Synthetic CT imaging for PET monitoring in proton therapy: a simulation study.

Objective.This study addresses a fundamental limitation of in-beam positron emission tomography (IB-PET) in proton therapy: the lack of direct anatomical representation in the images it produces. We aim to overcome this shortcoming by pioneering the application of deep learning techniques to create synthetic control CT images (sCT) from combining IB-PET and planning CT scan data.Approach.We conducted simulations involving six patients who underwent irradiation with proton beams. Leveraging the architecture of a visual transformer (ViT) neural network, we developed a model to generate sCT images of these patients using the planning CT scans and the inter-fractional simulated PET activity maps during irradiation. To evaluate the model's performance, a comparison was conducted between the sCT images produced by the ViT model and the authentic control CT images-serving as the benchmark.Main results.The structural similarity index was computed at a mean value across all patients of 0.91, while the mean absolute error measured 22 Hounsfield Units (HU). Root mean squared error and peak signal-to-noise ratio values were 56 HU and 30 dB, respectively. The Dice similarity coefficient exhibited a value of 0.98. These values are comparable to or exceed those found in the literature. More than 70% of the synthetic morphological changes were found to be geometrically compatible with the ones reported in the real control CT scan.Significance.Our study presents an innovative approach to surface the hidden anatomical information of IB-PET in proton therapy. Our ViT-based model successfully generates sCT images from inter-fractional PET data and planning CT scans. Our model's performance stands on par with existing models relying on input from cone beam CT or magnetic resonance imaging, which contain more anatomical information than activity maps.

The local environment and germline genetic variation predict cancer risk in the UK Biobank prospective cohort.

BACKGROUND: There is a growing body of evidence on the effect of the local environment exposure on cancer susceptibility. Nonetheless, several of the associations remain controversial. Moreover, our understanding of the possible interaction between the local environment and the genetic variability is still very limited. OBJECTIVE: The aim of this study was to clarify the role of the local environment and its possible interplay with genetics on common cancers development. METHODS: Using the UK Biobank (UKBB) prospective cohort, we selected 12 local environment exposures: nitrogen oxides, nitrogen dioxides, particulate matter (10 and 2.5 µm), noise pollution, urban traffic, living distance from the coast, percentage of greenspace, natural environment, water, and domestic garden within 1000 m from the residential coordinates of each participant. All these exposures were tested for association with 17 different types of cancer for a total of 53,270 cases and 302,645 controls. Additionally, a polygenic score (PGS) was computed for each cancer, to test possible gene-environment interactions. Finally, mediation analyses were carried out. RESULTS: Thirty-six statistically significant associations considering multiple testing (p < 2.19 × 10-4) were observed. Among the novel associations we observed that individuals living farther from the coast had a higher risk of developing prostate cancer (OR = 1.13, CI95% = 1.06-1.20, P = 1.98 × 10-4). This association was partially mediated by physical activity (indirect effect (IE) = -8.48 × 10-7) and the time spent outdoor (IE = 9.07 × 10-6). All PGSs showed statistically significant associations. Finally, genome-environment interaction analysis showed that local environment and genetic variability affect cancer risk independently. DISCUSSION: Living close to the coast and air pollution were associated with a decreased risk of prostate cancer and skin melanoma, respectively. These findings from the UKBB support the role of the local environment on cancer development, which is independent from genetics and may be mediated by several lifestyle factors.

Analysis of exposome and genetic variability suggests stress as a major contributor for development of pancreatic ductal adenocarcinoma.

BACKGROUND: The current knowledge on pancreatic ductal adenocarcinoma (PDAC) risk factors is limited and no study has comprehensively tested the exposome in combination with the genetic variability in relation to the disease susceptibility. AIM: The aim of this study was to analyze the exposome and its interaction with known genetic susceptibility loci, in relation to PDAC risk. METHODS: A case-control study nested in UK Biobank cohort was conducted on 816 PDAC cases and 302,645 controls. A total of 347 exposure variables, and a polygenic risk score (PRS) were analyzed through logistic regression. Gene-environment interaction analyses were conducted. RESULTS: A total of 52 associations under the Bonferroni corrected threshold of p < 1.46 × 10-4 were observed. Known risk factors such as smoking, pancreatitis, diabetes, PRS, heavy alcohol drinking and overweight were replicated in this study. As for novel associations, a clear indication for length and intensity of mobile phone use and the stress-related factors and stressful events with increase of PDAC risk was observed. Although the PRS was associated with PDAC risk (P = 2.09 × 10-9), statistically significant gene-exposome interactions were not identified. CONCLUSION: In conclusion, our results suggest that a stressful lifestyle and sedentary behaviors may play a major role in PDAC susceptibility independently from the genetic background.

