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The amazing effort of vaccination against COVID-19, with more than 2 billion vaccine doses administered all around the world as of 16 June 2021, has changed the history of this pandemic, drastically reducing the number of severe cases or deaths in countries were mass vaccination campaign have been carried out. However, the people’s rising enthusiasm has been blunted in late February 2021 by the report of several cases of unusual thrombotic events in combination with thrombocytopenia after vaccination with ChAdOx1 nCov-19 (Vaxzevria), and a few months later also after Ad26.COV2. S vaccines. Of note, both products used an Adenovirus-based (AdV) platform to deliver the mRNA molecule - coding for the spike protein of SARS-CoV-2. A clinical entity characterized by cerebral and/or splanchnic vein thrombosis, often associated with multiple thromboses, with thrombocytopenia and bleeding, and sometimes disseminated intravascular coagulation (DIC), was soon recognized as a new syndrome, named vaccine-induced immune thrombotic thrombocytopenia (VITT) or thrombosis with thrombocytopenia syndrome (TTS). VITT was mainly observed in females under 55 years of age, between 4 and 16 days after receiving only Adenovirus-based vaccine and displayed a seriously high fatality rate. This prompted the Medicine Regulatory Agencies of various countries to enforce the pharmacovigilance programs, and to provide some advices to restrict the use of AdV-based vaccines to some age groups. This point-of view is aimed at providing a comprehensive review of epidemiological issues, pathogenetic hypothesis and treatment strategies of this rare but compelling syndrome, thus helping physicians to offer an up-to dated and evidence-based counseling to their often alarmed patients.

Purpose We evaluated the effect of low-calorie mediterranean (MD) and vegetarian (VD) diets on gut microbiome (GM) composition and short-chain-fatty acids (SCFA) production. Methods We performed next generation sequencing (NGS) of 16S rRNA and SCFA analysis on fecal samples of 23 overweight omnivores (16 F; 7 M) with low-to-moderate cardiovascular risk. They were randomly assigned to a VD or MD, each lasting 3 months, with a crossover study design. Results Dietary interventions did not produce significant diversity in the GM composition at higher ranks (family and above), neither between nor within MD and VD, but they did it at genus level. MD significantly changed the abundance of Enterorhabdus , Lachnoclostridium and Parabacteroides , while VD significantly affected the abundance of Anaerostipes , Streptococcus , Clostridium sensu stricto, and Odoribacter . Comparison of the mean variation of each SCFA between MD and VD showed an opposite and statistically significant trend for propionic acid (+ 10% vs − 28%, respectively, p  = 0.034). In addition, variations of SCFA were negatively correlated with changes of some inflammatory cytokines such as VEGF, MCP-1, IL-17, IP-10 and IL-12, only after MD. Finally, correlation analyses showed a potential relationship—modulated by the two diets—between changes of genera and changes of clinical and biochemical parameters. Conclusions A short-term dietary intervention with MD or VD does not induce major change in the GM, suggesting that a diet should last longer than 3 months for scratching the microbial resilience. Changes in SCFA production support their role in modulating the inflammatory response, thus mediating the anti-inflammatory and protective properties of MD.

Background and Clinical Significance: Trousseau’s syndrome, characterized by recurrent thromboembolic events and non-bacterial thrombotic endocarditis, represents a severe paraneoplastic condition associated with poor prognosis in cancer patients. Due to the growing life expectancy of cancer patients, Trousseau’s syndrome is becoming more frequent. Consequently, risk of thrombosis and bleeding assessment, as well as early diagnosis and opportune therapy will gain importance. Case Presentation: We describe a case of a 63-year-old Caucasian male presenting with ischemic stroke. During management, he developed a mitral valve marantic endocarditis, and finally the diagnosis of pulmonary adenocarcinoma was performed. The case description is followed by a brief review of the relevant literature on the condition. Discussion and Conclusions: This case highlights the complexity of diagnosing and managing Trousseau’s syndrome. Early recognition, appropriate anticoagulation strategies, and the need for multidisciplinary management are crucial to improve the outcomes and the quality of life for cancer patients.

