A multi-subgroup predictive model based on clinical parameters and laboratory biomarkers to predict in-hospital outcomes of plasma exchange-centered artificial liver treatment in patients with hepatitis B virus-related acute-on-chronic liver failure.

Background: Postoperative risk stratification is challenging in patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) who undergo artificial liver treatment. This study characterizes patients' clinical parameters and laboratory biomarkers with different in-hospital outcomes. The purpose was to establish a multi-subgroup combined predictive model and analyze its predictive capability. Methods: We enrolled HBV-ACLF patients who received plasma exchange (PE)-centered artificial liver support system (ALSS) therapy from May 6, 2017, to April 6, 2022. There were 110 patients who died (the death group) and 110 propensity score-matched patients who achieved satisfactory outcomes (the survivor group). We compared baseline, before ALSS, after ALSS, and change ratios of laboratory biomarkers. Outcome prediction models were established by generalized estimating equations (GEE). The discrimination was assessed using receiver operating characteristic analyses. Calibration plots compared the mean predicted probability and the mean observed outcome. Results: We built a multi-subgroup predictive model (at admission; before ALSS; after ALSS; change ratio) to predict in-hospital outcomes of HBV-ACLF patients who received PE-centered ALSS. There were 110 patients with 363 ALSS sessions who survived and 110 who did not, and 363 ALSS sessions were analyzed. The univariate GEE models revealed that several parameters were independent risk factors. Clinical parameters and laboratory biomarkers were entered into the multivariate GEE model. The discriminative power of the multivariate GEE models was excellent, and calibration showed better agreement between the predicted and observed probabilities than the univariate models. Conclusions: The multi-subgroup combined predictive model generated accurate prognostic information for patients undergoing HBV-ACLF patients who received PE-centered ALSS.

Aridity modifies the responses of plant stoichiometry to global warming and nitrogen deposition in semi-arid steppes.

Global warming and nitrogen (N) deposition are known to unbalance the stoichiometry of carbon (C), N, and phosphorus (P) in terrestrial plants, but it is unclear how water availability regulates their effects along a natural aridity gradient. Here, we conducted manipulative experiments to determine the effects of experimental warming (WT) and N addition (NT) on plant stoichiometry in desert, typical, and meadow steppes with decreasing aridity. WT elevated air temperatures by 1.2-2.9 °C using open-top chambers. WT increased forb C:N ratio and thus its N use efficiency and competitiveness in desert steppes, whereas WT reduced forb C:N and C:P ratios in typical and meadow steppes. Plant N:P ratio, which reflects nutrient limitation, was reduced by WT in desert steppes but not for typical or meadow steppes. NT reduced plant C:N ratios and increased N:P ratios in all three steppes. NT reduced forb C:P ratios in desert and typical steppes, but it enhanced grass C:P ratio in meadow steppes, indicating an enhancement of P use efficiency and competitiveness of grasses in wet steppes. WT and NT had synergetic effects on grass C:N and C:P ratios in all three steppes, which helps to increase grasses' productivity. Under WT or NT, the changes in community C:N ratio were positively correlated with increasing aridity, indicating that aridity increases plants' N use efficiency. However, aridity negatively affected the changes in N:P ratios under NT but not WT, which suggests that aridity mitigates P limitation induced by N deposition. Our results imply that warming could shift the dominant functional group into forbs in dry steppes due to altered stoichiometry, whereas grasses become dominated plants in wet steppes under increasing N deposition. We suggest that global changes might break the stoichiometric balance of plants and water availability could strongly modify such processes in semi-arid steppes.

Clinical Parameters and Metabolomic Biomarkers That Predict Inhospital Outcomes in Patients With ST-Segment Elevated Myocardial Infarctions.

