92 research outputs found

    A proposal of quantum-inspired machine learning for medical purposes: An application case

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    Learning tasks are implemented via mappings of the sampled data set, including both the classical and the quantum framework. Biomedical data characterizing complex diseases such as cancer typically require an algorithmic support for clinical decisions, especially for early stage tumors that typify breast cancer patients, which are still controllable in a therapeutic and surgical way. Our case study consists of the prediction during the pre-operative stage of lymph node metastasis in breast cancer patients resulting in a negative diagnosis after clinical and radiological exams. The classifier adopted to establish a baseline is characterized by the result invariance for the order permutation of the input features, and it exploits stratifications in the training procedure. The quantum one mimics support vector machine mapping in a high-dimensional feature space, yielded by encoding into qubits, while being characterized by complexity. Feature selection is exploited to study the performances associated with a low number of features, thus implemented in a feasible time. Wide variations in sensitivity and specificity are observed in the selected optimal classifiers during cross-validations for both classification system types, with an easier detection of negative or positive cases depending on the choice between the two training schemes. Clinical practice is still far from being reached, even if the flexible structure of quantum-inspired classifier circuits guarantees further developments to rule interactions among features: this preliminary study is solely intended to provide an overview of the particular tree tensor network scheme in a simplified version adopting just product states, as well as to introduce typical machine learning procedures consisting of feature selection and classifier performance evaluation

    Radiomic analysis in contrast-enhanced spectral mammography for predicting breast cancer histological outcome

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    Contrast-Enhanced Spectral Mammography (CESM) is a recently introduced mammographic method with characteristics particularly suitable for breast cancer radiomic analysis. This work aims to evaluate radiomic features for predicting histological outcome and two cancer molecular subtypes, namely Human Epidermal growth factor Receptor 2 (HER2)-positive and triple-negative. From 52 patients, 68 lesions were identified and confirmed on histological examination. Radiomic analysis was performed on regions of interest (ROIs) selected from both low-energy (LE) and ReCombined (RC) CESM images. Fourteen statistical features were extracted from each ROI. Expression of estrogen receptor (ER) was significantly correlated with variation coefficient and variation range calculated on both LE and RC images; progesterone receptor (PR) with skewness index calculated on LE images; and Ki67 with variation coefficient, variation range, entropy and relative smoothness indices calculated on RC images. HER2 was significantly associated with relative smoothness calculated on LE images, and grading tumor with variation coefficient, entropy and relative smoothness calculated on RC images. Encouraging results for differentiation between ER+/ER−, PR+/PR−, HER2+/HER2−, Ki67+/Ki67−, High-Grade/Low-Grade and TN/NTN were obtained. Specifically, the highest performances were obtained for discriminating HER2+/HER2− (90.87%), ER+/ER− (83.79%) and Ki67+/Ki67− (84.80%). Our results suggest an interesting role for radiomics in CESM to predict histological outcomes and particular tumors’ molecular subtype

    A roadmap towards breast cancer therapies supported by explainable artificial intelligence

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    In recent years personalized medicine reached an increasing importance, especially in the design of oncological therapies. In particular, the development of patients’ profiling strategies suggests the possibility of promising rewards. In this work, we present an explainable artificial intelligence (XAI) framework based on an adaptive dimensional reduction which (i) outlines the most important clinical features for oncological patients’ profiling and (ii), based on these features, determines the profile, i.e., the cluster a patient belongs to. For these purposes, we collected a cohort of 267 breast cancer patients. The adopted dimensional reduction method determines the relevant subspace where distances among patients are used by a hierarchical clustering procedure to identify the corresponding optimal categories. Our results demonstrate how the molecular subtype is the most important feature for clustering. Then, we assessed the robustness of current therapies and guidelines; our findings show a striking correspondence between available patients’ profiles determined in an unsupervised way and either molecular subtypes or therapies chosen according to guidelines, which guarantees the interpretability characterizing explainable approaches to machine learning techniques. Accordingly, our work suggests the possibility to design data-driven therapies to emphasize the differences observed among the patients

