Reduced TMS-evoked EEG oscillatory activity in cortical motor regions in patients with post-COVID fatigue.

OBJECTIVE: Persistent fatigue is a major symptom of the so-called 'long-COVID syndrome', but the pathophysiological processes that cause it remain unclear. We hypothesized that fatigue after COVID-19 would be associated with altered cortical activity in premotor and motor regions. METHODS: We used transcranial magnetic stimulation combined with EEG (TMS-EEG) to explore the neural oscillatory activity of the left primary motor area (l-M1) and supplementary motor area (SMA) in a group of sixteen post-COVID patients complaining of lingering fatigue as compared to a sample of age-matched healthy controls. Perceived fatigue was assessed with the Fatigue Severity Scale (FSS) and Fatigue Rating Scale (FRS). RESULTS: Post-COVID patients showed a remarkable reduction of beta frequency in both areas. Correlation analysis exploring linear relation between neurophysiological and clinical measures revealed a significant inverse correlation between the individual level of beta oscillations evoked by TMS of SMA with the individual scores in the FRS (r(15) = -0.596; p = 0.012). CONCLUSIONS: Post-COVID fatigue is associated with a reduction of TMS-evoked beta oscillatory activity in SMA. SIGNIFICANCE: TMS-EEG could be used to identify early alterations of cortical oscillatory activity that could be related to the COVID impact in central fatigue.

Comparative expression of trophoblast cell-surface antigen 2 (TROP2) in the different molecular subtypes of invasive breast carcinoma: An immunohistochemical study of 94 therapy-naive primary breast tumors.

BACKGROUND: Sacituzumab govitecan, targeting trophoblast cell-surface antigen 2 (TROP2), is approved for the treatment of triple-negative and hormone receptor-positive/HER2-negative breast cancers. However, detailed studies comparing TROP2 protein expression in the different molecular subtypes of breast cancer are limited, and definitive evidence supporting the use of TROP2 as a biomarker for predicting response to this agent in patients with breast cancer is currently lacking. OBJECTIVE: To compare the expression of TROP2 in the different molecular subtypes of breast cancer. METHODS: Immunohistochemical staining for TROP2 was performed on 94 therapy-naive primary invasive breast carcinomas, including 25 luminal A-like, 25 luminal B-like, 19 HER2-like, and 25 triple-negative tumors. RESULTS: Intermediate to high levels of TROP2 expression were observed in the majority of carcinomas of each molecular subtype, with a wide range of expression in each subtype. Occasional tumors with low or absent TROP2 expression were encountered, including two metaplastic carcinomas which were completely negative for TROP2. CONCLUSIONS: Our observations support the continued investigation of the efficacy of sacituzumab govitecan in all molecular subtypes of breast carcinoma. Furthermore, the observed wide range of expression of TROP2 suggests that TROP2 may have potential utility as a biomarker for predicting responsiveness to sacituzumab govitecan. If this proves to be the case, then immunohistochemical staining for TROP2 would be critical for identifying those patients whose tumors are completely negative for TROP2, since these patients may be least likely or unlikely to respond to this agent, and alternative therapies may be more appropriate in such instances.

Integrating Exposure Assessment and Process Hazard Analysis: The Nano-Enabled 3D Printing Filament Extrusion Case.

Nanoparticles are being used in novel applications of the thermoplastics industry, including automotive parts, the sports industry and leisure and consumer goods, which can be produced nowadays through additive manufacturing. However, there is limited information on the health and safety aspects during the production of these new materials, mainly from recycled sources. This study covers the exposure assessment to nano- and micro-size particles emitted from the nanocomposites during the production of filaments for 3D printing through a compounding and extrusion pilot line using recycled (post-industrial) thermoplastic polyurethane (TPU) and recycled polyamide 12 (PA12), which have been also upcycled through reinforcement with iron oxide nanoparticles (Fe3O4 NPs), introducing matrix healing properties triggered by induction heating. The assessment protocol included near- and far-field measurements, considering the extruder as the primary emission source, and portable measuring devices for evaluating particulate emissions reaching the inhalable zone of the lab workers. A Failure Modes and Effects Analysis (FMEA) study for the extrusion process line was defined along with a Failure Tree Analysis (FTA) process in which the process deviations, their sources and the relations between them were documented. FTA allowed the identification of events that should take place in parallel (simultaneously) or in series for the failure modes to take place and the respective corrective actions to be proposed (additional to the existing control measures).

