Adoption of AI in Oncological Imaging: Ethical, Regulatory, and Medical-Legal Challenges

Artificial Intelligence (AI) algorithms have shown great promise in oncological imaging, outperforming or matching radiologists in retrospective studies, signifying their potential for advanced screening capabilities. These AI tools offer valuable support to radiologists, assisting them in critical tasks such as prioritizing reporting, early cancer detection, and precise measurements, thereby bolstering clinical decision-making. With the healthcare landscape witnessing a surge in imaging requests and a decline in available radiologists, the integration of AI has become increasingly appealing. By streamlining workflow efficiency and enhancing patient care, AI presents a transformative solution to the challenges faced by oncological imaging practices. Nevertheless, successful AI integration necessitates navigating various ethical, regulatory, and medical-legal challenges. This review endeavors to provide a comprehensive overview of these obstacles, aiming to foster a responsible and effective implementation of AI in oncological imaging.

Artificial Intelligence in Lung Cancer Imaging: From Data to Therapy

Lung cancer remains a global health challenge, leading to substantial morbidity and mortality. While prevention and early detection strategies have improved, the need for precise diagnosis, prognosis, and treatment remains crucial. In this comprehensive review article, we explore the role of artificial intelligence (AI) in reshaping the management of lung cancer. AI may have different potential applications in lung cancer characterization and outcome prediction. Manual segmentation is a time-consuming task, with high inter-observer variability, that can be replaced by AI-based approaches, including deep learning models such as U-Net, BCDU-Net, and others, to quantify lung nodules and cancers objectively and to extract radiomics features for the characterization of the tissue. AI models have also demonstrated their ability to predict treatment responses, such as immunotherapy and targeted therapy, by integrating radiomic features with clinical data. Additionally, AI-based prognostic models have been developed to identify patients at higher risk and personalize treatment strategies. In conclusion, this review article provides a comprehensive overview of the current state of AI applications in lung cancer management, spanning from segmentation and virtual biopsy to outcome prediction. The evolving role of AI in improving the precision and effectiveness of lung cancer diagnosis and treatment underscores its potential to significantly impact clinical practice and patient outcomes.

Radiomics and Artificial Intelligence in Renal Lesion Assessment

Radiomics, the extraction and analysis of quantitative features from medical images, has emerged as a promising field in radiology with the potential to revolutionize the diagnosis and management of renal lesions. This comprehensive review explores the radiomics workflow, including image acquisition, feature extraction, selection, and classification, and highlights its application in differentiating between benign and malignant renal lesions. The integration of radiomics with artificial intelligence (AI) techniques, such as machine learning and deep learning, can help patients' management and allow the planning of the appropriate treatments. AI models have shown remarkable accuracy in predicting tumor aggressiveness, treatment response, and patient outcomes. This review provides insights into the current state of radiomics and AI in renal lesion assessment and outlines future directions for research in this rapidly evolving field.

Biosorption of rare earth elements from luminophores by G. sulphuraria (Cyanidiophytina, Rhodophyta)

Lanthanides are indispensable constituents of modern technologies and are often challenging to acquire from natural resources. The demand for REEs is so high that there is a clear need to develop efficient and eco-friendly recycling methods. In the present study, freeze-dried biomass of the polyextremophile Galdieria sulphuraria was employed to recover REEs from spent fluorescent lamps (FL) luminophores by pretreating the freeze-dried biomass with an acid solution to favour ion exchange and enhance the binding sites on the cell surface available for the metal ions. Lanthanides were extracted from the luminophores using sulfuric acid solutions according to standardised procedures, and the effect of biosorbent dosage (0.5-5 mg/ml) and biosorption time (5-60 min) were evaluated. The content of individual REEs in the luminophores and the resulting algal biomass were determined using inductively coupled plasma mass spectrometry (ICP-MS). The most abundant REE in the luminophores was yttrium (287.42 mg/g dm, 91.60% of all REEs), followed by europium (20.98 mg/g, 6.69%); cerium, gadolinium, terbium and lanthanum was in trace. The best biosorption performances were achieved after 5 min and at the lowest biosorbent dosage (0.5 mg/mL). The highest total metal amount corresponded to 41.61 mg/g dried mass, and yttrium was the most adsorbed metal (34.59 mg/g dm, 82.88%), followed by cerium (4.01 mg/g); all other metals were less than 2 mg/g. The rapidity of the biosorption process and the low biosorbent dosage required confirmed this microalga as a promising material for creating an eco-sustainable protocol for recycling REEs.

Amplifying the Effects of Contrast Agents on Magnetic Resonance Images Using a Deep Learning Method Trained on Synthetic Data

OBJECTIVES

Artificial intelligence (AI) methods can be applied to enhance contrast in diagnostic images beyond that attainable with the standard doses of contrast agents (CAs) normally used in the clinic, thus potentially increasing diagnostic power and sensitivity. Deep learning-based AI relies on training data sets, which should be sufficiently large and diverse to effectively adjust network parameters, avoid biases, and enable generalization of the outcome. However, large sets of diagnostic images acquired at doses of CA outside the standard-of-care are not commonly available. Here, we propose a method to generate synthetic data sets to train an "AI agent" designed to amplify the effects of CAs in magnetic resonance (MR) images. The method was fine-tuned and validated in a preclinical study in a murine model of brain glioma, and extended to a large, retrospective clinical human data set.

MATERIALS AND METHODS

A physical model was applied to simulate different levels of MR contrast from a gadolinium-based CA. The simulated data were used to train a neural network that predicts image contrast at higher doses. A preclinical MR study at multiple CA doses in a rat model of glioma was performed to tune model parameters and to assess fidelity of the virtual contrast images against ground-truth MR and histological data. Two different scanners (3 T and 7 T, respectively) were used to assess the effects of field strength. The approach was then applied to a retrospective clinical study comprising 1990 examinations in patients affected by a variety of brain diseases, including glioma, multiple sclerosis, and metastatic cancer. Images were evaluated in terms of contrast-to-noise ratio and lesion-to-brain ratio, and qualitative scores.

