Altering the competitive environment of B cell epitopes significantly extends the duration of antibody production.

Persistent immunoglobulin G (IgG) production (PIP) provides long-term vaccine protection. While variations in the duration of protection have been observed with vaccines prepared from different pathogens, little is known about the factors that determine PIP. Here, we investigated the impact of three parameters on the duration of anti-peptide IgG production, namely amino acid sequences, protein carriers, and immunization programs. We show that anti-peptide IgG production can be transformed from transient IgG production (TIP) to PIP, by placing short peptides (Pi) containing linear B cell epitopes in different competitive environments using bovine serum albumin (BSA) conjugates instead of the original viral particles. When goats were immunized with the peste des petits ruminants (PPR) live-attenuated vaccine (containing Pi as the constitutive component) and BSA-Pi conjugate, anti-Pi IgG production exhibited TIP (duration < 60 days) and PIP (duration > 368 days), respectively. Further, this PIP was unaffected by subsequent immunization with the PPR live-attenuated vaccine in the same goat. When goats were coimmunized with PPR live-attenuated vaccine and BSA-Pi, the induced anti-Pi IgG production showed a slightly extended TIP (from ~60 days to ~100 days). This discovery provides new perspectives for studying the fate of plasma cells in humoral immune responses and developing peptide vaccines related to linear neutralizing epitopes from various viruses.

Immunogenicity evaluation of viral peptides via nonspecific interactions between anti-peptide IgYs and non-cognate peptides.

Immunogenicity can be evaluated by detecting antibodies (Abs) induced by an antigen. Presently deployed assays, however, do not consider the negative impacts of Ab poly-specificity, which is well established at the monoclonal antibody level. Here, we studied antibody poly-specificity at the serum level (i.e. nonspecific Ab-probe interactions, NSIs), and ended up establishing a new platform for viral peptide immunogenicity evaluation. We first selected three peptides of high, medium and low immunogenicity, using a 'vaccine serum response rate'-based approach (i.e. the gold standard). These three peptides (Pi) in the bovine serum albumin-Pi form were used to immunize chickens, resulting in longitudinal serum samples for screening with a non-cognate peptide library. The signal intensity of Ab-peptide specific binding and 'NSI count' was used to evaluate the viral peptides' immunogenicity. Only the NSI count agreed with the gold standard. The NSI count also provides more informative data on antibody production than the aggregated signal intensity by whole-protein-based indirect enzyme-linked immunosorbent assay.

Association between hospital racial composition and aortic valve replacement outcomes: A national inpatients sample database analysis.

BACKGROUND: Racial and ethnic disparities exist in the outcomes following surgical aortic valve replacement (SAVR) and transcatheter aortic valve implantation (TAVI). However, it is unclear whether hospital racial composition contributes to these racial disparities. METHODS: We analyzed the National Inpatient Sample (NIS) database from 2015 to 2019 to identify patients with aortic stenosis (AS) who received SAVR and TAVI. The Racial/Ethnic Diversity Index (RDI) was used to assess hospital racial composition as the proportion of nonwhite patients to total hospital admissions. Hospitals were categorized into RDI quintiles. Textbook outcome (TO) was defined as no in-hospital mortality, no postoperative complications and no prolonged length of stay (LOS). Multivariable mixed generalized linear models were conducted to assess the association between RDI and post-SAVR and post-TAVI outcomes. Moreover, quantile regression was used to assess the additional cost and length of stay associated with the RDI quintile. RESULTS: The study included 82,502 SAVR or TAVI performed across 3285 hospitals, with 47.4% isolated SAVR and 52.5% isolated TAVI. After adjustment, quintiles 4 and 5 demonstrated significantly lower odds of TO than the lowest RDI quintile in both the SAVR cohort (quintile 4, 0.79 [95% CI, 0.73-0.85]; quintile 5, 0.79 [95% CI, 0.73-0.86]) and TAVI cohort (quintile 4, 0.88 [95% CI, 0.82-0.95]; quintile 5, 0.80 [95% CI, 0.74-0.86]). Despite non-observable differences in in-hospital mortality across all RDI quintiles, the rate of AKI and blood transfusion increased with increasing RDI for both cohorts. Further, Higher RDI quintiles were associated with increased costs and longer LOS. From 2015 to 2019, post-TAVI outcomes improved across all RDI quintiles. CONCLUSIONS: Hospitals with a higher RDI experienced lower TO achievements, increased AKI, and blood transfusion, along with extended LOS and higher costs. Importantly, post-TAVI outcomes improved from 2015 to 2019 across all RDI groups.

