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Background and Objectives: Patients suffering from neurological diseases may develop dysarthria, a motor speech disorder affecting the execution of speech. Close and quantitative monitoring of dysarthria evolution is crucial for enabling clinicians to promptly implement patients' management strategies and maximizing effectiveness and efficiency of communication functions in term of restoring, compensating or adjusting. In the clinical assessment of orofacial structures and functions, at rest condition or during speech and non-speech movements, a qualitative evaluation is usually performed, throughout visual observation., Methods: To overcome limitations posed by qualitative assessments, this work presents a store-and-forward self-service telemonitoring system that integrates, within its cloud architecture, a convolutional neural network (CNN) for analyzing video recordings acquired by individuals with dysarthria. This architecture - called facial landmark Mask RCNN - aims at locating facial landmarks as a prior for assessing the orofacial functions related to speech and examining dysarthria evolution in neurological diseases., Results: When tested on the Toronto NeuroFace dataset, a publicly available annotated dataset of video recordings from patients with amyotrophic lateral sclerosis (ALS) and stroke, the proposed CNN achieved a normalized mean error equal to 1.79 on localizing the facial landmarks. We also tested our system in a real-life scenario on 11 bulbar-onset ALS subjects, obtaining promising outcomes in terms of facial landmark position estimation., Discussion and Conclusions: This preliminary study represents a relevant step towards the use of remote tools to support clinicians in monitoring the evolution of dysarthria., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Modern society has increasingly a diffusion of pollutants and emerging contaminants (e.g., different types of chemicals and endocrine disruptors in pharmaceuticals, pesticides, household cleaning, and personal care products, etc.) that have detrimental effects on the environment (atmosphere, hydrosphere, biosphere and anthroposphere) and also generate diseases and disorders on the people health. Environmental science requires efforts in the detection and elimination of manifold pollutants and emerging pollutants with appropriate product and process technologies. This study aims to analyze different paths of treatment technologies to investigate their evolution and predict new directions of promising technological trajectories to support the removal of contaminants directed to reach, whenever possible, sustainable development objectives. The work is mainly devoted to wastewater treatment technologies. A proposed model analyzes the evolution of patents (proxy of innovation and new technology) on publications (proxy of science and knowledge advances) to quantify the relative growth rate of new trajectories of technologies to remove pollutants and emerging contaminants. Results reveal that new directions of treatment technologies having an accelerated rate of growth are (in decreasing order): biochar and reverse osmosis in physical-based technologies, coagulation, and disinfection water treatments in chemical-based technologies and anaerobic processes in biological-based technologies. Other main technologies, such as carbon nanotubes and advanced oxidation processes, seem to be in the initial phase of development and need learning by using processes and further science and technology advances to be implemented as effective treatments and cost-effective methods. The results here show similar trends to global market revenue in water and wastewater treatment technologies. These findings bring us to the main information to extend the knowledge about new directions of technologies for the treatment and/or elimination of pollutants and microorganisms in order to support decisions of policymakers towards goals of sustainable development by reducing environmental degradation and people health disorders., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

In the presence of pandemic threats, such as Coronavirus Disease 2019 (COVID-19) crisis, vaccination is one of the fundamental strategies to cope with negative effects of new viral agents in society. The rollout of vast vaccination campaigns also generates the main issue of hesitancy and resistance to vaccines in a share of people. Many studies have investigated how to reduce the social resistance to vaccinations, however the maximum level of vaccinable people against COVID-19 (and in general against pandemic diseases), without coercion in countries, is unknown. The goal of this study is to solve the problem here by developing an empirical analysis, based on global data, to estimate the max share of people vaccinable in relation to socioeconomic wellbeing of nations. Results, based on 150 countries, reveal that vaccinations increase with the income per capita, achieving the maximum share of about 70% of total population, without coercion. This information can provide new knowledge to establish the appropriate goal of vaccination campaigns and in general of health policies to cope with next pandemic impacts, without restrictions that create socioeconomic problems. Overall, then, nations have a natural level of max vaccinable people (70% of population), but strict policies and mandates to achieve 90% of vaccinated population can reduce the quality of democracy and generate socioeconomic issues higher than (pandemic) crisis., (Copyright © 2022 Elsevier Inc. All rights reserved.)

New Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) causes the Coronavirus Disease 2019 (COVID-19), an infectious illness that has generated a pandemic crisis worldwide. One of the fundamental questions in science and society is how SARS-CoV-2 has been originated to design best practices directed to prevent and/or to cope with future hazardous pathogens. The study confronts this question here developing a meta-analysis, which endeavors to explain, whenever possible, unknown sources of the SARS-CoV-2. Findings suggest that the natural spillover of novel viral agents that generate more than 6.00 M deaths worldwide in about two years (such as, SARS-CoV-2 from February 2020 to March 2022) has a remote probability of occurrence (using an analogy with the probability of natural disasters generating a lot of fatalities), whereas science advances on hazardous viral agents and consequential lab accident have a (higher) probability of occurrence (about 13-20% like in manifold lab accidents). The findings of this meta-analysis suggest the vital role of improving the technical guidelines of biosafety at all levels in laboratories during the development of scientific research of experimental virology on hazardous pathogens to minimize risks of pandemic threats in environment and human society., (Copyright © 2022 Elsevier Inc. All rights reserved.)

How is the dynamics of Coronavirus Disease 2019 (COVID-19) in 2020 with an health policy of full lockdowns and in 2021 with a vast campaign of vaccinations? The present study confronts this question here by developing a comparative analysis of the effects of COVID-19 pandemic between April-September 2020 (based upon strong control measures) and April-September 2021 (focused on health policy of vaccinations) in Italy, which was one of the first European countries to experience in 2020 high numbers of COVID-19 related infected individuals and deaths and in 2021 Italy has a high share of people fully vaccinated against COVID-19 (>89% of population aged over 12 years in January 2022). Results suggest that over the period under study, the arithmetic mean of confirmed cases, hospitalizations of people and admissions to Intensive Care Units (ICUs) in 2020 and 2021 is significantly equal (p-value<0.01), except fatality rate. Results suggest in December 2021 lower hospitalizations, admissions to ICUs, and fatality rate of COVID-19 than December 2020, though confirmed cases and mortality rates are in 2021 higher than 2020, and likely converging trends in the first quarter of 2022. These findings reveal that COVID-19 pandemic is driven by seasonality and environmental factors that reduce the negative effects in summer period, regardless control measures and/or vaccination campaigns. These findings here can be of benefit to design health policy responses of crisis management considering the growth of COVID-19 pandemic in winter months having reduced temperatures and low solar radiations ( COVID-19 has a behaviour of influenza-like illness). Hence, findings here suggest that strategies of prevention and control of infectious diseases similar to COVID-19 should be set up in summer months and fully implemented during low-solar-irradiation periods (autumn and winter period)., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Coronavirus disease 2019 (COVID-19) continues to be a pandemic threat that is generating a constant state of alert in manifold countries. One of the strategies of defense against infectious diseases (e.g., COVID-19) is the vaccinations that decrease the numbers of infected individuals and deaths. In this context, the optimal level of vaccination for COVID-19 is a basic point to control this pandemic crisis in society. The study here,-using data of doses of vaccines administered per 100 inhabitants, confirmed cases and case fatality ratio of COVID-19 between countries (N=192) from March to May 2021,- clarifies the optimal levels of vaccination for reducing the number of infected individuals and, consequently, the numbers of deaths at global level. Findings reveal that the average level of administering about 80 doses of vaccines per 100 inhabitants between countries can sustain a reduction of confirmed cases and number of deaths. In addition, results suggest that an intensive vaccination campaign in the initial phase of pandemic wave leads to a lower optimal level of doses administered per 100 inhabitants (roughly 47 doses of vaccines administered) for reducing infected individuals; however, the growth of pandemic wave (in May, 2021) moves up the optimal level of vaccines to about 90 doses for reducing the numbers of COVID-19 related infected individuals. All these results here could aid policymakers to prepare optimal strategies directed to a rapid COVID-19 vaccination rollout, before the takeoff of pandemic wave, to lessen negative effects of pandemic crisis on environment and socioeconomic systems., (Copyright © 2021 Elsevier Inc. All rights reserved.)

