Genetic and environmental factors associated with the risk of cognitive decline and dementia

AD is the most common age related neurodegenerative disease in the industrialized world. Clinically AD is defined as a progressing decline of cognitive functions. Neuropathologically, AD is characterized by the aggregation of b-amyloid (Ab) peptide in the form of extracellular senile plaques, and hyperphosphorlylated tau protein in the form of intracellular neurofibrillary tangles. These neuropathological hallmarks are often accompanied by abundant microvascular damage and pronounced inflammation of the affected brain regions. In this thesis we investigated several aspects of AD focusing on the genetic aspect. We confirmed that Alpha 1 antichymotrypsin (ACT), an acute phase protein, was associated to AD subjects, being plasma levels higher in AD cases than controls. In addition, in a GWA study we demonstrated that two different gene, Clusterin and CR1 were strongly associated to AD. A single gene association not explain such a complex disease like AD. The goal should be to created a network of genetic, phenotypic and clinical data associated to AD. We used a new algorithm, the ANNs, aimed to map variables and search for connectivity among variables. We found specific variables associated to AD like cholesterol levels, the presence of variation in HMGCR enzyme and the age. Other factors such as the BMI, the amount of HDL and blood folate levels were also associated with AD. Pathogen infections, above all viral infections, have been previously associated to AD. The hypothesis suggests that virus and in particular herpes virus could enter the brain when an individual becomes older, perhaps because of a decline in the immune system. Our new hypothesis is that the presence of SNPs in our GWA gene study results in a genetic signature that might affect individual brain susceptibility to infection by herpes virus family during aging.

Risk factors for postoperative delirium in the elderly

Background: Delirium is defined as an acute disorder of attention and cognition. Delirium is common in hospitalized elderly patient and is associated with increased morbidity, length of stay and patient care costs. Although Delirium can develop at any time during hospitalization, it typically presents early in the post-operative period (Post-Operative Delirium, POD) in the surgery context. The molecular mechanism and possible genetics basis of POD onset are not known, as well as all the risk factors are not completely defined. Our hypothesis is that genetic risk factor involving the inflammatory response could have possible effects on the immunoneuroendocrine system. Moreover, our previous data (inflamm-aging) suggest that aging is associated with an increase of inflammatory status, favouring age-related diseases such as neurodegenerative diseases, frailty, depression among other. Some pro-inflammatory or anti-inflammatory cytokines, seem to play a crucial role in increasing the inflammatory status and in the communication and regulation of immunoneuroendocrine system. Objective: this study evaluated the incidence of POD in elderly patients undergoing general surgery, clinical/physical and psychological risk factors of POD insurgency and investigated inflammatory and genetic risk factors. Moreover, this study evaluated the consequence of POD in terms of institutionalization, development of permanent cognitive dysfunction or dementia and mortality Methods: patients aged over 65 admitted for surgery at the Urgency Unit of S.Orsola-Malpighi Hospital were eligible for this case–control study. Risk factors significantly associated with POD in univariate analysis were entered into multivariate analysis to establish those independently associated with POD. Preoperative plasma level of 9 inflammatory markers were measured in 42 control subjects and 43 subjects who developed POD. Functional polymorphisms of IL-1 α , IL-2, IL-6, IL-8, IL-10 and TNF-alpha cytokine genes were determined in 176 control subjects and 27 POD subjects. Results: A total of 351 patients were enrolled in the study. The incidence of POD was 13•2 %. Independent variables associated with POD were: age, co-morbidity, preoperative cognitive impairment, glucose abnormalities. Median length of hospital stay was 21 days for patients with POD versus 8 days for control patients (P < 0•001). The hospital mortality rate was 19 and 8•4 % respectively (P = 0•021) and mortality rate after 1 year was also higher in POD (P= 0.0001). The baseline of IL-6 concentration was higher in POD patients than patients without POD, whereas IL-2 was lower in POD patients compared to patients without POD. In a multivariate analysis only IL-6 remained associated with POD. Moreover IL-6, IL-8 and IL-2 are associated with co-morbidity, intra-hospital mortality, compromised functional status and emergency admission. No significant differences in genotype distribution were found between POD subjects and controls for any SNP analyzed in this study. Conclusion: In this study we found older age, comorbidity, cognitive impairment, glucose abnormalities and baseline of IL-6 as independent risk factors for the development of POD. IL-6 could be proposed as marker of a trait that is associated with an increased risk of delirium; i.e. raised premorbid IL-6 level predict for the development of delirium.

