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In the modern "omics" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.

Heterospilus sicanus (Marshall, 1888) is redescribed and illustrated based on the holotype of Dendrosoter sicanus Marshall, 1888 and on recently collected material from its type locality (Sicily, Italy). Previous host records for this species are unreliable. Here, the host of H. sicanus, the rare ptinid beetle Gastrallus pubens Fairmaire, 1875, is recorded for the first time, having been reared in a historic library in Palermo, Italy. Heterospilus sicanus is compared with the similar species Telebolus (= Heterospilus) corsicus Marshall, 1888, which was described in the same monograph from Corsica (France), and it is also redescribed and illustrated. Atoreuteus ceballosi Docavo Alberti, 1960, syn. nov. is synonymised under Heterospilus sicanus (Marshall, 1888), and Hormiopterus (= Rhaconotus) ollivieri Giraud var. flava Fahringer, 1931, syn. nov. is a junior synonym of Heterospilus cephi Rohwer, 1925. A key for determination of the Western Palaearctic Heterospilus species with a striate vertex is provided and the distributions of H. sicanus and H. corsicus are discussed.

Key Clinical Message We present a case of a single left hemisphere temporal–parietal stroke with subacute global aphasia and severe verbal apraxia and moderate dysphagia. The patient underwent a combined transcranial direct current stimulation (tDCS) over the left dorsolateral prefrontal cortex (DLPFC) and language stimulation with Virtual Reality Rehabilitation System (VRRS). Patient was treated in a 1‐h session, for 5 days a week, for 4 consecutive weeks. After treatment, evident improvements in the comprehension of oral and written language, swallowing abilities, and caregiver burden were detected. Power spectrum analysis of EEG data revealed significant enhancements of θ, α, and β waves from baseline to follow‐up. These preliminary results seem to confirm the reliability of the tDCS translational application in conjunction with computer‐based cognitive treatment for language disorders in a patient with stroke‐induced aphasia.

In several medical fields, generative AI tools such as ChatGPT have achieved optimal performance in identifying correct diagnoses only by evaluating narrative clinical descriptions of cases. The most active fields of application include oncology and COVID-19-related symptoms, with preliminary relevant results also in psychiatric and neurological domains. This scoping review aims to introduce the arrival of ChatGPT applications in neurorehabilitation practice, where such AI-driven solutions have the potential to revolutionize patient care and assistance. First, a comprehensive overview of ChatGPT, including its design, and potential applications in medicine is provided. Second, the remarkable natural language processing skills and limitations of these models are examined with a focus on their use in neurorehabilitation. In this context, we present two case scenarios to evaluate ChatGPT ability to resolve higher-order clinical reasoning. Overall, we provide support to the first evidence that generative AI can meaningfully integrate as a facilitator into neurorehabilitation practice, aiding physicians in defining increasingly efficacious diagnostic and personalized prognostic plans.

Individuals with acquired brain injuries (ABIs) may experience various complications related to poor coughing or impaired cough reflex (including risk of aspiration pneumonia or respiratory infections). For this reason, cough assessment is an important component in the clinical evaluation since patients with ABI are not able to cough voluntarily due to severe motor deficits. When voluntarily coughing is not possible, it is essential for clinical practices to find a quick and minimally invasive way to induce a cough reflex. In the present study, we evaluated the cough reflex in ABI patients using a new method based on a capsaicin spray stimulation test. In total, 150 healthy controls demographically matched with 50 ABI patients were included in this study. Clinical observations demonstrated robust cough response in both healthy controls and ABI patients, as well as the safety and tolerability of capsaicin spray stimulation. ABI patients with dysphagia were characterized by slower and delayed cough responses. Further studies are needed to validate this feasible, less-invasive, and simple-to-comprehend technique in inducing cough reflex. According to this preliminary evidence, we believe that this test might be translated into a simple and effective treatment to improve reflexive cough modulation in ABI patients.