Automatic Recognition of Ragged Red Fibers in Muscle Biopsy from Patients with Mitochondrial Disorders.

Mitochondrial dysfunction is considered to be a major cause of primary mitochondrial myopathy in children and adults, as reduced mitochondrial respiration and morphological changes such as ragged red fibers (RRFs) are observed in muscle biopsies. However, it is also possible to hypothesize the role of mitochondrial dysfunction in aging muscle or in secondary mitochondrial dysfunctions. The recognition of true histological patterns of mitochondrial myopathy can avoid unnecessary genetic investigations. The aim of our study was to develop and validate machine-learning methods for RRF detection in light microscopy images of skeletal muscle tissue. We used image sets of 489 color images captured from representative areas of Gomori's trichrome-stained tissue retrieved from light microscopy images at a 20× magnification. We compared the performance of random forest, gradient boosting machine, and support vector machine classifiers. Our results suggested that the advent of scanning technologies, combined with the development of machine-learning models for image classification, make neuromuscular disorders' automated diagnostic systems a concrete possibility.

Metabolomic Profile of Young Adults Born Preterm.

Prematurity is a risk factor for the development of chronic adult diseases. Metabolomics can correlate the biochemical changes to a determined phenotype, obtaining real information about the state of health of a subject at that precise moment. Significative differences in the metabolomic profile of preterm newborns compared to those born at term have been already identified at birth. An observational case-control study was performed at the University Hospital of Siena. The aim was to evaluate and compare the metabolomic profiles of young adults born preterm to those born at term. Urinary samples were collected from 67 young adults (18-23 years old) born preterm (mean gestational age of 30 weeks, n = 49), and at term of pregnancy (mean gestational age of 38 weeks, n = 18). The urinary spectra of young adults born preterm was different from those born at term and resembled what was previously described at birth. The Random Forest algorithm gave the best classification (accuracy 82%) and indicated the following metabolites as responsible for the classification: citrate, CH2 creatinine, fumarate and hippurate. Urine spectra are promising tools for the early identification of neonates at risk of disease in adulthood and may provide insight into the pathogenesis and effects of fetal programming and infants' outcomes.

AUTOMA: a wearable device to assess the upper limb muscular activity in patients with neuromuscular disorders.

Inherited muscular dystrophies and congenital myopathies present in early childhood with progressive muscle weakness, determining severe motor limitations. Active surveillance and management of associated complications have improved ambulation, function, quality of life and life expectancy. The need for repeatable, objective and quantitative measures to monitor the clinical course of the disease is a current issue, particularly in the new era where new flows of therapies are proposed to the patients. In this scenario, we designed and tested a wearable device termed AUTOMA that is able to provide quantification of the muscular impairment in the upper limb upon isokinetic tests through the integration of a force sensor and an electric goniometer. This allows qualitatively estimating the muscular functions with a systematic procedure. We carried out a preliminary pilot study on 9 patients that revealed the suitability of AUTOMA as an objective measurement tool for diagnosing and monitoring neuromuscular disorders, and opens to a more extensive clinical study in which to test and validate our platform intensively.

Newborn metabolomic profile mirrors that of mother in pregnancy.

BACKGROUND: Pregnancy is characterized by multiple metabolic processes to allow proper foetal development and ensure adequate stores. Little is known about the interactions between maternal and foetal metabolism during the last phase of pregnancy. Metabolomic offers potential to discover changes in maternal metabolism in pregnancy and their relation to the newborn metabolic status. OBJECTIVE: In this study we tested the hypothesis that metabolomic status in newborns at birth depends upon the metabolomic profile of their mothers in the last phase of pregnancy. STUDY DESIGN: Urine samples were collected from 36 pregnant women three weeks before delivery and from 21 healthy term newborns within 48 h after birth. Urines were analysed using proton nuclear magnetic resonance (1H NMR) spectroscopy and NMR urine spectra were evaluated through Principal Components Analysis. RESULTS: The first component of the PCA analysis showed two distinct metabolic groups: pregnant women and newborns. A significant correlation was found between urine metabolic profiles of newborns and those of their mothers. CONCLUSION: Urine metabolomic profiles of newborns at birth mirrors that of their mothers in the last phase of pregnancy. The metabolomic approach appears to be crucial to understand the maternal effects on foetal programming and infant outcomes.