RESULTS

In the preclinical study, virtual double-dose images showed high degrees of similarity to experimental double-dose images for both peak signal-to-noise ratio and structural similarity index (29.49 dB and 0.914 dB at 7 T, respectively, and 31.32 dB and 0.942 dB at 3 T) and significant improvement over standard contrast dose (ie, 0.1 mmol Gd/kg) images at both field strengths. In the clinical study, contrast-to-noise ratio and lesion-to-brain ratio increased by an average 155% and 34% in virtual contrast images compared with standard-dose images. Blind scoring of AI-enhanced images by 2 neuroradiologists showed significantly better sensitivity to small brain lesions compared with standard-dose images (4.46/5 vs 3.51/5).

CONCLUSIONS

Synthetic data generated by a physical model of contrast enhancement provided effective training for a deep learning model for contrast amplification. Contrast above that attainable at standard doses of gadolinium-based CA can be generated through this approach, with significant advantages in the detection of small low-enhancing brain lesions.

The role of the foam formulation in improving psoriasis treatment acceptability: a real-life experience and a literature review

BACKGROUND

Topical therapies represent the first-line treatment for mild-to-moderate psoriasis. Among various topical options, the fixed-dose combination of calcipotriene (Cal) and betamethasone dipropionate (BD) foam (Enstilar®, LEO Pharma, Ballerup, Denmark) showed superior efficacy to Cal and BD monotherapy and ointment and gel formulations. In addition, the Cal/BD foam is the only topical treatment allowed for either reactive treatment of relapse or twice-weekly maintenance use. Since treatment acceptability is crucial to optimize adherence, this paper presents a case series from a multicenter experience using the Cal/BD foam, to further characterize the use of this therapeutic approach. In addition, a narrative review of studies evaluating the acceptability of the Cal/BD foam, even compared with other formulations, is provided.

CASE SERIES

The case series involved adult patients with mild-to-moderate psoriasis treated with the Cal/BD foam from October 2021 to June 2022. A clinical and dermoscopic evaluation of plaques was provided for all patients. Data from the clinical practice report complete clinical resolution of plaques in most patients after 4 weeks of active treatment with the Cal/BD foam, and the dermoscopic clearance after a maximum of 8 weeks. Full adherence to treatment was also reported. Literature evidence suggests that the Cal/BD foam is easy to apply and presents high cosmetic acceptance, rapid onset of action, high efficacy, optimal safety, and a high patient preference. The high satisfaction obtained with Cal/BD foam suggests that this formulation is better accepted than others.

CONCLUSIONS

The Cal/BD foam represents a valuable approach for managing mild-to-moderate psoriasis, both in short and long-term treatment.

How do patients perceive the AI-radiologists interaction? Results of a survey on 2119 responders

PURPOSE

In this study we investigate how patients perceive the interaction between artificial intelligence (AI) and radiologists by designing a survey.

METHOD

We created a survey focused on the application of Artificial Intelligence in radiology which consisted of 20 questions distributed in three sections:Only completed questionnaires were considered for analysis.

RESULTS

2119 subjects completed the survey. Among them, 1216 respondents were over 60 years old, showing interest in AI even though they were not digital natives. Although >45% of the respondents reported a high level of education, only 3% said they were AI experts. 87% of respondents favored using AI to support diagnosis but would like to be informed. Only 10% would consult another specialist if their doctor used AI support. Most respondents (76%) said they would not feel comfortable if the diagnosis was made by the AI alone, highlighting the importance of the physician's role in the emotional management of the patient. Finally, 36% of respondents were willing to discuss the topic further in a focus group.

CONCLUSION

Patients' perception of the use of AI in radiology was positive, although still strictly linked to the supervision of the radiologist. Respondents showed interest and willingness to learn more about AI in the medical field, confirming how patients' confidence in AI technology and its acceptance is central to its widespread use in clinical practice.

Chest X-ray in Emergency Radiology: What Artificial Intelligence Applications Are Available?

Due to its widespread availability, low cost, feasibility at the patient's bedside and accessibility even in low-resource settings, chest X-ray is one of the most requested examinations in radiology departments. Whilst it provides essential information on thoracic pathology, it can be difficult to interpret and is prone to diagnostic errors, particularly in the emergency setting. The increasing availability of large chest X-ray datasets has allowed the development of reliable Artificial Intelligence (AI) tools to help radiologists in everyday clinical practice. AI integration into the diagnostic workflow would benefit patients, radiologists, and healthcare systems in terms of improved and standardized reporting accuracy, quicker diagnosis, more efficient management, and appropriateness of the therapy. This review article aims to provide an overview of the applications of AI for chest X-rays in the emergency setting, emphasizing the detection and evaluation of pneumothorax, pneumonia, heart failure, and pleural effusion.

Artificial Intelligence in Emergency Radiology: Where Are We Going?

Emergency Radiology is a unique branch of imaging, as rapidity in the diagnosis and management of different pathologies is essential to saving patients' lives. Artificial Intelligence (AI) has many potential applications in emergency radiology: firstly, image acquisition can be facilitated by reducing acquisition times through automatic positioning and minimizing artifacts with AI-based reconstruction systems to optimize image quality, even in critical patients; secondly, it enables an efficient workflow (AI algorithms integrated with RIS-PACS workflow), by analyzing the characteristics and images of patients, detecting high-priority examinations and patients with emergent critical findings. Different machine and deep learning algorithms have been trained for the automated detection of different types of emergency disorders (e.g., intracranial hemorrhage, bone fractures, pneumonia), to help radiologists to detect relevant findings. AI-based smart reporting, summarizing patients' clinical data, and analyzing the grading of the imaging abnormalities, can provide an objective indicator of the disease's severity, resulting in quick and optimized treatment planning. In this review, we provide an overview of the different AI tools available in emergency radiology, to keep radiologists up to date on the current technological evolution in this field.

Development and Validation of an AI-driven Mammographic Breast Density Classification Tool Based on Radiologist Consensus

Mammographic breast density (BD) is commonly visually assessed using the Breast Imaging Reporting and Data System (BI-RADS) four-category scale. To overcome inter- and intraobserver variability of visual assessment, the authors retrospectively developed and externally validated a software for BD classification based on convolutional neural networks from mammograms obtained between 2017 and 2020. The tool was trained using the majority BD category determined by seven board-certified radiologists who independently visually assessed 760 mediolateral oblique (MLO) images in 380 women (mean age, 57 years ± 6 [SD]) from center 1; this process mimicked training from a consensus of several human readers. External validation of the model was performed by the three radiologists whose BD assessment was closest to the majority (consensus) of the initial seven on a dataset of 384 MLO images in 197 women (mean age, 56 years ± 13) obtained from center 2. The model achieved an accuracy of 89.3% in distinguishing BI-RADS a or b (nondense breasts) versus c or d (dense breasts) categories, with an agreement of 90.4% (178 of 197 mammograms) and a reliability of 0.807 (Cohen κ) compared with the mode of the three readers. This study demonstrates accuracy and reliability of a fully automated software for BD classification. Keywords: Mammography, Breast, Convolutional Neural Network (CNN), Deep Learning Algorithms, Machine Learning Algorithms Supplemental material is available for this article. © RSNA, 2022.

