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Methyl orange (MO) is a common anionic azo dye that is harmful to the environment and biology, so it must be treated innocuously before it can be discharged. Adsorption is an effective method to remove anionic dyes. Nanotube mineral is a natural one-dimensional adsorption material, and its unique morphology and structure endow it with good adsorption capacity. Although there are many related studies, there is a lack of in-depth discussions on the influence of nanotube’s composition and structure on the adsorption of dyes and other pollutants. In this paper, two kinds of natural one-dimensional silicate minerals [halloysite nanotubes (HNTs) and chrysotile nanotubes (ChNTs)] with similar morphology but slightly different compositions and crystal structures were used as adsorbents, and MO solution was used as simulate pollutants. It is the first time to discuss in depth the influence of the composition and structure of nanotube minerals on their charge properties and the adsorption performance of methyl orange dyes. It is found that HNTs and ChNTs have different adsorption capacity due to the difference of electronegativity between Al 3+ and Mg 2+ in the crystal, so they possess negative and positive charges respectively in near-neutral solution, which leads to the adsorption capacity of MO by ChNTs with positive charges which is greater than that of HNTs.

Non-alcohol-associated fatty liver/steatohepatitis (NAFL/NASH) has become the leading cause of liver disease worldwide. NASH, an advanced form of NAFL, can be progressive and more susceptible to developing cirrhosis and hepatocellular carcinoma. Currently, lifestyle interventions are the most essential and effective strategies for preventing and controlling NAFL without the development of fibrosis. While there are still limited appropriate drugs specifically to treat NAFL/NASH, growing progress is being seen in elucidating the pathogenesis and identifying therapeutic targets. In this review, we discussed recent developments in etiology and prospective therapeutic targets, as well as pharmacological candidates in pre/clinical trials and patents, with a focus on diabetes, hepatic lipid metabolism, inflammation, and fibrosis. Importantly, growing evidence elucidates that the disruption of the gut–liver axis and microbe-derived metabolites drive the pathogenesis of NAFL/NASH. Extracellular vesicles (EVs) act as a signaling mediator, resulting in lipid accumulation, macrophage and hepatic stellate cell activation, further promoting inflammation and liver fibrosis progression during the development of NAFL/NASH. Targeting gut microbiota or EVs may serve as new strategies for the treatment of NAFL/NASH. Finally, other mechanisms, such as cell therapy and genetic approaches, also have enormous therapeutic potential. Incorporating drugs with different mechanisms and personalized medicine may improve the efficacy to better benefit patients with NAFL/NASH.

Ovarian cancer have a poor overall survival rate in patients, and late disease presentation and chemoresistance are the main factors that lead to the mortality of ovarian cancer. Cancer stem cells (CSCs), a small subpopulation of cancer cells, have been associated with resistance to chemo- and radio-therapy in cancer treatment. Hypoxia is a common characteristic of many malignant tumors, and increased HIF-1α expression predicts the poor prognosis of ovarian cancer. In this study, we reported the relationship between hypoxia and cancer stem cells-like properties in human ovarian cancer cell lines SKOV3 and HO8910, we found that hypoxia induced cancer stem cells-like properties in ovarian cancer cells. Moreover, SIRT1 was found to be the downstream target gene of HIF-1α, which was involved in the promotion of cancer stem cells-like features in ovarian cancer cells by hypoxia, and NF-κB signaling pathway was involved in hypoxia-induced SIRT1 up-regulation. Our results hinted that HIF1α and SIRT1 might serve as potential therapeutic targets for ovarian cancer.

Background The ability of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) to decrease certain microvascular events has called for the investigation of GLP-1 RAs against diabetic retinopathy (DR), but the evidence is limited. By combining data from observational and Mendelian randomization (MR) studies, we aimed to investigate whether GLP-1 RAs decrease the risk of DR. Methods We combined data from several Swedish Registers and identified patients with incident type 2 diabetes being treated with GLP-1 RAs between 2006 and 2015, and matched them to diabetic patients who did not use GLP-1 RAs as the comparisons. The Cox proportional hazards models were applied to assess the risk of DR. We further performed the summary-data-based MR (SMR) analyses based on the Genotype-Tissue Expression databases and the Genome-Wide Association Study of DR from the FinnGen consortium. Results A total of 2390 diabetic patients were treated with GLP-1 RAs and the incidence of DR was 5.97 per 1000 person-years. Compared with diabetic patients who did not use GLP-1 RAs having an incidence of 12.85 per 1000 person-years, the adjusted hazard ratio (HR) of DR was 0.42 [95% confidence interval (CI), 0.29–0.61]. Genetically-predicted GLP1R expression (the target of GLP-1 RAs) showed an inverse association with background [odds ratio (OR)=0.83, 95% CI, 0.71–0.97] and severe nonproliferative DR (OR=0.72, 95% CI, 0.53–0.98), and a non-significant association with overall (OR=0.97, 95% CI, 0.92–1.03) and proliferative DR (OR=0.98, 95% CI, 0.91–1.05). Conclusions Both observational and mendelian randomization analyses showed a significantly lower risk of DR for patients treated with GLP-1 RAs, which calls for further studies to validate these findings.