Development and characterization of a novel nanobody with SRMV neutralizing activity.

Peste des petits ruminants (PPR) is an acute, contact infectious disease caused by the small ruminant morbillivirus (SRMV), and its morbidity in goats and sheep can be up to 100% with significant mortality. Nanobody generated from camelid animals such as alpaca has attracted wide attention because of its unique advantages compared with conventional antibodies. The main objective of this study was to produce specific nanobodies against SRMV and identify its characteristics. To obtain the coding gene of SRMV-specific nanobodies, we first constructed an immune phage-displayed library from the VHH repertoire of alpaca that was immunized with SRMV-F and -H proteins. By using phage display technology, the target antigen-specific VHHs can be obtained after four consecutive rounds of biopanning. Results showed that the size of this VHH library was 2.26 × 1010 CFU/mL and the SRMV-F and -H specific phage particles were greatly enriched after four rounds of biopanning. The positive phage clones were selected and sequenced, and total of five independent different sequences of SRMV-specific nanobodies were identified. Subsequently, the DNA fragments of the five nanobodies were cloned into E. coli BL21(DE3), respectively, and three of them were successfully expressed and purified. Specificity and affinity towards inactivated SRMV of these purified nanobodies were then evaluated using the ELISA method. Results demonstrated that NbSRMV-1-1, NbSRMV-2-10, and NbSRMV-1-21 showed no cross-reactivity with other antigens, such as inactivated BTV, inactivated FMDV, His-tag labeled protein, and BSA. The ELISA titer of these three nanobodies against inactivated SRMV was up to 1:1000. However, only NbSRMV-1-21 displayed SRMV neutralizing activity at a maximum dilution of 1:4. The results indicate that the nanobodies against SRMV generated in this study could be useful in future applications. This study provided a novel antibody tool and laid a foundation for the treatment and detection of SRMV.

Interpretable machine learning in predicting drug-induced liver injury among tuberculosis patients: model development and validation study.

BACKGROUND: The objective of this research was to create and validate an interpretable prediction model for drug-induced liver injury (DILI) during tuberculosis (TB) treatment. METHODS: A dataset of TB patients from Ningbo City was used to develop models employing the eXtreme Gradient Boosting (XGBoost), random forest (RF), and the least absolute shrinkage and selection operator (LASSO) logistic algorithms. The model's performance was evaluated through various metrics, including the area under the receiver operating characteristic curve (AUROC) and the area under the precision recall curve (AUPR) alongside the decision curve. The Shapley Additive exPlanations (SHAP) method was used to interpret the variable contributions of the superior model. RESULTS: A total of 7,071 TB patients were identified from the regional healthcare dataset. The study cohort consisted of individuals with a median age of 47 years, 68.0% of whom were male, and 16.3% developed DILI. We utilized part of the high dimensional propensity score (HDPS) method to identify relevant variables and obtained a total of 424 variables. From these, 37 variables were selected for inclusion in a logistic model using LASSO. The dataset was then split into training and validation sets according to a 7:3 ratio. In the validation dataset, the XGBoost model displayed improved overall performance, with an AUROC of 0.89, an AUPR of 0.75, an F1 score of 0.57, and a Brier score of 0.07. Both SHAP analysis and XGBoost model highlighted the contribution of baseline liver-related ailments such as DILI, drug-induced hepatitis (DIH), and fatty liver disease (FLD). Age, alanine transaminase (ALT), and total bilirubin (Tbil) were also linked to DILI status. CONCLUSION: XGBoost demonstrates improved predictive performance compared to RF and LASSO logistic in this study. Moreover, the introduction of the SHAP method enhances the clinical understanding and potential application of the model. For further research, external validation and more detailed feature integration are necessary.