Semi-volatile organic contaminants (SVOCs) are known for their tendency to evaporate from source regions and undergo atmospheric transport to distant areas. Cold condensation intensifies dry deposition, particle deposition, and scavenging by snow and rain, allowing SVOCs to move from the atmosphere into terrestrial and aquatic ecosystems in alpine and polar regions. However, no standardized methods exist for the sampling, laboratory processing, and instrumental analysis of persistent organic pollutants (POPs) in snow. The lack of reference methods makes these steps highly variable and prone to errors. This study critically reviews the existing literature to highlight the key challenges in the sampling phase, aiming to develop a reliable, consistent, and easily reproducible technique. The goal is to simplify this crucial step of the analysis, allowing data to be shared more effectively through standardized methods, minimizing errors. Additionally, an innovative method for laboratory processing is introduced, which uses activated carbon fibers (ACFs) as adsorbents, streamlining the analysis process. The extraction method is applied to analyze polychlorobiphenyls (PCBs) and chlorinated pesticides (α-HCH, γ-HCH, p,p′-DDE, o,p′-DDT, HCB, and PeCB). The entire procedure, from sampling to instrumental analysis, is subsequently tested on snow samples collected on the Svalbard Islands. To validate the efficiency of the new extraction system, quality control measures based on the EPA methods 1668B and 1699 for aqueous methods are employed. This study presents a new, reliable method that covers both sampling and lab analysis, tailored for detecting POPs in snow.

Background/Objectives: Cranioplasty (CP) is the main surgical procedure aiming to repair a morphological defect in the skull. It has been shown that early CP is useful for patients with traumatic brain injury (TBI) to achieve functional recovery, whereas few studies have investigated the clinical effects of ultra-late CP on TBI outcomes. Methods: Here, we describe the clinical course over 2 years of a TBI patient who underwent CP 19 months after fronto-parietal decompressive craniectomy (DC) of a limited size. Results: We found that after ultra-late CP, a meaningful functional recovery (cognitive and motor), with emergence from a minimally conscious state and recovery of functional communication, was revealed. Conclusions: Our preliminary findings contribute to the actual debate on the timing of CP for this neurosurgical procedure’s therapeutic success, as early CP has already been shown.

The rising prevalence of mental illness is straining global mental health systems, particularly affecting older adults who often face deteriorating physical health and decreased autonomy and quality of life. Early detection and targeted rehabilitation are crucial in mitigating these challenges. Mindfulness acceptance and commitment therapy (ACT) holds promise for enhancing motivation and well-being among the elderly, although delivering such psychological interventions is hindered by limited access to services, prompting exploration of remote delivery options like mobile applications. In this paper, we introduce the BrainHeart App (v.1.1.8), a mobile application tailored to improve physical and mental well-being in seniors. The app features a 10-day ACT program and other sections promoting healthy lifestyle. In a pilot study involving twenty participants, individuals engaged in daily mental exercises for 10 days using the app. Clinical evaluations, including assessments of psychological flexibility, overall cognitive profile, mindfulness disposition, cognitive fusion, and heart rate collected with Polar H10, were conducted at baseline (T0) and one month post-intervention (T1). Analysis revealed significant improvements in almost all neuropsychological scores, with high usability reported (system usability scale average score: 82.3 ± 9.31). Additionally, a negative correlation was found between usability and experiential avoidance (r = −0.51; p = 0.026), and a notable difference in heart rate was observed between baseline and post-intervention (F-value = 3.06; p-value = 0.09). These findings suggest that mindfulness-ACT exercises delivered via the BrainHeart App can enhance the well-being of elderly individuals, highlighting the potential of remote interventions in addressing mental health needs in this population.

