Matter from light-light scattering via Breit-Wheeler events produced by two interacting Compton sources

We present the dimensioning of a photon-photon collider based on Compton gamma sources for the observation of Breit-Wheeler pair production and QED \u3b3\u3b3 events. Two symmetric electron beams, generated by photocathodes and accelerated in linacs, produce two gamma ray beams through Compton back scattering with two J-class lasers. Tuning the system energy above the Breit-Wheeler cross section threshold, a flux of electron-positron pairs is generated out of light-light interaction. The process is analyzed by start-to-end simulations. Realistic numbers of the secondary particle yield, referring to existing state-of-the-art set-ups and a discussion of the feasibility of the experiment taking into account the background signal are presented

Oviposition activity and seasonal pattern of a population of Aedes (Stegomyia) aegypti (L.) (Diptera: Culicidae) in subtropical Argentina

Monthly oviposition activity and the seasonal density pattern of Aedes aegypti were studied using larvitraps and ovitraps during a research carried out by the Public Health Ministry of Salta Province, in Tartagal, Aguaray and Salvador Mazza cities, in subtropical Argentina. The A. aegypti population was active in both dry and wet seasons with a peak in March, accordant with the heaviest rainfall. From May to November, the immature population level remained low, but increased in December. Ae. aegypti oviposition activity increased during the fall and summer, when the relative humidity was 60% or higher. Eggs were found in large numbers of ovitraps during all seasons but few eggs were observed in each one during winter. The occurrence and the number of eggs laid were variable when both seasons and cities were compared. The reduction of the population during the winter months was related to the low in the relative humidity of the atmosphere. Significant differences were detected between oviposition occurrences in Tartagal and Aguaray and Salvador Mazza cities, but no differences in the number of eggs were observed. Two factors characterize the seasonal distribution pattern of Ae. aegypti in subtropical Argentina, the absence of a break during winter and an oviposition activity concomitant of the high relative humidity of the atmosphere.Facultad de Ciencias Naturales y Muse

Compton sources for the observation of elastic photon-photon scattering events

We present the design of a photon-photon collider based on conventional Compton gamma sources for the observation of elastic \u3b3\u3b3 scattering. Two symmetric electron beams, generated by photocathodes and accelerated in linacs, produce two primary gamma rays through Compton backscattering with two high energy lasers. The elastic photon-photon scattering is analyzed by start-to-end simulations from the photocathodes to the detector. A new Monte Carlo code has been developed ad hoc for the counting of the QED events. Realistic numbers of the secondary gamma yield, obtained by using the parameters of existing or approved Compton devices, a discussion of the feasibility of the experiment and of the nature of the background are presented

Unsuspected Involvement of Spinal Cord in Alzheimer Disease

OBJECTIVE: Brain atrophy is an established biomarker for dementia, yet spinal cord involvement has not been investigated to date. As the spinal cord is relaying sensorimotor control signals from the cortex to the peripheral nervous system and vice-versa, it is indeed a very interesting question to assess whether it is affected by atrophy due to a disease that is known for its involvement of cognitive domains first and foremost, with motor symptoms being clinically assessed too. We, therefore, hypothesize that in Alzheimer’s disease (AD), severe atrophy can affect the spinal cord too and that spinal cord atrophy is indeed an important in vivo imaging biomarker contributing to understanding neurodegeneration associated with dementia. METHODS: 3DT1 images of 31 AD and 35 healthy control (HC) subjects were processed to calculate volume of brain structures and cross-sectional area (CSA) and volume (CSV) of the cervical cord [per vertebra as well as the C2-C3 pair (CSA23 and CSV23)]. Correlated features (ρ > 0.7) were removed, and the best subset identified for patients’ classification with the Random Forest algorithm. General linear model regression was used to find significant differences between groups (p ≤ 0.05). Linear regression was implemented to assess the explained variance of the Mini-Mental State Examination (MMSE) score as a dependent variable with the best features as predictors. RESULTS: Spinal cord features were significantly reduced in AD, independently of brain volumes. Patients classification reached 76% accuracy when including CSA23 together with volumes of hippocampi, left amygdala, white and gray matter, with 74% sensitivity and 78% specificity. CSA23 alone explained 13% of MMSE variance. DISCUSSION: Our findings reveal that C2-C3 spinal cord atrophy contributes to discriminate AD from HC, together with more established features. The results show that CSA23, calculated from the same 3DT1 scan as all other brain volumes (including right and left hippocampi), has a considerable weight in classification tasks warranting further investigations. Together with recent studies revealing that AD atrophy is spread beyond the temporal lobes, our result adds the spinal cord to a number of unsuspected regions involved in the disease. Interestingly, spinal cord atrophy explains also cognitive scores, which could significantly impact how we model sensorimotor control in degenerative diseases with a primary cognitive domain involvement. Prospective studies should be purposely designed to understand the mechanisms of atrophy and the role of the spinal cord in AD