Hydrogen sulfide regulates arsenic-induced cell death in yeast cells by modulating the antioxidative system.

Arsenic (As) is a metal with potentially toxic effects on different organisms. Hydrogen sulfide (H2S) plays a vital role in mitigating heavy metal toxicity by reducing oxidative stress in plants and animals. However, the role of H2S in alleviating arsenic toxicity in yeast cells remains unclear. In this study, the role of NaHS (exogenous physiological H2S) in alleviating As-induced yeast cell death was investigated. Yeast cells in the logarithmic phase were pretreated with 0.05 mmol/L NaHS for 6 h, and then incubated in the YPD medium with or without 1 mmol/L As. After 12 h of treatment, relative survival rate, H2S content, oxidative stress biomarkers, and antioxidant machinery were measured. Our results showed that sodium arsenite-induced yeast cell death and pretreatment with 0.05 mmol/L NaHS significantly alleviated sodium arsenite-induced cell death. Under sodium arsenite conditions, the levels of intracellular reactive oxygen species (ROS) and malondialdehyde (MDA) increased, accompanied by the inhibition of the catalase (CAT) activity and the downregulation of CTT1 expression. However, the activities of the superoxide dismutase (SOD) and glutathion peroxidase (GPX) increased, and the expression of SOD1 and GPX2 was markedly upregulated in the group treated with sodium arsenite. When yeast cells were pretreated with NaHS, the intracellular ROS and MDA levels decreased significantly, and the activities of SOD, CAT, and GPX increased significantly. This was associated with a significant increase in relative survival rate and H2S content compared to the arsenic treatment alone. Our findings indicate that NaHS alleviates sodium arsenite-induced yeast cell death, mainly by enhancing the antioxidant defense system.

Osteocalcin: A potential marker to identify and monitor girls with rapidly progressive central precocious puberty.

AIM: To evaluate the suitability of serum osteocalcin (OC) as a marker to distinguish between rapidly and non-rapidly progressive central precocious puberty (RP-CPP and NRP-CPP), as well as its potential to assess growth rates following treatment with gonadotropin-releasing hormone agonist (GnRHa). METHODS: Serum levels of OC were measured using enzyme-linked immunosorbent assays in girls diagnosed with either RP-CPP or NRP-CPP as well as in normal control subjects. Receiver operating characteristic (ROC) curve analysis was performed to determine the cut-off value for OC. Multivariate linear regression analysis was used to analyse the main influencing factors associated with OC. RESULTS: Serum OC levels were higher in the CPP girls when compared to normal controls (110.76 ± 43.69 vs 55.97 ± 20.96 ng/mL, P < 0.001). The level in the RP-CPP group was higher than the NRP-CPP group (153.28 ± 33.89 vs 88.33 ± 29.26 ng/mL, P < 0.001). The cut-off value of OC levels for distinguishing between RP-CPP and NRP-CPP was 107.05 ng/mL, the sensitivity was 94.7% and the specificity was 77.8%, which was superior to using the basal luteinising hormone (B-LH) levels, and the area under ROC curve (AUC) were 0.933 versus 0.695, respectively. Following 1-2 years of treatment with GnRHa for girls with CPP, both OC levels and the growth rates decreased to pre-pubertal values. B-LH levels, bone age and body weight were also significant factors, which affected OC levels. CONCLUSIONS: Serum OC levels may be a useful marker for distinguishing RP-CPP from NRP-CPP. In addition, it was also found to be a useful predictor for growth rate during GnRHa treatment.

