Biological risk in Italian prisons: data analysis from the second to the fourth wave of COVID-19 pandemic.

BACKGROUND: The management of COVID-19 in Italian prisons triggered considerable concern at the beginning of the pandemic due to numerous riots which resulted in inmate deaths, damages and prison breaks. The aim of this study is to shed some light, through analysis of the infection and relevant disease parameters, on the period spanning from the second to the fourth wave of the outbreak in Italy's prisons. METHODS: Reproductive number (Rt) and Hospitalisation were calculated through a Eulerian approach applied to differential equations derived from compartmental models. Comparison between trends was performed through paired t-test and linear regression analyses. RESULTS: The infection trends (prevalence and Rt) show a high correlation between the prison population and the external community. Both the indices appear to be lagging 1 week in prison. The prisoners' Rt values are not statistically different from those of the general population. The hospitalisation trend of inmates strongly correlates with the external population's, with a delay of 2 weeks. The magnitude of hospitalisations in prison is less than in the external community for the period analysed. CONCLUSIONS: The comparison with the external community revealed that in prison the infection prevalence was greater, although Rt values showed no significant difference, and the hospitalisation rate was lower. These results suggest that the consistent monitoring of inmates results in a higher infection prevalence while a wide vaccination campaign leads to a lower hospitalisation rate. All three indices demonstrate a lag of 1 or 2 weeks in prison. This delay could represent a useful time-window to strengthen planned countermeasures.

Sievert or Gray: Dose Quantities and Protection Levels in Emergency Exposure.

Mitigation or even elimination of adverse effects caused by ionizing radiation is the main scope of the radiation protection discipline. The interaction of radiation with living matter is quantified and correlated with biological effects by dose. The Sievert is the most well-known quantity, and it is used with the equivalent and effective dose to minimize stochastic effects. However, Gray is the reference quantity for sizing tissue reactions that could occur under high-exposure conditions such as in a radiation emergency. The topics addressed in this review are the choice to move from Sievert to Gray, how the operational quantities for environmental and individual monitoring of the detectors should consider such a change of units, and why reference levels substitute dose levels in emergency exposure.

Emergency Management in the Event of Radiological Dispersion in an Urban Environment.

Dispersion of a radiological source is a complex scenario in terms of first response, especially when it occurs in an urban environment. The authors in this paper designed, simulated, and analyzed the data from two different scenarios with the two perspectives of an unintentional fire event and a Radiological Dispersal Device (RDD) intentional explosion. The data of the simulated urban scenario are taken from a real case of orphan sources abandoned in a garage in the center of the city of Milan (Italy) in 2012. The dispersion and dose levels are simulated using Parallel Micro Swift Spray (PMSS) software, which takes into account the topographic and meteorological information of the reference scenarios. Apart from some differences in the response system of the two scenarios analyzed, the information provided by the modeling technique used, compared to other models not able to capture the actual urban and meteorological contexts, make it possible to modulate a response system that adheres to the real impact of the scenario. The authors, based on the model results and on the evidence provided by the case study, determine the various countermeasures to adopt to mitigate the impact for the population and to reduce the risk factors for the first responders.

A High-Performance Gamma Spectrometer for Unmanned Systems Based on Off-the-Shelf Components.

Since the Fukushima Daiichi Nuclear Power Plant accident in March 2011, the technology available for unmanned aerial vehicles (UAVs) for radiation monitoring has improved greatly. Remote access to radiation-contaminated areas not only eliminates unnecessary exposure of civilians or military personnel, but also allows workers to explore inaccessible places. Hazardous levels of radioactive contamination can be expected as a result of accidents in the nuclear power industry or as a result of the intentional release of radioactive materials for terrorist purposes (dirty bombs, building contamination, etc.). The possibility to detect, identify, and characterize radiation and nuclear material using mobile and remote sensing platforms is a common requirement in the radiation sensing community. The technology has applications in homeland security and law enforcement, customs and border protection, nuclear power plant safety and security, nuclear waste monitoring, environmental recovery, and the military. In this work, the authors have developed, implemented, and characterized a gamma-ray detection and spectroscopy system capable of operating on a UAV. The system was mainly developed using open-source software and affordable hardware components to reduce development and maintenance costs and provide satisfactory performance as a detection instrument. The designed platform can be used to perform mapping or localization tasks to improve the risk assessment process for first responders during the management of radiological and nuclear incidents. First, the design process of the system is described; the result of the characterization of the platform is then presented together with the use of the prototype installed on a UAV in an exercise simulating a radiological and nuclear contamination scenario.

