Early prognosis prediction for non-variceal upper gastrointestinal bleeding in the intensive care unit: based on interpretable machine learning.

INTRODUCTION: This study aims to construct a mortality prediction model for patients with non-variceal upper gastrointestinal bleeding (NVUGIB) in the intensive care unit (ICU), employing advanced machine learning algorithms. The goal is to identify high-risk populations early, contributing to a deeper understanding of patients with NVUGIB in the ICU. METHODS: We extracted NVUGIB data from the Medical Information Mart for Intensive Care IV (MIMIC-IV, v.2.2) database spanning from 2008 to 2019. Feature selection was conducted through LASSO regression, followed by training models using 11 machine learning methods. The best model was chosen based on the area under the curve (AUC). Subsequently, Shapley additive explanations (SHAP) was employed to elucidate how each factor influenced the model. Finally, a case was randomly selected, and the model was utilized to predict its mortality, demonstrating the practical application of the developed model. RESULTS: In total, 2716 patients with NVUGIB were deemed eligible for participation. Following selection, 30 out of a total of 64 clinical parameters collected on day 1 after ICU admission remained associated with prognosis and were utilized for developing machine learning models. Among the 11 constructed models, the Gradient Boosting Decision Tree (GBDT) model demonstrated the best performance, achieving an AUC of 0.853 and an accuracy of 0.839 in the validation cohort. Feature importance analysis highlighted that shock, Glasgow Coma Scale (GCS), renal disease, age, albumin, and alanine aminotransferase (ALP) were the top six features of the GBDT model with the most significant impact. Furthermore, SHAP force analysis illustrated how the constructed model visualized the individualized prediction of death. CONCLUSIONS: Patient data from the MIMIC database were leveraged to develop a robust prognostic model for patients with NVUGIB in the ICU. The analysis using SHAP also assisted clinicians in gaining a deeper understanding of the disease.

Identification and validation of tumor-specific T cell receptors from tumor infiltrating lymphocytes using tumor organoid co-cultures.

T cell receptor-engineered T cells (TCR-Ts) therapy is promising for cancer immunotherapy. Most studies have focused on identifying tumor-specific T cell receptors (TCRs) through predicted tumor neoantigens. However, current algorithms for predicting tumor neoantigens are unreliable and many neoantigens are derived from non-coding regions. Thus, the technological platform for identifying tumor-specific TCRs using natural antigens expressed on tumor cells is urgently needed. In this study, tumor organoids-enriched tumor infiltrating lymphocytes (oeT) were obtained by repeatedly stimulation of autologous patient-derived organoids (PDO) in vitro. The oeT cells specifically responded to autologous tumor PDO by detecting CD137 expression and the secretion of IFN-γ using enzyme-linked immunospot assay. The measurement of oeT cell-mediated killing of three-dimensional organoids was conducted using a caspase3/7 flow cytometry assay kit. Subsequently, tumor-specific T cells were isolated based on CD137 expression and their TCRs were identified through single-cell RT-PCR analysis. The specificity cytotoxicity of TCRs were confirmed by transferring to primary peripheral blood T cells. The co-culture system proved highly effective in generating CD8+ tumor-specific oeT cells. These oeT cells effectively induced IFN-γ secretion and exhibited specificity in killing autologous tumor organoids, while not eliciting a cytotoxic response against normal organoids. The analysis conducted by TCRs revealed a significant expansion of T cells within a specific subset of TCRs. Subsequently, the TCRs were cloned and transferred to peripheral blood T cells generation engineered TCR-Ts, which adequately recognized and killed tumor cell in a patient-specific manner. The co-culture system provided an approach to generate tumor-specific TCRs from tumor-infiltrating lymphocytes of patients with colorectal cancer, and tumor-specific TCRs can potentially be used for personalized TCR-T therapy.

Comprehensive Analysis of Immune Cell Infiltration and M2-Like Macrophage Biomarker Expression Patterns in Atrial Fibrillation.

