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

A prediction model for short-term neurodevelopmental impairment in preterm infants with gestational age less than 32 weeks

IntroductionEarly identification and intervention of neurodevelopmental impairment in preterm infants may significantly improve their outcomes. This study aimed to build a prediction model for short-term neurodevelopmental impairment in preterm infants using machine learning method.MethodsPreterm infants with gestational age  &lt; 32 weeks who were hospitalized in The Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, and were followed-up to 18 months corrected age were included to build the prediction model. The training set and test set are divided according to 8:2 randomly by Microsoft Excel. We firstly established a logistic regression model to screen out the indicators that have a significant effect on predicting neurodevelopmental impairment. The normalized weights of each indicator were obtained by building a Support Vector Machine, in order to measure the importance of each predictor, then the dimension of the indicators was further reduced by principal component analysis methods. Both discrimination and calibration were assessed with a bootstrap of 505 resamples.ResultsIn total, 387 eligible cases were collected, 78 were randomly selected for external validation. Multivariate logistic regression demonstrated that gestational age(p = 0.0004), extrauterine growth restriction (p = 0.0367), vaginal delivery (p = 0.0009), and hyperbilirubinemia (0.0015) were more important to predict the occurrence of neurodevelopmental impairment in preterm infants. The Support Vector Machine had an area under the curve of 0.9800 on the training set. The results of the model were exported based on 10-fold cross-validation. In addition, the area under the curve on the test set is 0.70. The external validation proves the reliability of the prediction model.ConclusionA support vector machine based on perinatal factors was developed to predict the occurrence of neurodevelopmental impairment in preterm infants with gestational age  &lt; 32 weeks. The prediction model provides clinicians with an accurate and effective tool for the prevention and early intervention of neurodevelopmental impairment in this population

Altered interictal cerebral blood flow in generalized tonic-clonic seizure: an arterial spin labeling based MRI study

Objective To study the alteration of interictal cerebral blood flow (CBF) of patients with generalized tonic-clonic seizure (GTCS) by pulsed arterial spin labeling (PASL), and uncover the neuropathophysiological mechanism of GTCS. Methods Twenty⁃nine patients with GTCS were included in this study, and the same number of age- and gender-matched healthy volunteers were set as controls. PASL data of all subjects were obtained on a Siemens MAGNETOM Trio 3.0T scanner. The regional cerebral blood flow of GTCS patients were compared with the controls by two-sample t-test. Results Compared with the controls, GTCS patients presented decreased regional cerebral blood flow in bilateral thalumus, brainstem and cerebellum, and also a part of cortical area of the right precuneus (P < 0.05, for all). The alteration of interictal regional cerebral blood flow in bilateral thalumus was not significantly related to seizure duration (r = -0.090, P = 0.643) and seizure frequency (r = -0.115, P = 0.551). Conclusion The decreased regional cerebral blood flow in bilateral thalumus, brainstem and cerebellum indicates the "mesencephalic epilepsy" theory in GTCS, which may contribute to the understanding of the pathophysiological mechanism of GTCS. DOI：10.3969/j.issn.1672-6731.2011.04.01

Changes and significance of vascular endothelial injury markers in patients with diabetes mellitus and pulmonary thromboembolism

Abstract Background To investigate the changes and clinical significance of vascular endothelial injury markers in type 2 diabetes mellitus (T2DM) complicated with pulmonary embolism (PE). Methods This prospective study enrolled patients with T2DM hospitalized in one hospital from January 2021 to June 2022. Soluble thrombomodulin (sTM) (ELISA), von Willebrand factor (vWF) (ELISA), and circulating endothelial cells (CECs) (flow cytometry) were measured. PE was diagnosed by computed tomography pulmonary angiography (CTPA). Results Thirty participants were enrolled in each group. The plasma levels of sTM (151.22 ± 120.57 vs. 532.93 ± 243.82 vs. 1016.51 ± 218.00 pg/mL, P  676.68 pg/mL for the diagnosis of T2DM + PE achieved an AUC of 0.973, while vWF > 13.75 ng/mL achieved an AUC of 0.954. The combination of sTM and vWF above their cutoff points achieved an AUC of 0.993, with 100% sensitivity and 96.7% specificity. Conclusions Patients with T2DM show endothelial injury and dysfunction, which were worse in patients with T2DM and PE. High sTM and vWF levels have certain clinical predictive values for screening T2DM accompanied by PE