Background Risk stratification and management of acute myocardial infarction patients continue to be challenging despite considerable efforts made in the last decades by many clinicians and researchers. The aim of this study was to investigate the metabolomic fingerprint of acute myocardial infarction using nuclear magnetic resonance spectroscopy on patient serum samples and to evaluate the possible role of metabolomics in the prognostic stratification of acute myocardial infarction patients. Methods In total, 978 acute myocardial infarction patients were enrolled in this study; of these, 146 died and 832 survived during 2 years of follow-up after the acute myocardial infarction. Serum samples were analyzed via high-resolution 1 H-nuclear magnetic resonance spectroscopy and the spectra were used to characterize the metabolic fingerprint of patients. Multivariate statistics were used to create a prognostic model for the prediction of death within 2 years after the cardiovascular event. Results In the training set, metabolomics showed significant differential clustering of the two outcomes cohorts. A prognostic risk model predicted death with 76.9% sensitivity, 79.5% specificity, and 78.2% accuracy, and an area under the receiver operating characteristics curve of 0.859. These results were reproduced in the validation set, obtaining 72.6% sensitivity, 72.6% specificity, and 72.6% accuracy. Cox models were used to compare the known prognostic factors (for example, Global Registry of Acute Coronary Events score, age, sex, Killip class) with the metabolomic random forest risk score. In the univariate analysis, many prognostic factors were statistically associated with the outcomes; among them, the random forest score calculated from the nuclear magnetic resonance data showed a statistically relevant hazard ratio of 6.45 ( p = 2.16×10 −16 ). Moreover, in the multivariate regression only age, dyslipidemia, previous cerebrovascular disease, Killip class, and random forest score remained statistically significant, demonstrating their independence from the other variables. Conclusions For the first time, metabolomic profiling technologies were used to discriminate between patients with different outcomes after an acute myocardial infarction. These technologies seem to be a valid and accurate addition to standard stratification based on clinical and biohumoral parameters.

ObjectivesSeveral physiological abnormalities that develop during COVID-19 are associated with increased mortality. In the present study, we aimed to develop a clinical risk score to predict the in-hospital mortality in COVID-19 patients, based on a set of variables available soon after the hospitalisation triage.SettingRetrospective cohort study of 516 patients consecutively admitted for COVID-19 to two Italian tertiary hospitals located in Northern and Central Italy were collected from 22 February 2020 (date of first admission) to 10 April 2020.ParticipantsConsecutive patients≥18 years admitted for COVID-19.Main outcome measuresSimple clinical and laboratory findings readily available after triage were compared by patients’ survival status (‘dead’ vs ‘alive’), with the objective of identifying baseline variables associated with mortality. These were used to build a COVID-19 in-hospital mortality risk score (COVID-19MRS).ResultsMean age was 67±13 years (mean±SD), and 66.9% were male. Using Cox regression analysis, tertiles of increasing age (≥75, upper vs <62 years, lower: HR 7.92; p<0.001) and number of chronic diseases (≥4 vs 0–1: HR 2.09; p=0.007), respiratory rate (HR 1.04 per unit increase; p=0.001), PaO2/FiO2 (HR 0.995 per unit increase; p<0.001), serum creatinine (HR 1.34 per unit increase; p<0.001) and platelet count (HR 0.995 per unit increase; p=0.001) were predictors of mortality. All six predictors were used to build the COVID-19MRS (Area Under the Curve 0.90, 95% CI 0.87 to 0.93), which proved to be highly accurate in stratifying patients at low, intermediate and high risk of in-hospital death (p<0.001).ConclusionsThe COVID-19MRS is a rapid, operator-independent and inexpensive clinical tool that objectively predicts mortality in patients with COVID-19. The score could be helpful from triage to guide earlier assignment of COVID-19 patients to the most appropriate level of care.

