Arbovirus screening of mosquitoes collected in 2022 in Emilia-Romagna, Italy, with the implementation of a real-time PCR for the detection of Tahyna virus.

Several Arboviruses (Arthropod-borne virus) are a concrete health risk. While some arboviruses, such as the West Nile virus (WNV) and the Usutu virus (USUV) are actively surveyed, others are neglected, including the Tahyna virus (TAHV). In this work, we tested - searching for all the three viruses - 37,995 mosquitoes collected in 95 attractive traps, baited by carbon dioxide, distributed in the lowlands of Emilia-Romagna, northern Italy, between 19 July and 12 August 2022. Among the 668 pools obtained, WNV was detected in 45 pools of Culex (Cx.) pipiens and USUV was recorded in 24 pools of the same mosquito; ten of these Cx. pipiens pools tested positive for both WNV and USUV. Interestingly, we recorded a significant circulation of both WNV lineage 1 (WNV-L1) and lineage 2 (WNV-L2): WNV-L1 strains were detected in 40 pools, WNV-L2 strains in three pools and both lineages were detected in two pools. TAHV was detected in 8 different species of mosquitoes in a total of 37 pools: Aedes (Ae.) caspius (25), Ae. albopictus (5), Ae. vexans (3), Cx. pipiens (2), Ae. cinereus (1) and Anopheles maculipennis sl (1). The significant number of Ae. caspius-pools tested positive and the estimated viral load suggest that this mosquito is the principal vector in the surveyed area. The potential involvement of other mosquito species in the TAHV cycle could usefully be the subject of further experimental investigation. The results obtained demonstrate that, with adequate sampling effort, entomological surveillance is able to detect arboviruses circulating in a given area. Further efforts must be made to better characterise the TAHV cycle in the surveyed area and to define health risk linked to this virus.

Variant-driven early warning via unsupervised machine learning analysis of spike protein mutations for COVID-19.

Never before such a vast amount of data, including genome sequencing, has been collected for any viral pandemic than for the current case of COVID-19. This offers the possibility to trace the virus evolution and to assess the role mutations play in its spread within the population, in real time. To this end, we focused on the Spike protein for its central role in mediating viral outbreak and replication in host cells. Employing the Levenshtein distance on the Spike protein sequences, we designed a machine learning algorithm yielding a temporal clustering of the available dataset. From this, we were able to identify and define emerging persistent variants that are in agreement with known evidences. Our novel algorithm allowed us to define persistent variants as chains that remain stable over time and to highlight emerging variants of epidemiological interest as branching events that occur over time. Hence, we determined the relationship and temporal connection between variants of interest and the ensuing passage to dominance of the current variants of concern. Remarkably, the analysis and the relevant tools introduced in our work serve as an early warning for the emergence of new persistent variants once the associated cluster reaches 1% of the time-binned sequence data. We validated our approach and its effectiveness on the onset of the Alpha variant of concern. We further predict that the recently identified lineage AY.4.2 ('Delta plus') is causing a new emerging variant. Comparing our findings with the epidemiological data we demonstrated that each new wave is dominated by a new emerging variant, thus confirming the hypothesis of the existence of a strong correlation between the birth of variants and the pandemic multi-wave temporal pattern. The above allows us to introduce the epidemiology of variants that we described via the Mutation epidemiological Renormalisation Group framework.

Trigeminal Neuralgia Associated With a Solitary Pontine Lesion: A Case Report.

Trigeminal neuralgia associated with brainstem lesions is currently considered as a rare condition and only few patients have been reported so far in literature. Tohyama and colleagues recently proposed the nosological entity of trigeminal neuralgia associated with solitary pontine lesion, trying to categorize it as a new clinical syndrome on its own. Based on this description, trigeminal neuralgia associated with solitary pontine lesion patients have an identical clinical presentation compared to other patients with trigeminal neuralgia but have a solitary pontine lesion. The nature of the pontine lesion has been attributed to several etiologies, including ischemia, demyelination or previous pontine viral neuritis. In those patients with a putative demyelinating lesion, a definite diagnosis of multiple sclerosis cannot be made due to the lack of dissemination in space. Very little is known in relation to the cerebrospinal fluid characteristics of this population of patients. We present a case of a 42-year-old man suffering of trigeminal neuralgia associated with solitary pontine lesion with a possible demyelinating etiology. The patient herein described had an atypical trigeminal neuralgia associated with a single pontine lesion. The MRI characteristics of the lesion, along with the presence of oligoclonal bands in the cerebrospinal fluid, suggested a demyelinating etiology. Trigeminal neuralgia associated with a solitary pontine lesion may be categorized as a possible manifestation of solitary sclerosis. Future research need to reveal which features can predict the risk of conversion to clinically defined multiple sclerosis and which treatments modify this risk.

A Diagnosis of Inflammatory Pseudotumor of the Liver by Contrast Enhaced Ultrasound and Fine-Needle Biopsy: A Case Report.

