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N6-methyladenosine (m6A) is the most abundant chemical modification in eukaryotic cells. It is a post-transcriptional modification of mRNA, a dynamic reversible process catalyzed by methyltransferase, demethylase, and binding proteins. Ferroptosis, a unique iron-dependent cell death, is regulated by various cell metabolic events, including many disease-related signaling pathways. And different ferroptosis inducers or inhibitors have been identified that can induce or inhibit the onset of ferroptosis through various targets and mechanisms. They have potential clinical value in the treatment of diverse diseases. Until now, it has been shown that in several cancer diseases m6A can be involved in the regulation of ferroptosis, which can impact subsequent treatment. This paper focuses on the concept, function, and biological role of m6A methylation modification and the interaction between m6A and ferroptosis, to provide new therapeutic strategies for treating malignant diseases and protecting the organism by targeting m6A to regulate ferroptosis.

This work was devised to discuss the effect of AIM2 on the immunosuppression of LUAD tumors, as well as its molecular mechanism. An allograft mouse model was built. Mouse macrophages were isolated and collected. The infiltration level of Mø and expression of M1 Mø, M2 Mø markers, and PD-L1 were assayed by IHC and flow cytometry. Expression levels of M1 Mø and M2 Mø marker genes and PD-L1 were detected by qPCR. The expression of proteins linked with JAK/STAT3 was tested by western blot. CD8+T cells and NK cells were activated in vitro and co-cultured with mouse macrophages, and their cytotoxicity was detected by LDH method. The proportion of CD206+PD-L1+ cells and the activation and proliferation of CD8+T cells were assayed by flow cytometry. Multicolor immunofluorescence was utilized to assay the co-localization of proteins. AIM2 demonstrated a high expression in LUAD, exhibiting a conspicuous positive correlation with the expression of the M2 Mø markers as well as PD-L1. Expression of M1 markers was upregulated after knockdown of AIM2, while M2 markers expression and PD-L1 were downregulated, and the colocalization of proteins linked with PD-L1 and M2 Mø was decreased. The infiltration and cytotoxicity of CD8+T cells and NK cells increased after silencing AIM2. After the knockdown of AIM2, which was enriched in the JAK/STAT3 pathway, the phosphorylation levels of JAK1, JAK2, and STAT3 were reduced, the immune infiltration level of CD8+T cells increased, and the co-localization level of PD-L1 and PD-1 dropped. The activity and proliferation level of CD8+T cells were increased with the reduced PD-1 expression. AIM2 fosters M2 Mø polarization and PD-L1 expression via the JAK/STAT3 pathway. Moreover, AIM2 promotes the immune escape of LUAD via the PD-1/PD-L1 axis. Our work may blaze a trail for the clinical treatment of LUAD.

Abstract Background Non-small cell lung cancer (NSCLC) is the most common lung cancer with high mortality across the world, but it is challenging to develop an effective therapy for NSCLC. Celastrol is a natural bioactive compound, which has been found to possess potential antitumor activity. However, the underlying molecular mechanisms of celastrol activity in NSCLC remain elusive. Methods Cellular function assays were performed to study the suppressive role of celastrol in human NSCLC cells (H460, PC-9, and H520) and human bronchial epithelial cells BEAS-2B. Cell apoptosis levels were analyzed by flow cytometry, Hoechst 33342, caspase-3 activity analysis, and western blot analysis. Intracellular reactive oxygen species (ROS) were analyzed by flow cytometry and fluorescence microscope. Expression levels of endoplasmic reticulum (ER) stress-related proteins and phosphorylated signal transducer and activator of transcription 3 (P-STAT3) were identified via western blot analysis. A heterograft model in nude mice was employed to evaluate the effect of celastrol in vivo. Results Celastrol suppressed the growth, proliferation, and metastasis of NSCLC cells. Celastrol significantly increased the level of intracellular ROS; thus, triggering the activation of the ER stress pathway and inhibition of the P-STAT3 pathway, and eventually leading to cell apoptosis, and the effects were reversed by the pre-treatment with N-Acetyl-l-cysteine (NAC). Celastrol also suppressed tumor growth in vivo. Conclusion The outcomes revealed that celastrol plays a potent suppressive role in NSCLC in vitro and in vivo. Celastrol induces apoptosis via causing mitochondrial ROS accumulation to suppress the STAT3 pathway. Celastrol may have potential application prospects in the therapy of NSCLC.