Breast milk: To each his own. From metabolomic study, evidence of personalized nutrition in preterm infants.

OBJECTIVES: The composition of milk from mothers delivering prematurely differs from that of full-term mature milk and changes over time. The aim of this study is to test the hypothesis that changes in milk metabolomic profile from mothers delivering prematurely persist over time when compared with mothers delivering at term. METHODS: Nuclear magnetic resonance spectroscopy was used to analyze the metabolome pattern of human milk samples collected from 18 mothers. Twelve mothers collected 12 term milk samples (one for each mother) once between 4 and 7 d after delivery. Six mothers delivering prematurely (29-31 wk of gestational age) and collected three samples each, once a week after delivery until the third week after birth. RESULTS: Principal component analysis identified two distinct metabolite groups, one represented by the 18 preterm milk samples and the other by term milk samples. Metabolite profiling identified that lactose and oligosaccharide levels were significantly more represented in preterm than in milk term samples. CONCLUSIONS: The preterm milk metabolome pattern undergoes maturation during the first 3 wk after birth, but at the end of the third week it still does not resemble the term milk pattern. The specific changes in mothers' milk metabolomic profiles according to their offspring might reflect the different nutritional requirement of each preterm infant. This knowledge is crucial to move from standardized nutritional protocols to tailored, individualized nutrition in preterm infants.

Predictive Role of Urinary Metabolic Profile for Abnormal MRI Score in Preterm Neonates.

BACKGROUND AND OBJECTIVE: Early identification of neonates at risk for brain injury is important to start appropriate intervention. Urinary metabolomics is a source of potential, noninvasive biomarkers of brain disease. We studied the urinary metabolic profile at 2 and 10 days in preterm neonates with normal/mild and moderate/severe MRI abnormalities at term equivalent age. METHODS: Urine samples were collected at two and 10 days after birth in 30 extremely preterm infants and analyzed using proton magnetic resonance spectroscopy. A 3 T MRI was performed at term equivalent age, and images were scored for white matter (WM), cortical grey matter (cGM), deep GM, and cerebellar abnormalities. Infants were divided in two groups: normal/mild and moderately/severely abnormal MRI scores. RESULTS: No significant clustering was seen between normal/mild and moderate/severe MRI scores for all regions at both time points. The ROC curves distinguished neonates at 2 and 10 days who later developed a markedly less mature cGM score from the others (2 d: area under the curve (AUC) = 0.72, specificity (SP) = 65%, sensitivity (SE) = 75% and 10 d: AUC = 0.80, SP = 78%, SE = 80%) and a moderately to severely abnormal WM score (2 d: AUC = 0.71, specificity (SP) = 80%, sensitivity (SE) = 72% and 10 d: AUC = 0.69, SP = 64%, SE = 89%). CONCLUSIONS: Early urinary spectra of preterm infants were able to discriminate metabolic profiles in patients with moderately/severely abnormal cGM and WM scores at term equivalent age. Urine spectra are promising for early identification of neonates at risk of brain damage and allow understanding of the pathogenesis of altered brain development.

Identification of a panel of cytokines in neonates with hypoxic ischemic encephalopathy treated with hypothermia.

PURPOSE: Inflammation is a crucial but understudied mechanism of neuronal injury after hypoxia-ischemia. The aim was to identify a panel of cytokines involved in brain injury in neonates with hypoxic ischemic encephalopathy (HIE). METHODS: Ten newborns with HIE undergoing to therapeutic hypothermia (TH, HIE Group) and 8 healthy newborns (CTRL Group) were enrolled. For the HIE group, 5 samples were collected: between 0 and 6 h of life (time 1), 12 h (time 2), 24 h (time 3), 48 h (time 4) and 96 h of life (time 5). For the CTRL group, one sample was collected. A panel of 48 inflammatory cytokines was determined in all samples. Data were analyzed using multivariate statistical analysis (Principal component analysis, PCA) RESULTS: 17 cytokines, among 48 analyzed, were found to be significantly different, initially, between the CTRL and HIE groups: 12 with reported pro-inflammatory effects and 5 with reported anti-inflammatory effects. In the HIE group cytokines showed a decreasing trend during the TH and at the end of treatment comparable to the CTRL group. IL-18 did demonstrate a slight increase at time 3 during HT but decreased steadily at sampling times, 4 and 5. CONCLUSIONS: Our data demonstrates that many pathways of the inflammatory cascade are activated following hypoxic-ischemic injury. This information will increase our understanding of changes in cytokines over time in neonates with HIE undergoing TH.