A Weighted-LSM Method to Improve Classification and Concentration Evaluation from Laser-Induced Fluorescence Spectra.

The detection of biological agents using optical systems is an open field of research. Currently, different spectroscopic techniques allow to detect and classify chemical agents while a fast and accurate technique able to identify biological agents is still under investigation. Some optical techniques, such as Laser-Induced Breakdown Spectroscopy (LIBS) or Laser-Induced Fluorescence (LIF), are already used as classification methods. However, the presence of background, spectrum similarities and other confounders make these techniques not very specific. This work shows a new method to achieve better performances in terms of classification and concentration evaluations. The method is based on the Weighted Least Square Minimization method. In fact, by using ad hoc weights, the LSM looks at specific features of the spectra, resulting in higher accuracy. In order to make a systematic analysis, numerical tests have been conducted. With these tests, the authors were able to highlight the various advantages and drawbacks of the new methodology proposed. Then, the method was applied to some LIF measurements to investigate the applicability of the method to preliminary experimental cases. The results show that, by using this new weighted LSM, it is possible to achieve better classification and concentration evaluation performances. Finally, the possible application of the new method is discussed.

Adaptive Quasi-Unsupervised Detection of Smoke Plume by LiDAR.

The early detection of fire is one of the possible applications of LiDAR techniques. The smoke generated by a fire is mainly compounded of CO2, H2O, particulate, and other combustion products, which involve the local variation of the scattering of the electromagnetic wave at specific wavelengths. The increases of the backscattering coefficient are transduced in peaks on the signal of the backscattering power recorded by the LiDAR system, located exactly where the smoke plume is, allowing not only the detection of a fire but also its localization. The signal processing of the LiDAR signals is critical in the determination of the performances of the fire detection. It is important that the sensitivity of the apparatus is high enough but also that the number of false alarms is small, in order to avoid the trigger of useless and expensive countermeasures. In this work, a new analysis method, based on an adaptive quasi-unsupervised approach was used to ensure that the algorithm is continuously updated to the boundary conditions of the system, such as the weather and experimental apparatus issues. The method has been tested on an experimental campaign of 227 pulses and the performances have been analyzed in terms of sensitivity and specificity.

Enhancing Radiation Detection by Drones through Numerical Fluid Dynamics Simulations.

This study addresses the optimization of the location of a radioactive-particle sensor on a drone. Based on the analysis of the physical process and of the boundary conditions introduced in the model, computational fluid dynamics simulations were performed to analyze how the turbulence caused by drone propellers may influence the response of the sensors. Our initial focus was the detection of a small amount of radioactivity, such as that associated with a release of medical waste. Drones equipped with selective low-cost sensors could be quickly sent to dangerous areas that first responders might not have access to and be able to assess the level of danger in a few seconds, providing details about the source terms to Radiological-Nuclear (RN) advisors and decision-makers. Our ultimate application is the simulation of complex scenarios where fluid-dynamic instabilities are combined with elevated levels of radioactivity, as was the case during the Chernobyl and Fukushima nuclear power plant accidents. In similar circumstances, accurate mapping of the radioactive plume would provide invaluable input-data for the mathematical models that can predict the dispersion of radioactivity in time and space. This information could be used as input for predictive models and decision support systems (DSS) to get a full situational awareness. In particular, these models may be used either to guide the safe intervention of first responders or the later need to evacuate affected regions.

