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Background and Objectives : The term long COVID refers to patients with a history of confirmed COVID-19 infection, who present symptoms that last for at least 2 months and cannot be explained by another diagnosis. Objectives: The present study aims to determine the most common symptoms of the long COVID syndrome and their impact on the quality of life. Materials and Methods : A prospective observational study was conducted on patients diagnosed with mild and moderate COVID-19 (based on a positive SARS-CoV-2 molecular diagnostic or rapid antigen test and severity form definition) at the Clinical Hospital of Infectious Diseases, Cluj-Napoca, Romania. Clinical examinations with detailed questions about symptoms were performed at the time of the diagnosis of COVID-19 and the six-month follow-up. Two years after COVID-19 infection, patients were invited to complete an online quality-of-life questionnaire regarding long COVID symptoms. Results : A total of 103 patients (35.92% males) with a mean age of 41.56 ± 11.77 were included in this study. Of the total number of patients, 65.04% presented mild forms of COVID-19. Data regarding the vaccination status showed that 83.5% were vaccinated against SARS-CoV-2. The most common symptoms at diagnosis were cough (80.6%), fatigue (80.4%), odynophagia (76.7%), and headaches (67.6%), with female patients being statistically more likely to experience it ( p = 0.014). Patients with moderate forms of the disease had higher levels of both systolic ( p = 0.008) and diastolic ( p = 0.037) blood pressure at diagnosis, but no statistical difference was observed in the 6-month follow-up. The most common symptoms at 2 years (in 29 respondent subjects) were represented by asthenia (51.7%), headache (34.5%), memory disorders (27.6%), abdominal meteorism (27.6%), and arthralgia (27.6%). In terms of cardiovascular symptoms, fluctuating blood pressure values (20.7%), palpitations (17.2%), and increased heart rate values (17.2%) were recorded. Conclusions : If at the time of diagnosis, the most frequent manifestations of the disease were respiratory, together with headache and fatigue, at re-evaluation, asthenia, decreased effort tolerance, and neuropsychiatric symptoms prevailed. Regarding the cardiovascular changes as part of the long COVID clinical picture, some patients developed prehypertension, palpitations, and tachycardia.

Macrocephaly, characterized by an abnormally large head circumference, often co-occurs with distinctive finger changes, presenting a diagnostic challenge for clinicians. This review aims to provide a current synthetic overview of the main acquired and genetic etiologies associated with macrocephaly and finger changes. The genetic cause encompasses several categories of diseases, including bone marrow expansion disorders, skeletal dysplasias, ciliopathies, inherited metabolic diseases, RASopathies, and overgrowth syndromes. Furthermore, autoimmune and autoinflammatory diseases are also explored for their potential involvement in macrocephaly and finger changes. The intricate genetic mechanisms involved in the formation of cranial bones and extremities are multifaceted. An excess in growth may stem from disruptions in the intricate interplays among the genetic, epigenetic, and hormonal factors that regulate human growth. Understanding the underlying cellular and molecular mechanisms is important for elucidating the developmental pathways and biological processes that contribute to the observed clinical phenotypes. The review provides a practical approach to delineate causes of macrocephaly and finger changes, facilitate differential diagnosis and guide for the appropriate etiological framework. Early recognition contributes to timely intervention and improved outcomes for affected individuals.