On the tracks of Nitrogen deposition effects on temperate forests at their southern European range - an observational study from Italy.

We studied forest monitoring data collected at permanent plots in Italy over the period 2000-2009 to identify the possible impact of nitrogen (N) deposition on soil chemistry, tree nutrition and growth. Average N throughfall (N-NO3 +N-NH4 ) ranged between 4 and 29 kg ha(-1)  yr(-1) , with Critical Loads (CLs) for nutrient N exceeded at several sites. Evidence is consistent in pointing out effects of N deposition on soil and tree nutrition: topsoil exchangeable base cations (BCE) and pH decreased with increasing N deposition, and foliar nutrient N ratios (especially N : P and N : K) increased. Comparison between bulk openfield and throughfall data suggested possible canopy uptake of N, levelling out for bulk deposition >4-6 kg ha(-1)  yr(-1) . Partial Least Square (PLS) regression revealed that - although stand and meteorological variables explained the largest portion of variance in relative basal area increment (BAIrel 2000-2009) - N-related predictors (topsoil BCE, C : N, pH; foliar N-ratios; N deposition) nearly always improved the BAIrel model in terms of variance explained (from 78.2 to 93.5%) and error (from 2.98 to 1.50%). N deposition was the strongest predictor even when stand, management and atmosphere-related variables (meteorology and tropospheric ozone) were accounted for. The maximal annual response of BAIrel was estimated at 0.074-0.085% for every additional kgN. This corresponds to an annual maximal relative increase of 0.13-0.14% of carbon sequestered in the above-ground woody biomass for every additional kgN, i.e. a median value of 159 kgC per kgN ha(-1)  yr(-1) (range: 50-504 kgC per kgN, depending on the site). Positive growth response occurred also at sites where signals of possible, perhaps recent N saturation were detected. This may suggest a time lag for detrimental N effects, but also that, under continuous high N input, the reported positive growth response may be not sustainable in the long-term.

Creatine transporter defect diagnosed by proton NMR spectroscopy in males with intellectual disability.

Creatine deficiency syndrome due to mutations in X-linked SLC6A8 gene results in nonspecific intellectual disability (ID). Diagnosis cannot be established on clinical grounds and is often based on the assessment of brain creatine levels by magnetic resonance spectroscopy (MRS). Considering high costs of MRS and necessity of sedation, this technique cannot be used as a first level-screening test. Likewise, gene test analysis is time consuming and not easily accessible to all laboratories. In this article feasibility of urine analysis (creatine/creatinine (Cr/Crn) ratio) performed by nuclear magnetic resonance (NMR) as a first level-screening test is explored. Before running a systematic selection of cases a preliminary study for further molecular analysis is shown. NMR urine spectra (n = 1,347) of male patients with an ID without a clinically recognizable syndrome were measured. On the basis of abnormal Cr/Crn ratio, three patients with the highest values were selected for molecular analysis. A confirmatory second urine test was positive in two patients and diagnosis was further confirmed by a decreased brain creatine level and by SLC6A8 gene analysis. A de novo mutation was identified in one. Another patient inherited a novel mutation from the mother who also has a mild ID. A repeat urine test was negative in the third patient and accordingly creatine level in the brain and SLC6A8 gene analysis both gave a normal result. We conclude that Cr/Crn ratio measured by NMR for male patients represents a rapid and useful first level screening test preceding molecular analysis.

Contribution of a municipal solid waste incinerator to the trace metals in the surrounding soil.

This study analyses the pedological environment of the area near a municipal waste incinerator that has been operating in the south-east district of Pisa for approximately 20 years. There are many other industrial activities in the area besides the incinerator, which represent possible sources of pollution, as well as heavy road traffic. The study area was defined by a 0-4-km zone around the site with a population of approximately 12,000 residents. The study included the physical and chemical characterisation of 100 samples of soil and an analysis of trace metals such as Cr, Ni, Pb, Zn, Hg, As and Cd. The samples were grouped into soil use categories. The results showed Zn, Pb and Hg correlated with their potentially mobile fractions, and suggested an anthropic contribution to their presence in the soil. Ni, Cr and As showed values attributable to a lithological origin. This was consistent with the PCA results. The aim was to define the environmental state of the soil of the area in order to create a reference for future research and to verify the possible presence of pollution from other sources (local industrial activities and traffic).

