Search

Abstract Emerged evidence has indicated that immunosuppression is involved in the occurrence and development of sepsis. To provide clinical practice recommendations on the immune function in sepsis, an expert consensus focusing on the monitoring and treatment of sepsis-induced immunosuppression was developed. Literature related to the immune monitoring and treatment of sepsis were retrieved from PubMed, Web of Science, and Chinese National Knowledge Infrastructure to design items and expert opinions were collected through an online questionnaire. Then, the Delphi method was used to form consensus opinions, and RAND appropriateness method was developed to provide consistency evaluation and recommendation levels for consensus opinions. This consensus achieved satisfactory results through two rounds of questionnaire survey, with 2 statements rated as perfect consistency, 13 as very good consistency, and 9 as good consistency. After summarizing the results, a total of 14 strong recommended opinions, 8 weak recommended opinions and 2 non-recommended opinions were produced. Finally, a face-to-face discussion of the consensus opinions was performed through an online meeting, and all judges unanimously agreed on the content of this consensus. In summary, this expert consensus provides a preliminary guidance for the monitoring and treatment of immunosuppression in patients with sepsis.

ObjectiveTo explore the feasibility of breeding cleaning degree mice with micro-barrier cages in conventional environmental facilities.MethodsClean-grade mice were housed and maintained in positive-pressure microbarrier cages in a general environment, during which third-party sampling of the microbial status of the animals in the microbarrier was performed on a quarterly frequency.ResultsFrom June 2020 to July 2022, no microorganisms that must be excluded by the national standard for cleaning degree mice have been detected in two consecutive years.ConclusionMicro-barrier cages can be used to raise and maintain cleaning grade mice in conventional environmental facilities.

In this investigation, a novel Fe3O4-enhanced biochar derived from winter melon (Fe3O4@WBC) was synthesised by an innovative ethylene glycol reduction and thermal polymerisation approach for efficiently eliminating U(VI) from contaminated environments. The factors influencing uranium(VI) adsorption by Fe3O4@WBC, including pH, adsorbent dosage, time, temperature, and initial U(VI) concentration were explored. The material's performance was characterised, and the underlying mechanism of U(VI) removal was analysed using various techniques. The results demonstrated that Fe3O4@WBC effectively removed U(VI), achieving a maximum adsorption capacity of 199.84 mg g−1 at a pH of 5.0. These findings provided a theoretical basis for the treatment of wastewater contaminated with U(VI). [ABSTRACT FROM AUTHOR]

Cancer treatments always face challenging problems, particularly drug resistance due to tumor cell heterogeneity. The existing datasets include the relationship between gene expression and drug sensitivities; however, the majority are based on tissue-level studies. Study drugs at the single-cell level are perspective to overcome minimal residual disease caused by subclonal resistant cancer cells retained after initial curative therapy. Fortunately, machine learning techniques can help us understand how different types of cells respond to different cancer drugs from the perspective of single-cell gene expression. Good modeling using single-cell data and drug response information will not only improve machine learning for cell–drug outcome prediction but also facilitate the discovery of drugs for specific cancer subgroups and specific cancer treatments. In this paper, we review machine learning and deep learning approaches in drug research. By analyzing the application of these methods on cancer cell lines and single-cell data and comparing the technical gap between single-cell sequencing data analysis and single-cell drug sensitivity analysis, we hope to explore the trends and potential of drug research at the single-cell data level and provide more inspiration for drug research at the single-cell level. We anticipate that this review will stimulate the innovative use of machine learning methods to address new challenges in precision medicine more broadly.