This study is devoted to proposing a useful intelligent prediction model to distinguish the severity of COVID-19, to provide a more fair and reasonable reference for assisting clinical diagnostic decision-making. Based on patients' necessary information, pre-existing diseases, symptoms, immune indexes, and complications, this article proposes a prediction model using the Harris hawks optimization (HHO) to optimize the Fuzzy K-nearest neighbor (FKNN), which is called HHO-FKNN. This model is utilized to distinguish the severity of COVID-19. In HHO-FKNN, the purpose of introducing HHO is to optimize the FKNN's optimal parameters and feature subsets simultaneously. Also, based on actual COVID-19 data, we conducted a comparative experiment between HHO-FKNN and several well-known machine learning algorithms, which result shows that not only the proposed HHO-FKNN can obtain better classification performance and higher stability on the four indexes but also screen out the key features that distinguish severe COVID-19 from mild COVID-19. Therefore, we can conclude that the proposed HHO-FKNN model is expected to become a useful tool for COVID-19 prediction.

This paper has proposed an effective intelligent prediction model that can well discriminate and specify the severity of Coronavirus Disease 2019 (COVID-19) infection in clinical diagnosis and provide a criterion for clinicians to weigh scientific and rational medical decision-making. With indicators as the age and gender of the patients and 26 blood routine indexes, a severity prediction framework for COVID-19 is proposed based on machine learning techniques. The framework consists mainly of a random forest and a support vector machine (SVM) model optimized by a slime mould algorithm (SMA). When the random forest was used to identify the key factors, SMA was employed to train an optimal SVM model. Based on the COVID-19 data, comparative experiments were conducted between RF-SMA-SVM and several well-known machine learning algorithms performed. The results indicate that the proposed RF-SMA-SVM not only achieves better classification performance and higher stability on four metrics, but also screens out the main factors that distinguish severe COVID-19 patients from non-severe ones. Therefore, there is a conclusion that the RF-SMA-SVM model can provide an effective auxiliary diagnosis scheme for the clinical diagnosis of COVID-19 infection.

Abstract Background Rhein is a lipophilic anthraquinone extensively found in medicinal herbs. Emerging evidence suggests that rhein has significant antitumor effects, supporting its potential use as an antitumor agent. The IL6/STAT3 signaling pathway has been suggested as an attractive target for the discovery of novel cancer therapeutics. Methods The human pancreatic cancer cell lines AsPC-1, Patu8988T, BxPC-3 and PANC-1, and immunodeficient mice were chosen as models to study the effects of rhein. The potent antiproliferative and proapoptotic effects of rhein were examined by cell viability, cellular morphology, apoptosis and colony formation assays. The STAT3 luciferase report assay, immunostaining analysis and Western blot analysis revealed the inhibition of the IL6/STAT3 signaling axis. Results Apoptosis was induced by adjunctive use of rhein with epidermal growth factor receptor (EGFR) inhibitors in pancreatic cancer cells as verified by cell apoptosis analysis and changes in the expression level of apoptotic/anti-apoptotic proteins BCL-2, BAX, Caspase 3 and Cl-PARP. Suppression of the phosphorylation of STAT3 and EGFR were also observed as a result of the treatment with a combination of rhein and EGFR inhibitors. Most interestingly, it was found that rhein considerably sensitized cells to erlotinib, thus suppressing tumor growth in PANC-1 and BxPC-3 xenograft models. The in vivo anti-tumor effect was associated with increased apoptosis and combined inhibition of the STAT3 and EGFR pathways in tumor remnants. Conclusions Rhein sensitizes human pancreatic cancer cells to EGFR inhibitors through inhibition of STAT3. Taken together, the results indicate that rhein offers a novel blueprint for pancreatic cancer therapy, particularly when combined with EGFR inhibitors.

