Towards the automatic calculation of the EQUAL Candida Score: Extraction of CVC-related information from EMRs of critically ill patients with candidemia in Intensive Care Units.

OBJECTIVES: Candidemia is the most frequent invasive fungal disease and the fourth most frequent bloodstream infection in hospitalized patients. Its optimal management is crucial for improving patients' survival. The quality of candidemia management can be assessed with the EQUAL Candida Score. The objective of this work is to support its automatic calculation by extracting central venous catheter-related information from Italian text in clinical notes of electronic medical records. MATERIALS AND METHODS: The sample includes 4,787 clinical notes of 108 patients hospitalized between January 2018 to December 2020 in the Intensive Care Units of the IRCCS San Martino Polyclinic Hospital in Genoa (Italy). The devised pipeline exploits natural language processing (NLP) to produce numerical representations of clinical notes used as input of machine learning (ML) algorithms to identify CVC presence and removal. It compares the performances of (i) rule-based method, (ii) count-based method together with a ML algorithm, and (iii) a transformers-based model. RESULTS: Results, obtained with three different approaches, were evaluated in terms of weighted F1 Score. The random forest classifier showed the higher performance in both tasks reaching 82.35%. CONCLUSION: The present work constitutes a first step towards the automatic calculation of the EQUAL Candida Score from unstructured daily collected data by combining ML and NLP methods. The automatic calculation of the EQUAL Candida Score could provide crucial real-time feedback on the quality of candidemia management, aimed at further improving patients' health.

Mortality in KPC-producing Klebsiella pneumoniae bloodstream infections: a changing landscape.

OBJECTIVES: To assess the impact of carbapenem resistance on mortality in Klebsiella pneumoniae bloodstream infection (BSI) in the era of novel ß-lactam/ß-lactamase inhibitor combinations. MATERIAL AND METHODS: Retrospective study of patients with K. pneumoniae BSI between January and August 2020 in 16 centres (CARBANEW study within the MULTI-SITA project). RESULTS: Overall, 426 patients were included: 107/426 (25%) had carbapenem-resistant K. pneumoniae (CR-Kp) BSI and 319/426 (75%) had carbapenem-susceptible K. pneumoniae (CS-Kp) BSI. Crude cumulative 30 day mortality was 33.8% and 20.7% in patients with, respectively, CR-Kp BSI and CS-Kp BSI (P = 0.027). Carbapenemase production or carbapenemase-encoding genes were detected in 84/98 tested CR-Kp isolates (85.7%), mainly KPC (78/84; 92.9%). Ceftazidime/avibactam was the most frequently used appropriate therapy for CR-Kp BSI (80/107; 74.7%). In multivariable analyses, variables showing an unfavourable association with mortality after correction for multiple testing were age-adjusted Charlson comorbidity index (HR 1.20; 95% CI 1.10-1.31, P < 0.001) and Pitt score (HR 1.33; 95% CI 1.15-1.55, P < 0.001), but not carbapenem resistance (HR 1.28, 95% CI 0.74-2.22, P = 0.410). In a propensity score-matched analysis, there was no difference in mortality between patients appropriately treated with ceftazidime/avibactam for CR-Kp BSI and patients appropriately treated with other agents (mainly meropenem monotherapy or piperacillin/tazobactam monotherapy) for CS-Kp BSI (HR 1.07; 95% CI 0.50-2.29, P = 0.866). CONCLUSIONS: Our results suggest that the increased mortality in CR-Kp BSI compared with CS-Kp BSI is not (or no longer) dependent on the type of therapy in areas where ceftazidime/avibactam-susceptible KPC-producing isolates are the most prevalent type of CR-Kp.

Pneumocystis jirovecii pneumonia in intensive care units: a multicenter study by ESGCIP and EFISG.

