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OBJECTIVE: To investigate the clinical characteristics of neonatal necrotizing enterocolitis (NEC) complicated by intestinal perforation and predict the incidence of intestinal perforation in NEC. METHODS: Neonates diagnosed with NEC at the Affiliated Hospital of Zunyi Medical University from January 2012 to May 2022 were enrolled, and the clinical data were collected and analyzed retrospectively. The patients were divided into two groups based on intestinal perforation occurrence or not. Mann-Whitney U tests, t-tests, chi-square tests, and fisher's exact tests were performed between-group comparisons. Logistic and lasso regressions were applied to screen independent risk factors for concomitant bowel perforation, and R software (RMS package) was used to formulate the nomogram prediction model. In addition, the receiver operating curve (ROC) and the calibration curve were drawn to verify the predictive power, while decision curve analysis (DCA) was constructed to evaluate the clinical applicability of the nomogram model. RESULTS: One hundred eighty neonates with NEC were included, of which 48 had intestinal perforations, and 132 did not; the overall incidence of intestinal perforation was 26.67% (48/180). Bloody stool (OR = 5.60), APTT ≥ 50 s (OR = 3.22), thrombocytopenia (OR = 4.74), and hypoalbuminemia (OR = 5.56) were identified as independent risk variables for NEC intestinal perforation (P < 0.05) through multivariate logistic regression analysis. These factors were then applied to develop a nomogram prediction model (C-index = 0.838) by using the R software. The area under the curve (AUC) for the nomogram in the training and validation cohorts were 0.838 (95% Cl: 0.768, 0.908) and 0.802 (95% CI: 0.659, 0.944), respectively. The calibration curve shown that the nomogram has a good predictive ability for predicting the risk of intestinal perforation occurrence. And the decision curve and clinical impact curve analyses demonstrated good clinical utility of the nomogram model. CONCLUSION: We found that Bloody stool, APTT ≥ 50 s, Thrombocytopenia, and hypoalbuminemia could be used as independent risk factors for predicting intestinal perforation in neonates with NEC. The nomogram model based on these variables had high predictive values to identify NEC patients with intestinal perforation.
Subject(s)
Hypoalbuminemia , Intestinal Perforation , Thrombocytopenia , Humans , Infant, Newborn , Intestinal Perforation/complications , Nomograms , Retrospective Studies , Risk Factors , Factor Analysis, StatisticalABSTRACT
OBJECTIVE: To analyze the clinical characteristics of hemophagocytic syndrome (HLH) children with different EB virus (EBV) DNA loads, and to explore the relationship between differential indicators and prognosis. METHODS: Clinical data of 73 children with HLH treated in our hospital from January 2015 to April 2022 were collected. According to EBV DNA loads, the children were divided into negative group (≤5×102 copies/ml), low load group (>5×102-<5×105 copies/ml) and high load group (≥5×105copies/mlï¼. The clinical symptoms and laboratory indexes of the three groups were compared, and the ROC curve was used to determine the best cut-off value of the different indexes. Cox regression model was used to analyze the independent risk factors affecting the prognosis of children, and to analyze the survival of children in each group. RESULTS: The proportion of female children, the swelling rate of liver and spleen lymph nodes and the involvement rate of blood, liver, circulation and central nervous system in the high load group were higher than those in the negative group. The incidence of disseminated intravascular coagulation(DIC) and central nervous system(CNS) involvement in the high load group were higher than those in the low load group. The liver swelling rate and circulatory system involvement rate in the low load group were higher than those in the negative group(P<0.05). PLT counts in the high load group were significantly lower than those in the negative group, and the levels of GGT, TBIL, CK-MB, LDH, TG, SF, and organ involvement were significantly higher than those in the negative group. The levels of CK, LDH, SF and the number of organ involvement in the high load group were significantly higher than those in the low load group. The levels of GGT and TBIL in low load group were significantly higher than those in negative group. In terms of treatment, the proportion of blood purification therapy in the high and low load group was significantly higher than that in the negative group(P<0.01). ROC curve analysis showed that the best cut-off values of PLT, LDH, TG and SF were 49.5, 1139, 3.12 and 1812, respectively. The appellate laboratory indicators were dichotomized according to the cut-off value, and the differential clinical symptoms were included in the Cox regression model. Univariate analysis showed that LDH>1139 U/L, SF>1812 µg/L, dysfunction of central nervous system, number of organ damage, DIC and no blood purification therapy were the risk factors affecting the prognosis of children (P<0.05); Multivariate analysis shows that PLT≤49.5×109/L and dysfunction of central nervous system were risk factors affecting the prognosis of children (P<0.05). Survival analysis showed that there was no significant difference in the survival rate among the three groups. CONCLUSION: The incidence of adverse prognostic factors in children with HLH in the EBV-DNA high load group is higher, and there is no significant difference in the survival rate of the three groups after blood purification therapy. Therefore, early identification and application of blood purification therapy is of great significance for children with HLH in the high load group.
Subject(s)
Lymphohistiocytosis, Hemophagocytic , Humans , Child , Female , Retrospective Studies , Risk Factors , DNA , PrognosisABSTRACT
MnO2 is one of the most widespread and cheapest materials in nature that can both adsorb arsenic and oxidize arsenite [As(III)] to arsenate [As(V)]. In this study, column ß-MnO2 [CM] with the main facet of {110} and pincer ß-MnO2 [PM] with the facets of {110} and {101} are synthesized and used to remove arsenic in water under different conditions. For the adsorption process, the experimental data are fitted well with the pseudo second-order kinetic model; the Langmuir model is better than the Freundlich model to describe the adsorption equilibrium isotherms. Furthermore, the As(III) oxidation rate can be denoted by the pseudo zero-order kinetic model and is related to the O2 concentration, the pH value, the light source and the initial concentration of As(III). Finally, the oxidation mechanism is investigated, and the oxidant should be related to O2. It is interesting to find that these two kinds of ß-MnO2 exhibit different pH effects for both adsorption and oxidation. For As(III), the adsorption and oxidation abilities of CM follow the order pH 9 > pH 7 > pH 4, whereas the adsorption and oxidation orders of PM are pH 4 > pH 7 > pH 9.