Early assessment of weight velocity can support frontline health workers in predicting malnutrition in HIV-exposed infants: preliminary results from a DREAM cohort in Malawi.

BACKGROUND: Children born to HIV-positive mothers are particularly susceptible to malnutrition. Currently, monitoring programs rely on punctual anthropometric measurements to assess child growth. Growth velocities could be an additional tool in identifying critical time windows for prevention and implementation of early intervention for malnutrition. METHODS: A retrospective analysis was conducted using data from 817 HIV exposed but uninfected children extracted from DREAM program database. By using the WHO reference for growth standards, patterns of weight velocity for different intervals of assessment from one to 18 months of age were explored. Odds ratios and multinomial logistic regressions between selected weight velocity Z-scores thresholds and successive malnutrition indices (at 6, 12, 18 months of age) were calculated. RESULTS: Weight velocity was above the standard mean in the first 3 months, then progressively declined over time. In children with normal nutritional status, significant risks of becoming malnourished (mild malnutrition - underweight [OR 10.8; 95% CI: 4.5-26], chronic malnutrition - stunting [OR 8.3; 95% CI: 2-34.9] and acute malnutrition - wasting [OR 11.7; 95% CI: 1.5-90.5]) started when weight velocity Z-scores <0, at all interval ages. Multinomial regression showed that in the first 6 months, the weight velocity decrements strongly impacted on underweight (OR 17.9; 95% CI: 4-80.7), while the risk of Stunting occurred later at 18 months (OR 8.7; 95% CI: 4.3-17.6), with highest impact at the lowest thresholds. CONCLUSIONS: The assessment of weight velocity Z-scores, coupled with the already validated malnutrition indices, can support frontline health workers in early prediction of child malnutrition and performing nutritional counselling in the context of HIV/AIDS and food insecurity.

Antidepressants for insomnia in adults.

BACKGROUND: Insomnia disorder is a subjective condition of unsatisfactory sleep (e.g. sleep onset, maintenance, early waking, impairment of daytime functioning). Insomnia disorder impairs quality of life and is associated with an increased risk of physical and mental health problems including anxiety, depression, drug and alcohol abuse, and increased health service use. hypnotic medications (e.g. benzodiazepines and 'Z' drugs) are licensed for sleep promotion, but can induce tolerance and dependence, although many people remain on long-term treatment. Antidepressant use for insomnia is widespread, but none is licensed for insomnia and the evidence for their efficacy is unclear. This use of unlicensed medications may be driven by concern over longer-term use of hypnotics and the limited availability of psychological treatments. OBJECTIVES: To assess the effectiveness, safety and tolerability of antidepressants for insomnia in adults. SEARCH METHODS: This review incorporated the results of searches to July 2015 conducted on electronic bibliographic databases: the Cochrane Central Register of Controlled Trials (CENTRAL, 2015, Issue 6), MEDLINE (1950 to 2015), Embase (1980 to 2015) and PsycINFO (1806 to 2015). We updated the searches to December 2017, but these results have not yet been incorporated into the review. SELECTION CRITERIA: Randomised controlled trials (RCTs) of adults (aged 18 years or older) with a primary diagnosis of insomnia and all participant types including people with comorbidities. Any antidepressant as monotherapy at any dose whether compared with placebo, other medications for insomnia (e.g. benzodiazepines and 'Z' drugs), a different antidepressant, waiting list control or treatment as usual. DATA COLLECTION AND ANALYSIS: Two review authors independently assessed trials for eligibility and extracted data using a data extraction form. A third review author resolved disagreements on inclusion or data extraction. MAIN RESULTS: The search identified 23 RCTs (2806 participants).Selective serotonin reuptake inhibitors (SSRIs) compared with placebo: three studies (135 participants) compared SSRIs with placebo. Combining results was not possible. Two paroxetine studies showed significant improvements in subjective sleep measures at six (60 participants, P = 0.03) and 12 weeks (27 participants, P < 0.001). There was no difference in the fluoxetine study (low quality evidence).There were either no adverse events or they were not reported (very low quality evidence).Tricyclic antidepressants (TCA) compared with placebo: six studies (812 participants) compared TCA with placebo; five used doxepin and one used trimipramine. We found no studies of amitriptyline. Four studies (518 participants) could be pooled, showing a moderate improvement in subjective sleep quality over placebo (standardised mean difference (SMD) -0.39, 95% confidence interval (CI) -0.56 to -0.21) (moderate quality evidence). Moderate quality evidence suggested that TCAs possibly improved sleep efficiency (mean difference (MD) 6.29 percentage points, 95% CI 3.17 to 9.41; 4 studies; 510 participants) and increased sleep time (MD 22.88 minutes, 95% CI 13.17 to 32.59; 4 studies; 510 participants). There may have been little or no impact on sleep latency (MD -4.27 minutes, 95% CI -9.01 to 0.48; 4 studies; 510 participants).There may have been little or no difference in adverse events between TCAs and placebo (risk ratio (RR) 1.02, 95% CI 0.86 to 1.21; 6 studies; 812 participants) (low quality evidence).'Other' antidepressants with placebo: eight studies compared other antidepressants with placebo (one used mianserin and seven used trazodone). Three studies (370 participants) of trazodone could be pooled, indicating a moderate improvement in subjective sleep outcomes over placebo (SMD -0.34, 95% CI -0.66 to -0.02). Two studies of trazodone measured polysomnography and found little or no difference in sleep efficiency (MD 1.38 percentage points, 95% CI -2.87 to 5.63; 169 participants) (low quality evidence).There was low quality evidence from two studies of more adverse effects with trazodone than placebo (i.e. morning grogginess, increased dry mouth and thirst). AUTHORS' CONCLUSIONS: We identified relatively few, mostly small studies with short-term follow-up and design limitations. The effects of SSRIs compared with placebo are uncertain with too few studies to draw clear conclusions. There may be a small improvement in sleep quality with short-term use of low-dose doxepin and trazodone compared with placebo. The tolerability and safety of antidepressants for insomnia is uncertain due to limited reporting of adverse events. There was no evidence for amitriptyline (despite common use in clinical practice) or for long-term antidepressant use for insomnia. High-quality trials of antidepressants for insomnia are needed.