Mapping Knowledge Landscapes and Emerging Trends in AI for Dementia Biomarkers: Bibliometric and Visualization Analysis.

BACKGROUND: With the rise of artificial intelligence (AI) in the field of dementia biomarker research, exploring its current developmental trends and research focuses has become increasingly important. This study, using literature data mining, analyzes and assesses the key contributions and development scale of AI in dementia biomarker research. OBJECTIVE: The aim of this study was to comprehensively evaluate the current state, hot topics, and future trends of AI in dementia biomarker research globally. METHODS: This study thoroughly analyzed the literature in the application of AI to dementia biomarkers across various dimensions, such as publication volume, authors, institutions, journals, and countries, based on the Web of Science Core Collection. In addition, scales, trends, and potential connections between AI and biomarkers were extracted and deeply analyzed through multiple expert panels. RESULTS: To date, the field includes 1070 publications across 362 journals, involving 74 countries and 1793 major research institutions, with a total of 6455 researchers. Notably, 69.41% (994/1432) of the researchers ceased their studies before 2019. The most prevalent algorithms used are support vector machines, random forests, and neural networks. Current research frequently focuses on biomarkers such as imaging biomarkers, cerebrospinal fluid biomarkers, genetic biomarkers, and blood biomarkers. Recent advances have highlighted significant discoveries in biomarkers related to imaging, genetics, and blood, with growth in studies on digital and ophthalmic biomarkers. CONCLUSIONS: The field is currently in a phase of stable development, receiving widespread attention from numerous countries, institutions, and researchers worldwide. Despite this, stable clusters of collaborative research have yet to be established, and there is a pressing need to enhance interdisciplinary collaboration. Algorithm development has shown prominence, especially the application of support vector machines and neural networks in imaging studies. Looking forward, newly discovered biomarkers are expected to undergo further validation, and new types, such as digital biomarkers, will garner increased research interest and attention.

Nurses' acceptance of nursing information systems: A multi-center cross-sectional study in China.

BACKGROUND: In China, nursing information systems (NIS) implementation can face numerous barriers to acceptance, including the attitudes of potential users. However, few studies have evaluated this acceptance. OBJECTIVE: The aim of this study was to explain the acceptance of NIS utilizing a survey based on unified theory of acceptance and use of technology. METHODS: A multi-center cross-sectional study utilizing an online survey was conducted. SPSS AMOS was used to conduct a structural equation modelling analysis. This research followed the STROBE Checklist. RESULTS: A total of 3973 Nurses participated in the study between January 2023 and March 2023. The acceptance of NIS among nurses was overall moderate to high. The proposed model has been rigorously tested and validated using empirical data, ensuring its credibility and dependability. Performance expectancy (PE), social influence (SI), and attitude significantly and positively affected intentions to use NIS. Effort expectancy (EE) did not show any significant effects in the sample. Facilitating conditions (FCs) was found to have a negative relationship with the intention to use NIS. There was a statistically significant difference BI between the different age groups, working years, and computer training experience. The model demonstrates a good fit with the observed data. CONCLUSIONS: This study identified PE, SI, and attitude as facilitators of nurses' intentions to use NIS. The findings about EE indicates that the ease of using NIS does not seem to be a concern among nurses. Moreover, high FC might be perceived as indicative of a complex system or extensive usage, that can lead to increased workload and reduced behavioural intention (BI). The significant differences in BI among various demographic groups highlight the need for more studies understanding the preferences and barriers faced by different, levels of experience and training backgrounds. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

Utilization of Lead Nitrate to Enhance the Impact of Hydroxamic Acids on the Hydrophobic Aggregation and Flotation Behavior of Cassiterite.