Application of infrared matrix-assisted laser desorption electrospray ionization mass spectrometry for morphine imaging in brain tissue.

Here, we present a method developed for the analysis of spatial distributions of morphine in mouse brain tissue using infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) coupled to a Q Exactive Plus mass spectrometer. The method is also capable of evaluating spatial distributions of the antiretroviral drug abacavir. To maximize sensitivity to morphine, we analyze various Orbitrap mass spectrometry acquisition modes utilizing signal abundance and frequency of detection as evaluation criteria. We demonstrate detection of morphine in mouse brain and establish that the selected ion monitoring mode provides 2.5 times higher sensitivity than the full-scan mode. We find that distributions of morphine and abacavir are highly correlated with the Pearson correlation coefficient R = 0.87. Calibration showed that instrument response is linear up to 40 pg/mm2 (3.8 µg/g of tissue).

Feasibility, Acceptability and Appropriateness of MedViewer: A Novel Hair-Based Antiretroviral Real-Time Clinical Monitoring Tool Providing Adherence Feedback to Patients and Their Providers.

Antiretroviral therapy (ART) adherence is key to achieving viral load suppression and ending the HIV epidemic but monitoring and supporting adherence using current interventions is challenging. We assessed the feasibility, acceptability and appropriateness of MedViewer (MV), a novel intervention that provides real-time adherence feedback for patients and providers using infra-red matrix-assisted laser desorption electrospray ionization (IR-MALDESI) for mass spectrometry imaging of daily ART concentrations in patients' hair. We used mixed methods to feasibility test MV at a busy Infectious Diseases (ID) clinic, enrolling 16 providers and 36 patients. Providers underwent standardized training; patients and providers watched an 8-min informational video about MV. We collected patient and provider data at baseline and within 24 h of clinic visits and, with patients, approximately 1 month after clinic visits. MedViewer was feasible, liked by patients and providers, and perceived to help facilitate adherence conversations and motivate patients to improve adherence. Trial Registration: NCT04232540.

Machine Learning-Based Classification to Disentangle EEG Responses to TMS and Auditory Input.

The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) offers an unparalleled opportunity to study cortical physiology by characterizing brain electrical responses to external perturbation, called transcranial-evoked potentials (TEPs). Although these reflect cortical post-synaptic potentials, they can be contaminated by auditory evoked potentials (AEPs) due to the TMS click, which partly show a similar spatial and temporal scalp distribution. Therefore, TEPs and AEPs can be difficult to disentangle by common statistical methods, especially in conditions of suboptimal AEP suppression. In this work, we explored the ability of machine learning algorithms to distinguish TEPs recorded with masking of the TMS click, AEPs and non-masked TEPs in a sample of healthy subjects. Overall, our classifier provided reliable results at the single-subject level, even for signals where differences were not shown in previous works. Classification accuracy (CA) was lower at the group level, when different subjects were used for training and test phases, and when three stimulation conditions instead of two were compared. Lastly, CA was higher when average, rather than single-trial TEPs, were used. In conclusion, this proof-of-concept study proposes machine learning as a promising tool to separate pure TEPs from those contaminated by sensory input.

New Insights on the Mechanisms of Myocardial Injury in Hypertensive Patients With COVID-19.