The importance and value of real-world data in healthcare cannot be overstated because it offers a valuable source of insights into patient experiences. Traditional patient-reported experience and outcomes measures (PREMs/PROMs) often fall short in addressing the complexities of these experiences due to subjectivity and their inability to precisely target the questions asked. In contrast, diary recordings offer a promising solution. They can provide a comprehensive picture of psychological well-being, encompassing both psychological and physiological symptoms. This study explores how using advanced digital technologies, i.e., automatic speech recognition and natural language processing, can efficiently capture patient insights in oncology settings. We introduce the MRAST framework, a simplified way to collect, structure, and understand patient data using questionnaires and diary recordings. The framework was validated in a prospective study with 81 colorectal and 85 breast cancer survivors, of whom 37 were male and 129 were female. Overall, the patients evaluated the solution as well made; they found it easy to use and integrate into their daily routine. The majority (75.3%) of the cancer survivors participating in the study were willing to engage in health monitoring activities using digital wearable devices daily for an extended period. Throughout the study, there was a noticeable increase in the number of participants who perceived the system as having excellent usability. Despite some negative feedback, 44.44% of patients still rated the app's usability as above satisfactory (i.e., 7.9 on 1-10 scale) and the experience with diary recording as above satisfactory (i.e., 7.0 on 1-10 scale). Overall, these findings also underscore the significance of user testing and continuous improvement in enhancing the usability and user acceptance of solutions like the MRAST framework. Overall, the automated extraction of information from diaries represents a pivotal step toward a more patient-centered approach, where healthcare decisions are based on real-world experiences and tailored to individual needs. The potential usefulness of such data is enormous, as it enables better measurement of everyday experiences and opens new avenues for patient-centered care.

In order to limit the spread of the novel betacoronavirus (SARS-CoV-2), it is necessary to detect positive cases as soon as possible and isolate them. For this purpose, machine-learning algorithms, as a field of artificial intelligence, have been recognized as a promising tool. The aim of this study was to assess the utility of the most common machine-learning algorithms in the rapid triage of children with suspected COVID-19 using easily accessible and inexpensive laboratory parameters. A cross-sectional study was conducted on 566 children treated for respiratory diseases: 280 children with PCR-confirmed SARS-CoV-2 infection and 286 children with respiratory symptoms who were SARS-CoV-2 PCR-negative (control group). Six machine-learning algorithms, based on the blood laboratory data, were tested: random forest, support vector machine, linear discriminant analysis, artificial neural network, k-nearest neighbors, and decision tree. The training set was validated through stratified cross-validation, while the performance of each algorithm was confirmed by an independent test set. Random forest and support vector machine models demonstrated the highest accuracy of 85% and 82.1%, respectively. The models demonstrated better sensitivity than specificity and better negative predictive value than positive predictive value. The F1 score was higher for the random forest than for the support vector machine model, 85.2% and 82.3%, respectively. This study might have significant clinical applications, helping healthcare providers identify children with COVID-19 in the early stage, prior to PCR and/or antigen testing. Additionally, machine-learning algorithms could improve overall testing efficiency with no extra costs for the healthcare facility.

Hydroxychloroquine (HCQ), an anti-malarial drug, is suggested as a promising candidate for the treatment of pregnancy-related disorders associated with endothelial activation, among which there is preeclampsia (PE). Arterial feto-placental endothelial cells (fpECAs) were isolated from control (CTR) and early-onset preeclamptic (EO-PE) placentas. The aim of this study was to test potential protective effects of HCQ in an in vitro model of endothelial activation as well as in cells isolated from EO-PE placentas. To mimic PE conditions, CTR fpECAs were exposed to a pro-inflammatory environment consisting of tumor necrosis factor α (TNF-α), interleukin (IL)-6 and IL-1β (furtherly referred as MIX) with or without varying concentrations of HCQ (1 µg/mL and 10 µg/mL). Their effect on wound healing and endothelial barrier integrity was analyzed. Variations in the expression of IL-8 and leukocyte adhesion molecules (LAM) on both mRNA and protein levels were determined between CTR and PE fpECAs in the presence or absence of HCQ. MIX decreased wound healing and stability of the endothelial barrier, but HCQ did not affect it. Significant differences between CTR and EO-PE fpECAs were observed in IL-8 mRNA, protein secretion, and vascular cell adhesion protein 1 ( VCAM-1) mRNA expression levels. After challenging CTR fpECAs with MIX, upregulation of both mRNA and protein levels was observed in all molecules. Combined treatment of HCQ and MIX slightly lowered VCAM-1 total protein amount. In CTR fpECAs, treatment with low concentrations of HCQ alone (1 µg/mL) reduced basal levels of IL-8 and VCAM-1 mRNA and secretion of IL-8, while in EO-PE fpECAs, a higher (10µg/mL) HCQ concentration slightly reduced the gene expression of IL-8 . Conclusion: These results provide additional support for the safety of HCQ, as it did not adversely affect endothelial functionality in control fpECAs at the tested concentration. Furthermore, the observed limited effects on IL-8 secretion in EO-PE fpECAs warrant further investigation, highlighting the need for clinical trials to assess the potential therapeutic effects of HCQ in preeclampsia. Conducting clinical trials would offer a more comprehensive understanding of HCQ's efficacy and safety, allowing us to explore its potential benefits and limitations in a real-world clinical setting.

