Temperature-humidity index monitoring during two summer seasons in dairy cow sheds in Mugello (Tuscany).

Many studies have reported that the impact of high temperatures affects physiology, welfare, health, and productivity of farm animals, and among these, the dairy cattle farming is one of the livestock sectors that suffers the greatest effects. The temperature-humidity index (THI) represents the state of the art in the evaluation of heat stress conditions in dairy cattle but often its measurement is not carried out in sheds. For this reason, the aim of this study was the monitoring of the THI in three dairy cattle farms in Mugello (Tuscany) to understand its influence on dairy cows. THI values were calculated using meteorological data from direct observation in sheds and outdoor environments. Data relating to the animal's behavior were collected using radio collars. The Pearson test and Mann-Kendall test were used for statistical analysis. The results highlighted a significant (P < 0.001) upward trend in THImax during the last 30 years both in Low Mugello (+ 1.1 every 10 years) and in High Mugello (+ 0.9 every 10 years). In Low Mugello sheds, during the period 2020-2022, more than 70% of daytime hours during the summer period were characterized by heat risk conditions (THI > 72) for livestock. On average the animals showed a significant (P < 0.001) decrease in time spent to feeding and rumination, both during the day and the night, with a significant (P < 0.001) increase in inactivity. This study fits into the growing demand for knowledge of the micro-climatic conditions within farms in order to support resilience actions for protecting both animal welfare and farm productivity from the effects of climate change. This could also be carried out thanks to estimation models which, based on the meteorological conditions forecast, could implement the thermal stress indicator (THI) directly from the high-resolution meteorological model, allowing to get a prediction of the farm's potential productivity loss based on the expected THI.

Radiomic Features Associated with Extent of Resection in Glioma Surgery.

Radiomics defines a set of techniques for extraction and quantification of digital medical data in an automated and reproducible way. Its goal is to detect features potentially related to a clinical task, like classification, diagnosis, prognosis, and response to treatment, going beyond the intrinsic limits of operator-dependency and qualitative description of conventional radiological evaluation on a mesoscopic scale. In the field of neuro-oncology, researchers have tried to create prognostic models for a better tumor diagnosis, histological and biomolecular classification, prediction of response to treatment, and identification of disease relapse. Concerning glioma surgery, the most significant aid that radiomics can give to surgery is to improve tumor extension detection and identify areas that are more prone to recurrence to increase the extent of tumor resection, thereby ameliorating the patients' prognosis. This chapter aims to review the fundamentals of radiomics models' creation, the latest advance of radiomics in neuro-oncology, and possible radiomic features associated with the extent of resection in the brain gliomas.

Functional outcomes, extent of resection, and bright/vague fluorescence interface in resection of glioblastomas involving the motor pathways assisted by 5-ALA.

BACKGROUND: 5-Aminolevulinic acid (5-ALA) fluorescence can maximize perirolandic glioblastoma (GBM) resection with low rates of postoperative sequelae. Our purpose was to present the outcomes of our experience and compare them with other literature reports to investigate the potential influence of different intraoperative monitoring strategies and to evaluate the role of intraoperative data on neurological and radiological outcomes in our series. METHODS: We retrospectively analyzed our prospectively collected database of GBM involving the motor pathways. Each patient underwent tumor exeresis with intraoperative 5-ALA fluorescence visualization. Our monitoring strategy was based on direct stimulation (DS), combined with cortical or transcranial MEPs. The radiological outcome was evaluated with CRET vs. residual tumor, and the neurological outcome as improved, unchanged, or worsened. We also performed a literature review to compare our results with state-of-the-art on the subject. RESULTS: Sixty-five patients were included. CRET was 63.1%, permanent postoperative impairment was 1.5%, and DS's lowest motor threshold was 5 mA. In the literature, CRET was 25-73%, permanent postoperative impairment 3-16%, and DS lowest motor threshold was 1-3 mA. Our monitoring strategy identified a motor pathway in 60% of cases in faint fluorescent tissue, and its location in bright/faint fluorescence was predictive of CRET (p < 0.001). A preoperative motor deficit was associated with a worse clinical outcome (p < 0.001). Resection of bright fluorescent tissue was stopped in 26%, and fluorescence type of residual tumor was associated with higher CRET grades (p < 0.001). CONCLUSIONS: Based on the data presented and the current literature, distinct monitoring strategies can achieve different onco-functional outcomes in 5-ALA-guided resection of a glioblastoma (GBM) motor pathway. Intraoperatively, functional and fluorescence data close to a bright/vague interface could be helpful to predict onco-functional outcomes.