BACKGROUND: Postoperative risk stratification is challenging in patients with ST-segment elevation myocardial infarction (STEMI) who undergo percutaneous coronary intervention. This study aimed to characterize the metabolic fingerprints of patients with STEMI with different inhospital outcomes in the early stage of morbidity and to integrate the clinical baseline characteristics to develop a prognostic prediction model. METHODS: Plasma samples were collected retrospectively from two propensity score-matched STEMI cohorts from May 6, 2020 to April 20, 2021. Cohort 1 consisted of 48 survivors and 48 non-survivors. Cohort 2 included 48 patients with unstable angina pectoris, 48 patients with STEMI, and 48 age- and sex-matched healthy controls. Metabolic profiling was generated based on ultra-performance liquid chromatography and a mass spectrometry platform. The comprehensive metabolomic data analysis was performed using MetaboAnalyst version 5.0. The hub metabolite biomarkers integrated into the model were tested using multivariate linear support vector machine (SVM) algorithms and a generalized estimating equation (GEE) model. Their predictive capabilities were evaluated using areas under the curve (AUCs) of receiver operating characteristic curves. RESULTS: Metabonomic analysis from the two cohorts showed that patients with STEMI with different outcomes had significantly different clusters. Seven differentially expressed metabolites were identified as potential candidates for predicting inhospital outcomes based on the two cohorts, and their joint discriminative capabilities were robust using SVM (AUC = 0.998, 95% CI 0.983-1) and the univariate GEE model (AUC = 0.981, 95% CI 0.969-0.994). After integrating another six clinical variants, the predictive performance of the updated model improved further (AUC = 0.99, 95% CI 0.981-0.998). CONCLUSION: A survival prediction model integrating seven metabolites from non-targeted metabonomics and six clinical indicators may generate a powerful early survival prediction model for patients with STEMI. The validation of internal and external cohorts is required.

Aridity stimulates responses of root production and turnover to warming but suppresses the responses to nitrogen addition in temperate grasslands of northern China.

Global warming and nitrogen (N) deposition are known to affect root dynamics in grasslands. However, previous studies were based only on a single ecosystem type, so it is unclear how warming and N addition affect root traits (root biomass, root-shoot ratio, root production and turnover) along the aridity gradient. In this study, we conducted an experiment to determine the effects of warming and N addition on root traits in desert, typical, and meadow grasslands in northern China, where the aridity gradually decreases from west to east across the region. Warming increased root-shoot ratio in dry year due to decline in soil water, but had a downward trend in root production and turnover in all three grasslands. N addition decreased root-shoot ratio in humid year due to increase in soil N, whereas did not significantly affect root production in any grasslands and increased root turnover in desert and meadow grasslands rather than typical grassland. Warming combined with N addition had negatively additive effects on root turnover in typical and meadow grasslands rather than desert grassland. N addition-induced changes in root biomass and root-shoot ratio were negatively affected by aridity in dry year. Aridity positively affected responses of root production and turnover to warming but negatively affected those responses to N addition. However, root-shoot ratio, root production and turnover under warming combined with N addition were not affected by aridity. Our results suggest that warming suppresses root carbon (C) input but N addition may exacerbate it in temperate grasslands, and warming combined with N addition suppresses it only in wet grasslands. Aridity promotes root C input under warming but suppresses it under N addition. However, aridity may little affect soil C and nutrient dynamics under global warming combined with N deposition in temperate grasslands in the future.

Effects of prebiotics on immunologic indicators and intestinal microbiota structure in perioperative colorectal cancer patients.