Lead nitrate (LN) is frequently employed as an activator in the flotation of cassiterite using hydroxamic acids as the collectors. This study investigated the effect of LN on the hydrophobic aggregation of cassiterite when benzohydroxamic acid (BHA), hexyl hydroxamate (HHA), and octyl hydroxamate (OHA) were used as the collectors through micro-flotation, focused beam reflectance measurement (FBRM) and a particle video microscope (PVM), zeta potential, and the extended DLVO theory. Micro-flotation tests confirmed that LN activated the flotation of cassiterite using the hydroxamic acids as collectors. Focused beam reflectance measurement (FBRM) and a particle video microscope (PVM) were used to capture in situ data on the changes in size distribution and morphology of cassiterite aggregates during stirring. The FBRM and PVM image results indicated that the addition of LN could promote the formation of hydrophobic aggregates of fine cassiterite, when BHA or HHA was used as the collector, and reduce the dosage of OHA needed to induce the formation of hydrophobic aggregates of cassiterite. The extended DLVO theory interaction energies indicated that the presence of LN could decrease the electrostatic interaction energies (Vedl) and increase the hydrophobic interaction energies (Vhy) between cassiterite particles, resulting in the disappearance of the high energy barriers that existed between the particles in the absence of LN. Thus, cassiterite particles could aggregate in the presence of LN when BHA, HHA, or a low concentration of OHA was used as the collector.

The interaction between water quality and meteorological factors on chlorophyll-a concentration in Honghu Lake: based on PiecewiseSEM-generalized additive model coupling model.

In order to explore the interactive effects of environmental factors on the chlorophyll-a (Chl-a) concentration variation in Honghu Lake, this study was based on the monitoring data of Chl-a mass concentration and water quality factors (water temperature, pH, dissolved oxygen, permanganate index, total nitrogen, total phosphorus) and meteorological factors (evaporation, precipitation, sunshine hours, average wind speed) at three research sites (Dakou, Chatan Island, Lantian) in Honghu Lake from January 2010 to December 2019. Time series analysis, piecewise structural equation model (PiecewiseSEM), and generalized additive model (GAM) were used to quantitatively study the spatial and temporal changes of different environmental factors and their interaction with chlorophyll-a concentration in Honghu Lake. The results showed that the effects of TN and DO on Chl-a at Dakou and Chatan Island were more significant than other environmental meteorological factors, while the effects of DO and CODMn on Chl-a at Lantian were more obvious. At the same time, it was found that Chl-a had a non-linear relationship with TN and DO at Dakou and Chatan Island, a non-linear relationship with DO at Lantian, and a linear relationship with CODMn. The interaction effect of dominant environmental meteorological factors on Chl-a was significantly higher than that of a single factor, and the explanation rates were 80.6%, 72.8%, and 64.6%, respectively. In conclusion, based on the Piecewise SEM and GAM model, it not only can reveal the influence of the interaction of influencing factors on the change of Chl-a concentration, but also has important significance for the early warning and control of lake eutrophication.

Shell Modulation of Hollow Metal Sulfide Nanocomposite for Stable Potassium Storage at Room and High Temperature.

The large size of K-ion makes the pursuit of stable high-capacity anodes for K-ion batteries (KIBs) a formidable challenge, particularly for high temperature KIBs as the electrode instability becomes more aggravated with temperature climbing. Herein, we demonstrate that a hollow ZnS@C nanocomposite (h-ZnS@C) with a precise shell modulation can resist electrode disintegration to enable stable high-capacity potassium storage at room and high temperature. Based on a model electrode, we identify an interesting structure-function correlation of the h-ZnS@C: with an increase in the shell thickness, the cyclability increases while the rate and capacity decrease, shedding light on the design of high-performance h-ZnS@C anodes via engineering the shell thickness. Typically, the h-ZnS@C anode with a shell thickness of 60 nm can deliver an impressive comprehensive performance at room temperature; the h-ZnS@C with shell thickness increasing to 75 nm can achieve an extraordinary stability (88.6 % capacity retention over 450 cycles) with a high capacity (450 mAh g-1) and a superb rate even at an extreme temperature of 60 °C, which is much superior than those reported anodes. This contribution envisions new perspectives on rational design of functional metal sulfides composite toward high-performance KIBs with insights into the significant structure-function correlation.

