Enhancement of PRMT6 binding to a novel germline GATA1 mutation associated with congenital anemia.

Mutations in the master hematopoietic transcription factor GATA1 are often associated with functional defects in erythropoiesis and megakaryopoiesis. In this study, we identified a novel GATA1 germline mutation (c.1162delGG, p.Leu387Leufs*62) in a patient with congenital anemia and occasional thrombocytopenia. The C-terminal GATA1, a rarely studied mutational region, undergoes frameshifting translation as a consequence of this double-base deletion mutation. To investigate the specific function and pathogenic mechanism of this mutant, in vitro mutant models of stable re-expression cells were generated. The mutation was subsequently validated to cause diminished transcriptional activity of GATA1 and defective differentiation of erythroid and megakaryocytes. Using proximity labeling and mass spectrometry, we identified selective alterations in the proximal protein networks of the mutant, revealing decreased binding to a set of normal GATA1-interaction proteins, including the essential co-factor FOG1. Notably, our findings further demonstrated enhanced recruitment of the protein arginine methyltransferase PRMT6, which mediates histone modification at H3R2me2a and represses transcription activity. We also found an enhanced binding of this mutant GATA1/PRMT6 complex to the transcriptional regulatory elements of GATA1's target genes. Moreover, treatment of the PRMT6 inhibitor MS023 could partially rescue the inhibited transcriptional and impaired erythroid differentiation caused by the GATA1 mutation. Taken together, our results provide molecular insights into erythropoiesis in which mutation leads to partial loss of GATA1 function and the broader role of PRMT6 and its inhibitor MS023 in congenital anemia, highlighting PRMT6 binding as a negative factor of GATA1 transcriptional activity in aberrant hematopoiesis.

A molecule-imprinted electrochemiluminescence sensor based on CdS@MWCNTs for ultrasensitive detection of fenpropathrin.

A molecularly-imprinted electrochemiluminescence sensor was constructed for the determination of fenpropathrin (FPT) by molecular imprinting technology. In this sensing platform, the introduction of CdS@MWCNTs significantly enhanced the initial ECL signal of the luminol-O2 system. Specifically, MWCNTs was used as a carrier to adsorb more CdS, in which CdS acted as a co-reaction promoter for luminescence. Molecularly imprinted polymer (MIP) containing specific recognition sites of FPT was used as the material for selective recognition. With increasing amount of FPT the ECL signal decreased. Under the optimum conditions, the ECL response was linearly related to the logarithm of FPT concentration. The developed ECL sensor allowed for sensitive determination of FPT and exhibited a wide linear range from 1.0 × 10- 10 mol L- 1 to 1.0 × 10- 6 mol L- 1. The limit of detection was 3.3 × 10- 11 mol L- 1 (S/N = 3). It can be used for the detection of FPT in vegetable samples.

Ultrasensitive solid-state electrochemiluminescence sensor based on lotus root shaped carbon fiber, CdSe QDs and Fe3O4 synergically amplify Ru(bpy)32+ luminophore signal for detection of cyfluthrin.

An efficient and innovative electrochemiluminescence (ECL) sensor was developed for trace detection of cyfluthrin. The sensor utilized materials such as lotus root shaped carbon fiber (Co CNFs), cadmium selenide quantum dots (CdSe QDs), and Fe3O4 to amplify Ru(bpy)32+ signals. Co CNFs, with its large specific surface area and porosity, served the purpose of not only enhancing the stability of the sensor by fixing CdSe QDs and Ru(bpy)32+ on the Co CNFs/GCE, but also facilitating electron transfer. CdSe QDs was involved in the luminescence reaction and collaborated with Ru(bpy)32+ to enhance the sensor's sensitivity, while Fe3O4 promoted electron transfer in the system due to its large surface area. The solid-state ECL sensor achieved satisfactory signal under the synergistic action of these components. The ECL signal of the sensor was quenched by cyfluthrin, and a favorable linear relationship was observed between the sensor and cyfluthrin in the concentration range 1 × 10-12 to 1 × 10-6 M. The detection limit of the sensor was 3.3 × 10-13 M (S/N = 3). The utilization of lotus root shaped carbon fiber, CdSe QDs, and Fe3O4 in the Ru(bpy)32+ system demonstrated a synergistic effect for cyfluthrin detection, presenting a new approach for the rapid determination analysis of pesticide residues in foods.