PURPOSE: Myocardial injury is common in hypertensive patients with 2019 coronavirus disease (COVID-19). Immune dysregulation could be associated to cardiac injury in these patients, but the underlying mechanism has not been fully elucidated. METHODS: All patients were selected prospectively from a multicenter registry of adults hospitalized with confirmed COVID-19. Cases had hypertension and myocardial injury, defined by troponin levels above the 99th percentile upper reference limit, and controls were hypertensive patients with no myocardial injury. Biomarkers and immune cell subsets were quantified and compared between the two groups. A multiple logistic regression model was used to analyze the associations of clinical and immune variables with myocardial injury. RESULTS: The sample comprised 193 patients divided into two groups: 47 cases and 146 controls. Relative to controls, cases had lower total lymphocyte count, percentage of T lymphocytes, CD8+CD38+ mean fluorescence intensity (MFI), and percentage of CD8+ human leukocyte antigen DR isotope (HLA-DR)+ CD38-cells and higher percentage of natural killer lymphocytes, natural killer group 2A (NKG2A)+ MFI, percentage of CD8+CD38+cells, CD8+HLA-DR+MFI, CD8+NKG2A+MFI, and percentage of CD8+HLA-DR-CD38+cells. On multivariate regression, the CD8+HLA-DR+MFI, CD8+CD38+MFI, and total lymphocyte count were associated significantly with myocardial injury. CONCLUSION: Our findings suggest that lymphopenia, CD8+CD38+MFI, and CD8+HLA-DR+MFI are immune biomarkers of myocardial injury in hypertensive patients with COVID-19. The immune signature described here may aid in understanding the mechanisms underlying myocardial injury in these patients. The study data might open a new window for improvement in the treatment of hypertensive patients with COVID-19 and myocardial injury.

Mass spectrometry imaging of hair identifies daily maraviroc adherence in HPTN 069/ACTG A5305.

Objective measures of adherence for antiretrovirals used as pre-exposure prophylaxis (PrEP) are critical for improving preventative efficacy in both clinical trials and real-world application. Current objective adherence measures either reflect only recent behavior (eg days for plasma or urine) or cumulative behavior (eg months for dried blood spots). Here, we measured the accumulation of the antiretroviral drug maraviroc (MVC) in hair strands by infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) mass spectrometry imaging (MSI) to evaluate adherence behavior longitudinally at high temporal resolution. An MSI threshold for classifying daily adherence was established using clinical samples from healthy volunteers following directly observed dosing of 1 to 7 doses MVC/week. We then used the benchmarked MSI assay to classify adherence to MVC-based PrEP regimens in hair samples collected throughout the 48-week HPTN069/ACTGA5305 study. We found that only ~32% of investigated hair samples collected during the study's active dosing period showed consistent daily PrEP adherence throughout a retrospective period of 30 days, and also found that profiles of daily individual adherence from MSI hair analysis could identify when patients were and were not taking study drug. The assessment of adherence from MSI hair strand analysis was 62% lower than adherence classified using paired plasma samples, the latter of which may be influenced by white-coat adherence. These findings demonstrate the ability of MSI hair analysis to examine daily variability of adherence behavior over a longer-term measurement and offer the potential for longitudinal comparison with risk behavior to target patient-specific adherence interventions and improve outcomes.

TMS-EEG perturbation biomarkers for Alzheimer's disease patients classification.

The combination of TMS and EEG has the potential to capture relevant features of Alzheimer's disease (AD) pathophysiology. We used a machine learning framework to explore time-domain features characterizing AD patients compared to age-matched healthy controls (HC). More than 150 time-domain features including some related to local and distributed evoked activity were extracted from TMS-EEG data and fed into a Random Forest (RF) classifier using a leave-one-subject out validation approach. The best classification accuracy, sensitivity, specificity and F1 score were of 92.95%, 96.15%, 87.94% and 92.03% respectively when using a balanced dataset of features computed globally across the brain. The feature importance and statistical analysis revealed that the maximum amplitude of the post-TMS signal, its Hjorth complexity and the amplitude of the TEP calculated in the window 45-80 ms after the TMS-pulse were the most relevant features differentiating AD patients from HC. TMS-EEG metrics can be used as a non-invasive tool to further understand the AD pathophysiology and possibly contribute to patients' classification as well as longitudinal disease tracking.