CRISPR diagnostics are powerful tools for detecting nucleic acids but are generally not deployable for the detection of clinically important proteins. Here, we report an u ltrasensitive CRISPR-based antibody detection (UCAD) assay that translates the detection of anti-SARS-CoV-2 antibodies into CRISPR-based nucleic acid detection in a homogeneous solution and is 10,000 times more sensitive than the classic immunoassays. Clinical validation using serum samples collected from the general population (n = 197), demonstrates that UCAD has 100% sensitivity and 98.5% specificity. With ultrahigh sensitivity, UCAD enables the quantitative analysis of serum anti-SARS-CoV-2 levels in vaccinated kidney transplant recipients who are shown to produce “undetectable” anti-SARS-CoV-2 using standard immunoassay. Because of the high sensitivity and simplicity, we anticipate that, upon further clinical validation against large cohorts of clinical samples, UCAD will find wide applications for clinical uses in both centralized laboratories and point-of-care settings. CRISPR diagnostics are routinely used for the detecting nucleic acids, but rarely for clinically important proteins. Here, by translating a CRISPR-based DNA test into an ultrasensitive assay for antibodies, the authors achieve antibody detection from serum samples at attomolar concentrations.

Using interpretable machine learning, we sought to define the immune microenvironment subtypes and distinctive genes in AD. ssGSEA, LASSO regression, and WGCNA algorithms were used to evaluate immune state in AD patients. To predict the fate of AD and identify distinctive genes, six machine learning algorithms were developed. The output of machine learning models was interpreted using the SHAP and LIME algorithms. For external validation, four separate GEO databases were used. We estimated the subgroups of the immunological microenvironment using unsupervised clustering. Further research was done on the variations in immunological microenvironment, enhanced functions and pathways, and therapeutic medicines between these subtypes. Finally, the expression of characteristic genes was verified using the AlzData and pan-cancer databases and RT-PCR analysis. It was determined that AD is connected to changes in the immunological microenvironment. WGCNA revealed 31 potential immune genes, of which the greenyellow and blue modules were shown to be most associated with infiltrated immune cells. In the testing set, the XGBoost algorithm had the best performance with an AUC of 0.86 and a P-R value of 0.83. Following the screening of the testing set by machine learning algorithms and the verification of independent datasets, five genes (CXCR4, PPP3R1, HSP90AB1, CXCL10, and S100A12) that were closely associated with AD pathological biomarkers and allowed for the accurate prediction of AD progression were found to be immune microenvironment-related genes. The feature gene-based nomogram may provide clinical advantages to patients. Two immune microenvironment subgroups for AD patients were identified, subtype2 was linked to a metabolic phenotype, subtype1 belonged to the immune-active kind. MK-866 and arachidonyltrifluoromethane were identified as the top treatment agents for subtypes 1 and 2, respectively. These five distinguishing genes were found to be intimately linked to the development of the disease, according to the Alzdata database, pan-cancer research, and RT-PCR analysis. The hub genes associated with the immune microenvironment that are most strongly associated with the progression of pathology in AD are CXCR4, PPP3R1, HSP90AB1, CXCL10, and S100A12. The hypothesized molecular subgroups might offer novel perceptions for individualized AD treatment.

Rheumatoid arthritis (RA) is a chronic, systemic, autoimmune disease that may lead to joint damage, deformity, and disability, if not treated effectively. Hedyotis diffusa Willd (HDW) and its main components have been widely used to treat a variety of tumors and inflammatory diseases. The present study utilized a network pharmacology approach, microarray data analysis and molecular docking to predict the key active ingredients and mechanisms of HDW against RA. Eleven active ingredients in HDW and 180 potential anti-RA targets were identified. The ingredients-targets-RA network showed that stigmasterol, beta-sitosterol, quercetin, kaempferol, and 2-methoxy-3-methyl-9,10-anthraquinone were key components for RA treatment. KEGG pathway results revealed that the 180 potential targets were inflammatory-related pathways with predominant enrichment of the AGE-RAGE, TNF, IL17, and PI3K-Akt signaling pathways. Screened through the PPI network and with Cytoscape software, RELA, TNF, IL6, TP53, MAPK1, AKT1, IL10, and ESR1 were identified as the hub targets in the HDW for RA treatment. Molecular docking was used to identify the binding of 5 key components and the 8 related-RA hub targets. Moreover, the results of network pharmacology were verified by vitro experiments. HDW inhibits cell proliferation in MH7A cells in a dose and time-dependent manner. RT-qPCR and WB results suggest that HDW may affect hub targets through PI3K/AKT signaling pathway, thereby exerting anti-RA effect. This study provides evidence for a clinical effect of HDW on RA and a research basis for further investigation into the active ingredients and mechanisms of HDW against RA.