Background: Macrophages play a crucial role in the progression of AF, closely linked to atrial inflammation and myocardial fibrosis. However, the functions and molecular mechanisms of different phenotypic macrophages in AF are not well understood. This study aims to analyze the infiltration characteristics of atrial immune cells in AF patients and further explore the role and molecular expression patterns of M2 macrophage-related genes in AF. Methods: This study integrates single-cell and large-scale sequencing data to analyze immune cell infiltration and molecular characterization of the LAA in patients with AF, using SR as a control group. CIBERSORT assesses immune cell types in LAA tissues; WGCNA identifies signature genes; cell clustering analyzes cell types and subpopulations; cell communication explores macrophage interactions; hdWGCNA identifies M2 macrophage gene modules in AF. AF biomarkers are identified using LASSO and Random Forest, validated with ROC curves and RT-qPCR. Potential molecular mechanisms are inferred through TF-miRNA-mRNA networks and single-gene enrichment analyses. Results: Myeloid cell subsets varied considerably between the AF and SR groups, with a significant increase in M2 macrophages in the AF group. Signals of inflammation and matrix remodeling were observed in AF. M2 macrophage-related genes IGF1, PDK4, RAB13, and TMEM176B were identified as AF biomarkers, with RAB13 and TMEM176B being novel markers. A TF-miRNA-mRNA network was constructed using target genes, which are enriched in the PPAR signaling pathway and fatty acid metabolism. Conclusion: Over infiltration of M2 macrophages may be an important factor in the progression of AF. The M2 macrophage-related genes IGF1, RAB13, TMEM176B and PDK4 may regulate the progression of AF through the PPAR signaling pathway and fatty acid metabolism.

Synergistic Effects of Soil-Based Irrigation and Manure Substitution for Partial Chemical Fertilizer on Potato Productivity and Profitability in Semiarid Northern China.

Soil-based irrigation and the partial substitution of chemical fertilizers with manure are promising practices to improve water and nitrogen (N) use efficiency. We hypothesize that their combination would simultaneously benefit potato production, tuber quality and profitability. A two-year experiment was conducted in semiarid northern China to investigate the combined effects of three water treatments [rainfed (W0), soil-based irrigation (W1), conventional irrigation (W2)] and three N treatments [no N (N0), chemical N (N1), 25% manure substitution (N2)] on these indicators, and to perform a comprehensive evaluation and correlation analysis. The results showed that water and N treatments separately affected all indicators except vitamin C content. Compared to W2, W1 significantly increased water productivity by 12% and irrigation water use efficiency (IWUE) by 30% due to 10% lower evapotranspiration and 21% lower water use. However, W1 and W2 negatively affected crude protein content. Conversely, this was compensated by the combination with N1 and N2. There were slight differences between N1 and N2 for all indicators on average across water treatments, while under W1, N2 significantly increased leaf area index (LAI) and N recovery efficiency (REN) by 18% and 29.4%, respectively, over N1. Also, comprehensive evaluations showed that W1N2 performed best, with the highest tuber yield, profit and acceptable quality. This can be explained by the increase in LAI, IWUE and REN due to the positive correlations with tuber yield and net return. Consequently, soil-based irrigation combined with 25% manure substitution had complementary effects on tuber quality and synergistic effects on potato productivity and profitability.

SERS detection platform based on a nucleic acid aptamer-functionalized Au nano-dodecahedron array for efficient simultaneous testing of colorectal cancer-associated microRNAs.

A surface-enhanced Raman scattering (SERS) detection platform was constructed based on Au nano-dodecahedrons (AuNDs) functionalized with nucleic acid aptamer-specific binding and self-assembly techniques. SERS labels were prepared by modifying Raman signaling molecules and complementary aptamer chains and were bound on the aptamer-functionalized AuNDs array. Using this protocol, the limits of detection (LODs) of miR-21 and miR-18a in the serum were 6.8 pM and 7.6 pM, respectively, and the detection time was 5 min. Additionally, miR-21 and miR-18a were detected in the serum of a mouse model of colorectal cancer. The results of this protocol were consistent with quantitative real-time polymerase chain reaction (qRT-PCR). This method provides an efficient and rapid method for the simultaneous testing of miRNAs, which has great potential clinical value for the early detection of colorectal cancer (CRC).

