Difficulties of children with symptoms of attention-deficit/hyperactivity disorder in processing temporal information concerning everyday life events.

It has been hypothesized that children with attention-deficit/hyperactivity disorder (ADHD) present difficulties in processing time durations. However, so far evidence on this difficulty and its related mechanisms has been unclear and collected only with rating scales or laboratory experimental tasks. The current study examined whether this difficulty can be seen in children carrying out everyday actions (e.g., telephone calls, cooking activities) and to what extent it is influenced by working memory (WM) abilities. In total, 182 children aged 7 to 10 years were included in the study: 91 children with ADHD symptoms and 91 typically developing (TD) children matched for gender and other characteristics. We administered sequence reordering, time reproduction, and duration comparison tasks, and as stimuli we used six movies lasting 10 to 60 s showing three women completing six different actions. We also collected measures of verbal and visuospatial WM tests (digit span and Corsi task). Children with ADHD symptoms tended to underestimate the long durations and were less accurate than TD children in remembering the exact order of events and in comparing the duration of two different events. These difficulties appeared to be related to WM abilities.

Effects of Curative Colorectal Cancer Surgery on Exhaled Volatile Organic Compounds and Potential Implications in Clinical Follow-up.

OBJECTIVE: The aim of this study was to determine whether the volatile organic compounds (VOCs) pattern in colorectal cancer (CRC) patients is modified by curative surgery for a potential application in the oncologic follow-up. BACKGROUND: CRC has been proved to induce metabolic derangements detectable by high through-output techniques in exhaled breath showing a specific pattern of VOCs. METHODS: Forty-eight CRC patients and 55 healthy controls (HC) entered the study. Thirty-two patients (M/F: 1.4; mean age 63 years) attended the oncologic follow-up (mean 24 months) and were found disease-free. Breath samples were collected under similar environmental conditions into a Tedlar bags and processed offline by thermal-desorption gas chromatography-mass spectrometry (TD-GC-MS). VOCs were selected by U test to build a Probabilistic Neural Network (PNN) model to set-up a training phase, which was cross-validated using the leave-one out method. RESULTS: A total of 11 VOCs were finally selected for their excellent discriminant performance in identifying disease-free patients in follow-up from CRC patients before surgery, (sensitivity 100%, specificity 97.92%, accuracy 98.75%, and AUC: 1). The same VOCs pattern discriminated follow-up patients from HC, with a sensitivity of 100%, specificity of 90.91%, accuracy of 94.25%, and AUC 0.959. CONCLUSIONS: Exhaled VOCs pattern from CRC patients is modified by cancer removal confirming the tight relationship between tumor metabolism and exhaled VOCs. PNN analysis provides a high discriminatory tool to identify patients disease-free after curative surgery suggesting potential implications in CRC screening and secondary prevention.

Breath Analysis: A Systematic Review of Volatile Organic Compounds (VOCs) in Diagnostic and Therapeutic Management of Pleural Mesothelioma.

Malignant pleural mesothelioma (MPM) is a rare neoplasm related to asbestos exposure and with high mortality rate. The management of patients with MPM is complex and controversial, particularly with regard to early diagnosis. In the last few years, breath analysis has been greatly implemented with this aim. In this review the strengths of breath analysis and preliminary results in searching breath biomarkers of MPM are highlighted and discussed, respectively. Through a systematic electronic literature search, collecting papers published from 2000 until December 2018, fifteen relevant scientific papers were selected. All papers considered were prospective, comparative, observational case-control studies although every single one pilot and based on a relatively small number of samples. The identification of diagnostic VOCs pattern, through breath sample characterization and the statistical data treatment, allows to obtain a strategic information for clinical diagnostics. To date the collected data provide just preliminary information and, despite the promising results and diagnostic accuracy, conclusions cannot be generalized due to the limited number of individuals included in each cohort study. Furthermore none of studies was externally validated, although validation process is a necessary step towards clinical implementation. Breathomics-based biomarker approach should be further explored to confirm and validate preliminary findings and to evaluate its potential role in monitoring the therapeutic response.

An electronic nose in the discrimination of obese patients with and without obstructive sleep apnoea.

Exhaled breath contains thousands of volatile organic compounds (VOCs) in gaseous form, which may be used as markers of airway inflammation and lung disease. Electronic noses enable quick and real-time pattern analysis of VOC spectra. It has been shown that the exhaled breath of patients with obstructive sleep apnoea (OSA) differs from that of non-obese controls. We aimed to assess the influence of obesity in the composition of exhaled VOCs by comparing obese subjects with and without OSA. Moreover, we aimed to identify the discriminant VOCs in the two groups.19 obese patients with established OSA (OO; age 51.2 ± 6.8; body mass index (BMI) 34.3 ± 3.5), 14 obese controls without OSA (ONO; age 46.5 ± 7.6; BMI 33.5 ± 4.1) and 20 non-obese healthy controls (HC; age 41.1 ± 12.6; BMI 24.9 ± 3.8) participated in a cross-sectional study. Exhaled breath was collected by a previously described method and sampled by using an electronic nose (Cyranose 320) and by gas chromatography-mass spectrometry (GC-MS) analysis. Breathprints were analyzed by canonical discriminant analysis on principal component reduction. Cross-validation accuracy (CVA) was calculated. Breathprints from the HC group were separated from those of OO (CVA = 97.4%) and ONO (CVA = 94.1%). Breathprints from OO were moderately separated from those of ONO (CVA = 67.6%).The presence of OSA alters the exhaled VOC pattern in obese subjects. The incomplete separation of breathprints between OO and ONO may be due to the same underlying inflammation caused by obesity.