Electrical Characterization of SiPM as a Function of Test Frequency and Temperature

Silicon Photomultipliers (SiPM) represent a promising alternative to classical photomultipliers, for instance, for the detection of photons in high energy physics and medical physics. In the present work, electrical characterizations of test devices - manufactured by ST Microelectronics - are presented. SiPMs with an area of 3.5x3.5 micron^2 and a cell pitch of 54 micron were manufactured as arrays of 64x64 cells and exhibiting a fill factor of 31%. The capacitance of SiPMs was measured as a function of reverse bias voltage at frequencies ranging from from 20 Hz up to 1 MHz and temperatures from 300 K down to 85 K. While leakage currents were measured at temperatures from 400 K down to 85 K. Thus, the threshold voltage - i.e., voltage corresponding to that at which the multiplication regime for the leakage current begins - could be determined as a function of temperature. Finally, an electrical model suited to reproduce the dependence of the frequency dependence of capacitance is presented.Comment: To appear on the Proceedings of the 13th ICATPP Conference on Astroparticle, Particle, Space Physics and Detectors for Physics Applications, Villa Olmo (Como, Italy), 3-7 October, 2011, to be published by World Scientific (Singapore

Fiberless, multi-channel fNIRS-EEG system based on silicon photomultipliers: Towards sensitive and ecological mapping of brain activity and neurovascular coupling

Portable neuroimaging technologies can be employed for long-term monitoring of neurophysiological and neuropathological states. Functional Near-Infrared Spectroscopy (fNIRS) and Electroencephalography (EEG) are highly suited for such a purpose. Their multimodal integration allows the evaluation of hemodynamic and electrical brain activity together with neurovascular coupling. An innovative fNIRS-EEG system is here presented. The system integrated a novel continuous-wave fNIRS component and a modified commercial EEG device. fNIRS probing relied on fiberless technology based on light emitting diodes and silicon photomultipliers (SiPMs). SiPMs are sensitive semiconductor detectors, whose large detection area maximizes photon harvesting from the scalp and overcomes limitations of fiberless technology. To optimize the signal-to-noise ratio and avoid fNIRS-EEG interference, a digital lock-in was implemented for fNIRS signal acquisition. A benchtop characterization of the fNIRS component showed its high performances with a noise equivalent power below 1 pW. Moreover, the fNIRS-EEG device was tested in vivo during tasks stimulating visual, motor and pre-frontal cortices. Finally, the capabilities to perform ecological recordings were assessed in clinical settings on one Alzheimer’s Disease patient during long-lasting cognitive tests. The system can pave the way to portable technologies for accurate evaluation of multimodal brain activity, allowing their extensive employment in ecological environments and clinical practice

Classification of Drivers’ Mental Workload Levels: Comparison of Machine Learning Methods Based on ECG and Infrared Thermal Signals

Mental workload (MW) represents the amount of brain resources required to perform concurrent tasks. The evaluation of MW is of paramount importance for Advanced Driver-Assistance Systems, given its correlation with traffic accidents risk. In the present research, two cognitive tests (Digit Span Test—DST and Ray Auditory Verbal Learning Test—RAVLT) were administered to participants while driving in a simulated environment. The tests were chosen to investigate the drivers’ response to predefined levels of cognitive load to categorize the classes of MW. Infrared (IR) thermal imaging concurrently with heart rate variability (HRV) were used to obtain features related to the psychophysiology of the subjects, in order to feed machine learning (ML) classifiers. Six categories of models have been compared basing on unimodal IR/unimodal HRV/multimodal IR + HRV features. The best classifier performances were reached by the multimodal IR + HRV features-based classifiers (DST: accuracy = 73.1%, sensitivity = 0.71, specificity = 0.69; RAVLT: accuracy = 75.0%, average sensitivity = 0.75, average specificity = 0.87). The unimodal IR features based classifiers revealed high performances as well (DST: accuracy = 73.1%, sensitivity = 0.73, specificity = 0.73; RAVLT: accuracy = 71.1%, average sensitivity = 0.71, average specificity = 0.85). These results demonstrated the possibility to assess drivers’ MW levels with high accuracy, also using a completely non-contact and non-invasive technique alone, representing a key advancement with respect to the state of the art in traffic accident prevention

Effectiveness and safety of adjunctive cenobamate in people with focal-onset epilepsy: Interim results after 24-week observational period from the BLESS study

Objective: Cenobamate is an antiseizure medication (ASM) with a dual mechanism of action that was recently approved for the treatment of focal seizures in adults. This analysis aimed to describe the outcomes at 12 and 24 weeks after starting cenobamate therapy in a real-world setting. Methods: BLESS [NCT05859854] is an ongoing, observational, retrospective and prospective cohort study to evaluate the real-world effectiveness and safety of adjunctive cenobamate in adults with uncontrolled focal epilepsy. Subgroup analysis was performed in subjects with 2 to 3 previous ASMs (early users) and those with >3 previous ASMs (late users). Results: The second interim analysis of the BLESS study included 388 participants with a median (interquartile range) age of 43.0 (31.0-54.0) years. They had a median of 6.0 (4.0-9.0) prior ASMs and a median of 7.2 (3.0-20.6) monthly seizures at baseline. The median monthly seizure frequency was reduced by 59.9% (19.2%-87.3%) from baseline to 24 weeks; 229 (59.0%) subjects had a >= 50% seizure frequency reduction, and 44 (11.3%) showed sustained seizure freedom. The proportion of participants taking <= 2 concomitant ASMs increased from 217 (56.5%) at baseline to 239 (65.7%) at 24 weeks. Among the early users (n = 76, 19.6%), the median reduction in monthly seizure frequency at 24 weeks was 78.0% (50.0-97.1%), and 76.3% of subjects had a >= 50% response rate. The frequency of adverse drug reactions (ADRs) was 5.3% and 23.4% in early and late users. The most frequent ADRs were somnolence, dizziness, and balance disorder; after the occurrence of ADRs, 63.5% of participants maintained the prescribed dose, and 5.2% permanently discontinued treatment. Significance: Cenobamate was effective in reducing seizure frequency in a real-world setting and showed a manageable safety profile. The treatment with cenobamate also reduced the burden of concomitant ASMs in both early and late users