AtVQ25 promotes salicylic acid-related leaf senescence by fine-tuning the self-repression of AtWRKY53.

Most mechanistic details of chronologically ordered regulation of leaf senescence are unknown. Regulatory networks centered on AtWRKY53 are crucial for orchestrating and integrating various senescence-related signals. Notably, AtWRKY53 binds to its own promoter and represses transcription of AtWRKY53, but the biological significance and mechanism underlying this self-repression remain unclear. In this study, we identified the VQ motif-containing protein AtVQ25 as a cooperator of AtWRKY53. The expression level of AtVQ25 peaked at mature stage and was specifically repressed after the onset of leaf senescence. AtVQ25-overexpressing plants and atvq25 mutants displayed precocious and delayed leaf senescence, respectively. Importantly, we identified AtWRKY53 as an interacting partner of AtVQ25. We determined that interaction between AtVQ25 and AtWRKY53 prevented AtWRKY53 from binding to W-box elements on the AtWRKY53 promoter and thus counteracted the self-repression of AtWRKY53. In addition, our RNA-sequencing data revealed that the AtVQ25-AtWRKY53 module is related to the salicylic acid (SA) pathway. Precocious leaf senescence and SA-induced leaf senescence in AtVQ25-overexpressing lines were inhibited by an SA pathway mutant, atsid2, and NahG transgenic plants; AtVQ25-overexpressing/atwrky53 plants were also insensitive to SA-induced leaf senescence. Collectively, we demonstrated that AtVQ25 directly attenuates the self-repression of AtWRKY53 during the onset of leaf senescence, which is substantially helpful for understanding the timing of leaf senescence onset modulated by AtWRKY53.

Systematic profiling of invasion-related gene signature predicts prognostic features of lung adenocarcinoma.

Due to the high heterogeneity of lung adenocarcinoma (LUAD), molecular subtype based on gene expression profiles is of great significance for diagnosis and prognosis prediction in patients with LUAD. Invasion-related genes were obtained from the CancerSEA database, and LUAD expression profiles were downloaded from The Cancer Genome Atlas. The ConsensusClusterPlus was used to obtain molecular subtypes based on invasion-related genes. The limma software package was used to identify differentially expressed genes (DEGs). A multi-gene risk model was constructed by Lasso-Cox analysis. A nomogram was also constructed based on risk scores and meaningful clinical features. 3 subtypes (C1, C2 and C3) based on the expression of 97 invasion-related genes were obtained. C3 had the worst prognosis. A total of 669 DEGs were identified among the subtypes. Pathway enrichment analysis results showed that the DEGs were mainly enriched in the cell cycle, DNA replication, the p53 signalling pathway and other tumour-related pathways. A 5-gene signature (KRT6A, MELTF, IRX5, MS4A1 and CRTAC1) was identified by using Lasso-Cox analysis. The training, validation and external independent cohorts proved that the model was robust and had better prediction ability than other lung cancer models. The gene expression results showed that the expression levels of MS4A1 and KRT6A in tumour tissues were higher than in normal tissues, while CRTAC1 expression in tumour tissues was lower than in normal tissues. The 5-gene signature prognostic stratification system based on invasion-related genes could be used to assess prognostic risk in patients with LUAD.

Genome-wide analysis of long non-coding RNAs in adult tissues of the melon fly, Zeugodacus cucurbitae (Coquillett).

BACKGROUND: Long non-coding RNAs (lncRNAs) are involved in many fundamental biological processes, such as transcription regulation, protein degradation, and cell differentiation. Information on lncRNA in the melon fly, Zeugodacus cucurbitae (Coquillett) is currently limited. RESULTS: We constructed 24 RNA-seq libraries from eight tissues (midgut, Malpighian tubules, fat body, ovary, and testis) of Z. cucurbitae adults. A total of 3124 lncRNA transcripts were identified. Among those, 1464 were lincRNAs, 1037 were intronic lncRNAs, 301 were anti-sense lncRNAs, and 322 were sense lncRNAs. The majority of lncRNAs contained two exons and one isoform. Differentially expressed lncRNAs were analyzed between tissues, and Malpighian tubules versus testis had the largest number. Some lncRNAs exhibited strong tissue specificity. Specifically expressed lncRNAs were identified and filtered in tissues of female and male Z. cucurbitae based on their expression levels. Four midgut-specific lncRNAs were validated by quantitative real-time polymerase chain reaction (RT-qPCR), and the data were consistent with RNA-seq data. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of targets of midgut-specific lncRNAs indicated an enrichment of the metabolic process. CONCLUSIONS: This was the first systematic identification of lncRNA in the melon fly. Expressions of lncRNAs in multiple adult tissues were evaluated by quantitative transcriptomic analysis. These qualitative and quantitative analyses of lncRNAs, especially the tissue-specific lncRNAs in Z. cucurbitae, provide useful data for further functional studies.