Biological Dual-Use Research and Synthetic Biology of Yeast.

In recent years, the publication of the studies on the transmissibility in mammals of the H5N1 influenza virus and synthetic genomes has triggered heated and concerned debate within the community of scientists on biological dual-use research; these papers have raised the awareness that, in some cases, fundamental research could be directed to harmful experiments, with the purpose of developing a weapon that could be used by a bioterrorist. Here is presented an overview regarding the dual-use concept and its related international agreements which underlines the work of the Australia Group (AG) Export Control Regime. It is hoped that the principles and activities of the AG, that focuses on export control of chemical and biological dual-use materials, will spread and become well known to academic researchers in different countries, as they exchange biological materials (i.e. plasmids, strains, antibodies, nucleic acids) and scientific papers. To this extent, and with the aim of drawing the attention of the scientific community that works with yeast to the so called Dual-Use Research of Concern, this article reports case studies on biological dual-use research and discusses a synthetic biology applied to the yeast Saccharomyces cerevisiae, namely the construction of the first eukaryotic synthetic chromosome of yeast and the use of yeast cells as a factory to produce opiates. Since this organism is considered harmless and is not included in any list of biological agents, yeast researchers should take simple actions in the future to avoid the sharing of strains and advanced technology with suspicious individuals.

Neural correlates of the psychedelic state as determined by fMRI studies with psilocybin.