Background Suggestibility is a personality trait that reflects a general tendency to accept messages. The Multidimensional Iowa Suggestibility Scale (MISS) is a self-report scale developed to measure the degree of individuals’ perceptions of their suggestibility. This study aimed to adapt the MISS in an Italian sample. Methods We conducted two studies. In the first study, 345 subjects (270 females (78%), mean age = 36.21 years ± 14.06 SD) completed the translated Italian version of the MISS, composed of five subscales (consumer suggestibility; persuadability; sensation contagion; physiological reactivity; peer conformity). We investigated the structural validity of the scale through confirmatory factor analysis (CFA) testing four measurement models (unidimensional, four-factor, hierarchical four factors, and bifactor) and explored reliability in terms of internal consistency through the McDonald’s omega. In the second study, we cross-validated the MISS on a new independent sample. We enrolled 277 participants (196 females (71%), mean age 30.56, SD = 12.58) who underwent the new version of the scale. We performed factor analyses to test structural validity and compared four measurement models. Then, we investigated reliability and conducted a latent variable analysis to explore divergent validity. Results The CFA in the first study revealed a bifactor solution of the MISS. This structure was interpretable and provided an adequate fit for the data. The final version of the scale was reduced to forty-six items with globally good indices of adaptation. The scale also demonstrated acceptable reliability in terms of internal consistency through the McDonald’s Hierarchical Omega. In the second study, we found that the bifactor structure was confirmed. Factor loadings inspection revealed that there was no justification to report only the separate scores for the subscales. We also found that the scale showed good internal consistency, but mixed evidence for divergent validity. Conclusions In the end, the Italian version of the MISS demonstrated good psychometric properties which will be discussed in detail below.

Abstract This study describes a dynamic non-linear mathematical approach for modeling the course of disease in acquired brain injury (ABI) patients. Data from a multicentric study were used to evaluate the reliability of the Michaelis–Menten (MM) model applied to well-known clinical variables that assess the outcome of ABI patients. The sample consisted of 156 ABI patients admitted to eight neurorehabilitation subacute units and evaluated at baseline (T0), 4 months after the event (T1) and at discharge (T2). The MM model was used to characterize the trend of the first Principal Component Analysis (PCA) dimension (represented by the variables: feeding modality, RLAS, ERBI-A, Tracheostomy, CRS-r and ERBI-B) in order to predict the most plausible outcome, in terms of positive or negative Glasgow outcome score (GOS) at discharge. Exploring the evolution of the PCA dimension 1 over time, after day 86 the MM model better differentiated between the time course for individuals with a positive and negative GOS (accuracy: 85%; sensitivity: 90.6%; specificity: 62.5%). The non-linear dynamic mathematical model can be used to provide more comprehensive trajectories of the clinical evolution of ABI patients during the rehabilitation period. Our model can be used to address patients for interventions designed for a specific outcome trajectory.

Background and aimAdvances in computing technology enabled researchers and clinicians to exploit technological devices for cognitive training and rehabilitation interventions. This expert review aims to describe the available software and device used for cognitive training or rehabilitation interventions of patients with neurological disorders.MethodsA scoping review was carried out to analyze commercial devices/software for computerized cognitive training (CCT) in terms of feasibility and efficacy in both clinical and home settings. Several cognitive domains responding to the different patients’ needs are covered.ResultsThis review showed that cognitive training for patients with neurological diseases is largely covered by several devices that are widely used and validated in the hospital setting but with few translations to remote/home applications. It has been demonstrated that technology and software-based devices are potential and valuable tools to administer remotely cognitive rehabilitation with accessible costs.ConclusionAccording to our results, CCT entails the possibility to continue cognitive training also in different settings, such as home, which is a significant breakthrough for the improvement of community care. Other possible areas of use should be the increase in the amount of cognitive therapy in the free time during the hospital stay.

Purpose: To determine the best predictor of lesion volume induced by magnetic resonance (MR)-guided focused ultrasound (MRgFUS) thalamotomy in patients with tremor-dominant symptoms in Parkinson’s disease (PD) and essential tremor (ET) patients. Methods: Thirty-six neurological patients with medication-refractory tremor (n°19 PD; n°17 ET) were treated using a commercial MRgFUS brain system (Exablate Neuro 4000, Insightec) integrated with a 1.5 T MRI unit (Sigma HDxt; GE Medical System). Linear regression analysis was used to determine how the demographic, clinical, radiological (Fazekas scale), volumetric (total GM/WM/CSF volume, cortical thickness), and MRgFUS-related parameters [Skull Density Ratio (SDR), n° of transducer elements, n° of sonications, skull area, maximal energy delivered (watt), maximal power delivered (joule), maximal sonication time delivered, maximal mean temperature reached (T°C_max), accumulated thermal dose (ATD)] impact on ventral intermediate (VIM)-thalamotomy-related 3D volumetric lesions of necrosis and edema. Results: The VIM thalamotomy was clinically efficacious in improving the tremor symptoms of all the patients as measured at 1 week after treatment. Multiple regression analysis revealed that T°C_max and n° of transducer elements were the best predictors of the necrosis and edema volumes. Moreover, total WM volume also predicted the size of necrosis. Conclusions: Our study provides new insights into the clinical MRgFUS procedures that can be used to forecast brain lesion size and improve treatment outcomes.