Binaural synthesis with head tracking is often used in spatial audio systems. The devices used for head tracking must provide data on the orientation of the listener's head. These data need to be highly accurate, and they need to be provided as fast and as frequently as possible. Therefore, head-tracking devices need to be equipped with high-quality inertial measurement unit (IMU) sensors. Since IMUs readily include triaxial accelerometers, gyroscopes, and magnetometers, it is crucial that all of these sensors perform well, as the head orientation is calculated from all sensor outputs. This paper discusses the challenges encountered in the process of the performance assessment of IMUs through appropriate measurements. Three distinct hardware platforms were investigated: five IMU sensors either connected to Arduino-based embedded systems or being an integral part of one, five smartphones across a broad range of overall quality with integrated IMUs, and a commercial virtual reality unit that utilizes a headset with integrated IMUs. An innovative measurement method is presented and proposed for comparing the performance of sensors on all three platforms. The results of the measurements performed using the proposed method show that all three investigated platforms are adequate for the acquisition of the data required for calculating the orientation of a device as the input to the binaural synthesis process. Some limitations that have been observed during the measurements, regarding data acquisition and transfer, are discussed.

Human biomonitoring has become a pivotal tool for supporting chemicals' policies. It provides information on real-life human exposures and is increasingly used to prioritize chemicals of health concern and to evaluate the success of chemical policies. Europe has launched the ambitious REACH program in 2007 to improve the protection of human health and the environment. In October 2020 the EU commission published its new chemicals strategy for sustainability towards a toxic-free environment. The European Parliament called upon the commission to collect human biomonitoring data to support chemical's risk assessment and risk management. This manuscript describes the organization of the first HBM4EU-aligned studies that obtain comparable human biomonitoring (HBM) data of European citizens to monitor their internal exposure to environmental chemicals. The HBM4EU-aligned studies build on existing HBM capacity in Europe by aligning national or regional HBM studies. The HBM4EU-aligned studies focus on three age groups: children, teenagers, and adults. The participants are recruited between 2014 and 2021 in 11 to 12 primary sampling units that are geographically distributed across Europe. Urine samples are collected in all age groups, and blood samples are collected in children and teenagers. Auxiliary information on socio-demographics, lifestyle, health status, environment, and diet is collected using questionnaires. In total, biological samples from 3137 children aged 6-12 years are collected for the analysis of biomarkers for phthalates, HEXAMOLL ® DINCH, and flame retardants. Samples from 2950 teenagers aged 12-18 years are collected for the analysis of biomarkers for phthalates, Hexamoll ® DINCH, and per- and polyfluoroalkyl substances (PFASs), and samples from 3522 adults aged 20-39 years are collected for the analysis of cadmium, bisphenols, and metabolites of polyaromatic hydrocarbons (PAHs). The children's group consists of 50.4% boys and 49.5% girls, of which 44.1% live in cities, 29.0% live in towns/suburbs, and 26.8% live in rural areas. The teenagers' group includes 50.6% girls and 49.4% boys, with 37.7% of residents in cities, 31.2% in towns/suburbs, and 30.2% in rural areas. The adult group consists of 52.6% women and 47.4% men, 71.9% live in cities, 14.2% in towns/suburbs, and only 13.4% live in rural areas. The study population approaches the characteristics of the general European population based on age-matched EUROSTAT EU-28, 2017 data; however, individuals who obtained no to lower educational level (ISCED 0-2) are underrepresented. The data on internal human exposure to priority chemicals from this unique cohort will provide a baseline for Europe's strategy towards a non-toxic environment and challenges and recommendations to improve the sampling frame for future EU-wide HBM surveys are discussed.

