathology were evaluated accordingly. Results: After 2 weeks of treatment, mice in the STZ+CAY10603 group exhibited reduction in uACR (P<0.05) and inhibition of glomerular mesangium expansion (P<0.05) compared with those of the mice in the STZ+Veh group. There was no statistically significant difference in the indicators between the CTL+Veh group and the CTL+CAY10603 group. In vitro cultured podocytes, compared with the control group, NLRP3 inflammasome activation was seen in the TGFß group. CAY10603 treatment significantly inhibited the activation of NLRP3 in the dosage-dependent manner (P<0.05). Compared with those of the WT group, the WT+STZ group showed increased uACR (P<0.05), obvious glomerulosclerosis and loss of podocytes numbers. Compared with those of the WT+STZ group, the HDAC6 KO+STZ group showed effectively reduction of uACR (P<0.05) and improvement in the renal pathological changes in mice. There was no significant difference in these aspects between the WT and HDAC6 KO groups. Conclusion: Inhibition of HDAC6 alleviates proteinuria and podocyte injury in the mouse model of DKD by suppressing the activation of NLRP3 inflammasome.

Identification and functional analysis of carbonyl reductases related to tetrahydrobiopterin synthesis in the silkworm, Bombyx mori.

The superfamily of short-chain dehydrogenases/reductases (SDRs) is crucial in biosynthetic and signalling pathways, in which the carbonyl reductases (CBRs) subfamily is important in the biosynthesis of tetrahydrobiopterin (BH4). BH4 is an essential coenzyme for animals, and its deficiency can lead to neurological diseases. There are few reports on CBRs involved in BH4 synthesis of silkworms, Bombyx mori. Here, we identified 67 SDR genes in B. mori (BmSDR) through whole genome survey for the first time. Based on bioinformatics analyses and KEGG verification, four BmCBRs that may be related to BH4 synthesis were further characterized and functionally analysed. The results showed these four genes were high expressed in the head and gonads of ah09 (a lem mutant with defective BH4 synthesis). Enzyme activity, BH4 content and the related gene expression levels after intracellular interference with BmCBR and the main catalytic enzymes sepiapterin reductase of B. mori (BmSpr) in the de novo pathway of BH4 showed BmCBR2 plays a role in the salvage pathway. BmCBR3 and BmCBR4 regulate BH4 synthesis through the alternative pathway. Among the four pathways of silkworm BH4 synthesis, the de novo pathway occupies the dominant position, followed by the alternative pathway and salvage pathway. According to the overexpression of BmCBR3 after interference with BmSpr, the BH4 content did not change significantly. It is speculated that BmCBR3 is located upstream of BmSpr. These results provide a theoretical basis for in-depth exploration of the role of BmSDR in B. mori and also provide clues for the research of other animal-related diseases.

A novel four-gene signature for predicting the prognosis of hepatocellular carcinoma.

OBJECTIVE: To identify and utilize gene signatures for the prognostic evaluation of postoperative patients with hepatocellular carcinoma (HCC). METHODS: The gene mRNA expression profiles and corresponding clinicopathological data of postoperative patients with HCC were downloaded from The Cancer Genome Atlas (TCGA) database. Highly differentially expressed genes (DEGs) in tumor tissues compared to adjacent tissues were identified, and their associations with the overall survival (OS) of HCC patients were analyzed. The strongly associated genes were used to develop a prognostic score for the survival stratification of HCC, and the underlying mechanisms were analyzed using bioinformatics. RESULTS: A total of 376 DEGs were identified and four DEGs (ADH4, COL15A1, RET and KCNJ16) were independently associated with OS. A prognostic score derived from the four genes could effectively stratify HCC patients with different OS outcomes, independent of clinical parameters. Patients with high scores exhibited poorer OS than patients with low scores (HR 5.526, 95% CI: 2.451-12.461, p < .001). The four genes were involved in cancer-related biological processes and were independent of each other in bioinformatics analyses. CONCLUSION: Four genes strongly associated with the prognosis of postoperative patients with HCC were identified, and the derived prognostic score was simple and valuable for overall survival prediction.

Transcriptome analysis of hepatopancreas in penaeus monodon under acute low pH stress.

The decrease of seawater pH can affect the metabolism, acid-base balance, immune response and immunoprotease activity of aquatic animals, leading to aquatic animal stress, impairing the immune system of aquatic animals and weakening disease resistance, etc. In this study, we performed high-throughput sequencing analysis of the hepatopancreas transcriptome library of low pH stress penaeus monodon, and after sequencing quality control, a total of 43488612-56271828 Clean Reads were obtained, and GO annotation and KEGG pathway enrichment analysis were performed on the obtained Clean Reads, and a total of 395 DEGs were identified. we mined 10 differentially expressed and found that they were significantly enriched in the Metabolic pathways (ko01100), Biosynthesis of secondary metabolites (ko01110), Nitrogen metabolism (ko00910) pathways, such as PIGA, DGAT1, DGAT2, UBE2E on Metabolic pathways; UGT, GLT1, TIM genes on Biosynthesis of secondary metabolites; CA, CA2, CA4 genes on Nitrogen metabolism, are involved in lipid metabolism, induction of oxidative stress and inflammation in the muscular body of spot prawns. These genes play an important role in lipid metabolism, induction of oxidative stress and inflammatory response in the muscle of the shrimp. In summary, these genes provide valuable reference information for future breeding of low pH-tolerant shrimp.

Identification of multifunctionality of the PmE74 gene and development of SNPs associated with low salt tolerance in Penaeus monodon.

Members of the E74-like factor (ELF) subfamily are involved in the immune stress process of organisms by regulating immune responses and the development of immune-related cells. PmE74 of Penaeus monodon was characterized and functionally analyzed in this study. The full length of PmE74 was 3106 bp, with a 5'-UTR of 297 bp, and a 3'-UTR of 460 bp. The ORF (Open reading frame) was 2349 bp and encoded 782 amino acids. Domain analysis showed that PmE74 contains a typical Ets domain. Multiple sequence alignment and phylogenetic tree analysis showed that PmE74 clustered with Litopenaeus vannamei E74 and displayed significant similarity (98.98%). PmE74 was expressed in all tissues tested in P. monodon, with the highest levels of expression observed in the testis, intestine, and epidermis. Different pathogen stimulation studies have revealed that PmE74 expression varies in response to different pathogen stimuli. A 96-h acute low salt stress study revealed that PmE74 in the hepatopancreas was upregulated and downregulated in the salinity 17 group and considerably downregulated in the salinity 3 group, whereas PmE74 in gill tissue was considerably downregulated in both groups. Further, by knocking down PmE74 and learning the trends of its linkage genes PmAQP1, PmNKA, PmE75, PmFtz-f1, PmEcR, and PmRXR in response to low salt stress, it was further indicated that PmE74 could have a vital role in the regulation of low salt stress. The SNP test revealed that PmE74-In1-53 was significantly associated with low salt tolerance traits in P. monodon (P < 0.05). The findings of this study can aid in the advancement of molecular marker-assisted breeding in P. monodon, as well as provide fundamental data and methodologies for further investigation of its low salt tolerance strains in P. monodon.