BACKGROUND: Pneumocystis jirovecii pneumonia (PJP) is an opportunistic, life-threatening disease commonly affecting immunocompromised patients. The distribution of predisposing diseases or conditions in critically ill patients admitted to intensive care unit (ICU) and subjected to diagnostic work-up for PJP has seldom been explored. MATERIALS AND METHODS: The primary objective of the study was to describe the characteristics of ICU patients subjected to diagnostic workup for PJP. The secondary objectives were: (i) to assess demographic and clinical variables associated with PJP; (ii) to assess the performance of Pneumocystis PCR on respiratory specimens and serum BDG for the diagnosis of PJP; (iii) to describe 30-day and 90-day mortality in the study population. RESULTS: Overall, 600 patients were included in the study, of whom 115 had presumptive/proven PJP (19.2%). Only 8.8% of ICU patients subjected to diagnostic workup for PJP had HIV infection, whereas hematological malignancy, solid tumor, inflammatory diseases, and solid organ transplants were present in 23.2%, 16.2%, 15.5%, and 10.0% of tested patients, respectively. In multivariable analysis, AIDS (odds ratio [OR] 3.31; 95% confidence interval [CI] 1.13-9.64, p = 0.029), non-Hodgkin lymphoma (OR 3.71; 95% CI 1.23-11.18, p = 0.020), vasculitis (OR 5.95; 95% CI 1.07-33.22, p = 0.042), metastatic solid tumor (OR 4.31; 95% CI 1.76-10.53, p = 0.001), and bilateral ground glass on CT scan (OR 2.19; 95% CI 1.01-4.78, p = 0.048) were associated with PJP, whereas an inverse association was observed for increasing lymphocyte cell count (OR 0.64; 95% CI 0.42-1.00, p = 0.049). For the diagnosis of PJP, higher positive predictive value (PPV) was observed when both respiratory Pneumocystis PCR and serum BDG were positive compared to individual assay positivity (72% for the combination vs. 63% for PCR and 39% for BDG). Cumulative 30-day mortality and 90-day mortality in patients with presumptive/proven PJP were 52% and 67%, respectively. CONCLUSION: PJP in critically ill patients admitted to ICU is nowadays most encountered in non-HIV patients. Serum BDG when used in combination with respiratory Pneumocystis PCR could help improve the certainty of PJP diagnosis.

Barriers to HCV micro-elimination in a cohort of people living with HIV (PLWH).

To achieve the World Health Organization goal of hepatitis C virus (HCV) eradication, barriers to treatment should be investigated and overcome. The aim of this study was to identify those barriers and describe the strategies adopted to achieve HCV micro-elimination in a cohort of coinfected people living with HIV (PLWH-HCV). Adult PLWH-HCV followed at our hospital with detectable serum HCV-RNA in 2018 were enrolled. After a three-year follow-up, barriers to HCV treatment were investigated and strategies to overcome them were described. Of 492 PLWH-HCV seen in 2018, 29 (5.9%) had detectable serum HCV-RNA. Eight out of 29 (27.6%) were excluded because they were already under treatment, while 2 others were excluded because they moved to other outpatient clinics. Among the remaining 19 study participants, the most common barriers to treatment were poor adherence to therapies and follow-up visits (n=9, 47%), recent HCV diagnosis awaiting proper staging (n=3, 16%) and treatment hesitancy (n=2, 10%). During the following three years, direct-acting antivirals (DAAs) treatment was completed in 11/19 (58%) cases, with achievement of sustained virological response in 100% of cases. For the remaining cases, 2/19 (10.5%) were lost to follow-up, 2/19 (10.5%) died before treatment initiation and 4/19 (21.0%) are still awaiting treatment. Despite 3 years of effort, HCV micro-elimination has not been achieved at our center. We observed that poor adherence and treatment hesitancy were the main barriers to treatment. Strategies addressing these issues need to be implemented.

Prevalence of Viral Hepatitis in Unselected, Consecutively Enrolled Patients Hospitalised for SARS-CoV-2.