Dynamics simulation of ammonia nitrogen absorption in a rural-urban canal on the Northeast China Plain.

To study dynamic laws of ammonia nitrogen retention in a typical rural-urban fringe canal, NaBr was selected as a conservative tracer agent, and NH4Cl as an additive nutritive salt to conduct an instantaneously added tracer experiment outdoors. On this basis, tracer additions for spiralling curve characterisation (TASCC) method and nutritive spiral indexes were used for the quantitative depiction of retention dynamics of NH4 +-N. The Michaelis-Menten (M-M) model was used to simulate absorption dynamic characteristics of NH4 +-N. Results showed that the variation range of absorption length of NH4 +-N under background concentration was 93.94-295.54 m with an average value of 177.41 m, the variation range of mass transfer coefficient was 0.16-0.38 mm/s with an average value of 0.26 mm/s, and the variation range of absorption rate was 0.16-0.38 mg/(m2⋅s) with an average value of 0.26 mg/(m2⋅s). The maximum absorption rate of NH4 +-N obtained via M-M equation simulation was 0.59-1.38 mg/(m2⋅s), and the subsaturation constant was 1.10-5.03 mg/L. The variability of the dynamic absorption length, overall dynamic absorption rate, and overall dynamic mass transfer coefficient shown by NH4 +-N within the range from background concentration to saturation concentration certified that TASCC could analyse the dynamic process of NH4 +-N retention and absorption by the canal.

Bioinformatics and system biology approaches to determine the connection of SARS-CoV-2 infection and intrahepatic cholangiocarcinoma.

INTRODUCTION: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of coronavirus disease 2019 (COVID-19), has infected millions of individuals worldwide, which poses a severe threat to human health. COVID-19 is a systemic ailment affecting various tissues and organs, including the lungs and liver. Intrahepatic cholangiocarcinoma (ICC) is one of the most common liver cancer, and cancer patients are particularly at high risk of SARS-CoV-2 infection. Nonetheless, few studies have investigated the impact of COVID-19 on ICC patients. METHODS: With the methods of systems biology and bioinformatics, this study explored the link between COVID-19 and ICC, and searched for potential therapeutic drugs. RESULTS: This study identified a total of 70 common differentially expressed genes (DEGs) shared by both diseases, shedding light on their shared functionalities. Enrichment analysis pinpointed metabolism and immunity as the primary areas influenced by these common genes. Subsequently, through protein-protein interaction (PPI) network analysis, we identified SCD, ACSL5, ACAT2, HSD17B4, ALDOA, ACSS1, ACADSB, CYP51A1, PSAT1, and HKDC1 as hub genes. Additionally, 44 transcription factors (TFs) and 112 microRNAs (miRNAs) were forecasted to regulate the hub genes. Most importantly, several drug candidates (Periodate-oxidized adenosine, Desipramine, Quercetin, Perfluoroheptanoic acid, Tetrandrine, Pentadecafluorooctanoic acid, Benzo[a]pyrene, SARIN, Dorzolamide, 8-Bromo-cAMP) may prove effective in treating ICC and COVID-19. CONCLUSION: This study is expected to provide valuable references and potential drugs for future research and treatment of COVID-19 and ICC.

TM-Score predicts immunotherapy efficacy and improves the performance of the machine learning prognostic model in gastric cancer.