Preoperative Prediction of Metastatic Lymph Nodes Posterior to the Right Recurrent Laryngeal Nerve in cN0 Papillary Thyroid Carcinoma.

Background: The advantages of the dissecting the metastatic lymph nodes posterior to the right recurrent laryngeal nerve (LN-prRLN) remain a great deal of controversies in papillary thyroid carcinoma (PTC) patients without clinical evidence. The purpose of our retrospective research was to investigate the predictive factors of the LN-prRLN in cN0 PTC patients. Methods and Materials: Altogether 251 consecutive cN0 PTC participants accepted unilateral or bilateral thyroidectomy accompanied with LN-prRLN dissection between June 2020 and May 2023 were included in the research. Then, univariate and multivariate logical regression analysis were conducted to analyze the relationship between the LN-prRLN and these predictive factors, and a predictive model was also developed. Surgical complications of LN-prRLN dissection were also presented. Results: The rate of LN-prRLN was 17.9% (45/251) in cN0 PTC patients after the analysis of postoperative histology. The age <55 years, multifocality, microcalcification, and BRAFV600E mutation were identified to be predictive factors of LN-prRLN in cN0 PTC patients. The risk score for LN-prRLN was calculated: risk score = 1.192 × (if age <55 years) + 0.808 × (if multifocality) + 1.196 × (if microcalcification in nodule) + 0.918 × (if BRAFV600E mutation in nodule). The rates of the transient hypoparathyroidism and hoarseness were 1.2% (3/251) and 2.0% (5/251), respectively. Conclusion: The age <55 years, multifocality, microcalcification, and BRAFV600E mutation are independent predictors of the LN-prRLN in cN0 PTC patients. An effective predictive model was established for predicting the LN-prRLN in cN0 PTC patients, with the aim to better guide the surgical treatment of PTC. A thorough inspection of the lateral compartment is recommended in PTC patients with risk factors. The multicenter research with long-term follow-up should be carried out to ascertain the optimal surgical approach for patients with PTC.

Inverse relationship between species competitiveness and intraspecific trait variability may enable species coexistence in experimental seedling communities.

Theory suggests that intraspecific trait variability may promote species coexistence when competitively inferior species have higher intraspecific trait variability than their superior competitors. Here, we provide empirical evidence for this phenomenon in tree seedlings. We evaluated intraspecific variability and plastic response of ten traits in 6750 seedlings of ten species in a three-year greenhouse experiment. While we observed no relationship between intraspecific trait variability and species competitiveness in competition-free homogeneous environments, an inverse relationship emerged under interspecific competition and in spatially heterogeneous environments. We showed that this relationship is driven by the plastic response of the competitively inferior species: Compared to their competitively superior counterparts, they exhibited a greater increase in trait variability, particularly in fine-root traits, in response to competition, environmental heterogeneity and their combination. Our findings contribute to understanding how interspecific competition and intraspecific trait variability together structure plant communities.

Benefits and trade-offs of replacing inorganic fertilizer by organic substrate in crop production: A global meta-analysis.

