Evaluation of the Edrophonium Challenge Test for Cervical Dystonia

A dual dopaminergic therapy with L-3,4-dihydroxyphenylalanine and chlorpromazine for the treatment of blepharospasm, a focal dystonia: Possible implications for striosomal D1 signaling

Impairment of balanced activity between dopamine D1 and D2 receptor functions in the striatum, particularly in striatal functional subdivisions (i.e., striosome and matrix compartments), has been proposed to underlie dystonia genesis. This study was undertaken to examine the therapeutic effect of dual dopaminergic modulation with L-3,4-dihydroxyphenylalanine (L-DOPA) and chlorpromazine (CPZ) in patients with blepharospasm, a focal dystonia. For this purpose, Dopacol tablets™ (L-DOPA 50 mg plus carbidopa 5 mg) and Wintermin™ (CPZ phenolphthalinate 180 mg/g) were used. Clinical evaluations were performed before and after an 8-week drug treatment interval using the Visual Analog Scale (VAS), Blepharospasm Disability Index (BSDI), modified VAS (mVAS), and Jankovic Rating Scale (JRS). The data were analyzed using non-parametric statistics. Results showed that in patients (n = 7) with blepharospasm, dystonia symptoms were significantly alleviated by the administration of both Dopacol tablets™ (one tablet × 3/day) and CPZ (5 mg × 3/day), as determined using the VAS, BSDI, mVAS, and JRS. In contrast, there was no improvement of dystonia symptoms in patients (n = 7) who ingested Dopacol tablets™ (one tablet × 3/day) alone, nor in those (n = 7) who ingested CPZ (5 mg × 3/day) alone. Thus, dual pharmacotherapy with L-DOPA and CPZ can exert a therapeutic effect on blepharospasm, suggesting that dystonia symptoms can be attenuated through dopaminergic modulation with inducing an increase in striatal D1-signals. Since dopamine D1 receptors are heavily enriched in the striosome compartment in the “human” striatum, our results also suggest that striosomal loss of D1-signaling may be important in the pathogenesis of dystonia.

Combining CT Images and Clinical Features of Four Periods to Predict Whether Patients Have Rectal Cancer

In this paper, we mainly use random forest and broad learning system (BLS) to predict rectal cancer. A total of 246 participants with computed tomography (CT) image records were enrolled. The total model in the training set (combined with imaging and clinical indicators) has the best prediction result, with the area under the curve (AUC) of 0.999 (95% confidence internal (CI): 0.996-1.000) and the accuracy of 0.990 (95%CI: 0.976-1.000). Model 3, the general model in the test set, has the best prediction result, with the AUC of 0.962 (95%CI: 0.915-1.000) and the accuracy of 0.920 (95%CI: 0.845-0.995). The results of the model using random forest prediction are compared with those using BLS prediction. It can be found that there is no statistical difference between the two results. Our prediction model combined with image features has a good prediction result, and this image feature is the most important among all features. Consequently, we can successfully predict rectal cancer through a combination of the clinical indicators and the comprehensive indicators of CT image characteristics in four different periods (plain scan, vein, artery, and excretion).

Cholinesterases and the fine line between poison and remedy

Acetylcholinesterase (AChE, EC 3.1.1.7) and butyrylcholinesterase (BChE, EC 3.1.1.8) are related enzymes found across the animal kingdom. The critical role of acetylcholinesterase in neurotransmission has been known for almost a century, but a physiological role for butyrylcholinesterase is just now emerging. The cholinesterases have been deliberately targeted for both therapy and toxicity, with cholinesterase inhibitors being used in the clinic for a variety of disorders and conversely for their toxic potential as pesticides and chemical weapons. Non-catalytic functions of the cholinesterases (ChEs) participate in both neurodevelopment and disease. Manipulating either the catalytic activities or the structure of these enzymes can potentially shift the balance between beneficial and adverse effect in a wide number of physiological processes.