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TiO2 is one of the most cheap materials which can both adsorb arsenic and oxidize arsenite [As(III)] to arsenate [As(V)]. In this study, anatase TiO2 crystals with different main facets such as {101}, {001} and {100} are synthesized and used to investigate arsenic adsorption kinetics, adsorption isotherms, photocatalytic oxidation (PCO) process and the pH effects. The adsorption kinetics of arsenic on TiO2 crystals can be described by the pseudo second-order kinetic model. For the adsorption isotherms, the Langmuir model is better than the Freundlich model for arsenic on these TiO2 crystals. For the PCO process, the rate of As(III) oxidation can be denoted by the pseudo first-order kinetic model. It should be noted that at neutral condition the adsorption and PCO rates of the three kinds of TiO2 crystals follow the order of {101}â¯>â¯{001}â¯>â¯{100}. The pH effect is above all important for both the arsenic adsorption and its PCO. The highest PCO speed appears at high pH values such as at pH 11 or 12.
Subject(s)
Arsenates/chemistry , Arsenic/chemistry , Arsenites/chemistry , Oxidants, Photochemical/chemistry , Titanium/chemistry , Water Pollutants, Chemical/chemistry , Water Purification/methods , Adsorption , Hydrogen-Ion Concentration , Oxidation-ReductionABSTRACT
Chronic cerebral hypoperfusion (CCH) is a basic pathological process that is comorbid with brain diseases, such as vascular Parkinsonism and Alzheimer's disease. Icariside II (ICS II), which is one of the main metabolites of icariin, has anti-inflammatory and antioxidant effects and protects against ischemic brain injury. This study aims to investigate the neuroprotective effects of ICS II on neuronal axon regeneration-related factors in a CCH rat model. Sprague-Dawley (SD) rats were divided into the following four groups: sham group, model group and 4 and 8 mg/kg/day ICS II administration groups. Learning and spatial memory functions were tested using a Morris water maze. Pathological changes were observed in the rat hippocampal tissue by hematoxylin and eosin (H&E) staining. Neuronal axon regeneration-related proteins (GAP-43, MAP-2 and Nogo-A) were observed by immunohistochemical staining and detected by the average optical density method. The results showed that 8 mg/kg/day of ICS II can effectively reduce the escape latency and prolong the target quadrant residence time at 12 weeks and that ICS II can improve the histopathological changes in the CA1 area of the rat hippocampus. Moreover, ICS II administration at 8 mg/kg/day significantly increased GAP-43 and MAP-2 expression and reduced Nogo-A expression in the CA1 area of the rat hippocampus at 12 weeks; however, significant differences were not observed at 4 and 8 weeks. Hence, ICS II at a dosage of 8 mg/kg/day could promote learning and memory abilities and improve histopathological changes in the rat hippocampus in a CCH rat model. These results may be related to the promotion of neuronal axon regeneration in the CA1 area of the hippocampus under increases in hippocampal GAP-43 and MAP-2 protein expression and decreased Nogo-A protein expression.
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BACKGROUND: Long intergenic noncoding RNAs (lincRNAs) are endogenous non-coding RNAs (ncRNAs) that are transcribed from 'intergenic' regions of the genome and may play critical roles in regulating gene expression through multiple RNA-mediated mechanisms. MicroRNAs (miRNAs) are single-stranded small ncRNAs of approximately 21-24 nucleotide (nt) that are involved in transcriptional and post-transcriptional gene regulation. While miRNAs functioning as mRNA repressors have been studied in detail, the influence of miRNAs on lincRNAs has seldom been investigated in plants. METHODS: LincRNAs as miRNA targets or decoys were predicted via GSTAr.pl script with a set of rules, and lincRNAs as miRNA targets were validated by degradome data. Conservation analysis of lincRNAs as miRNA targets or decoys were conducted using BLASTN and MAFFT. The function of lincRNAs as miRNA targets were predicted via a lincRNA-mRNA co-expression network, and the function of lincRNAs as miRNA decoys were predicted according to the competing endogenous RNA (ceRNA) hypothesis. RESULTS: In this work, we developed a computational method and systematically predicted 466 lincRNAs as 165 miRNA targets and 86 lincRNAs as 58 miRNA decoys in maize (Zea mays L.). Furthermore, 34 lincRNAs predicted as 33 miRNA targets were validated based on degradome data. We found that lincRNAs acting as miRNA targets or decoys are a common phenomenon, which indicates that the regulated networks of miRNAs also involve lincRNAs. To elucidate the function of lincRNAs, we reconstructed a miRNA-regulated network involving 78 miRNAs, 117 lincRNAs and 8834 mRNAs. Based on the lincRNA-mRNA co-expression network and the competing endogenous RNA hypothesis, we predicted that 34 lincRNAs that function as miRNA targets and 86 lincRNAs that function as miRNA decoys participate in cellular and metabolic processes, and play role in catalytic activity and molecular binding functions. CONCLUSIONS: This work provides a comprehensive view of miRNA-regulated networks and indicates that lincRNAs can participate in a layer of regulatory interactions as miRNA targets or decoys in plants, which will enable in-depth functional analysis of lincRNAs.