ObjectiveAs a common yet intractable complication of severe sepsis, acute respiratory distress syndrome (ARDS) is closely associated with poor clinical outcomes and elevated medical expenses. The aim of the current study is to generate a model combining transcriptional biomarkers and clinical parameters to alarm the development of ARDS in septic patients.MethodsGene expression profile (GSE66890) was downloaded from the Gene Expression Omnibus database and clinical data were extracted. Differentially expressed genes (DEGs) from whole blood leukocytes were identified between patients with sepsis alone and septic patients who develop ARDS. ARDS prediction model was constructed using backward stepwise regression and Akaike Information Criterion (AIC). Meanwhile, a nomogram based on this model was established, with subsequent internal validation.ResultsA total of 57 severe septic patients were enrolled in this study, and 28 (49.1%) developed ARDS. Based on the differential expression analysis, six DEGs (BPI, OLFM4, LCN2, CD24, MMP8 and MME) were screened. According to the outcome prediction model, six valuable risk factors (direct lung injury, shock, tumor, BPI, MME and MMP8) were incorporated into a nomogram, which was used to predict the onset of ARDS in septic patients. The calibration curves of the nomogram showed good consistency between the probabilities and observed values. The decision curve analysis also revealed the potential clinical usefulness of the nomogram. The area under the receiver operating characteristic (AUROC) for the prediction of ARDS occurrence in septic patients by the nomogram was 0.86 (95% CI = 0.767-0.952). A sensitivity analysis showed that the AUROC for the prediction of ARDS development in septic patients without direct lung injury was 0.967 (95% CI = 0.896-1.0).ConclusionsThe nomogram based on transcriptional biomarkers and clinical parameters showed a good performance for the prediction of ARDS occurrence in septic patients.

Glioma-associated macrophage/microglia (GAM) represents a key player in shaping a unique glioma ecosystem to facilitate tumor progression and therapeutic resistance. Numerous studies have been published concerning GAM, but no relevant bibliometric study has been performed yet. Our bibliometric study aimed to comprehensively summarize and analyze the global scientific output, research hotspots, and trendy topics of publications on GAM over time. Data on publications on GAM were collected using the Web of Science (WoS). The search date was 16 January 2022, and the publications were collected from 2002 to 2021. Totally, 1,224 articles and reviews were incorporated and analyzed in the current study. It showed that the annual publications concerning GAM kept increasing over the past 20 years. The United States had the largest number of publications and total citations. Holland, Kettenmann, and Gutmann were the top three authors in terms of citation frequency. Neuro-oncology represented the most influential journal in GAM studies, with the highest H-index, total citations, and publication numbers. The paper published by Hambardzumyan in 2016 had the highest local citations. Additionally, the analysis of keywords implied that “prognosis,” “tumor microenvironment,” and “immunotherapy” might become research hotspots. Furthermore, trendy topics in GAM studies suggested that “immune infiltration,” “immune microenvironment,” “bioinformatics,” “prognosis,” and “immunotherapy” deserved additional attention. In conclusion, this bibliometric study comprehensively analyzed the publication trend of GAM studies for the past 20 years, in which the research hotspots and trendy topics were also uncovered. This information offered scholars critical references for conducting in-depth studies on GAM in the future.

Abstract Tumor necrosis factor (TNF)-α-induced protein 8-like 2 (TIPE2) is a newly discovered negative immunoregulatory protein that is involved in various cellular immune responses to infections. However, the underlying mechanism by which TIPE2 affects the immune function of dendritic cells (DCs) is not yet understood. This study aimed to determine the correlations among DCs TIPE2 expression, autophagic activity and immune function in the context of sepsis. In addition, the signaling pathway by which TIPE2 regulates autophagy in DCs was investigated. We reported for the first time that TIPE2 overexpression (knock-in, KI) exerted an inhibitory effect on autophagy in DCs and markedly suppressed the immune function of DCs upon septic challenge both in vitro and in vivo. In addition, TIPE2 knockout (KO) in DCs significantly enhanced autophagy and improved the immune response of DCs in sepsis. Of note, we found that the transforming growth factor-β (TGF-β)-activated kinase-1 (TAK1)/c-Jun N-terminal kinase (JNK) pathway was inhibited by TIPE2 in DCs, resulting in downregulated autophagic activity. Collectively, these results suggest that TIPE2 can suppress the autophagic activity of DCs by inhibiting the TAK1/JNK signaling pathway and further negatively regulate the immune function of DCs in the development of septic complications.