    Mycobacterium tuberculosis Immune Response in Patients With Immune-Mediated Inflammatory Disease

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    Subjects with immune-mediated inflammatory diseases (IMID), such as rheumatoid arthritis (RA), have an intrinsic higher probability to develop active-tuberculosis (TB) compared to the general population. The risk ranges from 2.0 to 8.9 in RA patients not receiving therapies. According to the WHO, the RA prevalence varies between 0.3% and 1% and is more common in women and in developed countries. Therefore, the identification and treatment of TB infection (TBI) in this fragile population is important to propose the TB preventive therapy. We aimed to study the M. tuberculosis (Mtb) specific T-cell response to find immune biomarkers of Mtb burden or Mtb clearance in patients with different TB status and different risk to develop active-TB disease. We enrolled TBI subjects as example of Mtb-containment, the active-TB as example of a replicating Mtb status, and the TBI-IMID as fragile population. To study the Mtb-specific response in a condition of possible Mtb sterilization, we longitudinally enrolled TBI subjects and active-TB patients before and after TB therapy. Peripheral blood mononuclear cells were stimulated overnight with Mtb peptides contained in TB1- and TB2-tubes of the Quantiferon-Plus kit. Then, we characterized by cytometry the Mtb-specific CD4 and CD8 T cells. In TBI-IMID, the TB therapy did not affect the ability of CD4 T cells to produce interferon-γ, tumor necrosis factor-α, and interleukin-2, their functional status, and their phenotype. The TB therapy determined a contraction of the triple functional CD4 T cells of the TBI subjects and active-TB patients. The CD45RA- CD27+ T cells stood out as a main subset of the Mtb-specific response in all groups. Before the TB-preventive therapy, the TBI subjects had higher proportion of Mtb-specific CD45RA-CD27+CD4+ T cells and the active-TB subjects had higher proportion of Mtb-specific CD45RA-CD27-CD4+ T cells compared to other groups. The TBI-IMID patients showed a phenotype similar to TBI, suggesting that the type of IMID and the IMID therapy did not affect the activation status of Mtb-specific CD4 T cells. Future studies on a larger and better-stratified TBI-IMID population will help to understand the change of the Mtb-specific immune response over time and to identify possible immune biomarkers of Mtb-containment or active replication

    A Gradient-Based Approach for Breast DCE-MRI Analysis

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    Breast cancer is the main cause of female malignancy worldwide. Effective early detection by imaging studies remains critical to decrease mortality rates, particularly in women at high risk for developing breast cancer. Breast Magnetic Resonance Imaging (MRI) is a common diagnostic tool in the management of breast diseases, especially for high-risk women. However, during this examination, both normal and abnormal breast tissues enhance after contrast material administration. Specifically, the normal breast tissue enhancement is known as background parenchymal enhancement: it may represent breast activity and depends on several factors, varying in degree and distribution in different patients as well as in the same patient over time. While a light degree of normal breast tissue enhancement generally causes no interpretative difficulties, a higher degree may cause difficulty to detect and classify breast lesions at Magnetic Resonance Imaging even for experienced radiologists. In this work, we intend to investigate the exploitation of some statistical measurements to automatically characterize the enhancement trend of the whole breast area in both normal and abnormal tissues independently from the presence of a background parenchymal enhancement thus to provide a diagnostic support tool for radiologists in the MRI analysis

    Clinical characteristics and outcomes of vaccinated patients hospitalised with SARS-CoV-2 breakthrough infection: Multi-IPV, a multicentre study in Northern Italy