Differential Response of Wheat Rhizosphere Bacterial Community to Plant Variety and Fertilization.

The taxonomic assemblage and functions of the plant bacterial community are strongly influenced by soil and host plant genotype. Crop breeding, especially after the massive use of nitrogen fertilizers which led to varieties responding better to nitrogen fertilization, has implicitly modified the ability of the plant root to recruit an effective bacterial community. Among the priorities for harnessing the plant bacterial community, plant genotype-by-microbiome interactions are stirring attention. Here, we analyzed the effect of plant variety and fertilization on the rhizosphere bacterial community. In particular, we clarified the presence in the bacterial community of a varietal effect of N and P fertilization treatment. 16S rRNA gene amplicon sequence analysis of rhizospheric soil, collected from four wheat varieties grown under four N-P fertilization regimes, and quantification of functional bacterial genes involved in the nitrogen cycle (nifH; amoA; nirK and nosZ) were performed. Results showed that variety played the most important role and that treatments did not affect either bacterial community diversity or bacterial phyla abundance. Variety-specific response of rhizosphere bacterial community was detected, both in relation to taxa (Nitrospira) and metabolic functions. In particular, the changes related to amino acid and aerobic metabolism and abundance of genes involved in the nitrogen cycle (amoA and nosZ), suggested that plant variety may lead to functional changes in the cycling of the plant-assimilable nitrogen.

Development of machine learning models to prognosticate chronic shunt-dependent hydrocephalus after aneurysmal subarachnoid hemorrhage.

BACKGROUND: Shunt-dependent hydrocephalus significantly complicates subarachnoid hemorrhage (SAH), and reliable prognosis methods have been sought in recent years to reduce morbidity and costs associated with delayed treatment or neglected onset. Machine learning (ML) defines modern data analysis techniques allowing accurate subject-based risk stratifications. We aimed at developing and testing different ML models to predict shunt-dependent hydrocephalus after aneurysmal SAH. METHODS: We consulted electronic records of patients with aneurysmal SAH treated at our institution between January 2013 and March 2019. We selected variables for the models according to the results of the previous works on this topic. We trained and tested four ML algorithms on three datasets: one containing binary variables, one considering variables associated with shunt-dependency after an explorative analysis, and one including all variables. For each model, we calculated AUROC, specificity, sensitivity, accuracy, PPV, and also, on the validation set, the NPV and the Matthews correlation coefficient (ϕ). RESULTS: Three hundred eighty-six patients were included. Fifty patients (12.9%) developed shunt-dependency after a mean follow-up of 19.7 (± 12.6) months. Complete information was retrieved for 32 variables, used to train the models. The best models were selected based on the performances on the validation set and were achieved with a distributed random forest model considering 21 variables, with a ϕ = 0.59, AUC = 0.88; sensitivity and specificity of 0.73 (C.I.: 0.39-0.94) and 0.92 (C.I.: 0.84-0.97), respectively; PPV = 0.59 (0.38-0.77); and NPV = 0.96 (0.90-0.98). Accuracy was 0.90 (0.82-0.95). CONCLUSIONS: Machine learning prognostic models allow accurate predictions with a large number of variables and a more subject-oriented prognosis. We identified a single best distributed random forest model, with an excellent prognostic capacity (ϕ = 0.58), which could be especially helpful in identifying low-risk patients for shunt-dependency.

Effects of deciduous shade trees on surface temperature and pedestrian thermal stress during summer and autumn.