Background: Foot drop syndrome (FDS), characterized by severe weakness and atrophy of the dorsiflexion muscles of the feet, is commonly found in patients with severe acquired brain injury (ABI). If the syndrome is unilateral, the cause is often a peroneal neuropathy (PN), due to compression of the nervous trunk on the neck of the fibula at the knee level; less frequently, the cause is a previous or concomitant lumbar radiculopathy. Bilateral syndromes are caused by polyneuropathies and myopathies. Central causes, due to brain or spinal injury, mimic this syndrome but are usually accompanied by other symptoms, such as spasticity. Critical illness polyneuropathy (CIP) and myopathy (CIM), isolated or in combination (critical illness polyneuromyopathy, CIPNM), have been shown to constitute an important cause of FDS in patients with ABI. Assessing the causes of FDS in the intensive rehabilitation unit (IRU) has several limitations, which include the complexity of the electrophysiological tests, limited availability of neurophysiology consultants, and the severe disturbance in consciousness and lack of cooperation from patients. Objectives: We sought to propose a simplified electrophysiological screening that identifies FDS causes, particularly PN and CIPNM, to help clinicians to recognize the significant clinical predictors of poor outcomes in severe ABI at admission to IRU. Methods: This prospective, single-center study included 20 severe ABI patients with FDS (11 females/9 males, mean age 55.10 + 16.26; CRS-R= 11.90 + 6.32; LCF: 3.30 + 1.30; DRS: 21.45 + 3.33), with prolonged rehabilitation treatment (≥2 months). We applied direct tibialis anterior muscle stimulation (DMS) associated with peroneal nerve motor conduction evaluation, across the fibular head (NCS), to identify CIP and/or CIM and to exclude demyelinating or compressive unilateral PN. Results: At admission to IRU, simplified electrophysiological screening reported four unilateral PN, four CIP and six CIM with a CIPNM overall prevalence estimate of about 50%. After 2 months, the CIPNM group showed significantly poorer outcomes compared to other ABI patients without CIPNM, as demonstrated by the lower probability of achieving endotracheal-tube weaning (20% versus 90%) and lower CRS-R and DRS scores. Due to the subacute rehabilitation setting of our study, it was not possible to evaluate the motor results of recovery of the standing position, functional walking and balance, impaired by the presence of unilateral PN. Conclusions: The implementation of the proposed simplified electrophysiological screening may enable the early identification of unilateral PN or CIPNM in severe ABI patients, thereby contributing to better functional prognosis in rehabilitative settings.

The need to use renewable sources and matrices with energy potential is widely recognized. The development of innovative technologies aimed at the improvement of energy conversion processes and reducing environmental impacts is currently receiving increasing attention from the scientific community and policymakers. The presence of sugars in airborne particle materials is attributed to biomass combustion. For this reason, these compounds are considered markers of biomass burning. The purpose of this work was to evaluate the emissions produced by agroforestry biomass burning (citrus pruning) by simultaneously sampling both stack emissions and atmospheric particulates in the area around a biomass boiler to understand the real contribution of biomass burning to atmospheric pollution. The combustion tests were carried out by comparing the processes with and without particulate abatement system to see how biomass combustion’s contribution to particulate emission can be controlled and reduced. During the tests, the focus was on particulate matter (PM) speciation in terms of sugar marker identification and determination. This study aims to increase knowledge to better understand the contribution of biomass plants to air pollution and differentiate it from the contributions of other sources, such as vehicular traffic or domestic heating.