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    Background: Despite the well-known efficacy of anti-COVID-19 vaccines in preventing morbidity and mortality, several vaccinated individuals are diagnosed with SARS-CoV-2 breakthrough infection, which might require hospitalisation. This multicentre, observational, and retrospective study aimed to investigate the clinical characteristics and outcomes of vaccinated vs. non -vaccinated patients, both hospitalised with SARS-CoV-2 infection in 3 major hospitals in Northern Italy. Methods: Data collection was retrospective, and paper and electronic medical records of adult patients with a diagnosed SARS-CoV-2 infection were pseudo-anonymised and analysed. Vaccinated and non -vaccinated individuals were manually paired, using a predetermined matching criterion (similar age, gender, and date of hospitalisation). Demographic, clinical, treatment, and outcome data were compared between groups differing by vaccination status using Pearson's Chi-square and Mann -Whitney tests. Moreover, multiple logistic regression analyses were performed to assess the impact of vaccination status on ICU admission or intra-hospital mortality. Results: Data from 360 patients were collected. Vaccinated patients presented with a higher prevalence of relevant comorbidities, like kidney replacement therapy or haematological malignancy, despite a milder clinical presentation at the first evaluation. Non -vaccinated patients required intensive care more often than their vaccinated counterparts (8.8% vs. 1.7%, p = 0.002). Contrariwise, no difference in intra-hospital mortality was observed between the two groups (19% vs. 20%, p = 0.853). These results were confirmed by multivariable logistic regressions, which showed that vaccination was significantly associated with decreased risk of ICU admission (aOR=0.172, 95%CI: 0.039-0.542, p = 0.007), but not of intra-hospital mortality (aOR=0.996, 95%CI: 0.582-1.703, p = 0.987). Conclusions: This study provides real -world data on vaccinated patients hospitalised with COVID-19 in Northern Italy. Our results suggest that COVID-19 vaccination has a protective role in individuals with higher risk profiles, especially regarding the need for ICU admission. These findings contribute to our understanding of SARS-CoV-2 infection outcomes among vaccinated individuals and emphasise the importance of vaccination in preventing severe disease, particularly in those countries with lower first -booster uptake rates

    Association of kidney disease measures with risk of renal function worsening in patients with type 1 diabetes

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    Background: Albuminuria has been classically considered a marker of kidney damage progression in diabetic patients and it is routinely assessed to monitor kidney function. However, the role of a mild GFR reduction on the development of stage 653 CKD has been less explored in type 1 diabetes mellitus (T1DM) patients. Aim of the present study was to evaluate the prognostic role of kidney disease measures, namely albuminuria and reduced GFR, on the development of stage 653 CKD in a large cohort of patients affected by T1DM. Methods: A total of 4284 patients affected by T1DM followed-up at 76 diabetes centers participating to the Italian Association of Clinical Diabetologists (Associazione Medici Diabetologi, AMD) initiative constitutes the study population. Urinary albumin excretion (ACR) and estimated GFR (eGFR) were retrieved and analyzed. The incidence of stage 653 CKD (eGFR < 60 mL/min/1.73 m2) or eGFR reduction > 30% from baseline was evaluated. Results: The mean estimated GFR was 98 \ub1 17 mL/min/1.73m2 and the proportion of patients with albuminuria was 15.3% (n = 654) at baseline. About 8% (n = 337) of patients developed one of the two renal endpoints during the 4-year follow-up period. Age, albuminuria (micro or macro) and baseline eGFR < 90 ml/min/m2 were independent risk factors for stage 653 CKD and renal function worsening. When compared to patients with eGFR > 90 ml/min/1.73m2 and normoalbuminuria, those with albuminuria at baseline had a 1.69 greater risk of reaching stage 3 CKD, while patients with mild eGFR reduction (i.e. eGFR between 90 and 60 mL/min/1.73 m2) show a 3.81 greater risk that rose to 8.24 for those patients with albuminuria and mild eGFR reduction at baseline. Conclusions: Albuminuria and eGFR reduction represent independent risk factors for incident stage 653 CKD in T1DM patients. The simultaneous occurrence of reduced eGFR and albuminuria have a synergistic effect on renal function worsening

    Farnesoid X Receptor as a homeostat for hepatic nutrient metabolism, proliferation and intestinal inflammation : Novel insights into mechanisms of regulation