Immunotherapy is becoming increasingly important, but the overall response rate is relatively low in the treatment of gastric cancer (GC). The application of tumor mutational burden (TMB) in predicting immunotherapy efficacy in GC patients is limited and controversial, emphasizing the importance of optimizing TMB-based patient selection. By combining TMB and major histocompatibility complex (MHC) related hub genes, we established a novel TM-Score. This score showed superior performance for immunotherapeutic selection (AUC = 0.808) compared to TMB, MSI status, and EBV status. Additionally, it predicted the prognosis of GC patients. Subsequently, a machine learning model adjusted by the TM-Score further improved the accuracy of survival prediction (AUC > 0.8). Meanwhile, we found that GC patients with low TM-Score had a higher mutation frequency, higher expression of HLA genes and immune checkpoint genes, and higher infiltration of CD8+ T cells, CD4+ helper T cells, and M1 macrophages. This suggests that TM-Score is significantly associated with tumor immunogenicity and tumor immune environment. Notably, based on the RNA-seq and scRNA-seq, it was found that AKAP5, a key component gene of TM-Score, is involved in anti-tumor immunity by promoting the infiltration of CD4+ T cells, NK cells, and myeloid cells. Additionally, siAKAP5 significantly reduced MHC-II mRNA expression in the GC cell line. In addition, our immunohistochemistry assays confirmed a positive correlation between AKAP5 and human leukocyte antigen (HLA) expression. Furthermore, AKAP5 levels were higher in patients with longer survival and those who responded to immunotherapy in GC, indicating its potential value in predicting prognosis and immunotherapy outcomes. In conclusion, TM-Score, as an optimization of TMB, is a more precise biomarker for predicting the immunotherapy efficacy of the GC population. Additionally, AKAP5 shows promise as a therapeutic target for GC.

An ultrasensitive solid-state electrochemiluminescence sensor based on Ni-MOF@Ru(bpy)32+ and Au NPs@TiO2 for determination of permethrin.

The novel TiO2 and Ni-MOF materials were synthesized and utilized for the detection of permethrin (PET). A highly sensitive solid-state electrochemiluminescence (ECL) sensor was developed based on Ni-MOF@Ru(bpy)32+ and Au NPs@TiO2. In this sensing platform, Ru(bpy)32+-Tripropyl Amine (TPrA) was used as a luminescent signal, Ni-MOF acted as a carrier to carry more luminescent reagents Ru(bpy)32+. Au NPs acted as promoters facilitated electron transport and TiO2 could further enhance the luminescence intensity of the system by synergistical interaction with Au NPs. The possible mechanisms of signal amplification were investigated. The ECL intensity decreased significantly with increasing PET concentration, enabling the determination of PET amount through the observation of the change in ECL signal intensity (ΔI). Under optimal experimental conditions, the linear range of PET concentration from 1.0 × 10-11 mol L-1 to 1.0 × 10-6 mol L-1, with a detection limit of 3.3 × 10-12 mol L-1 (3S/N). This method was successfully applied to determine PET in various vegetable samples.

Typical urban gully nitrogen migration in Changchun City, China.

In this study, Yitong River, which is located in Changchun, a representative city in northeastern China, was selected as the research area. Using position monitoring and field measurements, we quantitatively investigated the migration path and flux of nitrogen in a gully region in Changchun City undergoing rapid urbanization. The results showed that at the Yitong River subwatershed, the total nitrogen input flux was 188 kg/hm(2), the degree of which can be ranked in descending order as fertilizer input > biological immobilization > feed > atmospheric deposition. The total nitrogen output flux was 102.5 kg/hm(2), ranked in descending degree as products > waste output > denitrification > surface runoff. The net nitrogen storage was 85.5 kg/hm(2). The migration path and flux of nitrogen were markedly impacted by human activities, showing an imbalance between input and output, as well as a tendency toward nitrogen accumulation and pollution. The nitrogen budget for the Yitong River subwatershed suggested that more than 50 % of the net anthropogenic nitrogen input was lost to the environment, and about 14.5 % was discharged in rivers, indicating that agricultural and human activities in the basin substantially impact the river water quality and thus alter the nitrogen environmental geochemistry. Reducing the application and improving the efficiency of nitrogenous fertilizer use as well as reclaiming human life waste are efficient approaches to decreasing the nitrogen input flux and environmental accumulation and to promoting the balance between nitrogen input and output. These practices are also effective approaches to reducing non-point source pollution.

Assessment of small strain modulus in soil using advanced computational models.

Small-strain shear modulus ([Formula: see text]) of soils is a crucial dynamic parameter that significantly impacts seismic site response analysis and foundation design. [Formula: see text] is susceptible to multiple factors, including soil uniformity coefficient ([Formula: see text]), void ratio (e), mean particle size ([Formula: see text]), and confining stress ([Formula: see text]). This study aims to establish a [Formula: see text] database and suggests three advanced computational models for [Formula: see text] prediction. Nine performance indicators, including four new indices, are employed to calculate and analyze the model's performance. The XGBoost model outperforms the other two models, with all three models achieving [Formula: see text] values exceeding 0.9, RMSE values below 30, MAE values below 25, VAF values surpassing 80%, and ARE values below 50%. Compared to the empirical formula-based traditional prediction models, the model proposed in this study exhibits better performance in IOS, IOA, a20-index, and PI metrics values. The model has higher prediction accuracy and better generalization ability.