Pregnant women's levels of toxic and essential minerals have been linked to birth outcomes yet have not been adequately investigated in South America. In Argentina, n = 696 maternal whole blood samples from Ushuaia ( n = 198) and Salta ( n = 498) were collected in 2011-2012 among singleton women at 36 ± 12 h postpartum and analyzed for blood concentrations of arsenic (As), cadmium (Cd), mercury (Hg), lead (Pb), copper (Cu), manganese (Mn), selenium (Se) and zinc (Zn). This study examined the associations between maternal elements levels and birth outcomes, and sociodemographic factors contributing to elements levels. Maternal age, parity, body mass index, smoking, and education were linked to concentrations of some but not all elements. In adjusted models, one ln-unit increase in Pb levels was associated with increased gestational age (0.2 weeks, 95% CI = 0.01-0.48) and decreased birth weight (-88.90 g, 95% CI = -173.69 to -4.11) and birth length (-0.46 cm, 95% CI = -0.85 to -0.08) in the Salta sample. Toxic elements concentrations were not associated with birth outcomes in Ushuaia participants. Birth outcomes are multifactorial problems, and these findings provide a foundation for understanding how the body burden of toxic and essential elements, within the socioeconomic context, may influence birth outcomes.

The current COVID-19 outbreak has highlighted the need for the development of new vaccines and drugs to combat Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2). Recently, various drugs have been proposed as potentially effective against COVID-19, such as remdesivir, infliximab and imatinib. Natural plants have been used as an alternative source of drugs for thousands of years, and some of them are effective for the treatment of various viral diseases. Emodin (1,3,8-trihydroxy-6-methylanthracene-9,10-dione) is a biologically active anthraquinone with antiviral activity that is found in various plants. We studied the selectivity of electrophilic aromatic substitution reactions on an emodin core (halogenation, nitration and sulfonation), which resulted in a library of emodin derivatives. The main aim of this work was to carry out an initial evaluation of the potential to improve the activity of emodin against human coronavirus NL63 (HCoV-NL63) and also to generate a set of initial SAR guidelines. We have prepared emodin derivatives which displayed significant anti-HCoV-NL63 activity. We observed that halogenation of emodin can improve its antiviral activity. The most active compound in this study was the iodinated emodin analogue E_3I, whose anti-HCoV-NL63 activity was comparable to that of remdesivir. Evaluation of the emodin analogues also revealed some unwanted toxicity to Vero cells. Since new synthetic routes are now available that allow modification of the emodin structure, it is reasonable to expect that analogues with significantly improved anti-HCoV-NL63 activity and lowered toxicity may thus be generated.

Magnetic nanoparticles gained considerable attention in last few years due to their remarkable properties. Superparamaganetism, non-toxicity, biocompatibility, chemical inertness, and environmental friendliness are some of the properties that make iron oxide nanoparticles (IONPs) an ideal choice for biomedical applications. Along with being easily tuneable and a tailored surface for conjugation of IONPs, their physio-chemical and biological properties can also be varied by modifying the basic parameters for synthesis that enhances the additional possibilities for designing novel magnetic nanomaterial for theranostic applications. This review highlights the synthesis, surface modification, and different applications of IONPs for diagnosis, imaging, and therapy. Furthermore, it also represents the recent report on the application of IONPs as enzyme mimetic compounds and a contrasting agent, and its significance in the field as an anticancer and antimicrobial agent.