Inflammatory pseudotumor (IPT) of the liver is a rare, benign lesion of unclear etiology, which may be misdiagnosed as hepatocellular carcinoma, cholangiocarcinoma, secondary tumor or abscess, because of its non-specific clinical, biochemical and radiologic findings. We present the case of a 48-old-year male in whom diagnosis of liver IPT was suspected by contrast enhanced ultrasound (CEUS) and confirmed by fine-needle liver biopsy. The diagnosis is in contrast to most of the literature reports in which the diagnosis was made only based on a surgical specimen. LEARNING POINTS: The inflammatory pseudotumor (IPT) of the liver is a rare benign disease that may be misdiagnosed as a malignant primary or secondary tumor.The diagnosis of IPT may be improved by the use of contrast enhanced ultrasound (CEUS) and the fine-needle liver biopsy without surgical intervention.The therapy of IPT may be monitored by ultrasonography (US) and CEUS.

Classification of Single Normal and Alzheimer's Disease Individuals from Cortical Sources of Resting State EEG Rhythms.

Previous studies have shown abnormal power and functional connectivity of resting state electroencephalographic (EEG) rhythms in groups of Alzheimer's disease (AD) compared to healthy elderly (Nold) subjects. Here we tested the best classification rate of 120 AD patients and 100 matched Nold subjects using EEG markers based on cortical sources of power and functional connectivity of these rhythms. EEG data were recorded during resting state eyes-closed condition. Exact low-resolution brain electromagnetic tomography (eLORETA) estimated the power and functional connectivity of cortical sources in frontal, central, parietal, occipital, temporal, and limbic regions. Delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-40 Hz) were the frequency bands of interest. The classification rates of interest were those with an area under the receiver operating characteristic curve (AUROC) higher than 0.7 as a threshold for a moderate classification rate (i.e., 70%). Results showed that the following EEG markers overcame this threshold: (i) central, parietal, occipital, temporal, and limbic delta/alpha 1 current density; (ii) central, parietal, occipital temporal, and limbic delta/alpha 2 current density; (iii) frontal theta/alpha 1 current density; (iv) occipital delta/alpha 1 inter-hemispherical connectivity; (v) occipital-temporal theta/alpha 1 right and left intra-hemispherical connectivity; and (vi) parietal-limbic alpha 1 right intra-hemispherical connectivity. Occipital delta/alpha 1 current density showed the best classification rate (sensitivity of 73.3%, specificity of 78%, accuracy of 75.5%, and AUROC of 82%). These results suggest that EEG source markers can classify Nold and AD individuals with a moderate classification rate higher than 80%.

Classification of Healthy Subjects and Alzheimer's Disease Patients with Dementia from Cortical Sources of Resting State EEG Rhythms: A Study Using Artificial Neural Networks.

Previous evidence showed a 75.5% best accuracy in the classification of 120 Alzheimer's disease (AD) patients with dementia and 100 matched normal elderly (Nold) subjects based on cortical source current density and linear lagged connectivity estimated by eLORETA freeware from resting state eyes-closed electroencephalographic (rsEEG) rhythms (Babiloni et al., 2016a). Specifically, that accuracy was reached using the ratio between occipital delta and alpha1 current density for a linear univariate classifier (receiver operating characteristic curves). Here we tested an innovative approach based on an artificial neural network (ANN) classifier from the same database of rsEEG markers. Frequency bands of interest were delta (2-4 Hz), theta (4-8 Hz Hz), alpha1 (8-10.5 Hz), and alpha2 (10.5-13 Hz). ANN classification showed an accuracy of 77% using the most 4 discriminative rsEEG markers of source current density (parietal theta/alpha 1, temporal theta/alpha 1, occipital theta/alpha 1, and occipital delta/alpha 1). It also showed an accuracy of 72% using the most 4 discriminative rsEEG markers of source lagged linear connectivity (inter-hemispherical occipital delta/alpha 2, intra-hemispherical right parietal-limbic alpha 1, intra-hemispherical left occipital-temporal theta/alpha 1, intra-hemispherical right occipital-temporal theta/alpha 1). With these 8 markers combined, an accuracy of at least 76% was reached. Interestingly, this accuracy based on 8 (linear) rsEEG markers as inputs to ANN was similar to that obtained with a single rsEEG marker (Babiloni et al., 2016a), thus unveiling their information redundancy for classification purposes. In future AD studies, inputs to ANNs should include other classes of independent linear (i.e., directed transfer function) and non-linear (i.e., entropy) rsEEG markers to improve the classification.

Differentiation of human umbilical cord-derived mesenchymal stem cells, WJ-MSCs, into chondrogenic cells in the presence of pulsed electromagnetic fields.

During cartilage regeneration, proliferation and differentiation of new chondrocytes are required and towards this goal, in humans electromagnetic stimulation has been used in order to increase the spontaneous regenerative capacity of bone and cartilage tissue. In vivo tissue engineering has pointed out that the absence of an abundant source of cells accelerating the healing process is a limiting factor in the ability to repair articular cartilage. Considering that the umbilical cord is a viable alternative source of mesenchymal stem cells (MSC), our study evaluated the possibility of a combined use of Wharton's jelly - mesenchymal stem cells (WJ-MSCs) and pulsed electromagnetic field (PMEF). The first effect observed was that compared with the untreated cells, when the WJ-MSCs were treated with PMEF, there was an increase in the division of cells and a rapid increase in cell density and the morphological and biochemical data showed that the treatment with PMEF reduced the time to obtain chondrocyte cell differentiation and deposition of extracellular matrix. Taken together these data indicate the capacity of PEMF to induce early differentiation of WJ-MSCs cells towards cartilaginous tissue.