Demonstration of the impact of COVID-19 on metabolic associated fatty liver disease by bioinformatics and system biology approach.

BACKGROUND: Severe coronavirus disease 2019 (COVID-19) has caused a great threat to human health. Metabolic associated fatty liver disease (MAFLD) is a liver disease with a high prevalence rate. Previous studies indicated that MAFLD led to increased mortality and severe case rates of COVID-19 patients, but its mechanism remains unclear. METHODS: This study analyzed the transcriptional profiles of COVID-19 and MAFLD patients and their respective healthy controls from the perspectives of bioinformatics and systems biology to explore the underlying molecular mechanisms between the 2 diseases. Specifically, gene expression profiles of COVID-19 and MAFLD patients were acquired from the gene expression omnibus datasets and screened shared differentially expressed genes (DEGs). Gene ontology and pathway function enrichment analysis were performed for common DEGs to reveal the regulatory relationship between the 2 diseases. Besides, the hub genes were extracted by constructing a protein-protein interaction network of shared DEGs. Based on these hub genes, we conducted regulatory network analysis of microRNA/transcription factors-genes and gene - disease relationship and predicted potential drugs for the treatment of COVID-19 and MAFLD. RESULTS: A total of 3734 and 589 DEGs were screened from the transcriptome data of MAFLD (GSE183229) and COVID-19 (GSE196822), respectively, and 80 common DEGs were identified between COVID-19 and MAFLD. Functional enrichment analysis revealed that the shared DEGs were involved in inflammatory reaction, immune response and metabolic regulation. In addition, 10 hub genes including SERPINE1, IL1RN, THBS1, TNFAIP6, GADD45B, TNFRSF12A, PLA2G7, PTGES, PTX3 and GADD45G were identified. From the interaction network analysis, 41 transcription factors and 151 micro-RNAs were found to be the regulatory signals. Some mental, Inflammatory, liver diseases were found to be most related with the hub genes. Importantly, parthenolide, luteolin, apigenin and MS-275 have shown possibility as therapeutic agents against COVID-19 and MAFLD. CONCLUSION: This study reveals the potential common pathogenesis between MAFLD and COVID-19, providing novel clues for future research and treatment of MAFLD and severe acute respiratory syndrome coronavirus 2 infection.

The resin-supported iron-copper bimetallic composite as highly active heterogeneous Fenton-like catalysts for degradation of gaseous toluene.

In this study, a resin-supported iron-copper bimetallic heterogeneous Fenton catalyst with excellent removal performance, superior economy and outstanding recoverability was synthesized by an impregnation method and used to remove gaseous toluene. Experiments disclosed that 3-FeCu@LXQ-10 possessed extremely high catalytic capacity. At a temperature of 30 °C, an initial toluene concentration of 200 mg/m3 and H2O2 atomization amount of 3 mmol/h, the toluene removal efficiency of 3-FeCu@LXQ-10 was 97.50%. Experimental tests had revealed that the bimetallic supported catalysts exhibited higher catalytic activity than single metal-supported catalysts, owing to an interaction effect between iron and copper metal ions. Furthermore, electron paramagnetic resonance (EPR) and radical quenching tests were carried out, and the results indicated •OH radicals performed a key role in the Fenton-like process. In addition, the iron-copper bimetallic catalysts exhibited good reusability and stability characteristics during six degradation cycles. This study shows promising potential in using FeCu@LXQ-10 as a heterogeneous catalyst for removing toluene.

Performance and mechanisms of iron/copper-doped zirconium-based catalyst containing hydroxyl radicals for enhanced removal of gaseous benzene.