The Coronavirus Disease 2019 (COVID-19) continues to generate a constant pandemic threat with new mutations of the viral agent (SARS-CoV-2) that create socioeconomic issues. One of the fundamental problems is the evaluation of the preparedness of countries to cope with COVID-19 pandemic crisis to detect and support factors associated with the reduction of mortality and the growth of vaccinations in society. The study here confronts this problem by developing two basic indexes, which measure the performance of countries to face pandemic threats. In particular, the Index r (as resilience) detects the countries having the best performance in the reduction of the negative impact of mortality related to COVID-19 pandemic and the Index p (as preparedness and prevention) assesses best-performer countries to support COVID-19 vaccinations in order to constrain future pandemic threats and support the recovery of socioeconomic systems. Index of resilience is a composite measure based on three indicators associated with COVID-19, given by average mortality, hospital occupancy and Intensive Care Units occupancy per 100 000 people, producing an overall score; Index of preparedness/prevention is a composite measure of two indicators related to COVID-19 vaccinations (i.e., doses of vaccines administered and total vaccinates per 100 000 people), producing also an overall score of performance. The application of these indexes on a case study of European countries, having a homogenous socioeconomic area, shows the strategic positioning of countries to cope with a major pandemic threat. Findings reveal that all countries have some weaknesses and no country has a high preparedness to cope with a major epidemic or pandemic. Moreover, results suggest that best-performer countries to cope with COVID-19 pandemic crisis have a smaller size of population and/or better public governance, associated with high expenditures in health system. These indexes can help policymakers for designing effective strategies to improve preparedness and prevention of countries to face future pandemic threats., (Copyright © 2021 Elsevier Inc. All rights reserved.)

The main goal of this study is to analyze the relation between commercial trade and pandemic severity in society, in order to support new hypotheses which can explain transmission dynamics of COVID-19, as well as promote policy responses to cope with future epidemics similar to COVID-19. This study considers the role of trade in the dynamics of pandemic diffusion, within and between countries, which has not been investigated yet in this emerging field of research. We focus on three large countries in Europe: Italy, France, and Spain. The analysis is performed at regional level (involving in total 52 European regions). Results suggest that the association between trade and pandemic severity seems to be supported by empirical evidence, making it possible to introduce new hypotheses for explaining transmission dynamics of COVID-19 within and between countries. In particular, international trade data is supposed to be used as a comprehensive indicator accounting for population density, economic dynamism, and human mobility. The statistical analyses, also in a multivariate context, strongly support this hypothesis and suggest that crisis management has to focus in the very first place on infections occurring outside the national boundaries, in order to cope with pandemic threat of new waves of COVID-19 and future similar epidemics/pandemics., (Copyright © 2021 Elsevier Inc. All rights reserved.)

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused the Coronavirus Disease 2019 (COVID-19), generating high numbers of COVID-19 related infected individuals and deaths, is still circulating in 2021 with new variants of the coronavirus, such that the state of emergency remains in manifold countries. Currently, there is still a lack of a full understanding of the factors determining the COVID-19 diffusion that clarify the causes of the variability of infections across different provinces and regions within countries. The main goal of this study is to explain new and main determinants underlying the diffusion of COVID-19 in society. This study focuses on international trade because this factor, in a globalized world, can synthetize different drivers of virus spread, such as mobility patterns, economic potentialities, and social interactions of an investigated areas. A case study research is performed on 107 provinces of Italy, one of the first countries to experience a rapid increase in confirmed cases and deaths. Statistical analyses from March 2020 to February 2021 suggest that total import and export of provinces has a high association with confirmed cases over time (average r > 0.78, p-value <.001). Overall, then, this study suggests total import and export as complex indicator of COVID-19 transmission dynamics that outclasses other common parameters used to justify the COVID-19 spread, given by economic, demographic, environmental, and climate factors. In addition, this study proposes, for the first time, a time-dependent correlation analysis between trade data and COVID-19 infection cases to explain the relation between confirmed cases and social interactions that are a main source of the diffusion of SARS-CoV-2 and subsequent negative impact in society. These novel findings have main theoretical and practical implications directed to include a new parameter in modelling of the diffusion of COVID-19 pandemic to support effective policy responses of crisis management directed to constrain the impact of COVID-19 pandemic and similar infectious diseases in society., (Copyright © 2021 Elsevier Inc. All rights reserved.)