Psychedelic drugs have a long history of use in healing ceremonies, but despite renewed interest in their therapeutic potential, we continue to know very little about how they work in the brain. Here we used psilocybin, a classic psychedelic found in magic mushrooms, and a task-free functional MRI (fMRI) protocol designed to capture the transition from normal waking consciousness to the psychedelic state. Arterial spin labeling perfusion and blood-oxygen level-dependent (BOLD) fMRI were used to map cerebral blood flow and changes in venous oxygenation before and after intravenous infusions of placebo and psilocybin. Fifteen healthy volunteers were scanned with arterial spin labeling and a separate 15 with BOLD. As predicted, profound changes in consciousness were observed after psilocybin, but surprisingly, only decreases in cerebral blood flow and BOLD signal were seen, and these were maximal in hub regions, such as the thalamus and anterior and posterior cingulate cortex (ACC and PCC). Decreased activity in the ACC/medial prefrontal cortex (mPFC) was a consistent finding and the magnitude of this decrease predicted the intensity of the subjective effects. Based on these results, a seed-based pharmaco-physiological interaction/functional connectivity analysis was performed using a medial prefrontal seed. Psilocybin caused a significant decrease in the positive coupling between the mPFC and PCC. These results strongly imply that the subjective effects of psychedelic drugs are caused by decreased activity and connectivity in the brain's key connector hubs, enabling a state of unconstrained cognition.

Transperineal Laser Ablation (TPLA) Treatment of Focal Low-Intermediate Risk Prostate Cancer.

Background: This interventional pilot study aimed to evaluate the short-term (3 years) efficacy of focal laser ablation (FLA) in treating the index lesion of low-intermediate-risk prostate cancer, along with assessing the safety of the procedure (ClinicalTrials.gov ID NCT04045756). Methods: Forty patients aged between 46 and 86 with histologically proven organ-confined prostate cancer and low-to-intermediate progression risk were included. FLA was performed under percutaneous fusion magnetic resonance/ultrasound guidance in a Day Hospital setting under local anesthesia. Patients underwent regular clinical and functional assessments through the international index of erectile function (IIEF-5) and the International Prostatism Symptom Score (IPSS), PSA measurements, post-procedure MRI scans, and biopsies at 36 months or if positive findings were detected earlier. Statistical analyses were conducted to assess trends in PSA levels and cavity dimensions over time. Results: Forty patients were initially included, with fifteen lost to follow-up. At 36 months, a mean PSA reduction of 60% was observed, and 80% of MRI scans showed no signs of in-field clinically significant residual/recurrent cancer. Biopsies at 36 months revealed no malignant findings in 20 patients. No deterioration in sexual function or urinary symptoms was recorded. Conclusions: FLA appears to be safe, feasible, and effective in the index lesion treatment of low-intermediate-risk prostate cancer, with a high rate of tumor eradication and preservation of quality of life.

Preclinical Development of the Na-K-2Cl Co-transporter-1 (NKCC1) Inhibitor ARN23746 for the Treatment of Neurodevelopmental Disorders.

Alterations in the expression of the Cl- importer Na-K-2Cl co-transporter-1 (NKCC1) and the exporter K-Cl co-transporter 2 (KCC2) lead to impaired intracellular chloride concentration in neurons and imbalanced excitation/inhibition in the brain. These alterations have been observed in several neurological disorders (e.g., Down syndrome and autism). Recently, we have reported the discovery of the selective NKCC1 inhibitor "compound ARN23746" for the treatment of Down syndrome and autism in mouse models. Here, we report on an extensive preclinical characterization of ARN23746 toward its development as a clinical candidate. ARN23746 shows an overall excellent metabolism profile and good brain penetration. Moreover, ARN23746 is effective in rescuing cognitive impairment in Down syndrome mice upon per os administration, in line with oral treatment of neurodevelopmental disorders. Notably, ARN23746 does not present signs of toxicity or diuresis even if administered up to 50 times the effective dose. These results further support ARN23746 as a solid candidate for clinical trial-enabling studies.

Visual attention and memory in professional traders.

