A clinical study of the effects of lead poisoning on the intelligence and neurobehavioral abilities of children

BACKGROUND: Lead is a heavy metal and important environmental toxicant and nerve poison that can destruction many functions of the nervous system. Lead poisoning is a medical condition caused by increased levels of lead in the body. Lead interferes with a variety of body processes and is toxic to many organs and issues, including the central nervous system. It interferes with the development of the nervous system, and is therefore particularly toxic to children, causing potentially permanent neural and cognitive impairments. In this study, we investigated the relationship between lead poisoning and the intellectual and neurobehavioral capabilities of children. METHODS: The background characteristics of the research subjects were collected by questionnaire survey. Blood lead levels were detected by differential potentiometric stripping analysis (DPSA). Intelligence was assessed using the Gesell Developmental Scale. The Achenbach Child Behavior Checklist (CBCL) was used to evaluate each child’s behavior. RESULTS: Blood lead levels were significantly negatively correlated with the developmental quotients of adaptive behavior, gross motor performance, fine motor performance, language development, and individual social behavior (P < 0.01). Compared with healthy children, more children with lead poisoning had abnormal behaviors, especially social withdrawal, depression, and atypical body movements, aggressions and destruction. CONCLUSION: Lead poisoning has adverse effects on the behavior and mental development of 2–4-year-old children, prescribing positive and effective precautionary measures

Characteristic Analysis of Salmonella Phage Pu29 and Its Application in Magnetic Separation and Enrichment of Salmonella

Salmonella pullorum phage Pu29 was comprehensively analyzed for its biological and genomic characteristics. A magnetic separation and enrichment technique for Salmonella was established using the phage Pu29 as a recognition element. The phage belonged to the genus Roufvirus and had an icosahedron head and an irreducible long tail. Pu29 had a wide host spectrum with an adsorption rate of 88.67% on host cells in 15 min, a latent period of 30 min, a rise period of 180 min, and a burst size of 115.74 PFU/cell. Meanwhile, Pu29 had good heat resistance (30–60 ℃) and pH tolerance (pH 4–11). Its genome was composed of 45 715 bp (GC content 46.08%) and 81 open reading frames (ORFs), including 18 ORFs with known functions that did not carry genes encoding toxicity or resistance factors. PhagePu29-MBs were prepared as a probe by coupling the phage with carboxylated nano-magnetic beads (MBs) through amide reaction. When 25 μg of the probe was incubated with Salmonella at 37 ℃ for 20 min, the highest capture rate of Salmonella of 83.93% and the lowest captured bacterial concentration of 45 CFU/mL were obtained. Transmission electron microscopy (TEM) was used to observe that PhagePu29-MBs could specifically capture Salmonella. In spiked samples, the highest capture rate of Salmonella separated and enriched by the probe reached 92.92%. The separation and enrichment process took approximately 30 min. Therefore, this study established a fast and highly specific magnetic separation method for Salmonella based on phage Pu29, which may lay the foundation for the development of a phage-based method for the rapid separation and enrichment of foodborne pathogens in food samples

MicroRNA-181a Functions as an Oncogene in Gastric Cancer by Targeting Caprin-1

MicroRNA-181a (miRNA-181a) is a multifaceted miRNA implicated in various cellular processes, particularly in cell fate determination and cellular invasion. It is frequently expressed aberrantly in human tumors and shows opposing functions in different types of cancers. In this study, we found that miRNA-181a is overexpressed in Gastric cancer (GC) tissues. Clinical and pathological analyses revealed that the expression of miRNA-181a is correlated with tumor size, lymph node metastasis, distant metastasis, and TNM stage. Kaplan-Meier analysis indicated that overexpression of miRNA-181a is associated with poor overall survival of patients with GC. Moreover, miRNA-181a is overexpressed in GC cells, and downregulation of miRNA-181a induced cell apoptosis and suppressed the proliferation, invasion, and metastasis of GC cells both in vitro and in vivo. Target prediction and luciferase reporter assay showed that caprin-1 was a direct target of miRNA-181a. Downregulation of caprin-1 expression resulted in a converse change with miRNA-181a in GC. Spearman’s correlation test confirmed that the expression of miRNA-181a expression was inversely correlated with that of caprin-1 in GC cells. Furthermore, the expression of caprin-1 increased after downregulation of miRNA-181a in the GC cells. Caprin-1 siRNA can rescue the oncogenic effect of miRNA-181a on GC cell proliferation, apoptosis, migration, and invasion. These findings suggest that miRNA-181a directly inhibits caprin-1 and promotes GC development. miRNA-181a could be a target for anticancer drug development