ROLE OF CARDIOPULMONARY EXERCISE TEST IN THE PREDICTION OF HEMODYNAMIC IMPAIRMENT IN PATIENTS WITH PULMONARY ARTERIAL HYPERTENSION

Periodic repetition of right heart catheterization (RHC) in pulmonary arterial hypertension (PAH) can be challenging. We evaluated the correlation between RHC and cardiopulmonary exercise test (CPET) aiming at CPET use as a potential noninvasive tool for hemodynamic burden evaluation. One hundred and forty‐four retrospective PAH patients who had performed CPET and RHC within 2 months were enrolled. The following analyses were performed: (a) CPET parameters in hemodynamic variables tertiles; (b) position of hemodynamic parameters in the peak end‐tidal carbon dioxide pressure (P_ETCO₂) versus ventilation/carbon dioxide output (VE/VCO₂) slope scatterplot, which is a specific hallmark of exercise respiratory abnormalities in PAH; (c) association between CPET and a hemodynamic burden score developed including mean pulmonary arterial pressure (mPAP), pulmonary vascular resistance (PVR), cardiac index, and right atrial pressure. VE/VCO₂ slope and peak P_ETCO₂ significantly varied in mPAP and PVR tertiles, while peak oxygen uptake (peak VO₂) and O₂ pulse varied in the tertiles of all hemodynamic parameters. P_ETCO₂ versus VE/VCO₂ slope showed a strong hyperbolic relationship (R² = 0.7627). Patients with peak P_ETCO₂ > median (26 mmHg) and VE/VCO₂ slope < median (44) presented lower mPAP and PVR (p < 0.005) than patients with peak P_ETCO₂ < median and VE/VCO₂ slope > median. Multivariate analysis individuated peak VO₂ (p = 0.0158) and peak P_ETCO₂ (p = 0.0089) as hemodynamic score independent predictors; the formula 11.584 − 0.0925 × peak VO₂ − 0.0811 × peak P_ETCO₂ best predicts the hemodynamic score value from CPET data. A significant correlation was found between estimated and calculated scores (p < 0.0001), with a precise match for patients with mild‐to‐moderate hemodynamic burden (76% of cases). The results of the present study suggest that CPET could allow to estimate the hemodynamic burden in PAH patients.

Bone marrow mesenchymal stem cells offer an immune-privileged niche to Cutibacterium acnes in case of implant-associated osteomyelitis

Considered as some of the most devastating complications, Cutibacterium acnes (C. acnes)-related osteomyelitis are among the hardest infections to diagnose and treat. Mesenchymal stem cells (MSCs) secrete number of immunomodulatory and antimicrobial soluble factors, making them an attractive treatment for bacterial infection. In this study, we examined MSCs/C. acnes interaction and analyzed the subsequent MSCs and bacteria's behaviors. Human bone marrow-derived MSCs were infected by C. acnes clinical strain harvested from non-infected bone site. Following 3 h of interaction, around 4% of bacteria were found in the intracellular compartment. Infected MSCs increased the secretion of prostaglandin E2 and indolamine 2,3 dioxygenase immunomodulatory mediators. Viable intracellular bacteria analyzed by infrared spectroscopy and atomic force microscopy revealed deep modifications in the wall features. In comparison with unchallenged bacteria, the viable intracellular bacteria showed (i) an increase in biofilm formation on orthopaedical-based materials, (ii) an increase in the invasiveness of osteoblasts and (iii) persistence in macrophage, suggesting the acquisition of virulence factors. Overall, these results showed a direct impact of C. acnes on bone marrow-derived MSCs, suggesting that blocking the C. acnes/MSCs interactions may represent an important new approach to manage chronic osteomyelitis infections. STATEMENT OF SIGNIFICANCE: The interaction of bone commensal C. acnes with bone marrow mesenchymal stem cells induces modifications in C. acnes wall characteristics. These bacteria increased (i) the biofilm formation on orthopaedical-based materials, (ii) the invasiveness of bone forming cells and (iii) the resistance to macrophage clearance through the modification of the wall nano-features and/or the increase in catalase production.

AIforCOVID: Predicting the clinical outcomes in patients with COVID-19 applying AI to chest-X-rays. An Italian multicentre study

Recent epidemiological data report that worldwide more than 53 million people have been infected by SARS-CoV-2, resulting in 1.3 million deaths. The disease has been spreading very rapidly and few months after the identification of the first infected, shortage of hospital resources quickly became a problem. In this work we investigate whether artificial intelligence working with chest X-ray (CXR) scans and clinical data can be used as a possible tool for the early identification of patients at risk of severe outcome, like intensive care or death. Indeed, further to induce lower radiation dose than computed tomography (CT), CXR is a simpler and faster radiological technique, being also more widespread. In this respect, we present three approaches that use features extracted from CXR images, either handcrafted or automatically learnt by convolutional neuronal networks, which are then integrated with the clinical data. As a further contribution, this work introduces a repository that collects data from 820 patients enrolled in six Italian hospitals in spring 2020 during the first COVID-19 emergency. The dataset includes CXR images, several clinical attributes and clinical outcomes. Exhaustive evaluation shows promising performance both in 10-fold and leave-one-centre-out cross-validation, suggesting that clinical data and images have the potential to provide useful information for the management of patients and hospital resources.

Prevalence of interstitial pneumonia suggestive of COVID-19 at 18F-FDG PET/CT in oncological asymptomatic patients in a high prevalence country during pandemic period: a national multi-centric retrospective study

PURPOSE

To assess the presence and pattern of incidental interstitial lung alterations suspicious of COVID-19 on fluorine-18-fluorodeoxyglucose positron emission tomography (PET)/computed tomography (CT) ([18F]FDG PET/CT) in asymptomatic oncological patients during the period of active COVID-19 in a country with high prevalence of the virus.