Unsuspected Involvement of Spinal Cord in Alzheimer Disease

Objective: Brain atrophy is an established biomarker for dementia, yet spinal cord involvement has not been investigated to date. As the spinal cord is relaying sensorimotor control signals from the cortex to the peripheral nervous system and vice-versa, it is indeed a very interesting question to assess whether it is affected by atrophy due to a disease that is known for its involvement of cognitive domains first and foremost, with motor symptoms being clinically assessed too. We, therefore, hypothesize that in Alzheimer’s disease (AD), severe atrophy can affect the spinal cord too and that spinal cord atrophy is indeed an important in vivo imaging biomarker contributing to understanding neurodegeneration associated with dementia. Methods: 3DT1 images of 31 AD and 35 healthy control (HC) subjects were processed to calculate volume of brain structures and cross-sectional area (CSA) and volume (CSV) of the cervical cord [per vertebra as well as the C2-C3 pair (CSA23 and CSV23)]. Correlated features (ρ > 0.7) were removed, and the best subset identified for patients’ classification with the Random Forest algorithm. General linear model regression was used to find significant differences between groups (p ≤ 0.05). Linear regression was implemented to assess the explained variance of the Mini-Mental State Examination (MMSE) score as a dependent variable with the best features as predictors. Results: Spinal cord features were significantly reduced in AD, independently of brain volumes. Patients classification reached 76% accuracy when including CSA23 together with volumes of hippocampi, left amygdala, white and gray matter, with 74% sensitivity and 78% specificity. CSA23 alone explained 13% of MMSE variance. Discussion: Our findings reveal that C2-C3 spinal cord atrophy contributes to discriminate AD from HC, together with more established features. The results show that CSA23, calculated from the same 3DT1 scan as all other brain volumes (including right and left hippocampi), has a considerable weight in classification tasks warranting further investigations. Together with recent studies revealing that AD atrophy is spread beyond the temporal lobes, our result adds the spinal cord to a number of unsuspected regions involved in the disease. Interestingly, spinal cord atrophy explains also cognitive scores, which could significantly impact how we model sensorimotor control in degenerative diseases with a primary cognitive domain involvement. Prospective studies should be purposely designed to understand the mechanisms of atrophy and the role of the spinal cord in AD

Frontal and Cerebellar Atrophy Supports FTSD-ALS Clinical Continuum

Background: Frontotemporal Spectrum Disorder (FTSD) and Amyotrophic Lateral Sclerosis (ALS) are neurodegenerative diseases often considered as a continuum from clinical, epidemiologic, and genetic perspectives. We used localized brain volume alterations to evaluate common and specific features of FTSD, FTSD-ALS, and ALS patients to further understand this clinical continuum. Methods: We used voxel-based morphometry on structural magnetic resonance images to localize volume alterations in group comparisons: patients (20 FTSD, seven FTSD-ALS, and 18 ALS) versus healthy controls (39 CTR), and patient groups between themselves. We used mean whole-brain cortical thickness (CT¯¯¯¯¯) to assess whether its correlations with local brain volume could propose mechanistic explanations of the heterogeneous clinical presentations. We also assessed whether volume reduction can explain cognitive impairment, measured with frontal assessment battery, verbal fluency, and semantic fluency. Results: Common (mainly frontal) and specific areas with reduced volume were detected between FTSD, FTSD-ALS, and ALS patients, confirming suggestions of a clinical continuum, while at the same time defining morphological specificities for each clinical group (e.g., a difference of cerebral and cerebellar involvement between FTSD and ALS). CT¯¯¯¯¯ values suggested extensive network disruption in the pathological process, with indications of a correlation between cerebral and cerebellar volumes and CT¯¯¯¯¯ in ALS. The analysis of the neuropsychological scores indeed pointed toward an important role for the cerebellum, along with fronto-temporal areas, in explaining impairment of executive, and linguistic functions. Conclusion: We identified common elements that explain the FTSD-ALS clinical continuum, while also identifying specificities of each group, partially explained by different cerebral and cerebellar involvement

A Machine Learning Approach for the Differential Diagnosis of Alzheimer and Vascular Dementia Fed by MRI Selected Features