Abstract Ferroptosis is a nonapoptotic form of programmed cell death triggered by the accumulation of reactive oxygen species (ROS) depended on iron overload. Although most investigations focus on the relationship between ferroptosis and cancer, neurodegenerative diseases, and ischemia/reperfusion injury, research on ferroptosis induced by immune-related inflammatory diseases, especially sepsis, is scarce. Sestrin2 (Sesn2), a highly evolutionary and stress-responsive protein, is critically involved in defense against oxidative stress challenges. Upregulated expression of Sesn2 has been observed in preliminary experiments to have an antioxidative function in the context of an inflammatory response. Nevertheless, the underlying function of Sesn2 in inflammation-mediated ferroptosis in the immune system remains uncertain. The current study aimed to demonstrate the protective effect of Sesn2 on ferroptosis and even correlations with ferroptosis and the functions of ferroptotic-dendritic cells (DCs) stimulated with lipopolysaccharide (LPS). The mechanism underlying DCs protection from LPS-induced ferroptosis by Sesn2 was further explored in this study. We found that the immune response of DCs assessed by co-stimulatory phenotypes was gradually enhanced at the peak time of 12 h upon 1 μg/ml LPS stimulation while ferroptosis in DCs treated with LPS at 24 h was significantly detected. LPS-induced ferroptosis showed a suppressive impact on DCs in phenotypic maturation, which was conversely relieved by the ferroptotic inhibitor. Compared with wild-type (WT) mice, DCs in genetic defective mice of Sesn2 (Sesn2−/−) exhibited exacerbated ferroptosis. Furthermore, the protective effect of Sesn2 on ferroptosis was noticed to be associated with the ATF4-CHOP-CHAC1 pathway, eventually exacerbating ferroptosis by degrading of glutathione. These results indicate that Sesn2 can suppress the ferroptosis of DCs in sepsis by downregulating the ATF4-CHOP-CHAC1 signaling pathway, and it might play an antioxidative role.

BackgroundSepsis is considered an intractable dysfunction that results from the disordered host immune response to uncontrolled infection. Even though the precise mechanism of sepsis remains unclear, scientific advances have highlighted the key role of various programmed cell death processes in the pathophysiology of sepsis. The current study aims to explore the worldwide research trend on programmed cell death in the setting of sepsis and assesses the achievements of publications from various countries, institutions, journals, and authors globally.Material and methodsAssociated publications during 2002–2022 with the topical subject of sepsis and programmed cell death were extracted from the Web of Science. VOSviewer was utilized to evaluate and map the published trend in the relevant fields.ResultsAll 2,037 relevant manuscripts with a total citation of 71,575 times were screened out by the end of 1 January 2022. China accounted for the largest number of publications (45.07%) and was accompanied by corporate citations (11,037) and H-index (48), which ranked second globally. The United States has been ranked first place with the highest citations (30,775) and H-index (88), despite a low publication number (29.95%), which was subsequent to China. The journal Shock accounted for the largest number of publications in this area. R. S. Hotchkiss, affiliated with Washington University, was considered to have published the most papers in the relevant fields (57) and achieved the highest citation frequencies (9,523). The primary keywords on the topic of programmed cell death in sepsis remarkably focused on “inflammation” “immunosuppression”, and “oxidative stress”, which were recognized as the core mechanisms of sepsis, eventually attributing to programmed cell death. The involved research on programmed cell death induced by immune dysregulation of sepsis was undoubtedly the hotspot in the pertinent areas.ConclusionsThe United States has been academically outstanding in sepsis-related research. There appears to be an incompatible performance between publications and quantity with China. Frontier advances may be consulted in the journal Shock. The leading-edge research on the scope of programmed cell death in sepsis should preferably focus on immune dissonance-related studies in the future.

The identification of special protein or RNA molecules via computational methods is of great importance in understanding their biological functions and developing new treatments for diseases [...]