This paper takes 2,876 papers published in Scientometrics as the sample, and the time span of these papers is nearly ten years. We have studied the intellectual structure and development trend of Scientometrics in two periods within five years, and made an empirical exploration and comparison of two methods of author bibliographic coupling methods—first author bibliographic coupling (FABCA) and all authors bibliographic coupling (AABCA). The results show that the intellectual structure of Scientometrics in the two periods are relatively stable, but the intellectual structure of the latter period is clearer, and the correlation and integration of the research topics is stronger than that of the previous period. There is a strong correlation between AABCA and FABCA, but each has its own characteristics, and there are subtle differences between them. The similarity between them can be found by authors rank correlation analysis, the cosine similarity analysis, and discipline research topic detection. However, the factor models fitting analysis, research topics detection and evolution show that there are differences between them. AABCA is sensitive to the discovery of research hotspots, and can detect more research topics than FABCA. While FABCA has advantages over AABCA in reflecting the frontier and innovation of the discipline. It can provide more information. Therefore, FABCA and AABCA have their own characteristics and cannot be replaced. The combination of the two methods is a powerful and effective research method to explore the intellectual structure and evolution trend of the discipline.

Heavy fine particulate matter (PM2.5) air pollution occurs frequently in China. However, epidemiological research on the association between short-term exposure to PM2.5 pollution and respiratory disease morbidity is still limited. This study aimed to explore the association between PM2.5 pollution and hospital emergency room visits (ERV) for total and cause-specific respiratory diseases in urban areas in Beijing. Daily counts of respiratory ERV from Jan 1 to Dec 31, 2013, were obtained from ten general hospitals located in urban areas in Beijing. Concurrently, data on PM2.5 were collected from the Beijing Environmental Protection Bureau, including 17 ambient air quality monitoring stations. A generalized-additive model was used to explore the respiratory effects of PM2.5, after controlling for confounding variables. Subgroup analyses were also conducted by age and gender. A total of 92,464 respiratory emergency visits were recorded during the study period. The mean daily PM2.5 concentration was 102.1±73.6 μg/m3. Every 10 μg/m3 increase in PM2.5 concentration at lag0 was associated with an increase in ERV, as follows: 0.23% for total respiratory disease (95% confidence interval [CI]: 0.11%-0.34%), 0.19% for upper respiratory tract infection (URTI) (95%CI: 0.04%-0.35%), 0.34% for lower respiratory tract infection (LRTI) (95%CI: 0.14%-0.53%) and 1.46% for acute exacerbation of chronic obstructive pulmonary disease (AECOPD) (95%CI: 0.13%-2.79%). The strongest association was identified between AECOPD and PM2.5 concentration at lag0-3 (3.15%, 95%CI: 1.39%-4.91%). The estimated effects were robust after adjusting for SO2, O3, CO and NO2. Females and people 60 years of age and older demonstrated a higher risk of respiratory disease after PM2.5 exposure. PM2.5 was significantly associated with respiratory ERV, particularly for URTI, LRTI and AECOPD in Beijing. The susceptibility to PM2.5 pollution varied by gender and age.

Background Microbial engineering aims to enhance the ability of bacteria to produce valuable products, including vitamin B 6 for various applications. Numerous microorganisms naturally produce vitamin B 6 , yet the metabolic pathways involved are rigorously controlled. This regulation by the accumulation of vitamin B 6 poses a challenge in constructing an efficient cell factory. Results In this study, we conducted transcriptome and metabolome analyses to investigate the effects of the accumulation of pyridoxine, which is the major commercial form of vitamin B 6 , on cellular processes in Escherichia coli . Our omics analysis revealed associations between pyridoxine and amino acids, as well as the tricarboxylic acid (TCA) cycle. Based on these findings, we identified potential targets for fermentation optimization, including succinate, amino acids, and the carbon-to-nitrogen (C/N) ratio. Through targeted modifications, we achieved pyridoxine titers of approximately 514 mg/L in shake flasks and 1.95 g/L in fed-batch fermentation. Conclusion Our results provide insights into pyridoxine biosynthesis within the cellular metabolic network for the first time. Our comprehensive analysis revealed that the fermentation process resulted in a remarkable final yield of 1.95 g/L pyridoxine, the highest reported yield to date. This work lays a foundation for the green industrial production of vitamin B 6 in the future.