Diagnosing people living with chronic viral hepatitis is challenging due to the absence of symptoms as long as liver decompensated cirrhosis come out. The aim of this retrospective study was to evaluate the prevalence of HBV and/or HCV infections in a non-selected population, hospitalised for SARS-CoV-2 infection in a tertiary care hospital in Northern Italy. During the study period 1,429 patients were admitted to hospital for SARS-CoV-2 infection, serologic tests for HBV and/or HCV were available for 382 (27%) patients and 3 were excluded due to their previous known serologic status. Among 379 patients, 235 (62%) were male, median age was 70 years (range 21-103), 360 (95%) were Caucasian. Among them, 372/379 (98%) were screened for HBsAg, 320/379 (84%) for HBcAb. HBsAg was positive in 2/372 (0.5%, 95% CI 0.0006-0.02) patients (only in one HBV-DNA was performed that was negative), while HBcAb was found positive in 55/320 (17%, 95% CI 0.13-0.22). Among 370/379 (98%) patients screened for HCV, 11/370 (3%, 95% CI 0.02-0.05) had positive HCV-Ab. Five out of 11 (45%) were tested for HCV-RNA that resulted positive in two patients (0.5%, 95% CI 0.0006-0.02). Considering this data, even though the screening was performed in only 27% of study population, a tailored screening in people with known risk factors for hepatitis might be preferable to universal screening in low prevalence areas. Also a prompt diagnostic workout should begin in case of clinical or laboratory suspicion of hepatitis and in those starting immunosuppressive treatments.

Characterization of T lymphocytes in severe COVID-19 patients.

In this observational study, 13 patients with severe COVID-19 and 10 healthy controls were enrolled. The data concerning the analysis of circulating T cells show that, in severe COVID-19 patients, the expansion of these cell compartments is prone to induce antibody response, inflammation (CCR4+ and CCR6+ TFH) and regulation (CD8+ Treg). This pathogenic mechanism could lead us to envision a possible new form of biological target therapy.

Antibacterial and ATP Synthesis Modulating Compounds from Salvia tingitana.

A surface extract of the aerial parts of Salvia tingitana afforded a nor-sesterterpenoid (1) and eight new sesterterpenoids (2-̵9), along with five known sesterterpenoids, five labdane and one abietane diterpenoid, one sesquiterpenoid, and four flavonoids. The structures of the new compounds were established by 1D and 2D NMR spectroscopy, HRESIMS, and VCD data and Mosher's esters analysis. The antimicrobial activity of compounds was evaluated against 30 human pathogens including 27 clinical strains and three isolates of marine origin for their possible implications on human health. The methyl ester of salvileucolide (10), salvileucolide-6,23-lactone (11), sclareol (15), and manool (17) were the most active against Gram-positive bacteria. The compounds were also tested for the inhibition of ATP production in purified mammalian rod outer segments. Terpenoids 10, 11, 15, and 17 inhibited ATP production, while only 17 inhibited also ATP hydrolysis. Molecular modeling studies confirmed the capacity of 17 to interact with mammalian ATP synthase. A significant reduction of ATP production in the presence of 17 was observed in Enterococcus faecalis and E. faecium isolates.

Real-Life Data in the Treatment of Neovascular Age-Related Macular Degeneration: Results from the Imaculaweb Registry Evaluated in a Single Italian Medical Retina Center.

INTRODUCTION: The aim of this study is to assess and compare the long-term clinical efficacy of anti-VEGF drugs using the Imaculaweb registry. METHODS: In this observational study based on the Imaculaweb registry, outcome measures were the number of injections, the change in mean visual acuity (VA) and central macular thickness (CMT), and the time between diagnosis and the first injection. RESULTS: In total, 126 eyes of 109 patients were included in the study. The mean VA was 49.4 ± 21.4, 54.1 ± 22.2, 51.6 ± 24.9, and 48.3 ± 25.7 letters at baseline and at the 1-, 2-, and 3-year follow-ups, respectively. Significant VA increases (p = 0.0002 for the first year and p = 0.045 for the second year) were documented at years 1 and 2 but not at year 3 (p = 0.8). The mean number of injections was 5.2, 2.6, and 2.3 at the 1-, 2-, and 3-year follow-ups, respectively. In the first year, 30% of the patients received at least 7 injections, while only 6.4% received <3 injections. CMT decreased significantly during the overall follow-up period, and intra- and subretinal fluid decreased (p < 0.0001). CONCLUSION: Imaculaweb turned out to be an effective tool to collect and share clinical data as well as to monitor patient outcome.