Cellular and Molecular Biomarkers for Risk Assessment of Colorectal cancer

The detection of Colorectal Cancer (CRC), at early stages, is one of the proven strategies resulting in a higher cure rate. In recent years, several studies have appeared identifying potential cancer markers in serum, plasma and stool in an attempt to improve actual screening procedures. Thus, the aim of the study was (1) Evaluate MN frequency, (2) Evaluate plasma ultrafiltrate capacity to induce MN formation, (3) Evaluate SEPT9 and NOTCH3 promoter methylation profile in peripheral blood lymphocytes from subjects resulted positive to fecal occult blood test and examined by colonoscopy. MN frequency was significantly higher in subjects with histological diagnosis of CRC and adenoma than control (p ≤ 0.001 and p ≤ 0.01, respectively). About, CF-MN analysis, a statistically significant difference was observed between CRC and control (p ≤ 0.05). On the other hand, SEPT9 and NOTCH3 promoter methylation status was significantly lower in CRC subjects than controls; additionally, NOTCH3 promoter methylation status was significantly lower in CRC subjects than adenoma subjects (p ≤ 0.01). The results obtained allow conclude that MN frequency varies according CRC pathologic status and, together with other variables, is a valid biomarker for adenoma and CRC risk. Additionally, the plasma of patients affected with CRC not only serve as a biomarker for oxidative stress but also as biomarker of genetic damage correlated with the carcinogenic process that verifies in colon-rectum. SEPT9 and NOTCH3 promoter methylation status, at peripheral blood level, varies according hystopathological changes observed in colon-rectum, suggesting that promoter methylation profile of these genes could be a reliable biomarker for CRC risk.

Risk analysis of tractor rollover in the normal operation in field

Tractor rollover represent a primary cause of death or serious injury in agriculture and despite the mandatory Roll-Over Protective Structures (ROPS), that reduced the number of injuries, tractor accidents are still of great concern. Because of their versatility and wide use many studies on safety are concerned with the stability of tractors, but they often prefer controlled tests or laboratory tests. The evaluation of tractors working in field, instead, is a very complex issue because the rollover could be influenced by the interaction among operator, tractor and environment. Recent studies are oriented towards the evaluation of the actual working conditions developing prototypes for driver assistance and data acquisition. Currently these devices are produced and sold by manufacturers. A warning device was assessed in this study with the aim to evaluate its performance and to collect data on different variables influencing the dynamics of tractors in field by monitoring continuously the working conditions of tractors operating at the experimental farm of the Bologna University. The device consists of accelerometers, gyroscope, GSM/GPRS, GPS for geo-referencing and a transceiver for the automatic recognition of tractor-connected equipment. A microprocessor processes data and provides information, through a dedicated algorithm requiring data on the geometry of the tested tractor, on the level of risk for the operator in terms of probable loss of stability and suggests corrective measures to reduce the potential instability of the tractor.

Dynamics of coastal aquifers: data-driven forecasting and risk analysis

This work is focused on the study of saltwater intrusion in coastal aquifers, and in particular on the realization of conceptual schemes to evaluate the risk associated with it. Saltwater intrusion depends on different natural and anthropic factors, both presenting a strong aleatory behaviour, that should be considered for an optimal management of the territory and water resources. Given the uncertainty of problem parameters, the risk associated with salinization needs to be cast in a probabilistic framework. On the basis of a widely adopted sharp interface formulation, key hydrogeological problem parameters are modeled as random variables, and global sensitivity analysis is used to determine their influence on the position of saltwater interface. The analyses presented in this work rely on an efficient model reduction technique, based on Polynomial Chaos Expansion, able to combine the best description of the model without great computational burden. When the assumptions of classical analytical models are not respected, and this occurs several times in the applications to real cases of study, as in the area analyzed in the present work, one can adopt data-driven techniques, based on the analysis of the data characterizing the system under study. It follows that a model can be defined on the basis of connections between the system state variables, with only a limited number of assumptions about the "physical" behaviour of the system.