Facile Fabrication of Hollow Nanoporous Carbon Architectures by Controlling MOF Crystalline Inhomogeneity for Ultra-Stable Na-Ion Storage.

Hollow nanoporous carbon architectures (HNCs) present significant utilitarian value for a wide variety of applications. Facile and efficient preparation of HNCs has long been pursued but still remains challenging. Herein, we for the first time demonstrate that single-component metal-organic frameworks (MOFs) crystals, rather than the widely reported hybrid ones which necessitate tedious operations for preparation, could enable the facile and versatile syntheses of functional HNCs. By controlling the growth kinetics, the MOFs crystals (STU-1) are readily engineered into different shapes with designated styles of crystalline inhomogeneity. A subsequent one-step pyrolysis of these MOFs with intraparticle difference can induce a simultaneous self-hollowing and carbonization process, thereby producing various functional HNCs including yolk-shell polyhedrons, hollow microspheres, mesoporous architectures, and superstructures. Superior to the existing methods, this synthetic strategy relies only on the complex nature of single-component MOFs crystals without involving tedious operations like coating, etching, or ligand exchange, making it convenient, efficient, and easy to scale up. An ultra-stable Na-ion battery anode is demonstrated by the HNCs with extraordinary cyclability (93 % capacity retention over 8000 cycles), highlighting a high level of functionality of the HNCs.

Multiple Accessible Redox-Active Sites in a Robust Covalent Organic Framework for High-Performance Potassium Storage.

Covalent organic framework (COF) materials with porous character and robust structure have significant applied implications for K-ion battery (KIB) anodes, but they are limited by the low reversible capacity and inferior rate capability. Here, based on theoretical calculations, we identified that a porous bulk COF featuring numerous pyrazines and carbonyls in the π-conjugated periodic skeleton could provide multiple accessible redox-active sites for high-performance potassium storage. Its porous structure with a surface-dominated storage mechanism enabled the fast and stable storage of K-ions. Its insolubility in organic electrolytes and small volumetric change after potassiation ensured a robust electrode for stable cycling. As a KIB anode, this bulk COF demonstrated an unprecedentedly outstanding combination of reversible capacity (423 mAh g-1 at 0.1 C), rate capability (185 mAh g-1 at 10 C), and cyclability. The theoretical simulation and comprehensive characterizations confirmed the active sites are contributed by C═O, C═N, and the cation-π effect.

Development and validation of a patient satisfaction survey for pharmaceutical service at primary care settings.

Patient satisfaction is a key quality indicator of pharmacy service. However, there are few studies that develop and validate patient satisfaction surveys applied to pharmaceutical services in primary care settings. It is imperative to establish a well-validated multidimensional instrument for evaluating the viability and sustainability of pharmacy service across geographically diverse regions in low- and middle-income countries. To develop and validate a patient satisfaction instrument for community pharmaceutical services, we carried out a cross-sectional survey in seven provinces across China. The study was conducted in four phases: (i) literature review-based item generation, (ii) expert panel-endorsed questionnaire refinement, (iii) pilot questionnaire development, and (iv) psychometric validation. Survey respondents were standard patients recruited locally and trained to conduct unannounced visits to preselected primary care centers. Between December 2020 and November 2021, the pilot survey comprised a total of 166 unannounced standard patient visits from 125 health-care facilities. The final 24-item Likert-type instrument encompassed five domains: relationship, medication counseling, empathy, accessibility, and overall satisfaction. The satisfactory survey revealed excellent internal consistency. Factor analyses resulted in a 4-factor solution that accounted for 70.7% variance. The results suggest that the questionnaire is a valid and reliable instrument, which has been taken an important step to evaluate patient satisfaction with pharmaceutical services in Chinese primary care settings. Further research on its cross-culture adaptation and applicability in urban retail pharmacy settings is warranted.