CD8+CD28-CD127loCD39+ regulatory T-cell expansion: A new possible pathogenic mechanism for HIV infection?

BACKGROUND: HIV-associated immunodeficiency is related to loss of CD4+ T cells. This mechanism does not explain certain manifestations of HIV disease, such as immunodeficiency events in patients with greater than 500 CD4+ T cells/µL. CD8+CD28-CD127loCD39+ T cells are regulatory T (Treg) lymphocytes that are highly concentrated within the tumor microenvironment and never analyzed in the circulation of HIV-infected patients. OBJECTIVES: We sought to analyze the frequency of CD8+CD28-CD127loCD39+ Treg cells in the circulation of HIV-infected patients. METHODS: The frequency of circulating CD8+CD28-CD127loCD39+ Treg cells was analyzed and correlated with viral load and CD4+ T-cell counts/percentages in 93 HIV-1-infected patients subdivided as follows: naive (n = 63), elite controllers (n = 19), long-term nonprogressors (n = 7), and HIV-infected patients affected by tumor (n = 4). The same analyses were performed in HIV-negative patients with cancer (n = 53), hepatitis C virus-infected patients (n = 17), and healthy donors (n = 173). RESULTS: HIV-infected patients had increased circulating levels of functional CD8+CD28-CD127loCD39+ Treg cells. These cells showed antigen specificity against HIV proteins. Their frequency after antiretroviral therapy (ART) correlated with HIV viremia, CD4+ T-cell counts, and immune activation markers, suggesting their pathogenic involvement in AIDS- or non-AIDS-related complications. Their increase after initiation of ART heralded a lack of virologic or clinical response, and hence their monitoring is clinically relevant. CONCLUSION: HIV infection induces remarkable expansion of CD8+CD28-CD127loCD39+ Treg cells, the frequency of which correlates with both clinical disease and signs of chronic immune cell activation. Monitoring their frequency in the circulation is a new marker of response to ART when effects on viremia and clinical response are not met.

Predictors of retention in care in HIV-infected patients in a large hospital cohort in Italy.

Retention in care is a key feature of the cascade of continuum of care, playing an important role in achieving therapeutic success and being crucial for reduction of HIV transmission. The aim of this study was to evaluate the rate of retention in care in a large referral centre in the North of Italy and to identify predictors associated with failed retention. All new HIV-infected subjects were consecutive enrolled from 1 January 2008 to 31 December 2014. Demographics, immune-virological status, hepatitis co-infection and timing of initiation of combined antiretroviral therapy (cART) data were collected at baseline and at the time of last observation. Failed retention in care was defined as lack of laboratory data, clinical visits and drug dispensation for more than 6 months from the last visit. Cox regression analysis was used. Multivariate analysis of variables with P<0.05 in univariate analysis was performed. We enrolled 269 patients (mean age 46.1 years). Males were 197 (73%), Italian 219 (81%) with mean length of disease of 5.1 years. cART was prescribed for 257 patients (95%). The rate of retention in care was 78.4% and the rate of virological suppression was 75%. Predictors of being loss to follow-up were foreign origin (P = 0.048), CD4+ count <200/mmc (P = 0.001) and not being treated for HIV infection (P = 0.0004). Predictors of cART efficacy were shorter duration of HIV infection and baseline HIV-RNA <100 000 copies/ml. These findings underline the necessity to improve retention in care by identifying groups at increased risk of being loss to follow-up. Retention in care of vulnerable population is crucial to reach 90-90-90 UNAIDS endpoint.

How has the cost of antiretroviral therapy changed over the years? A database analysis in Italy.