Fibroblast growth factor receptor 4 (FGFR4) is a tyrosine kinase receptor that is a member of the fibroblast growth factor receptor family and is stimulated by highly regulated ligand binding. Excessive expression of the receptor and its ligand, especially FGF19, occurs in many types of cancer. Abnormal FGFR4 production explains these cancer formations, and therefore, this receptor has emerged as a potential target for inhibiting cancer development. This review discusses the diverse mechanisms of oncogenic activation of FGFR4 and highlights some currently available inhibitors targeting FGFR4.

Background: It has been reported that a fraction of recovered coronavirus disease 2019(COVID-19) patients have retested positive for SARS-CoV-2. Clinical characteristics and risk factors for retesting positive have not been studied extensively. Methods: In this retrospective, single-center cohort study, we included adult patients (≥ 18 years old) diagnosed as COVID-19 in Affiliated Yueqing Hospital, Wenzhou Medical University, Zhejiang, China. All the patients were discharged before March 31, 2020, and were re-tested for SARS-CoV-2 RNA by real-time reverse-transcriptase polymerase-chain-reaction (RT-PCR) after meeting the discharge criteria. We retrospectively analyzed this cohort of 117 discharged patients and analyzed the differences between retest positive and negative patients in terms of demographics, clinical characteristics, laboratory findings, chest computed tomography (CT) features and treatment procedures. Findings: Compared with the negative group, the positive group had a higher proportion of patients with comorbidities (Odds Ratio(OR) =2·12, 95% Confidence Interval(CI) 0·48–9·46; p = 0·029), longer hospital stay (OR=1·21, 95% CI 1·07–1·36; p = 0·008), a higher proportion of patients with lymphocytopenia (p = 0·036), a higher proportion of antibiotics treatment (p = 0·008) and glucocorticoids treatment (p = 0·003). Multivariable regression showed increasing odds of positive SARS-CoV-2 retest after discharge associated with longer hospital stay (OR=1·22, 95% CI 1·08–1·38; p = 0·001), and lymphocytopenia (OR=7·74, 95% CI 1·70–35·21; p = 0·008) on admission. Interpretation: Patients with COVID-19 who met discharge criteria could still test positive for SARS-CoV-2 RNA. Longer hospital stay and lymphopenia could be potential risk factors for positive SARS-CoV-2 retest in COVID-19 patients after hospital discharge. Funding: Natural Science Foundation of Zhejiang Province, Medical Scientific Research Fund of Zhejiang Province, Wenzhou science and technology project

Spike-related traits such as spike length (Sl), fertile spikelet number (Fsn), sterile spikelet number (Ssn), grain number per spike (Gns), and thousand-kernel weight (Tkw) are important factors influencing wheat yield. However, reliably stable markers that can be used for molecular breeding in different environments have not yet been identified. In this study, a double haploid (DH) population was used for quantitative trait locus (QTL) mapping of five spike-related traits under four different nitrogen (N) supply dates in two locations and years. Seventy additive QTLs with phenotypic variation ranging from 4.12 to 34.74% and 10 major epistatic QTLs were identified. Eight important chromosomal regions on five chromosomes (1B, 2B, 2D, 5D, and 6A) were found. Sixteen stable QTLs were detected for which N application had little effect. Among those stable QTLs, QSl.sdau-2D-1, and QSl.sdau-2D-2, with phenotypic variation explained (PVE) of 10.4 and 24.2%, respectively, were flanked by markers Xwmc112 and Xcfd53 in the same order. The QTLs QSsn.sdau-2B-1, QFsn.sdau-2B-1, and QGns.sdau-2B, with PVE ranging from 4.37 to 28.43%, collocated in the Xwmc179-Xbarc373 marker interval. The consistent kernel wheat QTL (QTkw.sdau-6A) on the long arm of chromosome 6A, flanked by SSR markers Xbarc1055 and Xwmc553, showed PVE of 5.87–15.18%. Among these stable QTLs, the two flanking markers Xwmc112 and Xcfd53 have been validated using different varieties and populations for selecting Sl. Therefore, these results will be of great value for marker-assisted selection (MAS) in breeding programs and will accelerate the understanding of the genetic relationships among spike-related traits at the molecular level.