METHODS

This is a multi-center retrospective observational study involving 59 Italian centers. We retrospectively reviewed the prevalence of interstitial pneumonia detected during the COVID period (between March 16 and 27, 2020) and compared to a pre-COVID period (January-February 2020) and a control time (in 2019). The diagnosis of interstitial pneumonia was done considering lung alterations of CT of PET.

RESULTS

Overall, [18F]FDG PET/CT was performed on 4008 patients in the COVID period, 19,267 in the pre-COVID period, and 5513 in the control period. The rate of interstitial pneumonia suspicious for COVID-19 was significantly higher during the COVID period (7.1%) compared with that found in the pre-COVID (5.35%) and control periods (5.15%) (p < 0.001). Instead, no significant difference among pre-COVID and control periods was present. The prevalence of interstitial pneumonia detected at PET/CT was directly associated with geographic virus diffusion, with the higher rate in Northern Italy. Among 284 interstitial pneumonia detected during COVID period, 169 (59%) were FDG-avid (average SUVmax of 4.1).

CONCLUSIONS

A significant increase of interstitial pneumonia incidentally detected with [18F]FDG PET/CT has been demonstrated during the COVID-19 pandemic. A majority of interstitial pneumonia were FDG-avid. Our results underlined the importance of paying attention to incidental CT findings of pneumonia detected at PET/CT, and these reports might help to recognize early COVID-19 cases guiding the subsequent management.

The allosteric protein interactions in the proton-motive function of mammalian redox enzymes of the respiratory chain

Insight into mammalian respiratory complexes defines the role of allosteric protein interactions in their proton-motive activity. In cytochrome c oxidase (CxIV) conformational change of subunit I, caused by O₂ binding to heme a₃²⁺-Cu_B⁺ and reduction, and stereochemical transitions coupled to oxidation/reduction of heme a and Cu_A, combined with electrostatic effects, determine the proton pumping activity. In ubiquinone-cytochrome c oxidoreductase (CxIII) conformational movement of Fe-S protein between cytochromes b and c₁ is the key element of the proton-motive activity. In NADH-ubiquinone oxidoreductase (CxI) ubiquinone binding and reduction result in conformational changes of subunits in the quinone reaction structure which initiate proton pumping.

Comparison of Transfer Learning and Conventional Machine Learning Applied to Structural Brain MRI for the Early Diagnosis and Prognosis of Alzheimer's Disease

Alzheimer's Disease (AD) is the most common neurodegenerative disease, with 10% prevalence in the elder population. Conventional Machine Learning (ML) was proven effective in supporting the diagnosis of AD, while very few studies investigated the performance of deep learning and transfer learning in this complex task. In this paper, we evaluated the potential of ensemble transfer-learning techniques, pretrained on generic images and then transferred to structural brain MRI, for the early diagnosis and prognosis of AD, with respect to a fusion of conventional-ML approaches based on Support Vector Machine directly applied to structural brain MRI. Specifically, more than 600 subjects were obtained from the ADNI repository, including AD, Mild Cognitive Impaired converting to AD (MCIc), Mild Cognitive Impaired not converting to AD (MCInc), and cognitively-normal (CN) subjects. We used T1-weighted cerebral-MRI studies to train: (1) an ensemble of five transfer-learning architectures pretrained on generic images; (2) a 3D Convolutional Neutral Network (CNN) trained from scratch on MRI volumes; and (3) a fusion of two conventional-ML classifiers derived from different feature extraction/selection techniques coupled to SVM. The AD-vs-CN, MCIc-vs-CN, MCIc-vs-MCInc comparisons were investigated. The ensemble transfer-learning approach was able to effectively discriminate AD from CN with 90.2% AUC, MCIc from CN with 83.2% AUC, and MCIc from MCInc with 70.6% AUC, showing comparable or slightly lower results with the fusion of conventional-ML systems (AD from CN with 93.1% AUC, MCIc from CN with 89.6% AUC, and MCIc from MCInc with AUC in the range of 69.1-73.3%). The deep-learning network trained from scratch obtained lower performance than either the fusion of conventional-ML systems and the ensemble transfer-learning, due to the limited sample of images used for training. These results open new prospective on the use of transfer learning combined with neuroimages for the automatic early diagnosis and prognosis of AD, even if pretrained on generic images.

Determinants of pulmonary vascular resistance reduction with upfront oral therapy in idiopathic pulmonary arterial hypertension: relevance in risk assessment

Background

In pulmonary arterial hypertension (PAH) upfront oral therapy represents the standard of care for naive patients at low and intermediate risk. However little is known about associated changes in risk assessment and prediction of low risk status achievement.

Purpose

To evaluate determinants of PVR reduction in patients treated with upfront oral therapy and to create a score to predict PVR reduction after upfront oral treatment and compared its additive value on top of the European and REVEAL scoring system in predicting treatment response.

Methods

One-hundred-eighty-one consecutive naive PAH patients treated with upfront therapy at 11 italian centers were retrospectively evaluated. Evaluation included clinical, hemodynamic and simple echocardiographic parameters, together with European and REVEAL 2.0 risk scores.

Results

At the time of diagnosis, the majority of the patients was idiopathic PAH (80.6%), female (66.3%), at intermediate risk, 71.8% and 55.2%, respectively, according to the European (average method) and the REVEAL 2.0 risk scores. Ambrisentan-Tadalafil was the most frequent combination used (62%). The median PVR reduction obtained after 180 days (IQR 79–394) was −40.4% (IQR −25.8; −45.3).

Age ≥60 years, male-sex, baseline mPAP 48 mmHg associated with low CI (&lt;2.5 l/min/m2), and RV/LV ratio &gt;1 associated with low TAPSE (&lt;18 mm) emerged as independent predictors of poor PVR reduction, defined as the lower tertile of PVR changes (−25.8%). A treatment response score was created deriving weighted integers from the beta coefficient.

At second evaluation 78 (43.1%) patients achieved or remained at European-derived low risk status, while 63 (34.8%) considering the REVEAL 2.0 score.

Multivariate analysis for the prediction of treatment failure, defined as the absence of low-risk status at follow-up, demonstrated the incremental prognostic power of the models incorporating the treatment response score (≥3) on top of the European and REVEAL 2.0 scores, improving risk discrimination by 63.2% (IDI index 0.056) and 36.8% (IDI index 0.080), respectively.