One of the problems hardly clarified in Coronavirus Disease 2019 (COVID-19) pandemic crisis is to identify factors associated with a lower mortality of COVID-19 between countries to design strategies to cope with future pandemics in society. The study here confronts this problem by developing a global analysis based on more than 160 countries. This paper proposes that Gross Domestic Product (GDP) per capita, healthcare spending and air pollution of nations are critical factors associated with fatality rate of COVID-19. The statistical evidence seems in general to support that countries with a low average COVID-19 fatality rate have high expenditures in health sector >7.5% of GDP, high health expenditures per capita >$2,300 and a lower exposure of population to days exceeding safe levels of particulate matter (PM 2.5 ). Another relevant finding here is that these countries have lower case fatality rates (CFRs) of COVID-19, regardless a higher percentage of population aged more than 65 years. Overall, then, this study finds that an effective and proactive strategy to reduce the negative impact of future pandemics, driven by novel viral agents, has to be based on a planning of enhancement of healthcare sector and of environmental sustainability that can reduce fatality rate of infectious diseases in society., (Copyright © 2021 Elsevier Inc. All rights reserved.)

The goal of this study is a comparative analysis of the first and second wave of the Coronavirus disease 2019 (COVID-19) to assess the impact on health of people for designing effective policy responses to constrain negative effects of future pandemic waves of COVID-19 and similar infectious diseases in society. The research here focuses on a case study of Italy, one of the first countries to experience a rapid increase in numbers of COVID-19 related infected individuals and deaths. Statistical analyses, based on daily data from February 2020 to February 2021, suggest that the first wave of COVID-19 pandemic in Italy had a high negative impact on health of people over February-May 2020 period; after that, negative effects declined from June 2020 onwards. Second wave of COVID-19 pandemic from August 2020 to February 2021 had a growing incidence of confirmed cases also associated with variants of coronavirus, whereas admissions to Intensive Care Units and total deaths had lower levels compared to first wave of COVID-19. Lessons learned of this comparative analysis between first and second wave of the COVID-19 pandemic in Italy can be generalized in similar geo-economic areas to support effective policy responses of crisis management to constrain the negative impact on health of people of recurring waves of COVID-19 pandemic and similar infectious diseases in future., (Copyright © 2021 Elsevier Inc. All rights reserved.)

In the presence of the novel Coronavirus Disease (COVID-19) and other new viral agents, one of the fundamental problems in science is the evaluation of environmental and social weaknesses of cities/regions to the exposure of infectious diseases for preventing and/or containing new COVID-19 outbreaks and the diffusion of other viral agents that generate a negative impact on public health and economy of countries. The current monitoring of transmission dynamics of infectious diseases is mainly based on reproduction number (R 0 ) and fatality rates. However, this approach is a real-time monitoring of transmission dynamics for mitigating the numbers of COVID-19 related infected individuals and deaths. Reproduction number does not provide information to cope with future epidemics or pandemics. The main goal of this study is to propose the Index c (as contagions) that quantifies, ex-ante, the environmental risk of exposure of cities/regions to future epidemics of the COVID-19 and similar vital agents. This Index c synthetizes environmental, demographic, climatological and health risk factors of cities/regions that indicate their exposure to infectious diseases. Index c has a range from 1 (environmental and social weakness of urban areas leading to high levels of exposure to infectious diseases) to 0 (environment that reduces the risk of exposure to infectious diseases in society). The statistical evidence here, applied on case study of Italy, seems in general to support the predictive capacity of the Index c as a particularly simple but superior indicator in detecting the global correlation between potential risk of exposure of cities/regions to infectious diseases and actual risk given by infected individuals and deaths of the COVID-19. The Index c can support a proactive environmental strategy to help policymakers to prevent future pandemics similar to the COVID-19., (Copyright © 2020 Elsevier Inc. All rights reserved.)