The driving effect of global climate change (CC) on the ecohydrological process was quantitatively evaluated. Based on Geographic Information System technology, a Soil and Water Assessment Tool model suitable for watershed hydrological simulation was constructed to study the impact of climate and land-use change on runoff in the Second Songhua River (SSR) basin. Within the base period (1965–2010), the annual average temperature (AAT) of the SSR basin is 4.2 °C. Under the CC scenario representing concentration pathway (RCP) 4.5, the AAT of the watershed increased to 5.4 °C between 2020 and 2049. Under the CC scenarios of RCP 8.5 and RCP 4.5, the temperature in the watershed increased by 1.1 and 0.2 °C in June, respectively. The research results indicate that (1) there is a positive correlation between runoff and precipitation in the SSR watershed, and a negative correlation with temperature; (2) when the precipitation remains unchanged, the temperature increases by 1 °C and the runoff decreases by 7.2%; and (3) when the temperature remains constant, for every 10% increase in precipitation, the runoff increases by 30.5%. This study provides the scientific basis for water resource planning and sustainable development in the Northeast region and has important practical significance. HIGHLIGHTS Analyze the historical change characteristics of hydrometeorological elements.; Establish the Soil and Water Assessment Tool model suitable for watershed hydrological simulation.; Study the changes of hydrological elements in the basin under different land-use scenarios.;

In view of the importance of alkaline phosphatase (ALP) as a clinical diagnostic indicator of related diseases and physiological research, developing a reliable measurement assay with high efficiency and accuracy is of tremendous value. In this study, bifunctional carbon dots (CDs) with peroxidase-like and fluorescence properties were synthesized through a readily available solvothermal method. Peroxidase-like CDs could oxidaze colorless 1,4-phenylenediamine (PPD) to the colored oxidized product (oxPPD), which quenched the CDs' fluorescence. A multi-signal sensing system was strategically fabricated for detecting ALP for the first time, taking advantage of CDs' remarkable peroxidase-mimic activity and fluorescence properties. The limits of detection (LOD) and linear ranges for ALP was 0.034 and 0.027 U/L, 0.1 to 1.8 and 0.05 to 1.8 U/L by the colorimetric and fluorescent method, respectively. Besides, the results of hydrogel devices processed by smartphones also exhibited satisfactory results. The multi-signal strategy developed in this study provides a new impetus for designing different biosensors with bifunctional nanomaterials.

Hepatocellular carcinoma (HCC) is one of the most commonly diagnosed and malignant cancers worldwide. Conventional therapy strategies may not completely eradicate the tumor and may cause side effects during treatment. Nano-catalytic therapy, as a novel strategy, has attracted a great deal of attention. This study aimed to synthesize a multifunctional magneto-gold nanozyme AuNC@Fe3O4 and evaluate its anti-cancer potential in HepG2 cells in vitro. The characteristics of AuNC@Fe3O4 were assessed using a transmission electron microscope, dynamic light scattering, and energy-dispersive X-ray. The photothermal performance and peroxidase (POD)-like activity of AuNC@Fe3O4 were detected, using thermal camera and ultraviolet-visible spectrophotometer, respectively. The anti-cancer potential of AuNC@Fe3O4 was examined using cell counting kit-8, live/dead cell staining, and apoptosis analysis. Further research on HepG2 cells included the detection of intracellular reactive oxygen species (ROS) and lysosomal impairment. We observed that the AuNC@Fe3O4 had a small size, good photothermal conversion efficiency and high POD-like activity, and also inhibited cell proliferation and enhanced cell apoptotic ability in HepG2 cells. Furthermore, the AuNC@Fe3O4 enhanced ROS production and lysosomal impairment via the synergistic effect of photothermal and nano-catalytic therapies, which induced cell death or apoptosis. Thus, the magneto-gold nanozyme AuNC@Fe3O4 may offer a potential anti-cancer strategy for HCC.