BACKGROUND: The number of human immunodeficiency virus (HIV)-related hospitalizations has decreased worldwide in recent years, due to the availability of combined antiretroviral therapies (cART). The present analysis aimed to analyse the economic, and clinical burden of HIV management, after the introduction of systematic use of cART. METHODS: Data from HIV-infected patients, treated at Policlinico San Martino Hospital in Genova (Italy) were retrospectively collected. A comparison between years 2009 and 2015 was performed. HIV-related admissions were identified by using the Diagnosis-Related Group (DRG) codes. The resource consumption of outpatient services was derived by using a modelling approach. Expenditure for drugs was also analysed, as aggregate data. RESULTS: The number of HIV-infected patients was 898 in 2009 and 1006 in 2015. Overall, the virological success rate improved from 2009 to 2015, as the percentage of patients with HIV-RNA < 50 copies/mL increased from 79 to 89% (P < 0.05). The average incidence of hospitalizations per-patient decreased from 0.30 in 2009, to 0.13 in 2015. Average expenditure per-patient decreased from €10,107 in 2009 to €9063 in 2015. CONCLUSIONS: The present analysis confirmed the role of cART in controlling HIV viral load and, consequently, in reducing hospitalizations, admissions to day-hospital and the use of outpatient services. Clinical improvements and economic savings more than compensated the investments required to treat HIV-infected patients with cART. Health Authorities should invest in modern cART supply and universal treatment, to use at best the available resources and obtain a cost-effective improvement of health in people living with HIV. Additional research, with the involvement of different centers and the use of patient-specific data, are recommended to consolidate the findings of this analysis.

Is it still worthwhile to perform quarterly cd4+ t lymphocyte cell counts on hiv-1 infected stable patients?

BACKGROUND: In the last 20 years routine T CD4+ lymphocyte (CD4+) cell count has proved to be a key factor to determine the stage of HIV infection and start or discontinue of prophylaxis for opportunistic infections. However, several studies recently showed that in stable patients on cART a quarterly CD4+ cell count monitoring results in limited (or null) clinical relevance. The research is intended to investigate whether performing quarterly CD4+ cell counts in stable HIV-1 patients is still recommendable and to provide a forecast of the cost saving that could be achieved by reducing CD4+ monitoring in such a category of patients. METHODS: The study is based on data referring to all HIV-infected patients > 18 years of age being treated at two large infectious diseases units located in the metropolitan area of Genoa, Italy. The probability of CD4+ cell counts dropping below a threshold value set at 350 cells/mm3 is assessed using confidence intervals and Kaplan-Meier survival estimates, whereas multivariate Cox analysis and logistic regression are implemented in order to identify factors associated with CD4+ cell count falls below 350 cells/mm3. RESULTS: Statistical analysis reveals that among stable patients the probability of maintaining CD4+ >350 cell/mm3 is more than 98%. Econometric models indicate that HCV co-infection and HIV-RNA values >50 copies/mL in previous examinations are associated with CD4+ falls below 350 cells/mm3. Moreover, results suggest that the cost saving that could be obtained by reducing CD4+ examinations ranges from 33 to 67%. CONCLUSIONS: Empirical findings shows that patients defined as stable at enrollment are highly unlikely to experience a CD4+ value <350 cell/mm3 in the space/arc of a year. The research supports a recommendation for annual CD4+ monitoring in stable HIV-1 patients.

Combining macula clinical signs and patient characteristics for age-related macular degeneration diagnosis: a machine learning approach.

BACKGROUND: To investigate machine learning methods, ranging from simpler interpretable techniques to complex (non-linear) "black-box" approaches, for automated diagnosis of Age-related Macular Degeneration (AMD). METHODS: Data from healthy subjects and patients diagnosed with AMD or other retinal diseases were collected during routine visits via an Electronic Health Record (EHR) system. Patients' attributes included demographics and, for each eye, presence/absence of major AMD-related clinical signs (soft drusen, retinal pigment epitelium, defects/pigment mottling, depigmentation area, subretinal haemorrhage, subretinal fluid, macula thickness, macular scar, subretinal fibrosis). Interpretable techniques known as white box methods including logistic regression and decision trees as well as less interpreitable techniques known as black box methods, such as support vector machines (SVM), random forests and AdaBoost, were used to develop models (trained and validated on unseen data) to diagnose AMD. The gold standard was confirmed diagnosis of AMD by physicians. Sensitivity, specificity and area under the receiver operating characteristic (AUC) were used to assess performance. RESULTS: Study population included 487 patients (912 eyes). In terms of AUC, random forests, logistic regression and adaboost showed a mean performance of (0.92), followed by SVM and decision trees (0.90). All machine learning models identified soft drusen and age as the most discriminating variables in clinicians' decision pathways to diagnose AMD. CONCLUSIONS: Both black-box and white box methods performed well in identifying diagnoses of AMD and their decision pathways. Machine learning models developed through the proposed approach, relying on clinical signs identified by retinal specialists, could be embedded into EHR to provide physicians with real time (interpretable) support.