Replacing inorganic fertilizer with organic substrate contributes to sustainable agricultural production capacity. However, the effects of organic substitution regimes (OSR) on global crop productivity, soil carbon (C) and nitrogen (N) losses and biofertility as function of environmental variables have not been systematically quantified. Here, we have conducted a meta-analysis of these effects using field data (211 papers with 852 observations) collected around the world. Results indicated that OSR increased crop productivity (3.04 %) and soil biofertility (soil qMBC, qMBN, microbial richness, Shannon and functionality by 11.4 %, 21.1 %, 10.2 %, 3.95 %, and 38.5 %, respectively), and reduced soil N losses (N2O emissions, NH3 volatilization and soil N leaching by 26.5 %, 26.1 %, and 33.8 %, respectively), but increased CO2 emissions (19.4 %), and paddy fields CH4 emissions (41.2 %). N rate was an important factor influencing crop productivity and soil biofertility response to OSR, and crop productivity and soil biofertility had a greater positive response at moderate substitution rates in acid soil and long-term trials, but full substitution significantly decreased crop yield. Furthermore, the increase in soil biofertility and crop yield saturated in ~10-14 and ~ 22 years after organic substrate input. The emissions of CO2, CH4, and N2O significantly increased with increasing substitution rates, while the opposite was true for N leaching. The NH3 volatilization response to OSR presented a positive effect in acidic and coarse texture soil. OSR was more beneficial in mitigating soil C and N loss response (except CO2 emissions) in uplands compared to paddy fields. Therefore, implementation of OSR requires site-specific strategies to better achieve a balance between increasing crop production and reducing environmental benefits. Given that the OSR improvement varies depending on environmental variables, we propose a predictive model to initially assess the potential for OSR improvement. This study will provide scientific guidance on the reasonable application of organic substrate in agroecosystems.

Remobilization of Cd caused by iron oxide phase transformation and Mn2+ competition after stabilization by nano zero valent iron.

Stabilization techniques are vital in controlling Cd soil pollution. Nano zero valent iron (nZVI) has been extensively utilized for Cd remediation owing to its robust adsorption and reactivity. However, the environmental stress-induced stability of Cd after nZVI addition remains unclear. A pot experiment was conducted to evaluate the Cd bioavailability in continuously flooded (130 d) soil after stabilization with nZVI. The findings indicated that nZVI application did not result in a decline in Cd concentration in rice, as compared to the no-nZVI control. Additionally, nZVI simultaneously increased the available Cd concentration, iron-manganese oxide-bound (OX) Mn fraction, and relative abundance of Fe(III)-reducing bacteria, but it decreased OX-Cd and Mn availability in soil. Cadmium in rice tissues was positively correlated with the available Cd in soil. The results of subsequent adsorption tests demonstrated that CdO was the product of Cd adsorption by the nZVI aging products. Conversely, Mn2+ decreased the adsorption capacity of Cd-containing solutions. These results underscore the crucial role of both biotic and abiotic factors in undermining the stabilization of nZVI under continuous flooding conditions. This study offers novel insights into the regulation of nZVI-mediated Cd stabilization efficiency in conjunction with biological inhibitors and functional modification techniques.

A comparative study on the development of Chinese and English abilities of Chinese primary school students through two bilingual reading modes: human-AI robot interaction and paper books.

To address the challenges encountered by Chinese primary school students, particularly left-behind and migrant children, who exhibit a preference for animations, video games, and short videos over reading books and struggle with Chinese-English bilingual skills, this study introduces an educational robot AI-assisted method for simultaneous bilingual reading. To assess the effectiveness of this method, a 6-month Chinese-English bilingual extracurricular reading comparative experiment was conducted involving 85 grade 5 students from two classes in a primary school in Hangzhou, China. The AI-assisted class freely read 100 bilingual/English electronic picture books and 200 Chinese electronic classic serial picture books by employing the AI-assisted human-computer interactive electronic reading mode of the "Educational Robot+Audio Electronic Picture Book+Character-play Based Reading." In contrast, the paper book group read the same content presented in the traditional paper book format, following the "regular independent reading" mode. Post-experimental analyses were conducted employing t-tests and MANCOVA and the results revealed that: the primary factors influencing reading effectiveness are the choice of reading materials, reading tools, and reading mode, while reading time does not emerge as the principal influencing factor. Furthermore, students in the AI class demonstrated significant enhancements in bilingual reading motivation, reading amount, reading comprehension, independent learning ability, pronunciation proficiency, and test scores compared to their peers in the paper book class. The AI-assisted reading mode utilizing educational robots garnered positive feedback from teachers, parents, and students. It offers the potential to effectively substitute parental involvement in parent-child reading and English tutoring, while also enabling the simultaneous acquisition of bilingual proficiency in both Chinese and English. This approach proves to be highly effective, cost-efficient, and convenient, particularly for enhancing children's foreign language abilities. Moreover, it fosters positive reading habits and independent learning skills among primary school students, contributes to the establishment of lofty aspirations, and enhances bilingual performance. Overall, this innovative mode offers an effective means of facilitating children's acquisition of bilingualism and foreign language skills, as well as promoting reading education.