UAV-YOLOv8: A Small-Object-Detection Model Based on Improved YOLOv8 for UAV Aerial Photography Scenarios.

Unmanned aerial vehicle (UAV) object detection plays a crucial role in civil, commercial, and military domains. However, the high proportion of small objects in UAV images and the limited platform resources lead to the low accuracy of most of the existing detection models embedded in UAVs, and it is difficult to strike a good balance between detection performance and resource consumption. To alleviate the above problems, we optimize YOLOv8 and propose an object detection model based on UAV aerial photography scenarios, called UAV-YOLOv8. Firstly, Wise-IoU (WIoU) v3 is used as a bounding box regression loss, and a wise gradient allocation strategy makes the model focus more on common-quality samples, thus improving the localization ability of the model. Secondly, an attention mechanism called BiFormer is introduced to optimize the backbone network, which improves the model's attention to critical information. Finally, we design a feature processing module named Focal FasterNet block (FFNB) and propose two new detection scales based on this module, which makes the shallow features and deep features fully integrated. The proposed multiscale feature fusion network substantially increased the detection performance of the model and reduces the missed detection rate of small objects. The experimental results show that our model has fewer parameters compared to the baseline model and has a mean detection accuracy higher than the baseline model by 7.7%. Compared with other mainstream models, the overall performance of our model is much better. The proposed method effectively improves the ability to detect small objects. There is room to optimize the detection effectiveness of our model for small and feature-less objects (such as bicycle-type vehicles), as we will address in subsequent research.

Gut microbiota in systemic lupus erythematosus: A fuse and a solution.

Gut commensals help shape and mold host immune system and deeply influence human health. The disease spectrum of mankind that gut microbiome may associate with is ever-growing, but the mechanisms are still enigmas. Characterized by loss of self-tolerance and sustained self-attack, systemic lupus erythematosus (SLE) is labeled with chronic inflammation, production of autoantibodies and multisystem injury, which so far are mostly incurable. Gut microbiota and their metabolites, now known as important environmental triggers of local/systemic immune responses, have been proposed to be involved in SLE development and progression probably through the following mechanisms: translocation beyond their niches; molecular mimicry to cross-activate immune response targeting self-antigens; epitope spreading to expand autoantibodies spectrum; and bystander activation to promote systemic inflammation. Gut microbiota which varies between individuals may also influence the metabolism and bio-transformation of disease-modifying anti-rheumatic drugs, thus associated with the efficacy and toxicity of these drugs, adding another explanation for heterogenic therapeutic responses. Modulation of gut microbiota via diet, probiotics/prebiotics, antibiotics/phages, fecal microbiota transplantation, or helminth to restore immune tolerance and homeostasis is expected to be a promising neoadjuvant therapy for SLE. We reviewed the advances in this territory and discussed the application prospect of modulating gut microbiota in controlling SLE.

A novel prognostic model based on single-cell RNA sequencing data for hepatocellular carcinoma.

BACKGROUND: The tumour heterogeneous make-up of immune cell infiltrates is a key factor for the therapy response and prognosis of hepatocellular carcinoma (HCC). However, it is still a major challenge to comprehensively understand the tumour immune microenvironment (TIME) at the genetic and cellular levels. METHODS: HCC single-cell RNA sequencing (scRNA-seq) data were downloaded from the Gene Expression Omnibus (GEO) database, and gene expression data were retrieved from The Cancer Genome Atlas (TCGA) database and International Cancer Genome Consortium (ICGC) database. Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) was performed to evaluate the abundance of immune infiltrating cells. We employed weighted gene coexpression network analysis (WGCNA) to construct a gene coexpression network. Univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses were further used to construct a risk model. Moreover, the expression levels of model genes were assessed by qPCR. RESULTS: We defined 25 cell clusters based on the scRNA-seq dataset (GSE149614), and the clusters were labelled as various cell types by marker genes. Then, we constructed a weighted coexpression network and identified a total of 6 modules, among which the brown module was most highly correlated with tumours. Moreover, we found that the brown module was most closely related to monocytes (cluster 21). Through univariate Cox and LASSO analyses, we constructed a 3-gene risk model (RiskScore = 0.257*Expression CSTB + 0.263* Expression TALDO1 + 0.313* Expression CLTA). This risk model showed excellent predictive efficacy for prognosis in the TCGA-LIHC and ICGC cohorts. Additionally, patients with high risk scores were found to be less likely to benefit from immunotherapy. CONCLUSIONS: We developed a 3-gene signature (including CLTA, TALDO1 and CSTB) based on the heterogeneity of the TIME to predict the survival outcome and immunotherapy response.