: The aim of this study is to evaluate the relation between sleep quantity (TST), efficiency (SE) and regularity (SRI) and cardiometabolic parameters and eating habits. : Seventy clinically healthy adults (74% females; mean age 28.3 ± 10.1 years) were recruited at the Clinical Nutrition Unit of Careggi University Hospital, Florence, between October 2023 and December 2024. Sleep was monitored for 7 days using a Fitbit Alta HR actigraphy. Cardiometabolic health was assessed via bioimpedance and blood samples. Dietary habits were evaluated through 3-day food diaries and the Medi-Lite questionnaire. : Participants had an average TST of 7.4 ± 1.1 h, SE of 84.9 ± 6.9%, and SRI of 62.2 ± 19.9. Lower SRI (≤41, 1st quintile) was associated with higher fat mass (19.9 ± 6.7 vs. 15.2 ± 6.6%), higher total cholesterol (183.9 ± 20.9 vs. 155.0 ± 26.8 mg/dL), and lower folate (3.6 ± 1.6 vs. 5.6 ± 2.5 ng/mL) compared to higher SRI (≥80, 5th quintile). Sleeping <7 h/night was linked to higher BMI (22.6 ± 2.1 vs. 21.5 ± 2.0 kg/m ) and homocysteine (11.4 ± 2.3 vs. 10.4 ± 3.3 μmol/L). Weak but significant inverse correlations emerged between TST and BMI (R = -0.26, = 0.02) and between SRI and cholesterol (R = -0.28, = 0.01), but these associations disappeared in the multivariable linear regression adjusted model. : These findings underscore the role of sleep duration and regularity in shaping body composition and cardiometabolic health, supporting its relevance as a modifiable public health priority.

Neutrophils can promote or suppress tumor growth. These different immunological functions mirror a great heterogenicity of neutrophil maturation and activation status: low-density granulocytes (LDGs) and normal-density neutrophils (NDNs). LDGs participate in immune dysregulation during autoimmune disorders with an activated phenotype, while NDNs might exert immunosuppressive activities. Here, we investigated variations in distribution of LDGs and NDNs in benign and malignant hematological conditions using an optimized 10-color flow cytometry staining for immunophenotyping of the main circulating populations. A total of 102 consecutive subjects diagnosed with hematological malignancies was enrolled for immunophenotyping by flow cytometry. We showed impaired neutrophil subset distribution in myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) patients compared to healthy individuals, with intermediate and mature LDGs significantly reduced, also displaying a good diagnostic sensitivity in MDS (AUC, 0.793 and P  = 0.0013; and AUC, 0.7319 and P  = 0.0109, respectively) and AML (AUC, 0.9059 and P  = 0.0069; and AUC, 0.9176 and P  = 0.00057, respectively). In conclusion, LDG and NDN subsets could be altered in AML and MDS, in favor of more immature forms, suggesting that emergency hemopoiesis could be a first mechanism to sustain peripheral blood counts, while maintaining a pro-inflammatory microenvironment.