TMS combined with EEG: Recommendations and open issues for data collection and analysis.

Transcranial magnetic stimulation (TMS) evokes neuronal activity in the targeted cortex and connected brain regions. The evoked brain response can be measured with electroencephalography (EEG). TMS combined with simultaneous EEG (TMS-EEG) is widely used for studying cortical reactivity and connectivity at high spatiotemporal resolution. Methodologically, the combination of TMS with EEG is challenging, and there are many open questions in the field. Different TMS-EEG equipment and approaches for data collection and analysis are used. The lack of standardization may affect reproducibility and limit the comparability of results produced in different research laboratories. In addition, there is controversy about the extent to which auditory and somatosensory inputs contribute to transcranially evoked EEG. This review provides a guide for researchers who wish to use TMS-EEG to study the reactivity of the human cortex. A worldwide panel of experts working on TMS-EEG covered all aspects that should be considered in TMS-EEG experiments, providing methodological recommendations (when possible) for effective TMS-EEG recordings and analysis. The panel identified and discussed the challenges of the technique, particularly regarding recording procedures, artifact correction, analysis, and interpretation of the transcranial evoked potentials (TEPs). Therefore, this work offers an extensive overview of TMS-EEG methodology and thus may promote standardization of experimental and computational procedures across groups.

A Novel Algorithm to Improve PrEP Adherence Monitoring Using Dried Blood Spots.

Tenofovir diphosphate (TFVdp; an active metabolite of oral HIV pre-exposure prophylaxis (PrEP)) is measured in dried blood spots (DBS) to estimate adherence. However, TFVdp's long half-life in whole blood may lead to misclassification following a recent change in adherence. PrEP's other metabolite, emtricitabine triphosphate (FTCtp), has a shorter half-life in whole blood but adherence thresholds are undefined. We characterized DBS TFVdp and FTCtp concentrations across many dosing scenarios. Population pharmacokinetic models were fit to TFVdp and FTCtp DBS concentrations from a directly observed therapy study (NCT03218592). Concentrations were simulated for 90 days of daily dosing followed by 90 days of 1 to 7 doses/week and for event-driven PrEP (edPrEP) scenarios. Thresholds of 1,000 and 200 fmol/punch, for TFVdp and FTCtp, respectively, were reflective of taking 4 doses/week (a minimum target for effective PrEP in men). TFVdp was < 1,000 fmol/punch for 17 days after initiating daily PrEP and > 1,000 fmol/punch for 62 days after decreasing to 3 doses/week. Respectively, FTCtp was < 200 fmol/punch for 4 days and > 200 fmol/punch for 6 days. Accuracy of edPrEP adherence classification depended on duration between last sex act and DBS sampling for both measures with misclassification ranging from 9-100%. These data demonstrate adherence misclassification by DBS TFVdp for 2 months following a decline in adherence, elucidating the need for FTCtp to estimate recent adherence. We provide proof of principle that individualized interpretation is needed to support edPrEP adherence monitoring. Our collective approach facilitates clinicians' ability to interpret DBS results and administer patient-centric interventions.

Supported nanostructured photocatalysts: the role of support-photocatalyst interactions.

Heterogeneous photocatalysis employing semiconductor oxide photocatalysts is a sustainable and promising method for environmental remediation and clean energy generation. In this context, nanostructured photocatalysts, with at least one dimension in the 1‒100 nm size regime, have attracted ever-growing attention due to their unique and often enhanced size-dependent physicochemical properties. While their reduced size ensures enhanced photocatalytic performance, the same makes it difficult and time/energy-demanding to remove/recover such nanostructured photocatalysts from aqueous media. This fundamental limitation has paved the way towards developing supported nanophotocatalysts where the active photocatalytic nanostructures are coated on the surface of polymeric or inorganic support materials, often in a core@shell conformation. This arrangement solves the problem of photocatalysts' recovery for effective reuse or recycling and leads to improved and desired target properties due to specific photocatalyst-support interactions. While the enhanced physicochemical properties of supported photocatalysts have been widely studied in many target applications, the role of support-photocatalysts interactions in improving these properties remains unexplored. This review article provides an updated viewpoint on the photocatalyst-support interactions and the resulting unique physiochemical properties important for diverse photochemical applications and the design of practical devices. While exploring the properties of supported nanostructured metal oxide/sulfides photocatalysts such as TiO2 and MoS2, we also briefly discuss the common strategies employed to coat the active nanomaterials on the surface of different supports (organic/polymeric, inorganic, active, inert, and magnetic).

