Integrating clinical and biochemical markers: a novel nomogram for predicting lacunes in cerebral small vessel disease.

Background: Lacunes, a characteristic feature of cerebral small vessel disease (CSVD), are critical public health concerns, especially in the aging population. Traditional neuroimaging techniques often fall short in early lacune detection, prompting the need for more precise predictive models.

Methods: In this retrospective study, 587 patients from the Neurology Department of the Affiliated Hospital of Hebei University who underwent cranial MRI were assessed.

Unraveling the Predictors of Enlarged Perivascular Spaces: A Comprehensive Logistic Regression Approach in Cerebral Small Vessel Disease.

Background: This study addresses the predictive modeling of Enlarged Perivascular Spaces (EPVS) in neuroradiology and neurology, focusing on their impact on Cerebral Small Vessel Disease (CSVD) and neurodegenerative disorders.

Methods: A retrospective analysis was conducted on 587 neurology inpatients, utilizing LASSO regression for variable selection and logistic regression for model development. The study included comprehensive demographic, medical history, and laboratory data analyses.

Optimizing early neurological deterioration prediction in acute ischemic stroke patients following intravenous thrombolysis: a LASSO regression model approach.

Background: Acute ischemic stroke (AIS) remains a leading cause of disability and mortality globally among adults. Despite Intravenous Thrombolysis (IVT) with recombinant tissue plasminogen activator (rt-PA) emerging as the standard treatment for AIS, approximately 6-40% of patients undergoing IVT experience Early Neurological Deterioration (END), significantly impacting treatment efficacy and patient prognosis.

Objective: This study aimed to develop and validate a predictive model for END in AIS patients post rt-PA administration using the Least Absolute Shrinkage and Selection Operator (LASSO) regression approach.

Task-state skin potential abnormalities can distinguish major depressive disorder and bipolar depression from healthy controls.

Early detection of bipolar depression (BPD) and major depressive disorder (MDD) has been challenging due to the lack of reliable and easily measurable biological markers. This study aimed to investigate the accuracy of discriminating patients with mood disorders from healthy controls based on task state skin potential characteristics and their correlation with individual indicators of oxidative stress. A total of 77 patients with BPD, 53 patients with MDD, and 79 healthy controls were recruited.

Aberrant interhemispheric functional connectivity in major depressive disorder with and without anhedonia.

Objective: Anhedonia is a core feature of major depressive disorder (MDD), and as a subtype of depression, MDD with anhedonia may have exceptional neurobiological mechanisms. However, the neuropathology of anhedonia in MDD remains unclear. Thus, this study aimed to investigate the brain functional differences between MDD with and without anhedonia.

The Corrosion Behavior of AZ91D Magnesium Alloy in Simulated Haze Aqueous Solution.

The corrosion process of AZ91D magnesium alloy in simulated haze aqueous solution has been studied by electrochemical measurements, immersion tests and morphology characterization. Results show that AZ91D was corroded heavily in simulated haze aqueous solution due to the loose and breakable product film on the surface providing little corrosion barrier. The effect of different ions was investigated.