Education in Health Informatics: Perspectives from the Italian Society for Biomedical Informatics (SIBIM).

The evolution of socio-technological habits together with the widespread demand of post-acute and chronic treatments outside hospital boundaries drove the increased demand of medical informatics experts to develop tools for and support healthcare professionals. The recent COVID-19 pandemic further highlighted the need of physicians able to manage diseases virtually and remotely. Moreover, healthcare professionals need to access to innovative techniques and procedures to manage biomedical data, cloud-based communication, and data sharing procedures, often connected to innovative devices to support an effective precision in the health treatments. In this paper we report the experiences of the Italian Biomedical Informatics Society (SIBIM), in the definition and promotion of eHealth educational topics in medical and health professions teaching programs, as well as in bioengineering schools, showing how SIBIM members' efforts have been applied towards increasing the level of eHealth contents in medical schools.

The Representational Challenge for Designing and Managing 5P Medicine Ecosystems.

Health and social care systems around the globe currently undergo a transformation towards personalized, preventive, predictive, participative precision medicine (5PM), considering the individual health status, conditions, genetic and genomic dispositions, etc., in personal, social, occupational, environmental and behavioral context. This transformation is strongly supported by technologies such as micro- and nanotechnologies, advanced computing, artificial intelligence, edge computing, etc. For enabling communication and cooperation between actors from different domains using different methodologies, languages and ontologies based on different education, experiences, etc., we have to understand the transformed health ecosystems and all its components in structure, function and relationships in the necessary detail ranging from elementary particles up to the universe. That way, we advance design and management of the complex and highly dynamic ecosystem from data to knowledge level. The challenge is the consistent, correct and formalized representation of the transformed health ecosystem from the perspectives of all domains involved, representing and managing them based on related ontologies. The resulting business view of the real-world ecosystem must be interrelated using the ISO/IEC 21838 Top Level Ontologies standard. Thereafter, the outcome can be transformed into implementable solutions using the ISO/IEC 10746 Open Distributed Processing Reference Model. Model and framework for this system-oriented, architecture-centric, ontology-based, policy-driven approach have been developed by the first author and meanwhile standardized as ISO 23903 Interoperability and Integration Reference Architecture.

Pilot Study for a Model for the Collection of Waiting Lists Data.

The analysis of data on waiting lists in Italy is regulated by the PNGLA (National Plan for the Governance of Waiting Lists). However, the Plan does not specify the characteristics of the data to be returned by the Regions for the purposes of monitoring, with the result that it is frequently either in aggregate form, unreadable, or incomplete, and therefore cannot be analysed in any meaningful way. Fondazione the Bridge and AGENAS, with the University of Genoa and the University of Pavia, conducted a pilot study on a methodological model for the collection of waiting lists data. The model proved to be effective and replicable, also providing a more valuable opportunity to analyse waiting lists data.

Tuberculosis Infection Control: Experiences and Considerations from a Web Based Tool Implementation.

Tuberculosis (TB) remains a significant global health challenge. Indeed, according to the World Health Organization (WHO), TB is classified as the second most common cause of death worldwide due to a single infectious agent in 2022, following COVID-19. To effectively manage tuberculosis patients, it is necessary to ensure accurate diagnosis, prompt treatment initiation, and vigilant monitoring of patients' progress. In 2017, the TB Ge network was implemented and launched in two primary hospitals within the Liguria Region in Italy, with the main purpose to manage tuberculosis infections. This system, organized as a web-based tool, simplifies the manual input of patient's data and therapies, while automating the integration of test results from hospitals' Laboratory Information Systems (LIS), without requiring human intervention. The goal of this paper is to highlight the outcomes achieved through the implementation of the TB Ge network in a period seriously affected by the COVID-19 pandemia and outline future directions. More specifically, the aim is to extend its adoption to all hospitals in the Liguria Region, thus improving the management of tuberculosis infections across healthcare facilities.