Chronic stress and chronic pain share neuro-anatomical, endocrinological, and biological features. However, stress prepares the body for challenging situations or mitigates tissue damage, while pain is an unpleasant sensation due to nociceptive receptor stimulation. When pain is chronic, it might lead to an allostatic overload in the body and brain due to the chronic dysregulation of the physiological systems that are normally involved in adapting to environmental challenges. Managing stress and chronic pain (CP) in neurorehabilitation presents a significant challenge for healthcare professionals and researchers, as there is no definitive and effective solution for these issues. Patients suffering from neurological disorders often complain of CP, which significantly reduces their quality of life. The aim of this narrative review is to examine the correlation between stress and pain and their potential negative impact on the rehabilitation process. Moreover, we described the most relevant interventions used to manage stress and pain in the neurological population. In conclusion, this review sheds light on the connection between chronic stress and chronic pain and their impact on the neurorehabilitation pathway. Our results emphasize the need for tailored rehabilitation protocols to effectively manage pain, improve treatment adherence, and ensure comprehensive patient care.

A plethora of neuroimaging studies have focused on the discovery of potential neuroendophenotypes useful to understand the etiopathogenesis of autism and predict treatment response. Social robotics has recently been proposed as an effective tool to strengthen the current treatments in children with autism. However, the high clinical heterogeneity characterizing this disorder might interfere with behavioral effects. Neuroimaging is set to overcome these limitations by capturing the level of heterogeneity. Here, we provide a preliminary evaluation of the neural basis of social robotics and how extracting neural hallmarks useful to design more effective behavioral applications. Despite the endophenotype-oriented neuroimaging research approach is in its relative infancy, this preliminary evidence encourages innovation to address its current limitations.

The idea that individuals tend to choose a romantic partner following similarities on personality traits has always attracted much attention in the psychological literature, although results were controversial. We conducted a new data analysis approach to personality traits of 235 newlywed couples. Univariate analysis revealed that a neurotic husband is usually paired with a lesser extrovert and open wife. To figure out if this mating selection pattern may be translated in a mathematical predictive model a twofold approach was employed by using Partial Least Squares regression and machine learning algorithm. The experimental results demonstrate that marital assortment for personality is a multi-trait complementarity process but these data are unable to predict human mating., Author(s): Antonio Cerasa [sup.1] [sup.2] , Emiliano Cristiani [sup.3] , Barbara De Luca [sup.4] , Maria Luisa De Narda [sup.5] , Maria Concetta Cundò [sup.5] , Sara Concetta Bottani [sup.4] [...]

Information and communication technologies (ICTs) have become more widely used in the past years to help people with autism spectrum conditions (ASC). Serious games embedded into computers or tablets, as well as social robots, are the most employed ICT-related tools that are appealing to and appropriate for autistic children. The goal of ICT applications is to enhance behavioral abnormalities associated with ASC while also creating an interactive link between one person and one computer. Comparatively, to human-based therapy, ICT tools aid to inspire autistic children by providing predictability and regularity of tasks. Regaining social skills is the primary behavioral goal for which ICT tools have been designed and implemented. In the past several years, many studies have been created to show how effective it is at improving targeted behaviors. However, only a small number of researchers have used an RCT approach to evaluate its effectiveness. In this systematic review, we only included RCT studies where ICT technologies were used to help children with ASC in improving their social skills. Only 14 RCT studies satisfied the criteria and 12 described significant improvements, showing how the use of technology in educational contexts produced better improvement in developing several social skill facets with respect to the traditional face-to-face approach. Some studies used interventions and outcome measures focused on the core ASC symptoms, but many others addressed neurocognitive functions directly, like social cognition or emotional regulation, while other more general functions such as language or adaptive behaviors. We propose a classification based on processes and outcome measures to foster future research in this specific area of research. The behavioral intervention mediated by technological tools such as computer-based, tablet, and social robotics, undoubtedly provides a comfortable environment that promotes constant learning for people with ASC. Evidence provided in this review highlights the translational potential of this field of study in primary care practice and educational settings.