Conclusions

A significant proportion of PAH patients treated with upfront oral combination are not able to achieve a low-risk status. The treatment response score helps clinicians in predicting treatment failure at the time of diagnosis.

Funding Acknowledgement

Type of funding source: None

Interaction of Cutibacterium acnes with human bone marrow derived mesenchymal stem cells: a step toward understanding bone implant- associated infection development

Crosstalk between mesenchymal stem cells (MSCs) and bacteria plays an important role in regulating the regenerative capacities of MSCs, fighting infections, modulating immune responses and maintaining tissue homeostasis. Commensal Cutibacterium acnes (C. acnes) bacterium becomes an opportunistic pathogen causing implant-associated infections. Herein, we examined MSCs/C. acnes interaction and analysed the subsequent bacteria and MSCs behaviours following infection. Human bone marrow derived MSCs were infected by two clinical and one laboratory C. acnes strains. Following 3h of interaction, all bacterial strains were able to invade MSCs. Viable intracellular bacteria acquired virulence factors by increasing biofilm formation and/or by affecting macrophage phagocytosis. Although the direct and indirect (through neutrophil stimulation) antibacterial effects of the MSCs secretome were not enhanced following C. acnes infection, ELISA analysis revealed that C. acnes clinical strains are able to license MSCs to become immunosuppressive cell-like by increasing the secretion of IL-6, IL-8, PGE-2, VEGF, TGF-β and HGF. Overall, these results showed a direct impact of C. acnes on bone marrow derived MSCs, providing new insights into the development of C. acnes during implant-associated infections. STATEMENT OF SIGNIFICANCE: The originality of this work relies on the study of relationship between human bone marrow derived mesenchymal stem cells (MSCs) phenotype and C. acnes clinical strains virulence following cell infection. Our major results showed that C. acnes are able to invade MSCs, inducing a transition of commensal to an opportunistic pathogen behaviour. Although the direct and indirect antibacterial effects were not enhanced following C. acnes infection, secretome analysis revealed that C. acnes clinical strains were able to license MSCs to become immunosuppressive and anti-fibrotic cell-like. These results showed a direct impact of C. acnes on bone marrow derived MSCs, providing new insights into the development of C. acnes during associated implant infections.

Mechanisms of checkpoint inhibition-induced adverse events

Immune checkpoint inhibition has revolutionized the treatment of several solid cancers, most notably melanoma and non-small-cell lung cancer (NSCLC). Drugs targeting cytotoxic T lymphocyte antigen (CTLA)-4 and programmed cell death 1 (PD-1) have made their way into routine clinical use; however, this has not been without difficulties. Stimulation of the immune system to target cancer has been found to result in a reduction of self-tolerance, leading to the development of adverse effects that resemble autoimmunity. These adverse effects are erratic in their onset and severity and can theoretically affect any organ type. Several mechanisms for immune-related toxicity have been investigated over recent years; however, no consensus on the cause or prediction of toxicity has been reached. This review seeks to examine reported evidence for possible mechanisms of toxicity, methods for prediction of those at risk and a discussion of future prospects within the field.

A machine learning approach for differentiating malignant from benign enhancing foci on breast MRI

BACKGROUND

Differentiate malignant from benign enhancing foci on breast magnetic resonance imaging (MRI) through radiomic signature.

METHODS

Forty-five enhancing foci in 45 patients were included in this retrospective study, with needle biopsy or imaging follow-up serving as a reference standard. There were 12 malignant and 33 benign lesions. Eight benign lesions confirmed by over 5-year negative follow-up and 15 malignant histopathologically confirmed lesions were added to the dataset to provide reference cases to the machine learning analysis. All MRI examinations were performed with a 1.5-T scanner. One three-dimensional T1-weighted unenhanced sequence was acquired, followed by four dynamic sequences after intravenous injection of 0.1 mmol/kg of gadobenate dimeglumine. Enhancing foci were segmented by an expert breast radiologist, over 200 radiomic features were extracted, and an evolutionary machine learning method ("training with input selection and testing") was applied. For each classifier, sensitivity, specificity and accuracy were calculated as point estimates and 95% confidence intervals (CIs).

RESULTS

A k-nearest neighbour classifier based on 35 selected features was identified as the best performing machine learning approach. Considering both the 45 enhancing foci and the 23 additional cases, this classifier showed a sensitivity of 27/27 (100%, 95% CI 87-100%), a specificity of 37/41 (90%, 95% CI 77-97%), and an accuracy of 64/68 (94%, 95% CI 86-98%).

CONCLUSION

This preliminary study showed the feasibility of a radiomic approach for the characterisation of enhancing foci on breast MRI.

Decreased amount of vimentin N-terminal truncated proteolytic products in parkin-mutant skin fibroblasts

Vimentin, a member of cytoskeleton intermediate filaments proteins, plays a critical role in cell structure and dynamics. The present proteomic study reveals reduced amount of six different lengths, N-terminal truncated proteolytic products of vimentin, in the primary skin fibroblasts from two unrelated PD patients, as compared to control fibroblasts. The decreased amount of N-terminal truncated forms of vimentin in parkin-mutant fibroblasts, could contribute to impairment of cellular function, potentially contributing to the pathogenesis of Parkinson disease.

Allosteric Cooperativity in Proton Energy Conversion in A1-Type Cytochrome c Oxidase

Cytochrome c oxidase (CcO), the Cu_A, heme a, heme a₃, Cu_B enzyme of respiratory chain, converts the free energy released by aerobic cytochrome c oxidation into a membrane electrochemical proton gradient (ΔμH⁺). ΔμH⁺ derives from the membrane anisotropic arrangement of dioxygen reduction to two water molecules and transmembrane proton pumping from a negative (N) space to a positive (P) space separated by the membrane. Spectroscopic, potentiometric, and X-ray crystallographic analyses characterize allosteric cooperativity of dioxygen binding and reduction with protonmotive conformational states of CcO. These studies show that allosteric cooperativity stabilizes the favorable conformational state for conversion of redox energy into a transmembrane ΔμH⁺.

4972Upfront triple combination therapy with ambrisentan, tadalafil and subcutaneous treprostinil in incident patients with severe pulmonary arterial hypertension

Aim

Current treatments strategies for high-risk patients with pulmonary arterial hypertension (PAH) are based on the use of parenteral prostanoids. The evidence to support triple upfront combination therapy remains largely based on expert consensus or small studies. Aim of this study was to evaluate the efficacy and safety of an upfront triple combination therapy with ambrisentan, tadalafil and subcutaneous (sc) treprostinil in patients with severe PAH.