Machine learning-based prediction model of acute kidney injury in patients with acute respiratory distress syndrome.

BACKGROUND: Acute kidney injury (AKI) can make cases of acute respiratory distress syndrome (ARDS) more complex, and the combination of the two can significantly worsen the prognosis. Our objective is to utilize machine learning (ML) techniques to construct models that can promptly identify the risk of AKI in ARDS patients. METHOD: We obtained data regarding ARDS patients from the Medical Information Mart for Intensive Care III (MIMIC-III) and MIMIC-IV databases. Within the MIMIC-III dataset, we developed 11 ML prediction models. By evaluating various metrics, we visualized the importance of its features using Shapley additive explanations (SHAP). We then created a more concise model using fewer variables, and optimized it using hyperparameter optimization (HPO). The model was validated using the MIMIC-IV dataset. RESULT: A total of 928 ARDS patients without AKI were included in the analysis from the MIMIC-III dataset, and among them, 179 (19.3%) developed AKI after admission to the intensive care unit (ICU). In the MIMIC-IV dataset, there were 653 ARDS patients included in the analysis, and among them, 237 (36.3%) developed AKI. A total of 43 features were used to build the model. Among all models, eXtreme gradient boosting (XGBoost) performed the best. We used the top 10 features to build a compact model with an area under the curve (AUC) of 0.850, which improved to an AUC of 0.865 after the HPO. In extra validation set, XGBoost_HPO achieved an AUC of 0.854. The accuracy, sensitivity, specificity, positive prediction value (PPV), negative prediction value (NPV), and F1 score of the XGBoost_HPO model on the test set are 0.865, 0.813, 0.877, 0.578, 0.957 and 0.675, respectively. On extra validation set, they are 0.724, 0.789, 0.688, 0.590, 0.851, and 0.675, respectively. CONCLUSION: ML algorithms, especially XGBoost, are reliable for predicting AKI in ARDS patients. The compact model maintains excellent predictive ability, and the web-based calculator improves clinical convenience. This provides valuable guidance in identifying AKI in ARDS, leading to improved patient outcomes.

A Two-Phase Feature Selection Method for Identifying Influential Spreaders of Disease Epidemics in Complex Networks.

Network epidemiology plays a fundamental role in understanding the relationship between network structure and epidemic dynamics, among which identifying influential spreaders is especially important. Most previous studies aim to propose a centrality measure based on network topology to reflect the influence of spreaders, which manifest limited universality. Machine learning enhances the identification of influential spreaders by combining multiple centralities. However, several centrality measures utilized in machine learning methods, such as closeness centrality, exhibit high computational complexity when confronted with large network sizes. Here, we propose a two-phase feature selection method for identifying influential spreaders with a reduced feature dimension. Depending on the definition of influential spreaders, we obtain the optimal feature combination for different synthetic networks. Our results demonstrate that when the datasets are mildly or moderately imbalanced, for Barabasi-Albert (BA) scale-free networks, the centralities' combination with the two-hop neighborhood is fundamental, and for Erdos-Rényi (ER) random graphs, the centralities' combination with the degree centrality is essential. Meanwhile, for Watts-Strogatz (WS) small world networks, feature selection is unnecessary. We also conduct experiments on real-world networks, and the features selected display a high similarity with synthetic networks. Our method provides a new path for identifying superspreaders for the control of epidemics.