This study investigates the spatial-temporal evolution and the interconnectedness of land use/cover change (LUCC) and ecosystem service value (ESV). Such analysis can offer theoretical guidance and support decision-making for sustainable land resource development and ecological preservation in ecologically vulnerable cities within the Loess Plateau-Maowusu Desert transition zone. Utilizing Landsat data spanning 2000–2020, the paper examines the synergistic relationship between ESV and land use intensity in Shenmu City through bivariate spatial autocorrelation and the coupled coordination degree (CCD) model. Our findings indicate that the area of construction land in Shenmu City experienced the most significant change between 2000 and 2020, with a dynamism rate of 76.8%. This shift resulted in a decrease in the total ESV, from RMB 10.059 billion in 2000 to RMB 9.906 billion in 2020. The bivariate spatial autocorrelation analysis reveals a significant positive spatial correlation between ESV and land use intensity, while the CCD levels for both demonstrate a fluctuating yet overall upward trend over the 20-year period. The paper uncovers the spatial-temporal evolution of LUCC and ESV in Shenmu City along with their interconnected dynamics. The research outcomes can contribute valuable insights for reinforcing land resource utilization and promoting sustainable regional development within cities in the Loess Plateau-Maowusu Desert transition zone.

Alkaline phosphatase (ALP) is a crucial marker for the clinical analysis and detection of many diseases. In this study, an accurate signal amplification strategy was proposed for the sensing and quantification of alkaline phosphatase using poly (3, 4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS), gold nanoparticles (AuNPs), and Ag+. Signal amplification was achieved by the modification of PEDOT:PSS and AuNPs on glassy carbon electrodes. Atomic force microscopy was performed to characterize the morphology of the modified nanomaterials. To detect ALP, 1-naphthyl phosphate (1-NP) was used as the substrate, and alkaline phosphatase catalyzed 1-NP into 1-naphthol (1-N), which resulted in the reduction of Ag+ to Ag0 on the surface of the modified electrode (AuNPs/PEDOT:PSS/GCE). The deposition of Ag drastically enhanced the detection signal. Differential pulse voltammograms of 1-N, which is the enzymatic product from the ALP reaction with 1-NP, were recorded. In the linear range of 0.1–120 U L−1, a quantitative analysis of alkaline phosphatase was achieved, with high sensitivity and a low detection limit of 0.03 U L−1. Stable, selective, and reproducible electrochemical sensors were designed. Moreover, the proposed electrochemical sensor exhibited a prominent sensing performance in the spiked diluted human serum. Thus, the sensor can be used in numerous applications in alkaline phosphatase or other analyte detection.

To make full use of natural waste, a novel Mg-Al mixed oxide adsorbent was synthesized by the dip-calcination method using the fluff of the chinar tree (FCT) and an Mg(II) and Al(III) chloride solution as raw materials. The adsorbents were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared (FT-IR) spectroscopy, and X-ray photoelectron spectroscopy (XPS). The effects of the Mg/Al molar ratio and calcination temperature on the performance of the novel Mg-Al mixed oxide adsorbent were investigated. The optimized Mg-Al mixed oxide adsorbent had a Langmuir adsorption capacity of 53 mg/g. This adsorption capacity was higher than that of the separate Mg oxide and Al oxide. The synergy between Mg and Al is beneficial to the adsorption performance of the material. The fluoride adsorption capacity of the optimized Mg-Al mixed oxide adsorbent is only slightly affected by ions such as Cl−, NO3−, SO42−, Na+, and K+ and is excellent for use in recycling and real water. The hydroxyl groups on the surface of the Mg-Al mixed oxide adsorbent play a key role in the adsorption of fluorine. The as-obtained novel Mg-Al mixed oxide adsorbent is an efficient and environmentally friendly agent for fluoride removal from drinking water.