Methods

This is a multi-center retrospective analysis of patients with newly diagnosed severe PAH treated with upfront triple combination therapy with ambrisentan, tadalafil and sc treprostinil between 2014 and 2018. Clinical evaluations, WHO functional class (FC), 6-min walk distance, biomarkers and right heart catheterization were collected from the patients' medical records at baseline and during the follow-up.

Results

Overall, 20 patients (mean age 44±15 years, 15 female) were included.

Over a median follow-up of 12 months, all patients were still alive on triple combination therapy. At baseline 11 patients were in WHO-FC 3 and 9 patients in WHO-FC 4. At follow-up, WHO-FC (2.0±0.5 vs 3.5±0.5, p<0.001, improved in all: 2, 16, and 2 patients in FC 1, 2 and 3, respectively), exercise capacity (431±67 vs 152±130 m, p<0.001), NT-proBNP (423±260 vs 3492±1864 pg/ml; p<0.001), and haemodynamics (right atrial pressure 5±2 vs 13±3 mmHg, p<0.001; mean pulmonary artery pressure 42±5 vs 60±9 mmHg, p<0.001; cardiac index 3.5±0.8 vs 1.8±0.3 l/min/m2, p<0.001; pulmonary vascular resistance 5.5±1.3 vs 16.4±4.4 Wood units, p<0.001; pulmonary arterial compliance 2.5±0.9 vs 0.8±0.3 ml/mmHg, p<0.001) significantly improved compared with baseline. No patient discontinued the therapy due to serious adverse events.

Conclusions

Triple upfront combination therapy with ambrisentan, tadalafil and sc treprostinil is safe and offers clinical and heamodynamics benefits in incident patients with severe PAH.

Localization accuracy of robotic radiosurgery in 1-view tracking

PURPOSE

When a lung lesion is detected by only one couple of X-ray tube and image detector integrated with CyberKnife®, the fiducial-less tracking is limited to 1-view (34% of lung treatments at Centro Diagnostico Italiano). The aim of the study was mainly to determine the margin needed to take into account the localization uncertainty along the blind view (out-of-plane direction).

METHODS

36 patients treated in 2-view tracking modality (127 fractions in total) were included in the study. The actual tumor positions were determined retrospectively through logfile analysis and were projected onto 2D image planes. In the same plots the planned target positions based on biphasic breath-hold CT scans were represented preserving the metric with respect to the imaging center. The internal margin necessary to cover in out-of-plane direction the 95% of the target position distribution in the 95% of cases was calculated by home-made software in Matlab®. A validation test was preliminarily performed using XLT Phantom (CIRS) both in 2-view and 1-view scenarios.

RESULTS

The validation test proved the reliability of the method, in spite of some intrinsic limitations. Margins were estimated equal to 5 and 6 mm for targets in upper and lower lobe respectively. Biphasic breath-hold CT led to underestimate the target movement in the hypothetical out-of-plane direction. The inter-fractional variability of spine-target distance was an important source of uncertainty for 1-view treatments.

CONCLUSION

This graphic comparison method preserving metric could be employed in the clinical workflow of 1-view treatments to get patient-related information for customized margin definition.

Thyroid hormone in the regulation of hepatocellular carcinoma and its microenvironment

Hepatocellular carcinoma (HCC) commonly arises from a liver damaged by extensive inflammation and fibrosis. Various factors including cytokines, morphogens, and growth factors are involved in the crosstalk between HCC cells and the stromal microenvironment. Increasing our understanding of how stromal components interact with HCC and the signaling pathways involved could help identify new therapeutic and/or chemopreventive targets. It has become increasingly clear that the cross-talk between tumor cells and host stroma plays a key role in modulating tumor growth. Emerging reports suggest a relationship between HCC and thyroid hormone signaling (dysfunction), raising the possibility that perturbed thyroid hormone (TH) regulation influences the cancer microenvironment and cancer phenotype. This review provides an overview of the role of thyroid hormone and its related pathways in HCC and, specifically, its role in regulating the tumor microenvironment.

Diet Modulation Restores Autophagic Flux in Damaged Skeletal Muscle Cells

OBJECTIVES

Autophagy is a physiological and highly regulated mechanism, crucial for cell homeostasis maintenance. Its impairment seems to be involved in the onset of several diseases, including muscular dystrophies, myopathies and sarcopenia. According to few papers, chemotherapeutic drug treatment is able to trigger side effects on skeletal muscle tissue and, among these, a defective autophagic activation, which leads to the persistence of abnormal organelles within cells and, finally, to myofiber degeneration. The aim of this work is to find a strategy, based on diet modulation, to prevent etoposide-induced damage, in a model of in vitro skeletal muscle cells.

METHODS

Glutamine supplementation and nutrient deprivation have been chosen as pre-treatments to counteract etoposide effect, a chemotherapeutic drug known to induce oxidative stress and cell death. Cell response has been evaluated by means of morpho-functional, cytofluorimetric and molecular analyses.

RESULTS

Etoposide treated cells, if compared to control, showed dysfunctional mitochondria presence, ER stress and lysosomal compartment damage, confirmed by molecular investigations.

CONCLUSIONS

Interestingly, both dietary approaches were able to rescue myofiber from etoposide-induced damage. Glutamine supplementation, in particular, seemed to be a good strategy to preserve cell ultrastructure and functionality, by preventing the autophagic impairment and partially restoring the normal lysosomal activity, thus maintaining skeletal muscle homeostasis.

Bullous pemphigoid associated with ipilimumab therapy for advanced metastatic melanoma

Immunotherapy is now being routinely used in the management of many cancers. It is therefore vital that all clinicians are aware of the diverse array of cutaneous manifestations that can result from their use, which can vary from mild to life threatening.