Significant anti-spike protein receptor-binding domain (S-RBD) antibody responses have been demonstrated in patients with chronic disorder of consciousness (DOC) completing a COVID-19 vaccine regime with BNT162b2 (Pfizer–BioNTech). We now provide further prospective data on the immunogenicity of these patients followed by heterologous booster injection with mRNA-1273 (Moderna). These patients were compared with two different demographically comparable healthcare workers (HCW) groups who underwent homologous booster injection with BNT162b2 vaccine or heterologous booster injection with mRNA-1273. Antibody responses were evaluated at 21 days after the administration of the booster dose of vaccination. Results: No severe adverse reactions were reported after each type of vaccination. Heterologous boosting with mRNA-1273 elicited a higher increase of S-RBD IgG levels than homologous boosting with BNT162b2 both in DOC patients and HCW who had previously received two doses of BNT162b2. No significant difference was detected between DOC and HCW patients who received heterologous boosting. Conclusions: Despite the small sample size, our preliminary results suggest that heterologous boosting with mRNA-1273, following initial vaccination with BNT162b2, is safe and tends to be more immunogenic than homologous boosting, either in fragile people or in healthy controls.

The human pulvinar is considered a prototypical associative thalamic nucleus as it represents a key node in several cortico‐subcortical networks. Through this extensive connectivity to widespread brain areas, it has been suggested that the pulvinar may play a central role in modulating cortical oscillatory dynamics of complex cognitive and executive functions. Additionally, derangements of pulvinar activity are involved in different neuropsychiatric conditions including Lewy‐body disease, Alzheimer's disease, and schizophrenia. Anatomical investigations in nonhuman primates have demonstrated a topographical organization of cortico‐pulvinar connectivity along its dorsoventral and rostrocaudal axes; this specific organization shows only partial overlap with the traditional subdivision into subnuclei (anterior, lateral, medial, and inferior) and is thought to coordinate information processing within specific brain networks. However, despite its relevance in mediating higher‐order cognitive functions, such a structural and functional organization of the pulvinar in the human brain remains poorly understood. Track‐weighted dynamic functional connectivity (tw‐dFC) is a recently developed technique that combines structural and dynamic functional connectivity, allowing the identification of white matter pathways underlying the fluctuations observed in functional connectivity between brain regions over time. Herein, we applied a data‐driven parcellation approach to reveal topographically organized connectivity clusters within the human pulvinar complex, in two large cohorts of healthy human subjects. Unsupervised clustering of tw‐dFC time series within the pulvinar complex revealed dorsomedial, dorsolateral, ventral anterior, and ventral posterior connectivity clusters. Each of these clusters shows functional coupling to specific, widespread cortico‐subcortical white matter brain networks. Altogether, our findings represent a relevant step towards a better understanding of pulvinar anatomy and function, and a detailed characterization of his role in healthy and pathological conditions. [ABSTRACT FROM AUTHOR]

Semi-volatile organic contaminants (SVOCs) are known for their tendency to evaporate from source regions and undergo atmospheric transport to distant areas. Cold condensation intensifies dry deposition, particle deposition, and scavenging by snow and rain, allowing SVOCs to move from the atmosphere into terrestrial and aquatic ecosystems in alpine and polar regions. However, no standardized methods exist for the sampling, laboratory processing, and instrumental analysis of persistent organic pollutants (POPs) in snow. The lack of reference methods makes these steps highly variable and prone to errors. This study critically reviews the existing literature to highlight the key challenges in the sampling phase, aiming to develop a reliable, consistent, and easily reproducible technique. The goal is to simplify this crucial step of the analysis, allowing data to be shared more effectively through standardized methods, minimizing errors. Additionally, an innovative method for laboratory processing is introduced, which uses activated carbon fibers (ACFs) as adsorbents, streamlining the analysis process. The extraction method is applied to analyze polychlorobiphenyls (PCBs) and chlorinated pesticides (α-HCH, γ-HCH, p,p′-DDE, o,p′-DDT, HCB, and PeCB). The entire procedure, from sampling to instrumental analysis, is subsequently tested on snow samples collected on the Svalbard Islands. To validate the efficiency of the new extraction system, quality control measures based on the EPA methods 1668B and 1699 for aqueous methods are employed. This study presents a new, reliable method that covers both sampling and lab analysis, tailored for detecting POPs in snow. [ABSTRACT FROM AUTHOR]