Force behaviour of elastic chains during a simulated gap closure in extraction therapy cases.

OBJECTIVE: Tooth movement with elastic chains requires defined force magnitudes. This study assessed the force behaviour of different elastic chains at different configurations of gap width. METHODS: Self-ligating brackets of teeth 5 & 6 and 2 & 3 were bonded to two movable aluminium plates. The plates were positioned on a joint basis with varying distances of 0.5, 2.0, 4.0, 6.0, and 8.0 mm. Reset forces of open and closed chains from four different manufacturers were investigated in four different configurations. Configurations differed in either having an additional intermediate ring within the gap (#1, #3) and/or having intermediate rings between teeth adjacent to the gap (#1, #2), or by no intermediate rings (#4). Forces were measured with a universal testing machine. The results were statistically analysed using U-test, H-test and (if applicable) post-hoc tests with a significance level of .05. RESULTS: Configurations #1 and #3, and #2 and #4 formed homogenous subgroups (P < .001). Initial forces in configuration #4 were significantly higher than in configuration #3 (P = .029). Initial forces in closed chains were significantly higher than for open chains (P = .029). CONCLUSIONS: Intermediate chain rings adjacent to the gap are not required to modulate the force. In contrast, leaving a ring unapplied in the tooth gap can help modulate the force. Open thermoset chains with an additional ring within the gap (#3) seem to produce suitable initial forces for a gap closure of 4 mm. With a residual gap width of <2 mm, open thermoset chains and closed thermoset chains (#4) seem suitable.

Regional Precuneus Cortical Hyperexcitability in Alzheimer's Disease Patients.

OBJECTIVE: Neuronal excitation/inhibition (E/I) imbalance is a potential cause of neuronal network malfunctioning in Alzheimer's disease (AD), contributing to cognitive dysfunction. Here, we used a novel approach combining transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to probe cortical excitability in different brain areas known to be directly involved in AD pathology. METHODS: We performed TMS-EEG recordings targeting the left dorsolateral prefrontal cortex (l-DLPFC), the left posterior parietal cortex (l-PPC), and the precuneus (PC) in a large sample of patients with mild-to-moderate AD (n = 65) that were compared with a group of age-matched healthy controls (n = 21). RESULTS: We found that patients with AD are characterized by a regional cortical hyperexcitability in the PC and, to some extent, in the frontal lobe, as measured by TMS-evoked potentials. Notably, cortical excitability assessed over the l-PPC was comparable between the 2 groups. Furthermore, we found that the individual level of PC excitability was associated with the level of cognitive impairment, as measured with Mini-Mental State Examination, and with corticospinal fluid levels of Aß42 . INTERPRETATION: Our data provide novel evidence that precuneus cortical hyperexcitability is a key feature of synaptic dysfunction in patients with AD. The current results point to the combined approach of TMS and EEG as a novel promising technique to measure hyperexcitability in patients with AD. This index could represent a useful biomarker to stage disease severity and evaluate response to novel therapies. ANN NEUROL 2023;93:371-383.

Employment of 3D-Printed Bilayer Structures with Embedded Continuous Fibers for Thermal Management Applications: An Axial Cooling 4D-Printed Fan Application Case Study.