Professional traders need to process a large amount of visual information in their daily activity to judge how risky it is to trade specific investment products. Despite some studies investigating the effects of display clutter on traders, visual attention and memory were never investigated in controlled experimental tasks in this population. Following a preliminary study with 30 participants, visual selective attention and visual working memory were measured and compared between two groups of 15 traders and 15 non-traders (salespeople, acting as a control group) from a large-scale banking group in three experimental tasks measuring selective attention in complex visual contexts, simulating display clutter situations (Visual search), cognitive interference (Stroop task), and a delayed recall visual working memory task. In the Visual search task, traders displayed faster response times (RTs) than non-traders for small display sets, while their performance overlapped for large sets. In the Stroop task, traders showed faster RTs than non-traders but were nevertheless affected by cognitive interference. The memory task highlighted no significant differences between the groups. Therefore, this study found an advantage in traders' attention when processing visual information in small sets with no retention. This result could influence trading activity-determining an immediate use of relevant visual information in decision making-and traders' display layout organization.

On the Potential of Relational Databases for the Detection of Clusters of Infection and Antibiotic Resistance Patterns.

In recent years, several bacterial strains have acquired significant antibiotic resistance and can, therefore, become difficult to contain. To counteract such trends, relational databases can be a powerful tool for supporting the decision-making process. The case of Klebsiella pneumoniae diffusion in a central region of Italy was analyzed as a case study. A specific relational database is shown to provide very detailed and timely information about the spatial-temporal diffusion of the contagion, together with a clear assessment of the multidrug resistance of the strains. The analysis is particularized for both internal and external patients. Tools such as the one proposed can, therefore, be considered important elements in the identification of infection hotspots, a key ingredient of any strategy to reduce the diffusion of an infectious disease at the community level and in hospitals. These types of tools are also very valuable in the decision-making process related to antibiotic prescription and to the management of stockpiles. The application of this processing technology to viral diseases such as COVID-19 is under investigation.

mt-Ty 5'tiRNA regulates skeletal muscle cell proliferation and differentiation.

In this study, we sought to determine the role of tRNA-derived fragments in the regulation of gene expression during skeletal muscle cell proliferation and differentiation. We employed cell culture to examine the function of mt-Ty 5' tiRNAs. Northern blotting, RT-PCR as well as RNA-Seq, were performed to determine the effects of mt-Ty 5' tiRNA loss and gain on gene expression. Standard and transmission electron microscopy (TEM) were used to characterize cell and sub-cellular structures. mt-Ty 5'tiRNAs were found to be enriched in mouse skeletal muscle, showing increased levels in later developmental stages. Gapmer-mediated inhibition of tiRNAs in skeletal muscle C2C12 myoblasts resulted in decreased cell proliferation and myogenic differentiation; consistent with this observation, RNA-Seq, transcriptome analyses, and RT-PCR revealed that skeletal muscle cell differentiation and cell proliferation pathways were also downregulated. Conversely, overexpression of mt-Ty 5'tiRNAs in C2C12 cells led to a reversal of these transcriptional trends. These data reveal that mt-Ty 5'tiRNAs are enriched in skeletal muscle and play an important role in myoblast proliferation and differentiation. Our study also highlights the potential for the development of tiRNAs as novel therapeutic targets for muscle-related diseases.

A defect in mitochondrial protein translation influences mitonuclear communication in the heart.

The regulation of the informational flow from the mitochondria to the nucleus (mitonuclear communication) is not fully characterized in the heart. We have determined that mitochondrial ribosomal protein S5 (MRPS5/uS5m) can regulate cardiac function and key pathways to coordinate this process during cardiac stress. We demonstrate that loss of Mrps5 in the developing heart leads to cardiac defects and embryonic lethality while postnatal loss induces cardiac hypertrophy and heart failure. The structure and function of mitochondria is disrupted in Mrps5 mutant cardiomyocytes, impairing mitochondrial protein translation and OXPHOS. We identify Klf15 as a Mrps5 downstream target and demonstrate that exogenous Klf15 is able to rescue the overt defects and re-balance the cardiac metabolome. We further show that Mrps5 represses Klf15 expression through c-myc, together with the metabolite L-phenylalanine. This critical role for Mrps5 in cardiac metabolism and mitonuclear communication highlights its potential as a target for heart failure therapies.