AAGL 2021 classification system and risk of surgical complications in women submitted to surgery for endometriosis

Introduction: Recently, the American Association of Gynecologic Laparoscopists proposed a new classification and scoring system with the specific aim to assess surgical complexity. This study sought to assess if a higher AAGL score correlates with an increased risk of peri-operative complications in women submitted to surgery for endometriosis. Methods: This is a retrospective cohort study conducted in a third level referral center. We collected data from women with endometriosis submitted to complete surgical removal of endometriosis from January 2019 to December 2021. ENZIAN, r-ASRM classifications and AAGL total score was calculated for each patient. Population was divided in two groups according to the occurrence or not of at least one peri-operative complication. Our primary outcome was to evaluate the correlation between AAGL score and occurrence of complications. Results: During the study period we analyzed data from 282 eligible patients. Among them, 80 (28.4%) experienced peri-operative complications. No statistically significant difference was found between the two groups in terms of baseline characteristics, except for pre-operative hemoglobin (Hb), which was lower in patients with complications (p=0.001). Surgical variables associated with the occurrence of complications were recto-sigmoid surgery (p=0.003), ileocecal resection (0.034), and longer operative time (p=0.007). Furthermore, a higher ENZIAN B score (p=0.006), AAGL score (p=0.045) and stage (p=0.022) were found in the group of patients with complications. The multivariate analysis only confirmed the significant association between the occurrence of peri-operative complications and lower pre-operative Hb level (OR 0.74; 95% CI, 0.59 - 0.94; p=0.014), longer operative time (OR 1.00; 95% CI, 1.00 – 1.01; p=0.013), recto-sigmoid surgery - especially discoid resection (OR 8.73; 95% CI, 2.18 – 35; p=0.016) and ENZIAN B3 (OR 3.62; 95% CI, 1.46 – 8.99; p= 0.006). Conclusion: According to our findings, high AAGL scores or stages do not seem to increase the risk of peri-operative complications.

Developing a radiomic based machine learning model to identify patients with resected non-small-cell lung cancer at high risk of relapse

Background There is a wide variation of recurrence risk of Non-small-cell lung cancer (NSCLC) within the same Tumor Node Metastasis (TNM) stage, suggesting that other parameters are involved in determining this probability. Radiomics allows extraction of quantitative information from images that can be used for clinical purposes. The primary objective of this study is to develop a radiomic prognostic model that predicts a 3 year disease free-survival (DFS) of resected Early Stage (ES) NSCLC patients. Material and Methods 56 pre-surgery non contrast Computed Tomography (CT) scans were retrieved from the PACS of our institution and anonymized. Then they were automatically segmented with an open access deep learning pipeline and reviewed by an experienced radiologist to obtain 3D masks of the NSCLC. Images and masks underwent to resampling normalization and discretization. From the masks hundreds Radiomic Features (RF) were extracted using Py-Radiomics. Hence, RF were reduced to select the most representative features. The remaining RF were used in combination with Clinical parameters to build a DFS prediction model using Leave-one-out cross-validation (LOOCV) with Random Forest. Results and Conclusion A poor agreement between the radiologist and the automatic segmentation algorithm (DICE score of 0.37) was found. Therefore, another experienced radiologist manually segmented the lesions and only stable and reproducible RF were kept. 50 RF demonstrated a high correlation with the DFS but only one was confirmed when clinicopathological covariates were added: Busyness a Neighbouring Gray Tone Difference Matrix (HR 9.610). 16 clinical variables (which comprised TNM) were used to build the LOOCV model demonstrating a higher Area Under the Curve (AUC) when RF were included in the analysis (0.67 vs 0.60) but the difference was not statistically significant (p=0,5147).