The recovery of neurological deficits after ischemic stroke largely depends on the brain's ability to reorganize its undamaged neuronal circuits and neuronal plasticity phenomena. The consolidated evidence highlights the involvement of the patient's impaired nutritional conditions in post-stroke recovery and unsatisfying rehabilitative outcomes. Standardized nutritional protocols usually applied in hospitalized patients in a rehabilitation setting aim mainly to improve the general health conditions of patients, do not consider the high inter-individual variability in neurorehabilitation outcomes, and are not sufficiently modifiable to provide neuroprotective and restorative dietary patterns that could promote neuronal plasticity and functional recovery during neurorehabilitation. Neuronutrition, an emergent scientific field of neuroscience, represents a valid model of a personalized nutritional approach, assuring, for each patient, nutrients having antioxidant and anti-inflammatory properties, ensuring a balanced microbiota composition, and providing adequate neurotrophic support, essential for improving neuronal plasticity, brain functional recovery, and rehabilitative outcomes. In the present narrative review, we provide an overview of the current knowledge on neuronutrition as an adjuvant strategy of a personalized nutritional approach potentially effective in improving post-stroke neuroplasticity and neurorehabilitation by counteracting or at least limiting post-stroke oxidative/nitrosative stress, neuroinflammation, and gut–brain axis disturbance. [ABSTRACT FROM AUTHOR]

The sequelae of neurological disorders are the leading causes of disability in all industrialized countries [...]

Rice cultivation stands as the primary agricultural activity in Asia, generating a substantial amount of agricultural waste. Unfortunately, this waste is often disposed of through burning, contributing to severe environmental, health and climate issues. This study presents the characterization of PCDD/Fs, PCBs and PAHs. The emissions were quantified using a fixed-grid-system biomass plant and measuring the macro-pollutants online and sampling the organic micro-pollutants and metals in isokinetic mode, followed by ISO and CEN standards methods. Additionally, the role of agrochemicals was monitored in terms of metal catalysis resulting in POP emissions. This study provides the comprehensive characterization of the most relevant groups of pollutants (metals, PCDD/Fs, PCBs and PAHs) resulting from agricultural waste combustion. Prominent catalytic metals quantified were Cu (22–48 µg/Nm3) and Fe (78–113 µg/Nm3). Rice straw samples from AJK exhibited higher values of organochlorine micro-pollutants compared to those from Punjab and Sindh, i.e., ∑PCDD/F (2594 > 1493 > 856 pg/Nm3) and ∑PCB (41 > 38 > 30 pg/Nm3), respectively, whereas the organic micro-pollutants ∑c-PAH, indicators of incomplete combustion (PICs), were recorded high in the samples from Sindh followed by Punjab and AJK. The average EF is 100 pg/kg, 2.2 pg/kg and 1053.6 µg/kg for ∑PCDD/F, ∑PCB and ∑c-PAH. This study supports the idea that the phenomena leading to the formation of dioxin and dioxin-like compounds are influenced not only by poor combustion but also by the presence of metal catalysts in the burned fuel.

Introduction: The Wessex Head Injury Matrix (WHIM) was developed to assess patients with disorders of consciousness (DOC) and was tested in terms of inter-rater reliability (IRR) and test–retest reliability (TRR) in the year 2000. The American Congress of Rehabilitation and Medicine reported that IRR and TRR were unproven. We aim to assess the reliability of the WHIM in prolonged DOC patients (PDOC). Methods: A total of 51 PDOC patients (32 unresponsive wakefulness syndrome (UWS/VS) and 19 minimally conscious state (MCS)) who were hosted in a dedicated unit for long-term brain injury care were enrolled. The time from injury ranged from 182 to 3325 days. Two raters administered the Coma Recovery Scale-Revised (CRS-R) and the WHIM to test the IRR and TRR. The TRR was administered two weeks after the first assessment. Results: For the CRS-R, the agreement in IRR and TRR was perfect between the two raters. The agreement for the WHIM ranged from substantial to almost perfect for IRR and from fair to substantial for the TRR. Conclusions: The WHIM showed a strong IRR when administered by expert raters and strongly correlated with the CRS-R. This study provides further evidence of the psychometric qualities of the WHIM and the importance of its use in PDOC patients.