This study has two goals. The first is to explain the geo-environmental determinants of the accelerated diffusion of COVID-19 that is generating a high level of deaths. The second is to suggest a strategy to cope with future epidemic threats similar to COVID-19 having an accelerated viral infectivity in society. Using data on sample of N = 55 Italian province capitals, and data of infected individuals at as of April 7th, 2020, results reveal that the accelerate and vast diffusion of COVID-19 in North Italy has a high association with air pollution of cities measured with days exceeding the limits set for PM 10 (particulate matter 10 μm or less in diameter) or ozone. In particular, hinterland cities with average high number of days exceeding the limits set for PM 10 (and also having a low wind speed) have a very high number of infected people on 7th April 2020 (arithmetic mean is about 2200 infected individuals, with average polluted days greater than 80 days per year), whereas coastal cities also having days exceeding the limits set for PM 10 or ozone but with high wind speed have about 944.70 average infected individuals, with about 60 average polluted days per year; moreover, cities having more than 100 days of air pollution (exceeding the limits set for PM 10 ), they have a very high average number of infected people (about 3350 infected individuals, 7th April 2020), whereas cities having less than 100 days of air pollution per year, they have a lower average number of infected people (about 1014 individuals). The findings here also suggest that to minimize the impact of future epidemics similar to COVID-19, the max number of days per year that Italian provincial capitals or similar industrialized cities can exceed the limits set for PM 10 or for ozone, considering their meteorological conditions, is about 48 days. Moreover, results here reveal that the explanatory variable of air pollution in cities seems to be a more important predictor in the initial phase of diffusion of viral infectivity (on 17th March 2020, b 1  = 1.27, p < 0.001) than interpersonal contacts (b 2  = 0.31, p < 0.05). In the second phase of maturity of the transmission dynamics of COVID-19, air pollution reduces intensity (on 7th April 2020 with b' 1  = 0.81, p < 0.001) also because of the indirect effect of lockdown, whereas regression coefficient of transmission based on interpersonal contacts has a stable level (b' 2  = 0.31, p < 0.01). This result reveals that accelerated transmission dynamics of COVID-19 is due to mainly to the mechanism of "air pollution-to-human transmission" (airborne viral infectivity) rather than "human-to-human transmission". Overall, then, transmission dynamics of viral infectivity, such as COVID-19, is due to systemic causes: general factors that are the same for all regions (e.g., biological characteristics of virus, incubation period, etc.) and specific factors which are different for each region and/or city (e.g., complex interaction between air pollution, meteorological conditions and biological characteristics of viral infectivity) and health level of individuals (habits, immune system, age, sex, etc.). Lessons learned for COVID-19 in the case study here suggest that a proactive strategy to cope with future epidemics is also to apply especially an environmental and sustainable policy based on reduction of levels of air pollution mainly in hinterland and polluting cities- (having low wind speed, high percentage of moisture and number of fog days) -that seem to have an environment that foster a fast transmission dynamics of viral infectivity in society. Hence, in the presence of polluting industrialization in regions that can trigger the mechanism of air pollution-to-human transmission dynamics of viral infectivity, this study must conclude that a comprehensive strategy to prevent future epidemics similar to COVID-19 has to be also designed in environmental and socioeconomic terms, that is also based on sustainability science and environmental science, and not only in terms of biology, medicine, healthcare and health sector., Competing Interests: Declaration of competing interest The author declares that he is the sole author of this manuscript and he has no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. This study has none funders., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Chronic psychological stress is associated with accelerated biological aging, immune dysfunction, and premature morbidity and mortality. Changes in the relative proportions of T cell subpopulations are thought to be a characteristic of immunological aging; however, understanding of whether these changes are associated with chronic psychological stress is incomplete. This study investigated associations between chronic caregiving stress and distributions of T cell phenotypes in a sample of high stress mothers of children with Autism Spectrum Disorder (caregivers; n = 91) and low stress mothers of neurotypical children (controls; n = 88). Immune markers assessed were naïve (CD45RA + CD62L+), central memory (CD45RA-CD62L+), and effector memory (CD45RA-CD62L-) CD4+ and CD8+ T cells. We also examined the ratio of effector to naïve (E:N) CD4+ and CD8+ T cells. In models adjusted for age, body mass index, race/ethnicity, and antidepressant use, caregivers displayed higher percentages of effector memory CD8+ and CD4+ T cells as well as lower percentages of naïve CD8+ T cells and central memory CD8+ and CD4+ T cells compared to controls. Caregivers also displayed significantly higher E:N ratios for both CD4+ and CD8+ T cells. These findings were also independent of cytomegalovirus infection status. Furthermore, higher parental stress, across both groups, was related to several immune parameters. These findings provide preliminary evidence that chronic parental caregiving stress is associated with changes in relative proportions of T cell subpopulations that are consistent with accelerated immunological aging., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: Chronic life stress, such as the stress of caregiving, can promote pathophysiology, but the underlying cellular mechanisms are not well understood. Chronic stress may induce recalibrations in mitochondria leading to changes either in mitochondrial content per cell, or in mitochondrial functional capacity (i.e., quality)., Methods: Here we present a functional index of mitochondrial health (MHI) for human leukocytes that can distinguish between these two possibilities. The MHI integrates nuclear and mitochondrial DNA-encoded respiratory chain enzymatic activities and mitochondrial DNA copy number. We then use the MHI to test the hypothesis that daily emotional states and caregiving stress influence mitochondrial function by comparing healthy mothers of a child with an autism spectrum disorder (high-stress caregivers, n = 46) with mothers of a neurotypical child (control group, n = 45)., Results: The MHI outperformed individual mitochondrial function measures. Elevated positive mood at night was associated with higher MHI, and nightly positive mood was also a mediator of the association between caregiving and MHI. Moreover, MHI was correlated to positive mood on the days preceding, but not following the blood draw, suggesting for the first time in humans that mitochondria may respond to proximate emotional states within days. Correspondingly, the caregiver group, which had higher perceived stress and lower positive and greater negative daily affect, exhibited lower MHI. This effect was not explained by a mismatch between nuclear and mitochondrial genomes., Conclusions: Daily mood and chronic caregiving stress are associated with mitochondrial functional capacity. Mitochondrial health may represent a nexus between psychological stress and health., (Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