Analysis of characteristics of infectious pathogens in malignant tumors combined with bloodstream infection and significance of serum glucose detection

Background and purpose: The incidence rate of bloodstream infection (BSI) in patients with malignant tumor increases gradually with the progress of anti-tumor treatment. The treatment outcome is closely related to the infection of pathogen. At the same time, blood glucose also has a significant impact on the occurrence and development of the disease in this type of patients. This research aimed to retrospectively analyze the distribution characteristics of infectious pathogens isolated in patients with malignant tumors combined with bloodstream infection, the significance of serum glucose detection and prognostic value of its variation trend. Methods: Data of 434 malignant tumor patients with BSI and 409 patients without BSI treated in Fudan University Shanghai Cancer Center were retrospectively analyzed in this research. We utilized SPSS 26.0, Graphpad, Medcalc and Office software etc. to statistically analyze all the data covering clinical characteristics, infectious pathogens and biochemical parameters which were collected from Oct. 2019 to Dec. 2022. Results: The top three isolates in malignant tumor patients with BSI were Escherichia coli (29.4%), Klebsiella pneumoniae (13.8%) and Pseudomonas aeruginosa (4.8%). There were two or more mixed pathogenic bacteria in 8.5% patients. There were totally 100 deadly strains, among which the top three isolates were Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa, accounting for 21.0%, 12.0% and 10.0% of the diseases, respectively. Survival analysis showed that mixed infection had a poorer prognosis compared to single infection (P=0.000). The fasting blood glucose level at the initial stage of symptoms was significantly higher in malignant tumor patients with BSI (median 7.39 mmol/L, interquartile range 5.95-9.88 mmol/L) than in tumor patients without BSI (median 5.97 mmol/L, interquartile range 5.25-7.06 mmol/L, P=0.000). The area under curve (AUC) of the receiver operating characteristic (ROC) curve of the patients with BSI determined by the fasting glucose level at the beginning of the disease was 0.718, which was higher compared with procalcitonin (PCT), the classic diagnostic marker (AUC=0.708). The combination of these two parameters could even improve diagnostic efficiency (AUC=0.761). Furthermore, survival analysis showed that the prognosis of patients with high level of fasting glucose at the beginning of BSI was poor (HR=3.067, 95% CI: 1.375-6.838, P=0.000). In addition, the greater the glycemic variability at the beginning of BSI, the higher the risk of death was shown (HR=2.150, 95% CI: 1.125-4.109, P&lt;0.01). Conclusion: It is suggested that patients with clinically suspected BSI should use antibiotics based on the distribution of isolates, and glucose levels should be monitored to access the infection early so as to take timely intervention and obtain greater treatment benefits

Acute Mountain Sickness Is Associated With a High Ratio of Endogenous Testosterone to Estradiol After High-Altitude Exposure at 3,700 m in Young Chinese Men

Background: A large proportion of populations suffer from acute mountain sickness (AMS) after exposure at high altitude. AMS is closely related with age and gender implying that the sex hormones may play critical roles in AMS. Our observational study aimed to identify the association between the endogenous testosterone (T), estradiol (E2) and AMS.Methods: A total of 113 subjects were recruited in 2012. The participants were evaluated at 500 m and after acute (1 day) and short-term (7 days) high-altitude exposure at 3,700 m. The subjects also completed a case report form questionnaire and underwent blood pressure measurements and an echocardiography examination. The red blood cell (RBC) count, Hb concentration ([Hb]), hematocrit (HCT), E2, T, and erythropoietin (EPO) were measured.Results: Upon acute high-altitude exposure, E2 and EPO were significantly lower in AMS+ group, and T/E2 and stroke volume were higher. On the 1st day, AMS score correlated positively with the T/E2 ratio while it negatively correlated with E2. After 7 days at 3,700 m, the AMS+ subjects had higher erythropoietic parameters: EPO, T, and T/E2 were significantly higher in the AMS+ group. [Hb], RBC count, HCT, EPO, T and T/E2 were also correlated with AMS score. EPO, HCT, and the RBC count were also correlated with T/E2. Regression analyses indicated that T/E2 significantly correlated to AMS score and T/E2 on the 1st day was an independent predictor for AMS on the 7th day.Conclusion: AMS was correlated with T/E2 ratio and EPO. After short-term exposure, higher T/E2 may contribute to AMS together with EPO via erythropoiesis. Furthermore, T/E2 level at high altitude in the early stage was an independent predictor for AMS in the latter stage

Word Embeddings via Causal Inference: Gender Bias Reducing and Semantic Information Preserving