In a context of urban warming, the effects of trees on outdoor thermal stress are important even during the increasingly hot autumn season. This study examines the effects of a deciduous tree species (Tilia x europaea L) on surface temperature over different ground materials and in turn on human thermal comfort, with a particular focus on tree shade variation due to leaf fall. Grass, asphalt, and gravel-covered ground surfaces, both sun-exposed and under the Tilia, were monitored in Florence, Italy, during the summer (2014) and autumn (2017) seasons. The Index of Thermal Stress (ITS) was used to gauge the micrometeorological effects of the changing tree canopy, with tree defoliation quantified by the Plant Area Index. On clear summer days, thermal discomfort was especially pronounced over exposed asphalt, and even more intense above exposed gravel due to its higher reflectivity-while shaded surfaces showed large reductions in thermal stress. Even though incoming solar radiation decreases over the course of the fall season, the direct radiation under the gradually defoliating tree canopy actually increases. Due to this diminished shading effect, the differences in surface temperature between exposed and shaded asphalt shrink dramatically from about 20 to 3 °C. However, since ambient conditions become milder as the season progresses, the Tilia demonstrated a double benefit in terms of ITS: providing thermal comfort under its full canopy at the beginning of autumn and maintaining comfort even as its canopy thins out. At the same time, tree species with earlier defoliation may be unable to replicate such benefits.

Wild ungulates and environmental temperature: analysis on the possible utilization of data from sensor placed on GPS collars.

GPS collars for wildlife provide a large amount of spatio-temporal location data and are frequently equipped with sensors that record the animal-level environmental temperature at a schedulable sampling frequency. The simultaneous collection of environmental temperature and animal location may contribute not only to deepen the understanding of animal behavior in different climatic conditions, but also to increase the knowledge of climate features in inaccessible areas. The measurement of environmental temperature provided by the sensors, however, can be biased by several factors (e.g., surface temperature of the animal, direct solar radiation, precipitation), so in-depth studies are required to verify the correlation. The aim of this study was to identify an equation for correcting the collar-recorded temperature data, allowing to improve and refine the results obtained by the analysis of spatial data and to highlight the environmental factors having the greatest impact on the accuracy of the measures. Temperature data from GPS collars were obtained within a research on spatial behavior on 11 hinds while spatialized temperature data were obtained from LAMMA-IBIMET dataset. These data showed high correlation and an identical trend, although the GPS collar temperature data was always higher. This model could represent a tool to obtain an accurate measurement of temperatures in complex geographical areas with wild animals but low density of weather stations. The availability of corrected temperature data, recorded simultaneously with the animal location, could be useful for a more accurate comprehension of animal behavior in free-ranging conditions, both in case of forthcoming studies and to valorize existing datasets.

Urban Soil: Assessing Ground Cover Impact on Surface Temperature and Thermal Comfort.

The urban population growth, together with the contemporary deindustrialization of metropolitan areas, has resulted in a large amount of available land with new possible uses. It is well known that urban green areas provide several benefits in the surrounding environment, such as the improvement of thermal comfort conditions for the population during summer heat waves. The purpose of this study is to provide useful information on thermal regimes of urban soils to urban planners to be used during an urban transformation to mitigate surface temperatures and improve human thermal comfort. Field measurements of solar radiation, surface temperature (), air temperature (), relative humidity, and wind speed were collected on four types of urban soils and pavements in the city of Florence during summer 2014. Analysis of days under calm, clear-sky condition is reported. During daytime, sun-to-shadow differences for , apparent temperature index (ATI), and were significantly positive for all surfaces. Conversely, during nighttime, differences among all surfaces were significantly negative, whereas ATI showed significantly positive differences. Moreover, was significantly negative for grass and gravel. Relative to the shaded surfaces, was higher on white gravel and grass than gray sandstone and asphalt during nighttime, whereas gray sandstone was always the warmest surface during daytime. Conversely, no differences were found during nighttime for ATI and measured over surfaces that were exposed to sun during the day, whereas showed higher values on gravel than grass and asphalt during nighttime. An exposed surface warms less if its albedo is high, leading to a significant reduction of during daytime. These results underline the importance of considering the effects of surface characteristics on surface temperature and thermal comfort. This would be fundamental for addressing urban environment issues toward the heat island mitigation considering also the impact of urban renovation on microclimate.

Modeling Tree Shade Effect on Urban Ground Surface Temperature.