Affect and Cognition in Managerial Decision Making: A Systematic Literature Review of Neuroscience Evidence.

How do affect and cognition interact in managerial decision making? Over the last decades, scholars have investigated how managers make decisions. However, what remains largely unknown is the interplay of affective states and cognition during the decision-making process. We offer a systematization of the contributions produced on the role of affect and cognition in managerial decision making by considering the recent cross-fertilization of management studies with the neuroscience domain. We implement a Systematic Literature Review of 23 selected contributions dealing with the role of affect and cognition in managerial decisions that adopted neuroscience techniques/points of view. Collected papers have been analyzed by considering the so-called reflexive (X-) and reflective (C-) systems in social cognitive neuroscience and the type of decisions investigated in the literature. Results obtained help to support an emerging "unified" mind processing theory for which the two systems of our mind are not in conflict and for which affective states have a driving role toward cognition. A research agenda for future studies is provided to scholars who are interested in advancing the investigation of affect and cognition in managerial decision making, also through neuroscience techniques - with the consideration that these works should be at the service of the behavioral strategy field.

Mindfulness-based online intervention increases well-being and decreases stress after Covid-19 lockdown.

Mindfulness interventions were shown to be effective in improving well-being and reducing perceived stress in several conditions. These effects were also found in online mindfulness-based training, especially in employees in organizational environments. The aim of this study was to test the effectiveness of an online mindfulness intervention on healthy employees, especially after the first Italian Covid-19 lockdown. Participants in the intervention group underwent an 8-week mindfulness online training program based on the Mindfulness-Based Stress Reduction (MBSR) protocol compared to a control (no-intervention) group. All participants filled in weekly surveys for the whole intervention duration via online questionnaires to measure their habits, mindfulness (FFMQ-15), emotion regulation (ERQ), positive and negative affect (PANAS), depression, anxiety and stress (DASS-21), resilience (RSA) and insomnia (ISI). 69 participants in the intervention group and 63 in the no-treatment control group were considered in the longitudinal analyses. We found significant differences between the intervention and control groups over time in the measures of mindfulness (in particular the nonreactivity subscale), positive affect, depression, and insomnia. Moreover, we found that the frequency of practice and ease perceived in practicing were positively correlated to several indices of well-being (mindfulness, positive affect, cognitive reappraisal) and negatively correlated to several indices of stress (negative affect, depression, anxiety, stress, insomnia, expressive suppression). These results show the importance and effectiveness of online mindfulness training programs to cope with stress among employees, especially after the Covid-19 lockdown.

Effects of Ionizing Radiation on Flora Ten Years after the Fukushima Dai-ichi Disaster.

The aim of this work is to analyze the effects of ionizing radiation and radionuclides (like 137Cs) in several higher plants located around the Fukushima Dai-ichi Nuclear Power Plant (FNPP), evaluating both their adaptive processes and evolution. After the FNPP accident in March 2011 much attention was focused to the biological consequences of ionizing radiation and radionuclides released in the area surrounding the nuclear plant. This unexpected mishap led to the emission of radionuclides in aerosol and gaseous forms from the power plant, which contaminated a large area, including wild forest, cities, farmlands, mountains, and the sea, causing serious problems. Large quantities of 131I, 137Cs, and 134Cs were detected in the fallout. People were evacuated but the flora continued to be affected by the radiation exposure and by the radioactive dusts' fallout. The response of biota to FNPP irradiation was a complex interaction among radiation dose, dose rate, temporal and spatial variation, varying radiation sensitivities of the different plants' species, and indirect effects from other events. The repeated ionizing radiations, acute or chronic, guarantee an adaptation of the plant species, demonstrating a radio-resistance. Consequently, ionizing radiation affects the genetic structure, especially during chronic irradiation, reducing genetic variability. This reduction is associated with the different susceptibility of plant species to chronic stress. This would confirm the adaptive theory associated with this phenomenon. The effects that ionizing radiation has on different life forms are examined in this review using the FNPP disaster as a case study focusing the attention ten years after the accident.