Mesenchymal stem cells encapsulated into biomimetic hydrogel scaffold gradually release CCL2 chemokine in situ preserving cytoarchitecture and promoting functional recovery in spinal cord injury

Spinal cord injury (SCI) is an acute neurodegenerative disorder caused by traumatic damage of the spinal cord. The neuropathological evolution of the primary trauma involves multifactorial processes that exacerbate the pathology, worsening the neurodegeneration and limiting neuroregeneration. This complexity suggests that multi-therapeutic approaches, rather than any single treatment, might be more effective. Encouraging preclinical results indicate that stem cell-based treatments may improve the disease outcome due to their multi-therapeutic ability. Mesenchymal Stem Cells (MSCs) are currently considered one of the most promising approaches. Significant improvement in the behavioral outcome after MSC treatment sustained by hydrogel has been demonstrated. However, it is still not known how hydrogel contribute to the delivery of factors secreted from MSCs and what factors are released in situ. Among different mediators secreted by MSCs after seeding into hydrogel, we have found CCL2 chemokine, which could account for the neuroprotective mechanisms of these cells. CCL2 secreted from human MSCs is delivered efficaciously in the lesioned spinal cord acting not only on recruitment of macrophages, but driving also their conversion to an M2 neuroprotective phenotype. Surprisingly, human CCL2 delivered also plays a key role in preventing motor neuron degeneration in vitro and after spinal cord trauma in vivo, with a significant improvement of the motor performance of the rodent SCI models.

Endothelial cells, endoplasmic reticulum stress and oxysterols

Oxysterols are bioactive lipids that act as regulators of lipid metabolism, inflammation, cell viability and are involved in several diseases, including atherosclerosis. Mounting evidence linked the atherosclerosis to endothelium dysfunction; in fact, the endothelium regulates the vascular system with roles in processes such as hemostasis, cell cholesterol, hormone trafficking, signal transduction and inflammation. Several papers shed light the ability of oxysterols to induce apoptosis in different cell lines including endothelial cells. Apoptotic endothelial cell and endothelial denudation may constitute a critical step in the transition to plaque erosion and vessel thrombosis, so preventing the endothelial damaged has garnered considerable attention as a novel means of treating atherosclerosis. Endoplasmic reticulum (ER) is the site where the proteins are synthetized and folded and is necessary for most cellular activity; perturbations of ER homeostasis leads to a condition known as endoplasmic reticulum stress. This condition evokes the unfolded protein response (UPR) an adaptive pathway that aims to restore ER homeostasis. Mounting evidence suggests that chronic activation of UPR leads to cell dysfunction and death and recently has been implicated in pathogenesis of endothelial dysfunction. Autophagy is an essential catabolic mechanism that delivers misfolded proteins and damaged organelles to the lysosome for degradation, maintaining basal levels of autophagic activity it is critical for cell survival. Several evidence suggests that persistent ER stress often results in stimulation of autophagic activities, likely as a compensatory mechanism to relieve ER stress and consequently cell death. In this review, we summarize evidence for the effect of oxysterols on endothelial cells, especially focusing on oxysterols-mediated induction of endoplasmic reticulum stress.

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Endothelial cells dysfunction is critical in the process of atherothrombosis.

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Endoplasmic reticulum stress is a key component in endothelial cell dysfunction.

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Oxysterols are oxidation products of cholesterol found in atherosclerosis lesions.

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Oxysterols are potential modulators of endoplasmic reticulum stress.

A novel nonsense ATP7A pathogenic variant in a family exhibiting a variable occipital horn syndrome phenotype

We report on a family with occipital horn syndrome (OHS) diagnosed in the proband's late fifties. A novel ATP7A pathogenic variant (c.4222A > T, p.(Lys1408*)), representing the first nonsense variant and the second late truncation causing OHS rather than classic Menkes disease, was found to segregate in the family. The predicted maintenance of transmembrane domains is consistent with a residual protein activity, which may explain the mild clinical presentation.

Ten-year experience in the management of distal ureteral stones greater than 10 mm in size

AIM

Extracorporeal shock wave lithotripsy (ESWL) and semirigid ureteroscopy lithotripsy (URSL) have become standards of treatment for ureteral calculi. The aim of this retrospective study was to compare ESWL vs. URSL in terms of safety and efficacy for treatment of large distal ureteral stones ≥ 1cm.

PATIENTS AND METHODS

This investigation assessed 637 patients with distal ureteral stones (10 to 15mm in size). 313 in the ESWL group were treated on an outpatient basis using the LithoDiamond machine without anaesthesia. URSL was performed in 324 patients with a 6-8 Fr semirigid ureterorenoscope and YAG laser under spinal anaesthesia. A successful outcome was defined as the patient being stone free 1 month after treatment. For all patients the parameters, including stone-free rate, operation time, complications, were inserted retrospectively in this study after review of medical records and operating room logs.

RESULTS

The stone-free rate after URSL was 77.5% and 45.4% after ESWL treatment (p<0.001). The mean operative time between two groups was 74.7±9.8 for URSL group and 38.3±7.6 for ESWL group. The average number of office visits was 4.2 and 2.6 in patients treated with ESWL and URSL, respectively. Double j stents were inserted in 28.7% of patients. Twenty-one patients needed rehospitalisations for major complications. However, the differences in the overall complication rate were not statistically significant, with a rate of 16.3% for URSL and 14.4% for ESWL (p=0.246).

CONCLUSION

We have shown that URSL has enough safety and efficacy for the treatment of distal ureteral stones ≥ 1cm. URSL is associated with higher stone clearance rate as compared with ESWL.

Environmental nanoparticles are significantly over-expressed in acute myeloid leukemia

The increase in the incidence of acute myeloid leukemia (AML) may suggest a possible environmental etiology. PM2.5 was declared by IARC a Class I carcinogen. No report has focused on particulate environmental pollution together with AML. The study investigated the presence and composition of particulate matter in blood with a Scanning Electron Microscope coupled with an Energy Dispersive Spectroscope, a sensor capable of identifying the composition of foreign bodies. 38 peripheral blood samples, 19 AML cases and 19 healthy controls, were analyzed. A significant overload of particulate matter-derived nanoparticles linked or aggregated to blood components was found in AML patients, while almost absent in matched healthy controls. Two-tailed Student's t-test, MANOVA and Principal Component Analysis indicated that the total numbers of aggregates and particles were statistically different between cases and controls (MANOVA, P<0.001 and P=0.009 respectively). The particles detected showed to contain highly-reactive, non-biocompatible and non-biodegradable metals; in particular, micro- and nano-sized particles grouped in organic/inorganic clusters, with statistically higher frequency of a subgroup of elements in AML samples. The demonstration, for the first time, of an overload of nanoparticles linked to blood components in AML patients could be the basis for a possible, novel pathogenetic mechanism for AML development.

cAMP regulates the functional activity, coupling efficiency and structural organization of mammalian FOF1 ATP synthase

The present study shows that in isolated mitochondria and myoblast cultures depletion of cAMP, induced by sAC inhibition, depresses both ATP synthesis and hydrolysis by the FOF1 ATP synthase (complex V) of the oxidative phosphorylation system (OXPHOS). These effects are accompanied by the decrease of the respiratory membrane potential, decreased level of FOF1 connecting subunits and depressed oligomerization of the complex. All these effects of sAC inhibition are prevented by the addition of the membrane-permeant 8-Br-cAMP. These results show, for the first time, that cAMP promotes ATP production by complex V and prevents, at the same time, its detour to a mitochondrial membrane leak conductance, which is involved in cell death.