There is growing interest in the role that urban forests can play as urban microclimate modifiers. Tree shade and evapotranspiration affect energy fluxes and mitigate microclimate conditions, with beneficial effects on human health and outdoor comfort. The aim of this study was to investigate surface temperature () variability under the shade of different tree species and to test the capability in predicting of a proposed heat transfer model. Surface temperature data on asphalt and grass under different shading conditions were collected in the Cascine park, Florence, Italy, and were used to test the performance of a one-dimensional heat transfer model integrated with a routine for estimating the effect of plant canopies on surface heat transfer. Shading effects of 10 tree species commonly used in Italian urban settings were determined by considering the infrared radiation and the tree canopy leaf area index (LAI). The results indicate that, on asphalt, was negatively related to the LAI of trees ( reduction ranging from 13.8 to 22.8°C). On grass, this relationship was weaker probably because of the combined effect of shade and grass evapotranspiration on ( reduction ranged from 6.9 to 9.4°C). A sensitivity analysis confirmed that other factors linked to soil water content play an important role in reduction of grassed areas. Our findings suggest that the energy balance model can be effectively used to estimate of the urban pavement under different shading conditions and can be applied to the analysis of microclimate conditions of urban green spaces.

Transport of Glyphosate and Aminomethylphosphonic Acid under Two Soil Management Practices in an Italian Vineyard.

Worldwide, glyphosate is the most widely used herbicide in controlling the growth of annual and perennial weeds. An increasing number of studies have highlighted the environmental risk resulting from the use of this molecule in aquatic and terrestrial ecosystems. The objective of the study was to determine the transport of glyphosate and its degradation product, aminomethylphosphonic acid (AMPA), through runoff and transported sediment from a vineyard under two different soil management systems: harrowed inter-row (HR) and permanent grass covered inter-row (GR). The study was performed over a period of 4 yr. Glyphosate and AMPA concentrations were found to be higher in runoff and in transported sediment from HR compared with GR, regardless of the amount of runoff and transported sediment. The mean annual percentages of glyphosate loss, via runoff and transported sediment, were about 1.37 and 0.73% for HR and GR, respectively. Aminomethylphosphonic acid represented approximately 30.9 and 40.0% of the total glyphosate losses in GR and HR, respectively. Moreover, results suggested that rains occurring within 4 wk after treatment could cause the transport of glyphosate and AMPA in high concentrations. Soil analyses indicated that glyphosate content was below detection within 1 yr, whereas AMPA remained in the soil profiles along the vine row and in the inter-row. Results indicated that GR can reduce soil and herbicide loss by runoff in vineyard cropping system.

Leaching of Glyphosate and Aminomethylphosphonic Acid through Silty Clay Soil Columns under Outdoor Conditions.

Glyphosate [-(phosphono-methyl)-glycine] is the main herbicide used in the Chianti vineyards. Considering the pollution risk of the water table and that the vineyard tile drain may deliver this pollutant into nearby streams, the objective of the present study was to estimate the leaching losses of glyphosate under natural rainfall conditions in a silty clay soil in the Chianti area. The leaching of glyphosate and its metabolite (aminomethylphosphonic acid [AMPA]) through soils was studied in 1-m-deep soil columns under outdoor conditions over a 3-yr period. Glyphosate was detected in the leachates for up to 26 d after treatments at concentrations ranging between 0.5 and 13.5 µg L. The final peak (0.28 µg L) appeared in the leachates approximately 319 d after the first annual treatment. Aminomethylphosphonic acid first appeared (21.3 µg L) in the soil leachate 6.8 d after the first annual treatment. Aminomethylphosphonic acid detection frequency and measured concentration in the leachates were more than that observed for the glyphosate. Aminomethylphosphonic acid was detected in 20% of the soil leachates at concentrations ranging from 1 to 24.9 µg L. No extractable glyphosate was detected in the soil profile. However, the AMPA content in the lowest layer ranged from 13.4 to 21.1 mg kg, and on the surface layer, it ranged from 86.7 to 94 mg kg. Overall, these results indicate that both glyphosate and AMPA leaching through a 1-m soil column may be potential groundwater contaminants.

Seasonal differences in climate in the Chianti region of Tuscany and the relationship to vintage wine quality.