Bi-material composite structures with continuous fibers embedded on polymer substrates exhibit self-morphing under thermal stimulus induced by the different coefficients of thermal expansion (CTE) between the two constituent materials. In this study, a series of such structures are investigated in terms of fiber patterns and materials to achieve programmable and reversible transformations that can be exploited for thermal management applications. Stemming from this investigation's results, an axial cooling fan prototype is designed and fabricated with composite blades that passively alter their shape, specifically their curvature and twist angle, under different operating temperatures. A series of computational fluid dynamics (CFD) simulations are performed, subjecting the fan's geometry to different flow temperatures to measure differences in airflow deriving from the induced shape transformations. Corresponding experimental trials are additionally performed, aiming to validate the simulation results. The results indicate the potential of utilizing bilayer self-morphing configurations for the fabrication of smart components for cooling purposes.

The Effect of Coil Orientation on the Stimulation of the Pre-Supplementary Motor Area: A Combined TMS and EEG Study.

Studies using transcranial magnetic stimulation (TMS) have demonstrated the importance of direction and intensity of the applied current when the primary motor cortex (M1) is targeted. By varying these, it is possible to stimulate different subsets of neural elements, as demonstrated by modulation of motor evoked potentials (MEPs) and motor behaviour. The latter involves premotor areas as well, and among them, the presupplementary motor area (pre-SMA) has recently received significant attention in the study of motor inhibition. It is possible that, similar to M1, different neuronal populations can be activated by varying the direction and intensity of TMS; however, the absence of a direct electrophysiological outcome has limited this investigation. The problem can be solved by quantifying direct cortical responses by means of combined TMS and electroencephalography (TMS-EEG). We investigated the effect of variable coil orientations (0°, 90°, 180° and 270°) and stimulation intensities (100%, 120% and 140% of resting motor threshold) on local mean field potential (LMFP), transcranial evoked potential (TEP) peaks and TMS-related spectral perturbation (TRSP) from pre-SMA stimulation. As a result, early and late LMFP and peaks were larger, with the coil handle pointing posteriorly (0°) and laterally (90°). This was true also for TRSP in the ß-γ range, but, surprisingly, θ-α TRSP was larger with the coil pointing at 180°. A 90° orientation activated the right M1, as shown by MEPs elicitation, thus limiting the spatial specificity of the stimulation. These results suggest that coil orientation and stimulation intensity are critical when stimulating the pre-SMA.

Digital Innovation Enabled Nanomaterial Manufacturing; Machine Learning Strategies and Green Perspectives.

Machine learning has been an emerging scientific field serving the modern multidisciplinary needs in the Materials Science and Manufacturing sector. The taxonomy and mapping of nanomaterial properties based on data analytics is going to ensure safe and green manufacturing with consciousness raised on effective resource management. The utilization of predictive modelling tools empowered with artificial intelligence (AI) has proposed novel paths in materials discovery and optimization, while it can further stimulate the cutting-edge and data-driven design of a tailored behavioral profile of nanomaterials to serve the special needs of application environments. The previous knowledge of the physics and mathematical representation of material behaviors, as well as the utilization of already generated testing data, received specific attention by scientists. However, the exploration of available information is not always manageable, and machine intelligence can efficiently (computational resources, time) meet this challenge via high-throughput multidimensional search exploration capabilities. Moreover, the modelling of bio-chemical interactions with the environment and living organisms has been demonstrated to connect chemical structure with acute or tolerable effects upon exposure. Thus, in this review, a summary of recent computational developments is provided with the aim to cover excelling research and present challenges towards unbiased, decentralized, and data-driven decision-making, in relation to increased impact in the field of advanced nanomaterials manufacturing and nanoinformatics, and to indicate the steps required to realize rapid, safe, and circular-by-design nanomaterials.

Quantitative Imaging Analysis of the Spatial Relationship between Antiretrovirals, Reverse Transcriptase Simian-Human Immunodeficiency Virus RNA, and Fibrosis in the Spleens of Nonhuman Primates.