Early human albumin administration is associated with reduced mortality in septic shock patients with acute respiratory distress syndrome: A retrospective study from the MIMIC-III database.

Background: Sepsis-induced acute respiratory distress syndrome (ARDS) was associated with higher mortality. It is unclear whether albumin supplementation early in the course of ARDS can affect the prognostic outcomes of septic shock (SS) patients with ARDS. Methods: The MIMIC-III database was employed to identify SS patients with ARDS. The effect of early application (<24 h after ICU admission) of human albumin on 28-day mortality in SS patients with ARDS was explored. The propensity score matching was used to minimize the bias between the non-albumin and early albumin treatment groups. Results: The analysis for all eligible patients who received human albumin showed significantly lower 28-hospital mortality rates than the non-albumin group (37% versus 47%, p = 0.018). After propensity matching, the difference between the two groups also significantly (34.8% versus 48.1%, p = 0.031). Moreover, we found that the relationship between albumin use and reduced 28-day mortality was inconsistent across SOFA score subgroups (Pinteraction = 0.004, non-adjustment for multiple testing). Conclusion: Early human albumin administration in SS patients with ARDS was independently associated with a reduction of 28-day mortality. Furthermore, the benefit of human albumin treatment appeared to be more pronounced in patients with a SOFA score of ≤ 10.

Characteristics of rice straw decomposition and bacterial community succession for 2 consecutive years in a paddy field in southeastern China.

The characteristics of long-term rice straw decomposition and succession in the bacterial community in the double-rice system are still unclear. Here a 2-year continuous straw bag decomposition experiment was conducted to explore changes in nutrient release, enzyme activity, and bacterial community composition during rice straw decomposition in the double-rice system in Southeast China. After burial in soil, the cumulative dry matter loss rates of rice straw were 38.9%, 72.6%, and 82.7% after 2, 12, and 24 months, respectively. The change in the release rate of straw nitrogen and phosphorus was similar to the dry matter loss, but 93.5% of straw potassium was released after 1st month. Bacterial abundance and community diversity in straw increased rapidly, reaching peaks after 7 and 12 months, respectively. Straw extracellular enzyme activities were the highest in the first 2 months and then gradually decreased over time, and they significantly and positively correlated with straw decomposition rate. Straw decomposition was dominated by copiotrophic Bacilli and Flavobacteriia in the early stages and evolved to be dominated by oligotrophic Acidobacteria, Anaerolineae, Deltaproteobacteria, Saccharibacteria, and Sphingobacteriia in the later stages. Changes in the C/N and K content of straw are the main reasons for bacterial community succession during rice straw decomposition. This study can provide a scientific basis for developing efficient decomposing bacteria agents for rice straw.

Sleep Deprivation and Central Appetite Regulation.

Research shows that reduced sleep duration is related to an increased risk of obesity. The relationship between sleep deprivation and obesity, type 2 diabetes, and other chronic diseases may be related to the imbalance of appetite regulation. To comprehensively illustrate the specific relationship between sleep deprivation and appetite regulation, this review introduces the pathophysiology of sleep deprivation, the research cutting edge of animal models, and the central regulatory mechanism of appetite under sleep deprivation. This paper summarizes the changes in appetite-related hormones orexin, ghrelin, leptin, and insulin secretion caused by long-term sleep deprivation based on the epidemiology data and animal studies that have established sleep deprivation models. Moreover, this review analyzes the potential mechanism of associations between appetite regulation and sleep deprivation, providing more clues on further studies and new strategies to access obesity and metabolic disease.

Effects of Water Loss Stress under Tidal Effects on the Epiphytic Bacterial Community of Sargassum thunbergii in the Intertidal Zone.

