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Being exposed to electromagnetic fields has been suggested to increase the risk of developing Amyotrophic Lateral Sclerosis (ALS). Here, we investigated the effect of exposure to electromagnetic fields on ALS onset age and progression rate (ΔALSFRS-r). A large cohort of ALS patients (n = 1098) was geolocalized at the time of their diagnosis. Concomitantly, data on the distribution of power lines and repeater antennas (extremely low frequency electromagnetic fields) during the same period were retrieved. Exposure to each repeater antenna was calculated as the sum of 1/(distance from each antenna)^2. Exposure to power lines was calculated assuming each patient's address as the center of several circles of variable radius (100, 250, 500, 1000, and 2000 m). For each radius, the exposure was calculated as the length of the power lines included in the circle. Finally, patients were divided into low- and high-exposed based on the median of the exposure and compared using the Mann-Whitney test. A regression model (one for each radius) was also performed. Neither the onset age nor the ΔALSFRS-r differed among patients' low- and high-exposed to electromagnetic fields. Similarly, we could not find any significant relationship using the regression models. Our findings suggest that electromagnetic fields do not modify the ALS phenotype or progression.

MRI studies reported that ALS patients with bulbar and spinal onset showed focal cortical changes in corresponding regions of the motor homunculus. We evaluated the capability of brain 2-[We classified as pure bulbar (PB) patients with bulbar onset and a normal score in the spinal items of the ALSFRS-R, and as pure spinal (PS) patients with spinal onset and a normal score in the bulbar items at the time of PET. Forty healthy controls (HC) were enrolled. We compared PB and PS, and each patient group with HC. Metabolic clusters showing a statistically significant difference between PB and PS were tested to evaluate their accuracy in discriminating the two groups. We performed a leave-one-out cross-validation (LOOCV) over the entire dataset. Four classifiers were considered: support vector machines (SVM), K-nearest neighbours, linear classifier, and decision tree. Then, we used a separate test set, including 10% of patients, with the remaining 90% composing the training set.We included 63 PB, 271 PS, and 40 HC. PB showed a relative hypometabolism compared to PS in bilateral precentral gyrus in the regions of the motor cortex involved in the control of bulbar function. SVM showed the best performance, resulting in the lowest error rate in both LOOCV (4.19%) and test set (9.09 ± 2.02%).Our data support the concept of the focality of ALS onset and the use of 2-[

Background MRI studies reported that ALS patients with bulbar and spinal onset showed focal cortical changes in corresponding regions of the motor homunculus. We evaluated the capability of brain 2-[18F]FDG-PET to disclose the metabolic features characterizing patients with pure bulbar or spinal motor impairment. Methods We classified as pure bulbar (PB) patients with bulbar onset and a normal score in the spinal items of the ALSFRS-R, and as pure spinal (PS) patients with spinal onset and a normal score in the bulbar items at the time of PET. Forty healthy controls (HC) were enrolled. We compared PB and PS, and each patient group with HC. Metabolic clusters showing a statistically significant difference between PB and PS were tested to evaluate their accuracy in discriminating the two groups. We performed a leave-one-out cross-validation (LOOCV) over the entire dataset. Four classifiers were considered: support vector machines (SVM), K-nearest neighbours, linear classifier, and decision tree. Then, we used a separate test set, including 10% of patients, with the remaining 90% composing the training set. Results We included 63 PB, 271 PS, and 40 HC. PB showed a relative hypometabolism compared to PS in bilateral precentral gyrus in the regions of the motor cortex involved in the control of bulbar function. SVM showed the best performance, resulting in the lowest error rate in both LOOCV (4.19%) and test set (9.09 ± 2.02%). Conclusions Our data support the concept of the focality of ALS onset and the use of 2-[18F]FDG-PET as a biomarker for precision medicine-oriented clinical trials.