Climatic factors and weather type frequencies affecting Tuscany are examined to discriminate between vintages ranked into the upper- and lower-quartile years as a consensus from six rating sources of Chianti wine during the period 1980 to 2011. These rankings represent a considerable improvement on any individual publisher ranking, displaying an overall good consensus for the best and worst vintage years. Climate variables are calculated and weather type frequencies are matched between the eight highest and the eight lowest ranked vintages in the main phenological phases of Sangiovese grapevine. Results show that higher heat units; mean, maximum and minimum temperature; and more days with temperature above 35 °C were the most important discriminators between good- and poor-quality vintages in the spring and summer growth phases, with heat units important during ripening. Precipitation influences on vintage quality are significant only during veraison where low precipitation amounts and precipitation days are important for better quality vintages. In agreement with these findings, weather type analysis shows good vintages are favoured by weather type 4 (more anticyclones over central Mediterranean Europe (CME)), giving warm dry growing season conditions. Poor vintages all relate to higher frequencies of either weather type 3, which, by producing perturbation crossing CME, favours cooler and wetter conditions, and/or weather type 7 which favours cold dry continental air masses from the east and north east over CME. This approach shows there are important weather type frequency differences between good- and poor-quality vintages. Trend analysis shows that changes in weather type frequencies are more important than any due to global warming.

Air temperature exposure and outdoor occupational injuries: a significant cold effect in Central Italy.

OBJECTIVE: To investigate the short-term effect of air temperature on outdoor occupational injuries (out_OI) in Central Italy, also by taking different geographical factors and employment sectors of workers into account. METHODS: Out_OI for all of Tuscany (Central Italy), from 2003 to 2010 (n=162,399), were provided by the National Institute of Insurance for Occupational Illness and Injury. Representative daily meteorological data of the geographical area under study were obtained from the European Reanalysis-interim climatological reanalysis archive. Relationships between short-term changes in air temperature and out_OI were studied through Generalised Additive Models. RESULTS: The exposure-response curves of out_OI and short-term changes in air temperature generally showed significant out_OI increases when cold conditions occurred. The air temperature breakpoint corresponded to the 10th centile (-0.8°C) of the air temperature time series used in this study: a 1°C decrease in temperature below the 10th centile corresponded to a 2.3% (CI 1.3% to 3.3%) increase of out_OI throughout all of Tuscany. The cold effect was strongest in plain areas, especially when out_OI occurred in vehicles other than cars. No relationships of injuries with temperature extremes were observed in workers who generally spend half or most of their time outdoors, such as construction, land and forestry workers. However, these latter outdoor workers showed significant linear associations of injuries with typical (far-from-extreme) temperatures. CONCLUSIONS: This large population-based study highlights the significant and independent effects of short-term air temperature changes (especially cold) in triggering out_OI. These findings represent the first step towards developing a geographically differentiated, operative outdoor-temperature-occupational-health warning system aimed at preventing outdoor work injuries.

Environmental temperature and thermal indices: what is the most effective predictor of heat-related mortality in different geographical contexts?

The aim of this study is to identify the most effective thermal predictor of heat-related very-elderly mortality in two cities located in different geographical contexts of central Italy. We tested the hypothesis that use of the state-of-the-art rational thermal indices, the Universal Thermal Climate Index (UTCI), might provide an improvement in predicting heat-related mortality with respect to other predictors. Data regarding very elderly people (≥ 75 years) who died in inland and coastal cities from 2006 to 2008 (May-October) and meteorological and air pollution were obtained from the regional mortality and environmental archives. Rational (UTCI) and direct thermal indices represented by a set of bivariate/multivariate apparent temperature indices were assessed. Correlation analyses and generalized additive models were applied. The Akaike weights were used for the best model selection. Direct multivariate indices showed the highest correlations with UTCI and were also selected as the best thermal predictors of heat-related mortality for both inland and coastal cities. Conversely, the UTCI was never identified as the best thermal predictor. The use of direct multivariate indices, which also account for the extra effect of wind speed and/or solar radiation, revealed the best fitting with all-cause, very-elderly mortality attributable to heat stress.

Seasonal variation, weather and behavior in day-care children: a multilevel approach.