Understanding atmospheric mercury chemistry is the key for explaining the biogeochemical cycle of mercury and for improving the predictive capability of computational models. Increased efforts are being made to ensure comparable Hg speciation measurements in the air through establishing metrological traceability. While traceability for elemental mercury has been recently set, this is by no means the case for gaseous oxidized mercury (GOM). Since a calibration unit suitable for traceable GOM calibrations based on evaporation of HgCl 2 solution was recently developed, the purpose of our work was to extensively evaluate its performance. A highly specific and sensitive 197 Hg radiotracer was used for validation over a wide range of concentrations. By comparing experimental and calculated values, we obtained recoveries for the calibration unit. The average recoveries ranged from 88.5% for 1178 ng m -3 HgCl 2 gas concentration to 39.4% for 5.90 ng m -3 HgCl 2 gas concentration. The losses were due to the adsorption of oxidized Hg on the inner walls of the calibrator and tubing. An adsorption isotherm was applied to estimate adsorption enthalpy (ΔH ads ); a ΔH ads value of -12.33 kJ mol -1 was obtained, suggesting exothermal adsorption. The results of the calibrator performance evaluation suggest that a newly developed calibration unit is only suitable for concentrations of HgCl 2 higher than 1 µg m -3 . The concentration dependence of recoveries prevents the system from being used for calibration of instruments for ambient GOM measurements. Moreover, the previously assessed uncertainty of this unit at µg m -3 level (2.0%, k = 2) was re-evaluated by including uncertainty related to recovery and was found to be 4.1%, k = 2. Calibrator performance was also evaluated for HgBr 2 gas calibration; the recoveries were much lower for HgBr 2 gas than for HgCl 2 gas even at a high HgBr 2 gas concentration (>1 µg m -3 ). As HgBr 2 is often used as a proxy for various atmospheric HgBr species, the suitability of the unit for such calibration must be further developed.

Low-cost sensors can be used to improve the temporal and spatial resolution of an individual's particulate matter (PM) intake dose assessment. In this work, personal activity monitors were used to measure heart rate (proxy for minute ventilation), and low-cost PM sensors were used to measure concentrations of PM. Intake dose was assessed as a product of PM concentration and minute ventilation, using four models with increasing complexity. The two models that use heart rate as a variable had the most consistent results and showed a good response to variations in PM concentrations and heart rate. On the other hand, the two models using generalized population data of minute ventilation expectably yielded more coarse information on the intake dose. Aggregated weekly intake doses did not vary significantly between the models (6-22%). Propagation of uncertainty was assessed for each model, however, differences in their underlying assumptions made them incomparable. The most complex minute ventilation model, with heart rate as a variable, has shown slightly lower uncertainty than the model using fewer variables. Similarly, among the non-heart rate models, the one using real-time activity data has less uncertainty. Minute ventilation models contribute the most to the overall intake dose model uncertainty, followed closely by the low-cost personal activity monitors. The lack of a common methodology to assess the intake dose and quantifying related uncertainties is evident and should be a subject of further research.

This work reports the development of ultralight interwoven ultrathin graphitic carbon nitride (g-CN) nanosheets for use as a potential adsorbent in a passive sampler (PAS) designed to bind Hg 2+ ions. The g-CN nanosheets were prepared from bulk g-CN synthesised via a modified high-temperature short-time (HTST) polycondensation process. The crystal structure, surface functional groups, and morphology of the g-CN nanosheets were characterised using a battery of instruments. The results confirmed that the as-synthesized product is composed of few-layered nanosheets. The adsorption efficiency of g-CN for binding Hg 2+ (100 ng mL -1 ) in sea, river, rain, and Milli-Q quality water was 89%, 93%, 97%, and 100%, respectively, at natural pH. Interference studies found that the cations tested (Co 2+ , Ca 2+ , Zn 2+ , Fe 2+ , Mn 2+ , Ni 2+ , Bi 3+ , Na + , and K + ) had no significant effect on the adsorption efficiency of Hg 2+ . Different parameters were optimised to improve the performance of g-CN such as pH, contact time, and amount of adsorbent. Optimum conditions were pH 7, 120 min incubation time and 10 mg of nanosheets. The yield of nanosheets was 72.5%, which is higher compared to other polycondensation processes using different monomers. The g-CN sheets could also be regenerated up to eight times with only a 20% loss in binding efficiency. Overall, nano-knitted g-CN is a promising low-cost green adsorbent for use in passive samplers or as a transducing material in sensor applications., Competing Interests: The authors declare no conflict of interest.