Electrical discharge machining (EDM) is one of the important machining processes to produce mold components. When using the EDM process, surface quality, processing time, accuracy, and electrode cost must be considered. The electrode wear is the main factor that causes error on the geometric accuracy, especially the workpiece corner. Therefore, this study proposes a novel electrode design to improve the geometric accuracy for the EDM process. Firstly, the effect of discharge current, electrode diameter, and depth of cut on the electrode wear and workpiece corner were investigated. Multiple regression and analysis of variant were used to analyze the experiment data. The electrode end-face design with compensation rule and algorithm was established based on the data analysis and error value. Furthermore, a compensated electrode end-face design system with human machine interface, which has a procedure guiding function, was developed. The system can design the electrode end-face for minimizing workpiece corner error and improve geometric accuracy. Finally, cutting experiments were conducted to verify the proposed method, and the results show that the proposed method can effectively enhance the geometric accuracy by around 22~37%.

Abstract Background The clinical efficiency of routine oxygen therapy is uncertain in patients with acute heart failure (AHF) who do not have hypoxemia. The aim of this study was to investigate the association between oxygen therapy and clinical outcomes in normoxemic patients hospitalized with AHF using real-world data. Methods Normoxemic patients diagnosed with AHF on ICU admission from the electronic ICU (eICU) Collaborative Research Database were included in the current study, in which the study population was divided into the oxygen therapy group and the ambient-air group. Propensity score matching (PSM) was applied to create a balanced covariate distribution between patients receiving supplemental oxygen and those exposed to ambient air. Linear regression and logistic regression models were performed to assess the associations between oxygen therapy and length of stay (LOS), and all-cause in-hospital as well as ICU mortality rates, respectively. A series of sensitivity and subgroup analyses were conducted to further validate the robustness of our findings. Results A total of 2922 normoxemic patients with AHF were finally included in the analysis. Overall, 42.1% (1230/2922) patients were exposed to oxygen therapy, and 57.9% (1692/2922) patients did not receive oxygen therapy (defined as the ambient-air group). After PSM analysis, 1122 pairs of patients were matched: each patient receiving oxygen therapy was matched with a patient without receiving supplemental oxygen. The multivariable logistic model showed that there was no significant interaction between the ambient air and oxygen group for all-cause in-hospital mortality [odds ratio (OR) 1.30; 95% confidence interval (CI) 0.92–1.82; P = 0.138] or ICU mortality (OR 1.39; 95% CI 0.83–2.32; P = 0.206) in the post-PSM cohorts. In addition, linear regression analysis revealed that oxygen therapy was associated with prolonged ICU LOS (OR 1.11; 95% CI 1.06–1.15; P

IntroductionAs the first bibliometric analysis of COVID-19 and immune responses, this study will provide a comprehensive overview of the latest research advances. We attempt to summarize the scientific productivity and cooperation across countries and institutions using the bibliometric methodology. Meanwhile, using clustering analysis of keywords, we revealed the evolution of research hotspots and predicted future research focuses, thereby providing valuable information for the follow-up studies.MethodsWe selected publications on COVID-19 and immune response using our pre-designed search strategy. Web of Science was applied to screen the eligible publications for subsequent bibliometric analyses. GraphPad Prism 8.0, VOSviewer, and CiteSpace were applied to analyze the research trends and compared the contributions of countries, authors, institutions, and journals to the global publications in this field.ResultsWe identified 2,200 publications on COVID-19 and immune response published between December 1, 2019, and April 25, 2022, with a total of 3,154 citations. The United States (611), China (353), and Germany (209) ranked the top three in terms of the number of publications, accounting for 53.3% of the total articles. Among the top 15 institutions publishing articles in this area, four were from France, four were from the United States, and three were from China. The journal Frontiers in Immunology published the most articles (178) related to COVID-19 and immune response. Alessandro Sette (31 publications) from the United States were the most productive and influential scholar in this field, whose publications with the most citation frequency (3,633). Furthermore, the development and evaluation of vaccines might become a hotspot in relevant scope.ConclusionsThe United States makes the most indispensable contribution in this field in terms of publication numbers, total citations, and H-index. Although publications from China also take the lead regarding quality and quantity, their international cooperation and preclinical research need to be further strengthened. Regarding the citation frequency and the total number of published articles, the latest research progress might be tracked in the top-ranking journals in this field. By analyzing the chronological order of the appearance of retrieved keywords, we speculated that vaccine-related research might be the novel focus in this field.