OBJECTIVE: The aim of the present study was to investigate the effects of prebiotics (containing fructooligosaccharides, xylooligosaccharides, polydextrose, and resistant dextrin) intake on immune function and intestinal microbiota structure in perioperative patients with colorectal cancer (CRC). METHODS: A randomized, double-blind, no-treatment parallel control clinical trial involving 140 perioperative patients (90 men and 50 women, aged 40-75 y) with CRC was performed. Patients were randomly divided into two groups: an intervention group (prebiotic group, n = 70) that received prebiotic supplementation of 30 g/d for 7 d, and a control group (non-prebiotic group, n = 70) that received no prebiotic supplementation. The nutritional and immunologic indices were evaluated for both groups before and after operation and analyzed against baseline values. Moreover, fecal samples were collected from 40 patients randomly chosen from the two groups to study intestinal microbiota, which was analyzed by sequencing the V3-V4 region of 16S ribosomal DNA using the Illumina (San Diego, CA) MiSeq (PE 2 × 300 bp) platform. RESULTS: Oral intake of prebiotics produced significant effects on immunologic indices in both the preoperative and postoperative periods, but the patterns of effects were different. In the preoperative period, prebiotics increased serum levels of immunoglobulin G (IgG; P = 0.02), IgM (P = 0.00), and transferrin (P = 0.027; all P < 0.05). In the postoperative period, enhanced levels of IgG (P = 0.003), IgA (P = 0.007), suppressor/cytotoxic T cells (CD3+CD8+; P = 0.043), and total B lymphocytes (CD19+; P = 0.012) were identified in the prebiotic group (all P < 0.05). The differences in the intestinal microbiota at the phylum level were not statistically significant between the intervention and control groups (P > 0.05). At the genus level, prebiotics increased the abundance of Bifidobacterium (P = 0.017) and Enterococcus (P = 0.02; both P < 0.05) but decreased the abundance of Bacteroides (P = 0.04) in the preoperative period (all P < 0.05). In the postoperative period, the abundance of Bacteroides (P = 0.04) was decreased, but the abundance of Enterococcus (P = 0.00), Bacillus (P = 0.01), Lactococcus (P = 0.00), and Streptococcus (P = 0.037) increased in the non-prebiotic group (all P < 0.05); however, no significant change was identified in the abundance of Enterococcus (P = 0.56), Lactococcus (P = 0.07), and Streptococcus (P = 0.56) as a result of prebiotic intervention in this period (all P > 0.05). The abundance of Escherichia-Shigella was increased after prebiotic intake in the postoperative period (P = 0.014, P < 0.05). There was a notable trend of decline in the abundance of intestinal microbiota from preoperative to postoperative in the non-prebiotic group. CONCLUSIONS: Prebiotic intake is recommended to improve serum immunologic indicators in patients with CRC 7 d before operation. Prebiotics improved the abundance of four commensal microbiota containing opportunistic pathogens in patients with CRC. Surgical stress decreased the abundance of most intestinal microbiota in the intestinal tract but increased the abundance of some opportunistic pathogens and commensal microbiota. Bacteroides is a relevant bacterial species for further research on the mechanism of prebiotics.

A probe with double acetoxyl moieties for hydrazine and its application in living cells.

As a common chemical reductant, hydrazine has been widely used in various fields. However, its high toxicity to human and environment have also attracted people's attention. In this work, a new fluorescence "turn-on" probe based on coumarin for hydrazine was successfully synthesized. The probe with double acetoxyl moieties as the reaction sites can obtain the detection limit as low as 2.98 nM for the detection of hydrazine in distilled water, which was lower than the U.S. Environmental Protection Agency standard (10 ppb). In addition, it also responded obvious fluorescence enhancement and high selectivity to hydrazine over other molecules. Furthermore, this probe could visualize the hydrazine in living cells.

[Application of Combined Detection of Fusion Gene and BIOMED-2 Standardized Ig Gene Rearrangement System in Childhood B-cell Acute Lymphoblastic Leukemia].

OBJECTIVE: To explore the application of combined detection of fusion gene and BIOMED-2 standardized immunoglobulin (Ig) gene rearrangement system in diagnosis and treatment of children with acute lymphoblastic leukemia (ALL). METHODS: Multiplex-PCR amplifications and RQ-PCR of RNA/DNA were performed using ALL fusion gene detection kit and BIOMED-2 primer. The Ig gene rearrangements were analyzed by using PCR fragment analysis system. RESULTS: Out of 251 children with B-ALL, 77 cases were TEL-AML1(+) , 28 cases were E2A-PBX1(+) , 10 cases were MLL-AF4(+) , 11 cases were BCR-ABL(+) , the total positive rate was 50.2%, 82.5% showed IgH VH-JH rearrangement, 53.4% showed IgK rearrangement. The positive rate of combined detection of fusion gene and gene rearrangement was 99%. E2A-PBX1(+) and MLL-AF4(+) with IgK(+) gene rearrangement group was compared with negative control group, the difference was statistically significant (P < 0.001 or P = 0.005); 105 ALL fusion gene positive cases had been detected by fluorescence in situ hybridization (FISH) simultaneously, the accordance rate of fusion gene and FISH was more than 94%. CONCLUSION: The combined detection of ALL fusion gene and BIOMED-2 standardized clonality analysis system can improve the positive detected rate of B-ALL dramatically, and make the grouping of disease prognosis more accurately; this combined detection is a more faster and sensitive method than FISH.