Intraoperative venous congestion rather than hypotension is associated with acute adverse kidney events after cardiac surgery: a retrospective cohort study.

BACKGROUND: The pathophysiological mechanisms by which venous congestion and hypotension lead to acute adverse kidney events after cardiac surgery with cardiopulmonary bypass have not been elucidated. We tested the hypothesis that intraoperative hypotension and venous congestion are associated with acute kidney injury and acute kidney disease. METHODS: Primary exposures were venous congestion and intraoperative hypotension defined by central venous pressure ≥12, 16, or 20 mm Hg or mean arterial pressure ≤55, 65, or 75 mm Hg. The primary outcomes were acute kidney injury and acute kidney disease. Multivariable logistic regression and Cox proportional hazard models were used, adjusted for relevant confounding factors and multiple comparisons. RESULTS: Of 5127 eligible subjects, 1070 (20.9%) and 327 (7.2%) developed acute kidney injury and acute kidney disease, respectively. The occurrence of acute kidney injury was statistically associated with both venous congestion and intraoperative hypotension. The cumulative incidence rate for new onset acute kidney disease was 1.34 (95% confidence interval [CI], 1.21-1.60) per 100 person-days. Acute kidney disease was significantly associated with each 10 min epoch of central venous pressure ≥12 mm Hg (hazard ratio [HR]=1.03; 99% CI, 1.01-1.06; P<0.001), ≥16 mm Hg (HR=1.04; 99% CI, 1.01-1.07; P<0.001), and ≥20 mm Hg (HR=1.07; 99% CI, 1.02-1.13; P<0.001). Venous congestion was associated with an 8-17% increased risk for de novo renal replacement therapy. In contrast, intraoperative hypotension was not associated with development of acute kidney disease. CONCLUSION: Although both venous congestion and intraoperative hypotension are associated with acute kidney injury, only venous congestion correlates with acute kidney disease among patients undergoing cardiac surgery requiring cardiopulmonary bypass. The reported associations are suggestive of a pathophysiological role of venous congestion in acute kidney disease.

Effect of G-quadruplex loop mutations on the G-quadruplex formation, protein binding and transcription of BmPOUM2 in Bombyx mori.

A G-quadruplex (G4) was identified in the promoter of transcription factor BmPOUM2 in Bombyx mori. This G4 structure contains three loops and is bound by transcription factor BmLARK, facilitating the transcription of BmPOUM2. However, the relationship between the structure and function of the BmPOUM2 G4 remains to be clarified. In this study, loop mutants of the BmPOUM2 G4 structure were generated to study the function of the structure in transcription regulation. The results revealed that mutations of Loops A and B could not completely suppress G4 formation, but affected the binding of the G4 structure with BmLARK and the promoter activity. The mutation (C-to-T) of the one-nucleotide-loop, Loop C, enhanced the G4 formation, its binding with BmLARK and the transcription activity of the BmPOUM2 promoter. It is speculated that the binding site of BmLARK probably is on the G-quartet planes, rather than on the loops, which may assist the maintenance and modification of the G4 structure and its protein binding activity.