Intertidal macroalgae face periodic water loss and rehydration caused by daily tidal changes. However, the effect of water loss stress on algal epiphytic bacteria has not yet been reported. In this study, the effects of water loss stress on the epiphytic bacteria community of Sargassum thunbergii were analyzed, and the different responses of epiphytic bacteria to water loss stress were compared between male and female algae. The results showed that after water loss stress, the diversity of the epiphytic bacterial community of S. thunbergii first decreased and then increased. Among the dominant taxa, the abundance of Cyanobacteria decreased significantly, whereas the abundance of Portibacter and Aquimarina first increased and then decreased. Additionally, the indicator species and the abundance of predicted functional genes related to carbon, nitrogen, and sulfur metabolism both changed significantly. More importantly, when the epiphytic bacteria were analyzed separately according to the algal sex, the changes in algal epiphytic bacterial community structure and indicator species were more significant, and there were sexual differences. Therefore, it was concluded that water loss stress has a significant effect on the community structure and function of the epiphytic bacteria on S. thunbergii. Meanwhile, the epiphytic bacteria community of two sexes of S. thunbergii differed in the response to water loss stress. IMPORTANCE Periodic water loss caused by the tide is an important environmental factor that is faced by intertidal macroalgae, but the impact of periodic water loss on the epiphytic bacterial communities associated with macroalgae is still unknown. Through this study, we found that the diversity, the relative abundance of dominant taxa, the indicator species, and the abundance of the predicted functional genes in the epiphytic bacteria on S. thunbergii changed with the time of water loss. Moreover, male and female S. thunbergii exhibited different responses to water loss stress. This study not only paves the way for the delineation of the interactions between S. thunbergii and its epiphytic bacteria but also provides new insights for the mechanisms of the adaptation and evolution of macroalgae in the intertidal zone.

Effects of rice root exudates on aggregation, dissolution and bioaccumulation of differently-charged Ag nanoparticles.

The biological toxicity and eco-environmental risk of metal nanoparticles (MNPs) is closely related to their stability. The stability of MNPs not only depends on their own properties but also on the effects of biological and environmental factors. To better understand the interaction between biological factors and MNPs in aquatic environments, the effects of total rice root exudates (T-RRE) on the aggregation, dissolution and bioaccumulation of Ag nanoparticles (AgNPs) with different surface charges were investigated in detail. Results indicated that T-RRE can induce the aggregation and sedimentation, and hinder the dissolution of polyethyleneimine-coated AgNPs (AgNPs@PEI) with positive surface charges as well as reducing the bioaccumulation of Ag in rice roots. T-RRE had no obvious effect on the dispersion stability of AgNPs@Cit (negatively charged citrate-coated AgNPs) and AgNPs@PVP (near electrically neutral polyvinylpyrrolidone-coated AgNPs), although T-RRE could induce the dissolution of AgNPs@Cit and AgNPs@PVP. In the molecular fractions of T-RRE, high-molecular-weight root exudates (H-RRE) play a key role in inducing the aggregation of AgNPs@PEI and hindering the bioaccumulation of Ag in rice roots. Compared with H-RRE, low-molecular-weight root exudates (L-RRE) can promote the dissolution of AgNPs@Cit and AgNPs@PVP, but it can obviously promote silver accumulation in rice roots. The difference in charge intensity between L-RRE and T-RRE plays a key role in inducing the aggregation and dissolution of AgNPs with different charges. These findings provide a foundation for investigation of the interactions between rice root exudates and nanoparticles with different surface charges in complex environmental systems.

Effect of high soil C/N ratio and nitrogen limitation caused by the long-term combined organic-inorganic fertilization on the soil microbial community structure and its dominated SOC decomposition.