Increasing aridity, temperature and soil pH induce soil C-N-P imbalance in grasslands.

Due to the different degrees of controls exerted by biological and geochemical processes, climate changes are suggested to uncouple biogeochemical C, N and P cycles, influencing biomass accumulation, decomposition and storage in terrestrial ecosystems. However, the possible extent of such disruption in grassland ecosystems remains unclear, especially in China's steppes which have undergone rapid climate changes with increasing drought and warming predicted moving forward in these dryland ecosystems. Here, we assess how soil C-N-P stoichiometry is affected by climatic change along a 3500-km temperate climate transect in Inner Mongolia, China. Our results reveal that the soil from more arid and warmer sites are associated with lower soil organic C, total N and P. The ratios of both soil C:P and N:P decrease, but soil C:N increases with increasing aridity and temperature, indicating the predicted decreases in precipitation and warming for most of the temperate grassland region could lead to a soil C-N-P decoupling that may reduce plant growth and production in arid ecosystems. Soil pH, mainly reflecting long-term climate change in our sites, also contributes to the changing soil C-N-P stoichiometry, indicating the collective influences of climate and soil type on the shape of soil C-N-P balance.

Overexpression of minichromosome maintenance 2 predicts poor prognosis in patients with gastric cancer.

We examined the expression of minichromosome maintenance 2 (MCM2) in gastric cancer and adjacent normal tissues and estimated the possible value of MCM2 as a novel prognostic marker. Using real-time PCR, western blotting and immunohistochemistry, we examined the expression of MCM2 in gastric carcinoma and paired normal gastric mucosa. Statistical analysis of the expression of MCM2 mRNA and protein in gastric cancer and normal tissues was performed to evaluate the relationship between MCM2 expression and clinicopathological characteristics in gastric cancer. The expression of MCM2 mRNA and protein in gastric carcinomas was significantly higher compared to that in normal gastric mucosa (P=0.04). Immunohistochemistry analysis showed that MCM2 expression was significantly up-regulated in tumor and metastastic lymph node tissues compared with the corresponding non-cancerous mucosa (P<0.05). Positive expression of MCM2 was significantly associated with patient age, T category and the presence of lymph node metastasis (P<0.05). There were no differences between MCM2 expression and gender, tumor size, tumor location, M category, International Union Against Cancer (UICC) stage, vessel invasion and tumor differentiation. Patients with negative tumor MCM2 expression displayed a better survival time than those with positive MCM2 expression (P<0.05). Survival analysis showed that positive MCM2 expression (P<0.05), T stage (P<0.05) and N stage (P<0.05) were independent prognostic factors for disease-free survival (DFS) and overall survival (OS). Our data suggest that MCM2 could serve as a novel prognostic biomarker in gastric carcinoma.

Cloning and expression of special F protein from human liver.

AIM: To clone human liver special F protein and to express it in a prokaryotic system. METHODS: Total RNA was isolated from human liver tissue and first-strand cDNA was reverse transcribed using the PCR reverse primer. Following this, cDNA of the F protein was ligated into the clone vector pUCm-T. The segment of F protein's cDNA was subcloned into the expression vector pET-15b and transformed into E. coli BL21 (DE3) pLyss. Isopropy-beta-D-thiogalactoside (IPTG) was then used to induce expression of the target protein. RESULTS: The cDNA clone of human liver special F protein (1134bp) was successfully produced, with the cDNA sequence being published in Gene-bank: DQ188836. We confirmed the expression of F protein by Western blot with a molecular weight of 43 kDa. The expressed protein accounted for 40% of the total protein extracted. CONCLUSION: F protein expresses cDNA clone in a prokaryotic system, which offers a relatively simple way of producing sufficient quantities of F protein and contributes to understanding the principal biological functions of this protein.