Although current antiretroviral therapy (ART) has increased life expectancy, a cure for human immunodeficiency virus (HIV) remains elusive due to the persistence of the virus in tissue reservoirs. In the present study, we sought to elucidate the relationship between antiretrovirals (ARVs) and viral expression in the spleen. We performed mass spectrometry imaging (MSI) of 6 different ARVs, RNAscope in situ hybridization of viral RNA, and immunohistochemistry of three different fibrosis markers in the spleens of 8 uninfected and 10 reverse transcriptase simian-human immunodeficiency virus (RT-SHIV)-infected rhesus macaques (infected for 6 weeks) that had been dosed for 10 days with combination ART. Using MATLAB, computational quantitative imaging analysis was performed to evaluate the spatial and pharmacological relationships between the 6 ARVs, viral RNA, and fibrotic deposition. In these spleens, >50% of the spleen tissue area was not covered by any detectable ARV response (any concentration above the limits of detection for individual ARVs). The median spatial ARV coverage across all tissues was driven by maraviroc followed by efavirenz. Yet >50% of RNA-positive cells were not exposed to any detectable ARV. Quantifiable maraviroc and efavirenz colocalization with RNA-positive cells was usually greater than the in vitro concentration inhibiting 50% replication (IC50). Fibrosis markers covered more than 50% of the spleen tissue area and had negative relationships with cumulative ARV coverages. Our findings suggest that a heterogeneous ARV spatial distribution must be considered when evaluating viral persistence in lymphoid tissue reservoirs.

The link between cutaneous inflammation and cognitive impairment.

Cognitive impairment is a symptom of neurological disorders, including dementia and Alzheimer's disease; and mild cognitive impairment can be a precursor of both disorders. Aged humans and animal models with other systemic disorders, such as cardiovascular diseases and diabetes, display a higher incidence of cognitive decline. Epidemiological studies have shown that the incidence of cognitive impairment also is higher in subjects with certain inflammatory skin disorders, including psoriasis and chronic eczematous dermatitis. Chronologically aged individuals exhibit increased cutaneous inflammation and elevated circulating cytokine levels, linked to alterations in epidermal function, which itself can induce cutaneous inflammation. Conversely, strategies that improve epidermal function can lower cytokine levels in both the skin and circulation. Thus, it seems likely that epidermal dysfunction could contribute, at least in part, to the development of chronic low-grade inflammation, also termed 'inflammaging', in the elderly. The evidence of cognitive impairment in patients with inflammatory dermatoses suggests a link between cutaneous inflammation and cognitive impairment. Because of the pathogenic role of epidermal dysfunction in ageing-associated cutaneous inflammation, improvements in epidermal function could be an alternative approach for mitigation of the ageing-associated decline in cognitive function.

Occupational Safety Analysis for COVID-Instigated Repurposed Manufacturing Lines: Use of Nanomaterials in Injection Moulding.

The COVID-19 pandemic instigated massive production of critical medical supplies and personal protective equipment. Injection moulding (IM) is considered the most prominent thermoplastic part manufacturing technique, offering the use of a large variety of feedstocks and rapid production capacity. Within the context of the European Commission-funded imPURE project, the benefits of IM have been exploited in repurposed IM lines to accommodate the use of nanocomposites and introduce the unique properties of nanomaterials. However, these amendments in the manufacturing lines highlighted the need for targeted and thorough occupational risk analysis due to the potential exposure of workers to airborne nanomaterials and fumes, as well as the introduction of additional occupational hazards. In this work, a safety-oriented failure mode and effects analysis (FMEA) was implemented to evaluate the main hazards in repurposed IM lines using acrylonitrile butadiene styrene (ABS) matrix and silver nanoparticles (AgNPs) as additives. Twenty-eight failure modes were identified, with the upper quartile including the seven failure modes presenting the highest risk priority numbers (RPN), signifying a need for immediate control action. Additionally, a nanosafety control-banding tool allowed hazard classification and the identification of control actions required for mitigation of occupation risks due to the released airborne silver nanoparticles.