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    Our body hosts several molecules that function as hormones to regulate metabolism in the liver. Bile acids (BAs) are molecules produced by the liver and stored in the gall bladder. After eating a meal, BAs are secreted in the intestine, where they help the digestion of fats and vitamins. Subsequently, most BAs are re-absorbed in the intestine and recycled to the liver, where they function as hormones to regulate hepatic metabolism. Meanwhile, glucose, triacylglycerols and amino acids are absorbed in the intestine and reach the liver. The fate of BAs and nutrients in the liver is tightly connected through the function of one protein, the Farnesoid X Receptor (FXR). As explained in Chapter 2, FXR acts as a ‘homeostat’ of liver metabolism, meaning a gatekeeper of metabolic homeostasis, since it senses environmental changes (fed state) and drives transcriptional programs that inhibit BA synthesis, and redistribute the energy substrates. In Chapter 3, we report a novel function of FXR as a metabolic regulator of amino acids. In mouse liver tissue and isolated liver cells, FXR activation resulted in upregulation of proteins involved in amino acid degradation, ureagenesis and glutamine synthesis. The impact of our findings is therefore substantial, as it might be possible to prevent the accumulation of toxic ammonium in patients with liver disease, by activating FXR in these patients. Metabolism relates closely to cell proliferation and inflammation, since you need to adapt your metabolic needs in order to grow or defend yourself from pathogens or injury. In the fed state, FXR activates FGF19 in the intestine. FGF19 is a hormone-like regulating hepatic metabolism. In Chapter 4, we show that FGF19 targets both metabolism and cell proliferation, thereby FGF19-based therapeutics may have tumorigenic risks. The combination of environmental factors (e.g. diet), dysregulation of immune response and damage in the intestinal epithelial barrier function, may trigger inflammatory bowel disease (IBD) in genetically predisposed individuals. FXR activation attenuates the severity of colitis in murine models of IBD. In Chapter 5, we show that FXR activation decreases the levels of anti-inflammatory cytokines in plasma, and counteracts the depletion in splenic dendritic cells (DC) and the increase in Tregs, both occurring as a consequence of colitis. We propose that FXR activation may induce DC retention in the spleen and affect the chemotactic environment in the colon. The central role of FXR in various aspects of metabolism and inflammation makes FXR an attractive drug target in cholestatic diseases, non-alcoholic steatohepatitis (NASH), IBD, and metabolic syndrome, but current compounds act as full agonists of FXR that may have undesired biological actions.Coregulatory proteins are eligible targets for pharmacological modulation of selective FXR functions.In Chapter 6, we identify HOXA9 and NSD1 as proteins which bind and regulate FXR in liver cells. In conclusion, active FXR protects against liver ammonium toxicity and fat accumulation and intestinal inflammation. Elucidation of FXR mechanistic actions is necessary the rational design of a new generation of FXR drugs, selectively activating or repressing specific FXR functions

    Impaired pregnenolone secretion after combined cyproterone acetate and ethynyl estradiol therapy in hirsute patients.

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    6 women affected by hirsutism, either of idiopathic origin or due to polycystic ovary syndrome, have been treated with cyproterone acetate and ethynyl estradiol in combined therapy using, respectively, 100 mg and 50 micrograms/day, from the 5th to the 25th day of the cycle. The adrenal function was assessed before treatment and at the end of the 4th month of therapy, evaluating the peripheral plasma concentrations of pregnenolone (delta 5P), progesterone, 17-OH-progesterone, dehydro-epiandrosterone sulfate, androstenedione, testosterone, and cortisol in basal conditions and after dexamethasone suppression and an adrenocorticotropic hormone (ACTH) stimulation test. A group of healthy, untreated females were examined in the early follicular phase, as controls, Before therapy, the hirsute patient showed testosterone and androstenedione plasma levels, which were significantly higher than in the controls, and a significant reduction in pregnenolone response to ACTH. After 4 months of therapy with cyproterone acetate plus ethynyl estradiol, a significant decrease was found in testosterone and androstenedione plasma levels, and pregnenolone basal plasma levels, dexamethasone suppressibility, and response to ACTH were also markedly reduced, showing a significant difference versus the same patients before therapy and versus the control group. The existence of an impairment in adrenal function after cyproterone acetate plus ethynyl estradiol therapy at the given dose seems to be evident only in the case of directly ACTH-dependent adrenal enzymatic activities responsible for cholesterol cleavage to pregnenolone
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