Human biomonitoring (HBM) programs consist of several interrelated and equally important steps. Of these steps, the study design must answer a specific question: How many individuals must be recruited in order to define the spatial or temporal trends of exposure to environmental pollutants in a given HBM study? Two components must be considered at this stage: the population variability of the expected exposure and the performance characteristics of the analytical methods used. The objective of the present study was to quantify the contribution to the required sample size arising from (i) measurement uncertainty and (ii) inter-laboratory measurement variability. For this purpose, the sample size was calculated using the measurement uncertainty of one laboratory, inter-laboratory comparison exercise data, and population variability for commonly studied metals (mercury, cadmium, and lead) in blood. Measurement uncertainty within one laboratory proved to have little influence on the sample size requirements, while the inter-laboratory variability of the three metals increased the requirements considerably, particularly in cases of low population variability. The multiple laboratories approach requires that laboratory variability be considered as early as the planning stage; a single-laboratory approach is thus a cost-effective compromise in HBM to reduce variability due to the participation of different laboratories.

Low-cost sensors are a current trend in citizen science projects that focus on air quality. Until now, devices incorporating such sensors have been tested primarily for their technical capabilities and limitations, whereas their usability and acceptability amongst the public rarely goes beyond proof of concept, leaving user experience (UX) unstudied. The authors argue that UX should be taken into account to make sure that products and services are fit for purpose. Nineteen volunteers tested and evaluated a prototype device and provided feedback through semi-structured interviews and during focus group sessions. Their UX was then coded using mixed coding methods regarding device functionality and recommendations for future product development. The results indicate that UX can identify potentially problematic design aspects while giving deeper insights into user needs. For example, UX recognized that one of the most important aspects of user involvement and motivation was successful data harvesting, which frequently failed. This study recommends that future developers of low-cost portable air quality sensor systems prioritize reliable data transmission to minimize data loss. This will ensure an efficient and positive UX that supports user engagement in citizen science based research where collecting sensor-based data is the primary objective., Competing Interests: The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in writing of the manuscript; or in the decision to publish the results.

Aquatic ecosystems are an essential component of the biogeochemical cycle of mercury (Hg), as inorganic Hg can be converted to toxic methylmercury (MeHg) in these environments and reemissions of elemental Hg rival anthropogenic Hg releases on a global scale. Quantification of effluent Hg releases to aquatic systems globally has focused on discharges to the global oceans, rather than contributions to freshwater systems that affect local exposures and risks associated with MeHg. Here we produce a first-estimate of sector-specific, spatially resolved global aquatic Hg discharges to freshwater systems. We compare our release estimates to atmospheric sources that have been quantified elsewhere. By analyzing available quantitative and qualitative information, we estimate that present-day global Hg releases to freshwater environments (rivers and lakes) associated with anthropogenic activities have a lower bound of ~1000 Mg· a-1. Artisanal and small-scale gold mining (ASGM) represents the single largest source, followed by disposal of mercury-containing products and domestic waste water, metal production, and releases from industrial installations such as chlor-alkali plants and oil refineries. In addition to these direct anthropogenic inputs, diffuse inputs from land management activities and remobilization of Hg previously accumulated in terrestrial ecosystems are likely comparable in magnitude. Aquatic discharges of Hg are greatly understudied and further constraining associated data gaps is crucial for reducing the uncertainties in the global biogeochemical Hg budget.

The difference in arsenic concentration and speciation between benthic (Pteromylaeus bovinus, Myliobatis aquila) and pelagic rays (Pteroplatytrygon violacea) from the northern Adriatic Sea (Gulf of Trieste) in relation to their size (age) was investigated. High arsenic concentrations were found in both groups with tendency of more efficient arsenic accumulation in benthic species, particularly in muscle (32.4 to 362 µg·g-1 of total arsenic). This was attributed to species differences in arsenic access, uptake and retention. In liver most arsenic was present in a form of arsenobetaine, dimethylarsinic acid and arsenoipids, whereas in muscle mainly arsenobetaine was found. The good correlations between total arsenic/arsenobetaine and size reflect the importance of accumulation of arsenobetaine with age. Arsenobetaine is an analogue of glycine betaine, a known osmoregulator in marine animals and both are very abundant in mussels, representing an important source of food for benthic species P. bovinus and M. aquila.