Among dementia-like diseases, Alzheimer disease (AD) and vascular dementia (VD) are two of the most frequent. AD and VD may share multiple neurological symptoms that may lead to controversial diagnoses when using conventional clinical and MRI criteria. Therefore, other approaches are needed to overcome this issue. Machine learning (ML) combined with magnetic resonance imaging (MRI) has been shown to improve the diagnostic accuracy of several neurodegenerative diseases, including dementia. To this end, in this study, we investigated, first, whether different kinds of ML algorithms, combined with advanced MRI features, could be supportive in classifying VD from AD and, second, whether the developed approach might help in predicting the prevalent disease in subjects with an unclear profile of AD or VD. Three ML categories of algorithms were tested: artificial neural network (ANN), support vector machine (SVM), and adaptive neuro-fuzzy inference system (ANFIS). Multiple regional metrics from resting-state fMRI (rs-fMRI) and diffusion tensor imaging (DTI) of 60 subjects (33 AD, 27 VD) were used as input features to train the algorithms and find the best feature pattern to classify VD from AD. We then used the identified VD–AD discriminant feature pattern as input for the most performant ML algorithm to predict the disease prevalence in 15 dementia patients with a “mixed VD–AD dementia” (MXD) clinical profile using their baseline MRI data. ML predictions were compared with the diagnosis evidence from a 3-year clinical follow-up. ANFIS emerged as the most efficient algorithm in discriminating AD from VD, reaching a classification accuracy greater than 84% using a small feature pattern. Moreover, ANFIS showed improved classification accuracy when trained with a multimodal input feature data set (e.g., DTI + rs-fMRI metrics) rather than a unimodal feature data set. When applying the best discriminant pattern to the MXD group, ANFIS achieved a correct prediction rate of 77.33%. Overall, results showed that our approach has a high discriminant power to classify AD and VD profiles. Moreover, the same approach also showed potential in predicting earlier the prevalent underlying disease in dementia patients whose clinical profile is uncertain between AD and VD, therefore suggesting its usefulness in supporting physicians' diagnostic evaluations

Entomonematodos como agentes de control biológico de mosquitos en Argentina

Los culícidos constituyen uno de los grupos de insectos con mayor número de especies, siendo responsables de provocar numerosas enfermedades, la mayoría graves para el hombre. Ante este escenario, el uso de los enemigos naturales para su control es una alternativa segura para el ambiente, y específica, que puede ser eficaz a largo plazo. Los nematodos constituyen un grupo de parásitos y patógenos comunes en insectos que pueden producir importantes epizootias naturales con elevadas prevalencias. Son capaces de regular las poblaciones de insectos y mantenerlas por debajo de los niveles de daño económico y/o transmisión de enfermedades.Centro de Estudios Parasitológicos y de Vectore

Diversity, abundance, and presence of mosquito vectors of yellow fever in Northeast of Corrientes province

Yellow fever is currently increasing in importance in Argentina due to outbreaks in neighboring countries such as Brazil and Paraguay that cover a great part of the Misiones and Corrientes border. Due to several epizootic events in the south of Brazil between 2020 and 2021, in March and April 2021, we perform a mosquito survey to evaluate abundance and distributions of species vectors of Yellow fever virus (YFV) in several selvatic locations with presence of monkey Alouatta caraya in Northeast of Corrientes province: Las Marias, Tají Poty, Garabi, Garruchos, San Carlos, Colonia Liebig and near the Chimiray stream.Para acceder a la videoconferencia completa, hacer clic en "Enlace externo".Sociedad Latinoamericana de Ecología de Vectore

History of migraine and volume of brain infarcts: The italian project on stroke at young age (IPSYS)

BACKGROUND AND PURPOSE: Migraine has been shown to increase cerebral excitability, promote rapid infarct expansion into tissue with perfusion deficits, and result in larger infarcts in animal models of focal cerebral ischemia. Whether these effects occur in humans has never been properly investigated. METHODS: In a series of consecutive patients with acute ischemic stroke, enrolled in the setting of the Italian Project on Stroke at Young Age, we assessed acute as well as chronic infarct volumes by volumetric magnetic resonance imaging, and compared these among different subgroups identified by migraine status. RESULTS: A cohort of 591 patients (male, 53.8%; mean age, 37.5±6.4 years) qualified for the analysis. Migraineurs had larger acute infarcts than non-migraineurs (median, 5.9 cm3 [interquartile range (IQR), 1.4 to 15.5] vs. 2.6 cm3 [IQR, 0.8 to 10.1], P<0.001), and the largest volumes were observed in patients with migraine with aura (median, 9.0 cm3 [IQR, 3.4 to 16.6]). In a linear regression model, migraine was an independent predictor of increased log (acute infarct volumes) (median ratio [MR], 1.64; 95% confidence interval [CI], 1.22 to 2.20), an effect that was more prominent for migraine with aura (MR, 2.92; 95% CI, 1.88 to 4.54). CONCLUSION: s These findings reinforce the experimental observation of larger acute cerebral infarcts in migraineurs, extend animal data to human disease, and support the hypothesis of increased vulnerability to ischemic brain injury in people suffering migraine