With widening deployments of natural language processing (NLP) in daily life, inherited social biases from NLP models have become more severe and problematic. Previous studies have shown that word embeddings trained on human-generated corpora have strong gender biases that can produce discriminative results in downstream tasks. Previous debiasing methods focus mainly on modeling bias and only implicitly consider semantic information while completely overlooking the complex underlying causal structure among bias and semantic components. To address these issues, we propose a novel methodology that leverages a causal inference framework to effectively remove gender bias. The proposed method allows us to construct and analyze the complex causal mechanisms facilitating gender information flow while retaining oracle semantic information within word embeddings. Our comprehensive experiments show that the proposed method achieves state-of-the-art results in gender-debiasing tasks. In addition, our methods yield better performance in word similarity evaluation and various extrinsic downstream NLP tasks

Modelling Survival Events with Longitudinal Covariates Measured with Error

In survival analysis, time-dependent covariates are usually present as longitudinal data collected periodically and measured with error. The longitudinal data can be assumed to follow a linear mixed effect model and Cox regression models may be used for modelling of survival events. The hazard rate of survival times depends on the underlying time-dependent covariate measured with error, which may be described by random effects. Most existing methods proposed for such models assume a parametric distribution assumption on the random effects and specify a normally distributed error term for the linear mixed effect model. These assumptions may not be always valid in practice. In this article, we propose a new likelihood method for Cox regression models with error-contaminated time-dependent covariates. The proposed method does not require any parametric distribution assumption on random effects and random errors. Asymptotic properties for parameter estimators are provided. Simulation results show that under certain situations the proposed methods are more efficient than the existing methods. © 2013 Copyright Taylor and Francis Group, LLC

Prediction of Drought-Resistant Genes in Arabidopsis thaliana Using SVM-RFE

Background: Identifying genes with essential roles in resisting environmental stress rates high in agronomic importance. Although massive DNA microarray gene expression data have been generated for plants, current computational approaches underutilize these data for studying genotype-trait relationships. Some advanced gene identification methods have been explored for human diseases, but typically these methods have not been converted into publicly available software tools and cannot be applied to plants for identifying genes with agronomic traits. Methodology: In this study, we used 22 sets of Arabidopsis thaliana gene expression data from GEO to predict the key genes involved in water tolerance. We applied an SVM-RFE (Support Vector Machine-Recursive Feature Elimination) feature selection method for the prediction. To address small sample sizes, we developed a modified approach for SVM-RFE by using bootstrapping and leave-one-out cross-validation. We also expanded our study to predict genes involved in water susceptibility. Conclusions: We analyzed the top 10 genes predicted to be involved in water tolerance. Seven of them are connected to known biological processes in drought resistance. We also analyzed the top 100 genes in terms of their biological functions. Our study shows that the SVM-RFE method is a highly promising method in analyzing plant microarray data for studyin

Evaluation of Tolerability, Pharmacokinetics and Pharmacodynamics of Vicagrel, a Novel P2Y12 Antagonist, in Healthy Chinese Volunteers

Background: Vicagrel is a novel anti-platelet drug and hydrolyzed to the same intermediate as clopidogrel via esterase, instead of CYP2C19. Here we report the first clinical trial on the tolerability, pharmacokinetics and pharmacodynamics of different doses of vicagrel, and comparison with clopidogrel in healthy Chinese volunteers.Methods: This study was conducted in two parts. Study I was a dose-escalating (5–15 mg) study. For each dose, 15 participants were randomized into three groups (total n = 45); nine participants were given vicagrel, three were given clopidogrel, and three were given a placebo. Study II was conducted to assess interactions between vicagrel and aspirin in 15 healthy participants. The plasma concentrations of the metabolites of vicagrel and clopidogrel were determined using a LC-MS/MS method. Platelet aggregation was assessed using the VerifyNow-P2Y12 assay.Results: Vicagrel (5–15 mg per day) dosing for 10 days or addition of aspirin was well tolerated in healthy volunteers. The exposure of the active metabolite increased proportionally across the dose range and was higher (~10-fold) than clopidogrel. The levels of IPA dosing 75 mg clopidogrel were between the responses of 5 mg and 10 mg vicagrel. After a single loading dose of vicagrel (30 mg) and a once-daily maintenance dose (7.5 mg) for 8 days, the maximum inhibition of platelet aggregation was similar to that seen with the combined use of vicagrel and aspirin (100 mg/day).Conclusion: Oral vicagrel demonstrated a favorable safety profile and excellent anti-platelet activity, which could be a promising P2Y12 antagonist as anti-platelet drug and can be further developed in phase II/III studies, and marketing for the unmet medical needs of cardiovascular diseases. The study was registered at http://www.chictr.org.cn (ChiCTR-IIR-16009260)