In the present study, novel copper-doped zirconium-based MOF (UIO-66) and copper-doped iron-based UIO-66 catalysts were prepared by hydrothermal synthesis method to improve the removal performance of gaseous benzene. The characteristics of the catalysts were analyzed by means of XRD, SEM, XPS, BET, and EPR. The copper loading catalyst had high crystallinity and irregular globular. The three kinds of catalysts with different Cu/Fe ratios had regular cubic shape. Compared with the catalyst supported with single copper, the bimetal Cu/Fe modification had a certain adjustment effect on the morphology, which specifically reflected in the uniform size and shape of catalyst particles with better dispersibility. The factors of different metal loading, dose of H2O2, and reaction temperature on benzene removal have been studied. It has been observed that in heterogeneous advanced oxidation removal of benzene, 3-Cu@UIO-66 and Cu1.5/Fe1.5@UIO-66 achieved the highest benzene removal efficiency of 81.2% and 94.6%, respectively. EPR results showed that the increase of Cu loading and different Cu/Fe ratios promoted the yield of hydroxyl radicals, thus promoted the benzene removal efficiency. The efficiency of heterogeneous oxidation removal of benzene first increased and then decreased with the increase of temperature due to H2O2 instability. DFT calculations exhibited that the Feoct-Cu-O site was a more effective activation site than the single Feoct-O site. Dissociative adsorption occurred with the O-O bond of H2O2 cracked, and the formed hydroxyls parallel adsorbed on the benzene surface. The combination of benzene and hydroxyls was strong chemisorption with the torsion angle of benzene ring obviously turned. The work was of great importance for identifying the roles of the novel catalyst for the removal of benzene pollutant from waste gases.

Commercial SCR catalyst modified with Cu metal to simultaneously efficiently remove NO and toluene in the fuel gas.

Developing an environmentally friendly selective catalytic reduction (SCR) catalyst to effectively eliminate both nitric oxides (NO) and toluene has garnered significant attention for regulating emissions from automobiles and the combustion of fossil fuels. This study synthesized a series of novel commercial V2O5-WO3/TiO2 catalysts modified with Cu through the wet impregnation method, which was employed to simultaneously remove NO and toluene from the fuel gas. The assessment of catalyst removal performance was conducted at a selective catalytic reduction system, and the experimental results showed a significant increase in the catalytic activity due to the modification of the copper metal. The 10% Cu/SCR catalyst showed a superior activity that the NO and toluene conversion reached 100% and 95.56% at 300 °C, respectively. Subsequently, various characterization techniques were employed to investigate the crystal phase, morphology, physical features, chemical states, and surface acidity properties of the synthesis catalysts. According to the characterization results, the presence of Cu metal did not have a noticeable impact on the physical property. However, the redox performance was enhanced, and the number of surface acidic sites was also increased after adding Cu to the SCR catalyst. Furthermore, the redox cycle of Cu metal and V species was facilitated to produce more active oxygen which helped to improve the NO and toluene conversion. This work offered a novel perspective into the synergistic oxidation of both NO and toluene, which was potentially relevant for improving the selective catalytic reduction process in coal-fired power plants.

The influence of COVID-19 on colorectal cancer was investigated using bioinformatics and systems biology techniques.

Introduction: Coronavirus disease 2019 (COVID-19) is a global pandemic and highly contagious, posing a serious threat to human health. Colorectal cancer (CRC) is a risk factor for COVID-19 infection. Therefore, it is vital to investigate the intrinsic link between these two diseases. Methods: In this work, bioinformatics and systems biology techniques were used to detect the mutual pathways, molecular biomarkers, and potential drugs between COVID-19 and CRC. Results: A total of 161 common differentially expressed genes (DEGs) were identified based on the RNA sequencing datasets of the two diseases. Functional analysis was performed using ontology keywords, and pathway analysis was also performed. The common DEGs were further utilized to create a protein-protein interaction (PPI) network and to identify hub genes and key modules. The datasets revealed transcription factors-gene interactions, co-regulatory networks with DEGs-miRNAs of common DEGs, and predicted possible drugs as well. The ten predicted drugs include troglitazone, estradiol, progesterone, calcitriol, genistein, dexamethasone, lucanthone, resveratrol, retinoic acid, phorbol 12-myristate 13-acetate, some of which have been investigated as potential CRC and COVID-19 therapies. Discussion: By clarifying the relationship between COVID-19 and CRC, we hope to provide novel clues and promising therapeutic drugs to treat these two illnesses.

Bioinformatics and system biology approach to identify the influences of SARS-CoV-2 on metabolic unhealthy obese patients.