Prognostic factors and impact of management strategies for status epilepticus: The STEPPER study in the Emilia-Romagna region, Italy

Objective: The STEPPER (Status Epilepticus in Emilia-Romagna) study aimed to investigate the clinical characteristics, prognostic factors, and treatment approaches of status epilepticus (SE) in adults of the Emilia-Romagna region (ERR), Northern Italy. Methods: STEPPER, an observational, prospective, multicentric cohort study, was conducted across neurology units, emergency departments, and intensive care units of the ERR over 24 months (October 2019–October 2021), encompassing incident cases of SE. Patients were followed up for 30 days. Results: A total of 578 cases were recruited (56% female, mean age = 70 years, 32% with previous diagnosis of epilepsy, 43% with in-hospital onset, 35% stuporous/comatose, 46% with nonconvulsive SE). Etiology was known in 87% (acute 43%, remote 24%, progressive 17%, definite epileptic syndrome 3%). The mean pre-SE Rankin Scale score was 2, the Status Epilepticus Severity Score was ≥4 in 33%, the Epidemiology-Based Mortality Score in Status Epilepticus score was ≥64 in 61%, and 34% were refractory. The sequence of treatments followed current clinical practice guidelines in 63%. Benzodiazepines (BDZs) were underused as first-line therapy (71%), especially in in-hospital onset cases; 15% were treated with continuous intravenous anesthetic drugs. Mortality was 24%; 63% of survivors had functional worsening. At the two-step multivariable analysis, incorrect versus correct treatment sequence with correct BDZ dose was the strongest predictor of failure to resolve SE in the in-hospital group (odds ratio [OR] = 4.42, 95% confidence interval [CI] = 1.86–10.5), with a similar trend in the out-of-hospital group (OR = 2.22, 95% CI =.98–5.02). In turn, failure to resolve was the strongest predictor of 30-day mortality (OR = 11.3, 95% CI = 4.16–30.9, out-of-hospital SE; OR = 6.42, 95% CI = 2.79–14.8, in-hospital SE) and functional worsening (OR = 5.83, 95% CI = 2.05–16.6, out-of-hospital SE; OR = 9.30, 95% CI 2.22–32.3, in-hospital SE). Significance: The STEPPER study offers insights into real-world SE management, highlighting its significant morbidity and functional decline implications. Although nonmodifiable clinical factors contribute to SE severity, modifiable factors such as optimized first-line therapies and adherence to guidelines can potentially influence prognosis

Expression of 19 microRNAs in glioblastoma and comparison with other brain neoplasia of grades I-III

Several biomarkers have been proposed as useful parameters to better specify the prognosis or to delineate new target therapy strategies for glioblastoma patients. MicroRNAs could represent putative target molecules, considering their role in tumorigenesis, cancer progression and their specific tissue expression. Although several studies have tried to identify microRNA signature for glioblastoma, a microRNA profile is still far from being well-defined. In this work the expression of 19 microRNAs (miR-7, miR-9, miR-9 17, miR-10a, miR-10b, miR-17, miR-20a, miR-21, miR-26a, miR-27a, miR-31, miR-34a, miR-101, miR-137, miR-182, miR-221, miR-222, miR-330, miR-519d) was evaluated in sixty formalin-fixed and paraffin-embedded glioblastoma samples using a locked nucleic acid real-time PCR. Moreover, a comparison of miRNA expressions was performed between primary brain neoplasias of different grades (grades IV-I). The analysis of 14 validated miRNA expression in the 60 glioblastomas, using three different non-neoplastic references as controls, revealed a putative miRNA signature: mir-10b and miR-21 were up-regulated, while miR-7, miR-31, miR-101, miR-137, miR-222 and miR-330 were down-regulated in glioblastomas. Comparing miRNA expression between glioblastoma group and gliomas of grades I-III, 3 miRNAs (miR-10b, mir-34a and miR-101) showed different regulation statuses between high-grade and low-grade tumors. miR-10b was up-regulated in high grade and significantly down-regulated in low-grade gliomas, suggesting that could be a candidate for a GBM target therapy. This study provides further data for the identification of a miRNA profile for glioblastoma and suggests that different-grade neoplasia could be characterized by different expression of specific miRNA

Construction and characterization of the detection modules for the Muon Portal Project

The Muon Portal Project is a joint initiative between research and industrial partners, aimed at the construction of a real size detector protoype (6×3×7 m3) for the inspection of containers by the muon scattering technique, devised to search for hidden high-Z fissile materials and provide a full 3D tomography of the interior of the container in a scanning time of the order of minutes. The muon tracking detector is based on a set of 48 detection modules (size 1 m × 3 m), each built with 100 extruded scintillator strips, so as to provide four X-Y detection planes, two placed above and two below the container to be inspected. Two wavelength shifting (WLS) fibres embedded in each strip convey the emitted photons to Silicon Photomultipliers (SiPM) which act as photosensors. After a research and development phase, which led to the choice and test of the individual components, the construction of the full size detector has already started. The paper describes the results of the mass characterization of the photosensors and the construction and test measurements of the first detection modules of the Project