The application of organic fertilizers, such as straw and manure, is an efficient approach to maintain soil productivity. However, the effect of these organic fertilizers on soil microbial nutrient balance has not yet been established. In this study, the effects of the long-term combined organic-inorganic fertilization on microbial community were investigated by conducting a 30-year-long field test. Overall, the following five fertilizer groups were employed: inorganic NP fertilizer (NP), inorganic NK fertilizer (NK), inorganic NPK fertilizer (NPK), NPK + manure (MNPK), and NPK + straw (SNPK). The results indicated that the mean natural logarithm of the soil C:N:P acquisition enzyme ratio was 1.04:1.11:1.00 under organic-inorganic treatments, which showed a deviation from its overall mean ratio of 1:1:1. This indicates that microbial resources do not have a balance. Vector analysis (vector angle <45°) and threshold elemental ratio analysis (RC:N-TERC:N > 0) further demonstrated that the microbial metabolism was limited by Nitrogen (N) under SNPK and MNPK treatments. N limitation further influenced soil microbial community structure and its dominated SOC decomposition. Specifically, Microbial communities transformed into a more oligotrophic-dominant condition (fungal, Acidobacteria, Chloroflexi) from copiotrophic-dominant (Proteobacteria, Actinobacteria) condition with increasing N limitation. Lysobacter genus and Blastocatellaceae family, in the bacterial communities along with the Mortierella elongata species in fungal communities, were markedly associated with the N limitation, which could be the critical biomarker that represented N limitation. Both correlation analysis and partial least squares path modeling showed significant positive effects of N limitation on the ratio of bacterial functional genes (Cellulase/Amylase), involved in recalcitrant SOC degradation.

Cardiac steroid ouabain transcriptionally increases human leukocyte antigen DR expression on monocytes.

Sepsis is a life-threatening disease characterized by acute multiple organ dysfunction and immunosuppression that is also called as immunoparalysis. Increasing evidence suggests that immunoparalysis largely contributes to the high mortality of sepsis, but the effective remedies are lacking. As an important antigen presentation molecule, human leukocyte antigen DR (HLA-DR) is remarkably down-regulated in sepsis-induced immunoparalysis, therefore, re-stimulation of HLA-DR expression is expected to be useful in reversing immunoparalysis. We previously described that ouabain, as a Na+, K+-ATPase ligand, is able to counteract immunoparalysis by regulating TH1 cytokines expression. Here, we expanded the finding that ouabain not only prevents LPS-induced down-regulation of HLA-DR on monocytes, but also transcriptionally activates HLA-DR α/ß expression mediated by CIITA4, IRF1, c-Src, and Stat1 phosphorylation. Since ouabain can improve sepsis-induced immunoparalysis by multiple mechanisms, we propose that ouabain may be a promising agent in septic therapy that deserves further investigation.

EMT and Cancer Cell Stemness Associated With Chemotherapeutic Resistance in Esophageal Cancer.

Drug resistance often occurs after chemotherapy in esophageal cancer patients, leading to cancer metastasis and recurrence. However, the relationship among cancer cell migration, recurrence and drug resistance in esophageal cancer drug-resistant cells has not been clearly explained. In this study, we constructed paclitaxel (PTX)-resistant esophageal cancer cells to explore the causes of drug resistance and poor prognosis after chemotherapy in esophageal cancer. Colony formation assay was used to evaluate the difference of colony formation between parental cells and drug resistance cells. Microsphere formation assay was used to examine the phenotype of stem cells. Wound healing and Transwell assays were used to detect the migration ability of drug-resistant cells. Western blotting and immunofluorescence assays were used to explore the mechanisms. Finally, we used nude mouse xenograft model to explore the tumor characteristics and the expression of relative proteins to verify our findings in vivo. Our study demonstrated that the cancer cell stemness characteristics exist in drug-resistant esophageal cancer cells, that expressed the biomarkers of stem cells and were prone to epithelial-mesenchymal transition (EMT). Our results suggested that the expression of EMT biomarkers and stemness-related proteins increased in esophageal cancer cells after continuously using chemotherapeutic drugs for a period of time. This study indicated that simultaneously targeting EMT and stemness could be a better strategy for the treatment of esophageal cancer drug resistance.