Ozone exposure, defoliation of beech (Fagus sylvatica L.) and visible foliar symptoms on native plants in selected plots of South-Western Europe.

The relationships between crown defoliation of beech, visible foliar symptoms on native vegetation and ozone exposure were investigated on permanent monitoring sites in South-Western Europe in the years 2000-2002. Relationships between defoliation of beech and O3 (seasonal mean, 2-week maximum, AOT40) were investigated by means of multiple regression models (11 plots, 1-3 years of data each) and a model based on temporal autocorrelation of defoliation data (14 plots, 1-3 years of data each). Different multiple regression techniques were used. The four models generated (R2=0.71-0.85, explained variance in cross-validation 61-78%) identified several significant predictors of defoliation, with AOT40 (p=0.008) and foliar content of phosphorous (p=0.0002-0.0004) being common to all models. The autocorrelation model (R2=0.55; p<0.0001) was used to calculate expected defoliation on the basis of the previous year's defoliation, and model predictions were used as an estimate of expected defoliation under constant site and environmental condition. Residuals (predicted-measured) plotted against current AOT40 shows that a possible effect of ozone occurs only at very high AOT40 (>35,000 ppbh). O3-like visible foliar symptoms were recorded on 65 species at 47% of the common monitoring sites in 2001 and 38% in 2002. No relationship was found between O3 exposure, frequency of symptomatic sites and frequency of species with symptoms (R2=0.11; p>0.05). A number of questions related to the ecological and methodological basis of the survey were identified. Inherent sampling and non-sampling errors and multicollinearity of the data suggest great caution when examining results obtained from mensurational, correlative studies.

Metal contamination in urban soils of coastal Tuscany (Italy).

Urban soils are often contaminated by metals deriving from human activities. Urban polluted soils can affect human health through direct physical contact or through the food chain. The behaviour of metals is affected by chemical and physical soil properties. Heavy metal concentration was determined in some soils of three medium sized towns of coastal Tuscany, Central Italy. Soil samples were collected in roadsides, urban agricultural soils (allotments), playgrounds and public parks. The analysis included total metal content (Pb, Cu, Zn, Ni, Cd), and sequential extraction. Lead reached the highest levels in the soils and was higher near roads. In urban agricultural soils and in allotments Cu was present in noticeable quantities (300 mg kg(-1)). The presence of Cu in urban soils seems to be typical of soils used for a long period as agricultural land, especially vineyards in the area covered by this study. Sequential extraction was performed to evaluate the mobility of the metals and to better understand the impact of the anthropogenic activity on urban sites. In the present study principal components analysis (PCA) is employed to describe the characteristics of urban soils.

Estrogen-like activity of seafood related to environmental chemical contaminants.

BACKGROUND: A wide variety of environmental pollutants occur in surface waters, including estuarine and marine waters. Many of these contaminants are recognised as endocrine disrupting chemicals (EDCs) which can adversely affect the male and female reproductive system by binding the estrogen receptor and exhibiting hormone-like activities. In this study the estrogenic activity of extracts of edible marine organisms for human consumption from the Mediterranean Sea was assayed. METHODS: Marine organisms were collected in two different areas of the Mediterranean Sea. The estrogenic activity of tissues was assessed using an in vitro yeast reporter gene assay (S. cerevisiae RMY 326 ER-ERE). Concentrations of polychlorinated biphenyls (PCBs) (congeners 28, 52, 101, 118, 138, 153, 180) in fish tissue was also evaluated. RESULTS: Thirty-eight percent of extracts showed a hormone-like activity higher than 10% of the activity elicited by 10 nM 17b-estradiol (E2) used as control. Total PCB concentrations ranged from 0.002 up to 1.785 ng/g wet weight. Chemical analyses detected different levels of contamination among the species collected in the two areas, with the ones collected in the Adriatic Sea showing concentrations significantly higher than those collected in the Tyrrhenian Sea (p < 0.01). CONCLUSION: The more frequent combination of chemicals in the samples that showed higher estrogenic activity was PCB 28, PCB 101, PCB 153, PCB 180. The content of PCBs and estrogenic activity did not reveal any significant correlation.