Introduction: The severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) has posed a significant challenge to individuals' health. Increasing evidence shows that patients with metabolic unhealthy obesity (MUO) and COVID-19 have severer complications and higher mortality rate. However, the molecular mechanisms underlying the association between MUO and COVID-19 are poorly understood. Methods: We sought to reveal the relationship between MUO and COVID-19 using bioinformatics and systems biology analysis approaches. Here, two datasets (GSE196822 and GSE152991) were employed to extract differentially expressed genes (DEGs) to identify common hub genes, shared pathways, transcriptional regulatory networks, gene-disease relationship and candidate drugs. Results: Based on the identified 65 common DEGs, the complement-related pathways and neutrophil degranulation-related functions are found to be mainly affected. The hub genes, which included SPI1, CD163, C1QB, SIGLEC1, C1QA, ITGAM, CD14, FCGR1A, VSIG4 and C1QC, were identified. From the interaction network analysis, 65 transcription factors (TFs) were found to be the regulatory signals. Some infections, inflammation and liver diseases were found to be most coordinated with the hub genes. Importantly, Paricalcitol, 3,3',4,4',5-Pentachlorobiphenyl, PD 98059, Medroxyprogesterone acetate, Dexamethasone and Tretinoin HL60 UP have shown possibility as therapeutic agents against COVID-19 and MUO. Conclusion: This study provides new clues and references to treat both COVID-19 and MUO.

Sanwei DouKou Decoction ameliorate Alzheimer disease by increasing endogenous neural stem cells proliferation through the Wnt/ß-catenin signalling pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Sanwei DouKou decoction (SDKD) is a traditional Chinese medicine (TCM) prescription derived from the Tibetan medical book "Si Bu Yi Dian" and is clinically used for the treatment of Alzheimer's disease (AD). However, the potential mechanism of SDKD treatment for AD remains elusive. AIM OF THE STUDY: This study aims to explore the potential mechanism by which SDKD alleviates AD. MATERIALS AND METHODS: Extracts of SDKD were identified with Gas chromatograph-mass spectrometer (GC-MS). 5 × FAD mice were treated with SDKD for 8 weeks. The efficacy of SDKD against AD was evaluated by in-vivo experiments. Morris water maze and contextual fear conditioning tests were used to detect the learning and memory ability of mice. Hematoxylin-eosin staining (H&E) staining was used to observe the pathological changes of brain tissue. Immunohistochemistry was used to detect the positive expression of Nestin in hippocampus. In in-vitro experiments, the Cell Counting Kit 8 (CCK-8) technique was used to detect cell viability, the proliferation of neural stem cells was detected by immunofluorescence staining, the intracellular protein expression was detected by Western Blot. RESULTS: The results of this study suggested that SDKD may ameliorate AD. SDKD significantly shortened the escape latency of mice in the Morris water maze experiment, increased the number of times the mice crossed the target quadrant, and prolonged freezing time in the contextual fear memory experiment. SDKD also improved neuronal pathology in the hippocampus, decreased neuronal loss, and increased Nestin protein levels. Furthermore, in in-vitro experiments, SDKD could significantly increase Neural stem cells (NSCs) viability, promoted NSCs proliferation, and also effectively activated the Wnt/ß-catenin signalling pathway, increased Wnt family member 3A (Wnt3a), ß-catenin and CyclinD1 protein levels, activated the NSCs proliferation pathways in AD model mouse brain tissue. CONCLUSIONS: The present study demonstrated that sanwei doukou decoction can ameliorate AD by increasing endogenous neural stem cells proliferation through the Wnt/ß-catenin signalling pathway. Our observations justify the traditional use of SDKD for a treatment of AD in nervous system.

Biological nutrients removal performance under starvation stress: Efficacy deterioration and recovery.

Biological nutrients removal performance affected by starvation stress was investigated via the addition of pre-anoxic stage to SBR. COD removal efficiency maintained at around 90% regardless of the starvation stress. Starvation stress presented significant impact on nitrogen and phosphorus removal, with noticeable reduction of TN removal and remarkable deterioration of TP removal as prolonging the pre-anoxic time, which was mainly attributed to the integrative effect of carbon source competition, depression of denitrification and invalid P release as well as the variation of microbial community. It was notable that starvation stress exerted distinct evolution on microbial community. The improvement in relative abundance of the certain genera relating to denitrification was the main reason for the partial recovery of nitrogen removal after eliminating stress starvation. The promotion of P uptake capacity accompanied with the relief of invalid P release and the enriched DPAOs accounted for the complete recovery of phosphorus removal.