This study analyzes the effect of weather variables, such as solar radiation, indoor and outdoor air temperature, relative humidity and time spent outdoor, on the behavior of 2-year-old children and their affects across different seasons: winter, spring and summer. Participants were a group of 61 children (33 males and 28 females) attending four day-care centers in Florence (Central Italy). Mean age of children at the beginning of the study was 24.1 months (SD = 3.6). We used multilevel linear analyses to account for the hierarchical structure of our data. The study analyzed the following behavioral variables: Activity Level, Attentional Focusing, Frustration, and Aggression. Results showed a different impact of some weather variables on children's behavior across seasons, indicating that the weather variable that affects children's behavior is usually the one that shows extreme values during the studied seasons, such as air temperature and relative humidity in winter and summer. Studying children and their reactions to weather conditions could have potentially wide-reaching implications for parenting and teaching practices, as well as for researchers studying social relationships development.

Mediterranean climate patterns and wine quality in North and Central Italy.

Results show that the year-to-year quality variation of wines produced in North and Central Italy depends on the large-scale climate variability, and that the wine quality improvement in the last four decades is partially due to an increase of temperature and to a decrease of precipitation in West and Central Mediterranean Europe (WME; CME). In addition, wine quality is positively correlated with air temperature throughout the entire active period of the grapevine, weakly negatively correlated with precipitation in spring, and well negatively correlated in summer and fall. The month-to-month composites of the NAO anomaly show that, in years of good quality wine, this anomaly is negative in late spring, oscillates around zero in summer, and is positive in early fall; while, in years of bad quality wine, it is positive in late spring and summer, and negative in early fall, i.e. its polarity has an opposite sign in spring and fall in good versus bad years. The composite seasonal maps show that good wines are produced when the spring jet stream over the Atlantic diverts most of the weather perturbations towards North Europe, still providing a sufficient amount of rainwater to CME; when summer warming induced by southerly winds is balanced by the cooling induced by westerly winds; and when a positive geopotential anomaly over WME shelters CME from fall Atlantic storms. Bad quality wines are produced when the jet stream favors the intrusion of the Atlantic weather perturbations into the Mediterranean. Results suggest that atmospheric pattern persistencies can be used as precursors for wine quality forecast.

Symptom control and health-related quality of life in allergic rhinitis with and without comorbid asthma: A multicentre European study.

BACKGROUND: Allergic rhinitis (AR) is a major non-communicable disease that affects the health-related quality of life (HRQoL) of patients. However, data on HRQoL and symptom control in AR patients with comorbid asthma (AR + asthma) are lacking. METHODS: In this multicentre, cross-sectional study, patients with AR were screened and administered questionnaires of demographic characteristics and health conditions (symptoms/diagnosis of AR and asthma, disease severity level, and allergic conditions). HRQoL was assessed using a modified version of the RHINASTHMA questionnaire (30, 'not at all bothered' - 150 'very much bothered') and symptom control was evaluated by a modified version of the Control of Allergic Rhinitis/Asthma Test (CARAT) (0, 'no control' - 30, 'very high control'). RESULTS: Out of 643 patients with AR, 500 (78%) had asthma as a comorbidity, and 54% had moderate-severe intermittent AR, followed by moderate-severe persistent AR (34%). Compared to the patients with AR alone, patients with AR + asthma had significantly higher RHINASTHMA (e.g., median RHINASTHMA-total score 48.5 vs. 84, respectively) and a significantly lower CARAT score (median CARAT-total score 23 vs. 16.5, respectively). Upon stratifying asthma based on severity, AR patients with severe persistent asthma had worse HRQoL and control than those with mild persistent asthma. The association was significantly higher among non-obese participants compared to obese ones, with RHINASTHMA-upper symptoms score but not with CARAT. CONCLUSIONS: Our observation of poorer HRQoL and symptoms control in AR patients with comorbid asthma supports the importance of a comprehensive approach for the management of AR in case of a comorbid allergic condition.

Heat-related mortality in the Florentine area (Italy) before and after the exceptional 2003 heat wave in Europe: an improved public health response?