Evidence for immunomodulation and apoptotic processes induced by cationic polystyrene nanoparticles in the hemocytes of the marine bivalve Mytilus

Polymeric nanoparticles can reach the marine environment from different sources as weathering of plastic debris and nanowaste. Nevertheless, few data are available on their fate and impact on marine biota. Polystyrene nanoparticles (PS NPs) can be considered as a model for studying the effects of nanoplastics in marine organisms: recent data on amino-modified PS NPs (PS-NH2) toxicity in sea urchin embryos underlined that marine invertebrates can be biological targets of nanoplastics. Cationic PS NPs have been shown to be toxic to mammalian cells, where they can induce apoptotic processes; however, no information is available on their effects and mechanisms of action in the cells of marine organisms. In this work, the effects of 50 nm PS-NH2 were investigated in the hemocytes of the marine bivalve Mytilus galloprovincialis. Hemocytes were exposed to different concentrations (1, 5, 50 μg/ml) of PS-NH2 suspension in ASW. Clear signs of cytoxicity were evident only at the highest concentrations (50 μg/ml). On the other hand, a dose dependent decrease in phagocytic activity and increase in lysozyme activity were observed. PS-NH2 NPs also stimulated increase in extracellular ROS (reactive oxygen species) and NO (nitric oxide) production, with maximal effects at lower concentrations. Moreover, at the highest concentration tested, PS-NH2 NPs induced apoptotic process, as evaluated by Flow cytometry (Annexin V binding and mitochondrial parameters). The results demonstrate that in marine invertebrates the immune function can represent a significant target for PS-NPs. Moreover, in Mytilus hemocytes, PS-NH2 NPs can act through mechanisms similar to those observed in mammalian cells. Further research is necessary on specific mechanisms of toxicity and cellular uptake of nanoplastics in order to assess their impact on marine biota.

Osteopontin neutralisation abrogates the liver progenitor cell response and fibrogenesis in mice

BACKGROUND

Chronic liver injury triggers a progenitor cell repair response, and liver fibrosis occurs when repair becomes deregulated. Previously, we reported that reactivation of the hedgehog pathway promotes fibrogenic liver repair. Osteopontin (OPN) is a hedgehog-target, and a cytokine that is highly upregulated in fibrotic tissues, and regulates stem-cell fate. Thus, we hypothesised that OPN may modulate liver progenitor cell response, and thereby, modulate fibrotic outcomes. We further evaluated the impact of OPN-neutralisation on murine liver fibrosis.

METHODS

Liver progenitors (603B and bipotential mouse oval liver) were treated with OPN-neutralising aptamers in the presence or absence of transforming growth factor (TGF)-β, to determine if (and how) OPN modulates liver progenitor function. Effects of OPN-neutralisation (using OPN-aptamers or OPN-neutralising antibodies) on liver progenitor cell response and fibrogenesis were assessed in three models of liver fibrosis (carbon tetrachloride, methionine-choline deficient diet, 3,5,-diethoxycarbonyl-1,4-dihydrocollidine diet) by quantitative real time (qRT) PCR, Sirius-Red staining, hydroxyproline assay, and semiquantitative double-immunohistochemistry. Finally, OPN expression and liver progenitor response were corroborated in liver tissues obtained from patients with chronic liver disease.

RESULTS

OPN is overexpressed by liver progenitors in humans and mice. In cultured progenitors, OPN enhances viability and wound healing by modulating TGF-β signalling. In vivo, OPN-neutralisation attenuates the liver progenitor cell response, reverses epithelial-mesenchymal-transition in Sox9+ cells, and abrogates liver fibrogenesis.

CONCLUSIONS

OPN upregulation during liver injury is a conserved repair response, and influences liver progenitor cell function. OPN-neutralisation abrogates the liver progenitor cell response and fibrogenesis in mouse models of liver fibrosis.

Altered protein expression pattern in skin fibroblasts from parkin-mutant early-onset Parkinson's disease patients

Parkinson's disease (PD) is the most common neurodegenerative movement disorder caused primarily by selective degeneration of the dopaminergic neurons in substantia nigra. In this work the proteomes extracted from primary fibroblasts of two unrelated, hereditary cases of PD patients, with different parkin mutations, were compared with the proteomes extracted from commercial adult normal human dermal fibroblasts (NHDF) and primary fibroblasts from the healthy mother of one of the two patients. The results show that the fibroblasts from the two different cases of parkin-mutant patients display analogous alterations in the expression level of proteins involved in different cellular functions, like cytoskeleton structure-dynamics, calcium homeostasis, oxidative stress response, protein and RNA processing.

Antibiotic Sensitivity of Bacillus clausii Strains in Commercial Preparation

Recently has been acknowledged the healthy use of Bacillus and related bacteria as probiotics. A mixture reported to contain four probiotic strains of Bacillus clausii is marketed as an OTC (Over The Counter) medicinal supplement for human use. Their poliantibiotic resistant property, useful for restoring the gut microbiota during antibiotic treatment, raises the question about the risk of resistance transfer. In order to better assess the risk-benefit ratio it is important to always monitoring the pattern and stability of resistance spectra in these bacteria. In this work, we have extensively redefined the antibiotic susceptibility profile of these four probiotic strains. Resistance phenotype has been determined by screening a large number of antibiotics, including natural products (such as penicillin, vancomycin and erythromycin), and completely synthetic molecules (such as fluoroquinolones). Extensive comparison with a wild type strain belonging to the normal intestinal microbiome was carried out. The molecular basis of some resistances was determined. Observed antibiotic resistances were correlated with previous and new data in safety evaluations of these strains for human use.