Explainable and Interpretable Machine Learning for Antimicrobial Stewardship: Opportunities and Challenges.

There is growing interest in exploiting the advances in artificial intelligence and machine learning (ML) for improving and monitoring antimicrobial prescriptions in line with antimicrobial stewardship principles. Against this background, the concepts of interpretability and explainability are becoming increasingly essential to understanding how ML algorithms could predict antimicrobial resistance or recommend specific therapeutic agents, to avoid unintended biases related to the "black box" nature of complex models. In this commentary, we review and discuss some relevant topics on the use of ML algorithms for antimicrobial stewardship interventions, highlighting opportunities and challenges, with particular attention paid to interpretability and explainability of employed models. As in other fields of medicine, the exponential growth of artificial intelligence and ML indicates the potential for improving the efficacy of antimicrobial stewardship interventions, at least in part by reducing time-consuming tasks for overwhelmed health care personnel. Improving our knowledge about how complex ML models work could help to achieve crucial advances in promoting the appropriate use of antimicrobials, as well as in preventing antimicrobial resistance selection and dissemination.

NMR Metabolite Profiling for the Characterization of Vessalico Garlic Ecotype and Bioactivity against Xanthomonas campestris pv. campestris.

The Italian garlic ecotype "Vessalico" possesses distinct characteristics compared to its French parent cultivars Messidor and Messidrôme, used for sowing, as well as other ecotypes in neighboring regions. However, due to the lack of a standardized seed supply method and cultivation protocol among farmers in the Vessalico area, a need to identify garlic products that align with the Vessalico ecotype arises. In this study, an NMR-based approach followed by multivariate analysis to analyze the chemical composition of Vessalico garlic sourced from 17 different farms, along with its two French parent cultivars, was employed. Self-organizing maps allowed to identify a homogeneous subset of representative samples of the Vessalico ecotype. Through the OPLS-DA model, the most discriminant metabolites based on values of VIP (Variable Influence on Projections) were selected. Among them, S-allylcysteine emerged as a potential marker for distinguishing the Vessalico garlic from the French parent cultivars by NMR screening. Additionally, to promote sustainable agricultural practices, the potential of Vessalico garlic extracts and its main components as agrochemicals against Xanthomonas campestris pv. campestris, responsible for black rot disease, was explored. The crude extract exhibited a MIC of 125 µg/mL, and allicin demonstrated the highest activity among the tested compounds (MIC value of 31.25 µg/mL).

Sustainable Agrochemical Exploitation of Ligurian Aromatic Plant Ecotypes.

The characterization of local improved varieties as well as the reduction of synthetic chemical fertilizers are sustainable approaches in the vision of a new precision Farming. Aim of our study was to improve the geographical characterization of local ecotypes and to identify peculiar features of new crops in terms of bioactive compounds. NMR and LC-MS metabolite profiling approaches followed by multivariate data analysis were applied to characterize local rosemary and garlic ecotypes. With the aim of applying for a protected designation of origin, orthogonal partial least squares discriminant analysis (OPLS-DA) was used to identify representative sensory quality indicators for Vessalico garlic and rosemary "Eretto Liguria" local ecotypes, Variable Influence on Projections (VIP) values of OPLS-DA indicated six metabolites as quality indicators for Vessalico garlic and sixteen metabolites as quality indicators for rosemary "Eretto Liguria". Finally, to discover and utilize new ecotypes in a sustainable way, Vessalico garlic extracts antiviral activity, previously evaluated against Tomato brown rugose fruit virus (ToBRFV), a Tobamovirus affecting tomato crops, was extended to Pepino mosaic virus (PepMV) with positive results.