High ambient temperatures have been associated with increased mortality across the world. Several studies suggest that timely preventive measures may reduce heat-related excess mortality. The main aim of this study was to detect the temporal modification of heat-related mortality, in older adults (aged 65-74) and in elderly ≥75 years old, in the Florentine area by comparing previous (1999-2002) and subsequent (2004-2007) periods to the summer of 2003, when a regional Heat-Health Warning System (HHWS) was set up. Mortality data from 1999 to 2007 (May-September) were provided by the Mortality Registry of the Tuscany Region (n = 21,092). Weather data were used to assess daily apparent temperatures (AT). Case-crossover time-stratified designs and constrained segmented distributed lag models were applied. No significant heat-related mortality odds ratio (OR) variations were observed among the sub-periods. Nevertheless, a general OR decrease dating from 1999-2002 (OR 1.23; lack of HHWS) to 2004-2005 (OR 1.21; experimental HHWS running only for Florence) and to 2006-2007 (OR 1.12; official HHWS extended to the whole Florentine area) was observed when the maximum AT was considered. This modification was only evident in subjects ≥75 years old. The heat effect was higher and sustained for more days (until lag 9) during the period 1999-2002 than 2004-2007. The decrease of the excessive heat effect on mortality between periods with the absence and existence of a HHWS is also probably due to the mitigation of preventive measures and the implementation of a HHWS with specific interventions for safeguarding the health of the "frail elderly".

Effects of biochar on berseem clover (Trifolium alexandrinum, L.) growth and heavy metal (Cd, Cr, Cu, Ni, Pb, and Zn) accumulation.

Urban soil pollution by heavy metals (HMs) is a pressing problem in the development of urban agriculture (UA). In this context, the use of amendments, such as biochar, and phytoremediation are considered potentially cost-effective alternatives to conventional methods, and can be also combined to improve the remediation of soils from HMs. A pot experiment was performed to investigate the combined effect of berseem clover (Trifolium alexandrinum, L.) and biochar amendment in remediating a sandy soil collected near a shooting range area co-contaminated with Cd, Cr, Cu, Ni, Pb, and Zn. The biochar, obtained from a wood-chip gasifier fed with a mix of Douglas (Pseudotsuga menziesii, Mirb.) and Black Pine (Pinus nigra, J.F.Arnold) wood, was applied at two rates (0.8% and 1.6%, w/w). Eighteen weeks after sowing, all plants were harvested. The roots and aboveground tissues of the crops were separately collected and analyzed. The tested biochar effectively adsorbed the HMs (Cd, Cr, Cu, Ni, Pb, and Zn) from the soil. Biochar increased DW production of aboveground and root tissues. Moreover, biochar significantly reduced the concentration of Cr, Cu, Ni, and Pb in the aboveground tissues of berseem clover, although a significant reduction was not detected for Cd and Zn. Results indicated that berseem clover was a Cr, Ni and Pb excluder. However, this species can be considered suitable for Cu phytoextraction and Cd and Zn phytostabilization of slightly polluted urban soil. Only the Cu levels in the aerial biomass were below the acceptable limit for use as fodder.

Intraoperative Ultrasonography for Surgery of Cranial Traumatic Acute Subdural Hematoma: Technical Note.

BACKGROUND: Intraoperative ultrasonography (IOUS) in traumatic brain injury is a fast, easy, and low-cost technique that has been poorly investigated so far even though it could potentially answer many of the intraoperative needs of the surgeon. The aim of this study was to investigate the role of IOUS in patients undergoing surgery for traumatic acute subdural hematoma (aSDH), focusing on its influence on intraoperative surgical strategy, particularly regarding the management of intracerebral contusions (ICCs) associated with aSDH. METHODS: Data of patients who consecutively underwent surgical evacuation of traumatic aSDH with IOUS assistance at our institution from May 2017 to December 2020 were retrospectively analyzed. Patients were dichotomized into an ICC group (ICCs associated with aSDH on preoperative computed tomography scan) and no ICC group (no ICCs associated with aSDH on preoperative computed tomography scan). RESULTS: The study included 41 patients. Before aSDH evacuation, IOUS findings were similar to preoperative computed tomography data. After aSDH evacuation, IOUS detected a new-onset ICC in 13% of patients in the no ICC group and a volume increase of the known ICCs in 22% of patients in the ICC group. Therefore, IOUS made it possible to evacuate these new-onset or expanding hematomas in the same operation, changing our surgical strategy and avoiding a delayed reintervention. CONCLUSIONS: Our study suggests that IOUS in patients undergoing surgery for traumatic aSDH can promptly identify possible evolution of a primary head injury, leading to early and effective treatment.