The SCIDhu PBL model of human Ig production was modified by using human interleukin-6 (hIL-6) secreting tumors for continuous hIL-6 production, in vivo. On day one, SCID mice were injected subcutaneously with 200 microliters PBS (control mice), 10(4) SP2/0-Ag14 cells (IL-6+ mice) or 10(4) hIL-6 secreting SP2/0-hIL6.17 cells (IL-6- mice). The mice were reconstituted with human PBMC on day two and immunized with 100 micrograms of tetanus toxoid (TT) on days two and fifteen. Serum hIL-6 concentrations in IL-6+ mice ranged between 2.9 and 38.1 ng/ml by days 26-33. IL-6+ mice had enlarged spleens and lymph nodes (LN). Flow cytometry and histology showed that SCIDhu PBL mouse spleen, LN and peritoneal exudate cells (PEC) contained mostly murine myeloid lineage cells. In addition, many more human B cells, T cells and IL-2R(+)-activated lymphocytes were present in spleen, LN and PEC of IL-6+ mice. Despite enhanced lymphocyte engraftment and activation, by day 14 IL-6+ mice produced up to 6-fold less TT-specific IgG relative to total IgG than either control group. TT-specific and total Ig sera concentrations were equivalent in all three groups on days 26-33. Our results suggest that sustained circulating hIL-6 enhanced human delayed-type hypersensitivity (DTH)-like inflammatory responses with consequential inhibition of TT-specific IgG production in SCIDhu PBL mice.

A 15-year-old female with acquired von Willebrand disease associated with hypothyroidism is presented and discussed. The patient was initially seen for right lower quadrant abdominal pain and menorrhagia. Once hypothyroidism was diagnosed and treated her coagulation abnormality resolved.