Background Obesity and its associated health complications have become a global public health concern, necessitating innovative approaches to weight management. One emerging area of research focuses on the influence of chronotype, an individual’s preferred timing for daily activities, on eating habits, weight regulation, and metabolic health. Recent observational studies suggest that the misalignment between an individual’s chronotype and external cues, such as meal timing, may contribute to metabolic dysregulation and obesity, but evidence from intervention studies is still limited. This study protocol describes a randomized controlled trial designed to explore the effects of a chronotype-adapted diet, compared with a diet with a conventional calorie distribution, on weight loss, cardiometabolic health, and gut microbiota composition. Methods A total of 150 overweight/obese adults will be recruited for this 4-month parallel-group, randomized, two-arm, open-label, superiority trial with 1:1 allocation ratio. Participants will be randomly assigned to either the intervention group or the control group. The intervention group will receive a low-calorie chronotype-adapted diet with a calorie distribution adapted to the individual chronotype (morning or evening), optimizing meal timing according to their peak metabolic periods. The control group will follow a standardized low-calorie healthy eating plan without considering chronotype. Both diets will have equivalent daily calorie content, adjusted according to gender and starting weight. Anthropometric measurements, body composition, blood, and fecal samples will be obtained from each participant at the beginning and the end of the study. The primary outcome is weight change from baseline. Secondary outcomes are changes from baseline in body mass index (BMI), fat mass, lipid and glycemic profile, fecal microbiota profile, and short-chain fatty acids (SCFAs). Discussion The results of this randomized controlled trial have the potential to advance our understanding of the complex interactions between chronotype, diet, body weight, and health outcomes. By providing evidence for personalized dietary interventions based on individuals’ circadian preferences, this research could offer insights into personalized nutrition strategies. Such knowledge could guide the development of innovative dietary interventions to optimize the prevention and management of overweight and obesity, while also improving the risk profile of these individuals. Trial registration ClinicalTrials.gov NCT05941871. Registered on 18 May 2023.

The aim of this study was to assess the incidence of deep vein thrombosis (DVT) of the lower limbs, using serial compression ultrasound (CUS) surveillance, in acutely ill patients with COVID-19 pneumonia admitted to a non-ICU setting. Multicenter, prospective study of patients with COVID-19 pneumonia admitted to Internal Medicine units. All patients were screened for DVT of the lower limbs with serial CUS. Anticoagulation was defined as: low dose (enoxaparin 20-40 mg/day or fondaparinux 1.5-2.5 mg/day); intermediate dose (enoxaparin 60-80 mg/day); high dose (enoxaparin 120-160 mg or fondaparinux 5-10 mg/day or oral anticoagulation). The primary end-point of the study was the diagnosis of DVT by CUS. Over a two-month period, 227 consecutive patients with moderate-severe COVID-19 pneumonia were enrolled. The incidence of DVT was 13.7% (6.2% proximal, 7.5% distal), mostly asymptomatic. All patients received anticoagulation (enoxaparin 95.6%) at the following doses: low 57.3%, intermediate 22.9%, high 19.8%. Patients with and without DVT had similar characteristics, and no difference in anticoagulant regimen was observed. DVT patients were older (mean 77±9.6 vs 71±13.1 years; p = 0.042) and had higher peak D-dimer levels (5403 vs 1723 ng/mL; p = 0.004). At ROC analysis peak D-dimer level >2000 ng/mL (AUC 0.703; 95% CI 0.572-0.834; p = 0.004) was the most accurate cut-off value able to predict DVT (RR 3.74; 95%CI 1.27-10, p = 0.016). The incidence of DVT in acutely ill patients with COVID-19 pneumonia is relevant. A surveillance protocol by serial CUS of the lower limbs is useful to timely identify DVT that would go otherwise largely undetected.

Diet may influence early biological processes involved in colorectal carcinogenesis. Red and processed meat intake has been associated to increased colorectal cancer (CRC) risk, potentially through heme-driven oxidative and genotoxic mechanisms. This 12-week behavioral, free-living, randomized, open-label study evaluated how three different diets impact CRC risk markers: a meat-based diet (MBD: high risk), a meat-based diet with α-tocopherol supplementation (MBD-T: medium risk, hypothesized to attenuate heme-induced oxidative stress and lipid peroxidation), and a pesco-vegetarian diet (PVD: low risk). A total of 113 healthy adults (18–50 years) were randomized, and 103 completed the study. The primary outcome was fecal water (FW) genotoxicity at baseline and after 12 weeks; secondary outcomes included FW cytotoxicity, lipoperoxidation, fecal short-chain fatty acids (SCFAs) and bile acids, and blood biomarkers related to iron metabolism and inflammation, also measured pre- and post-intervention. Mixed-effects linear models (time × diet), adjusted for age, sex, and BMI, were applied. FW genotoxicity increased significantly after MBD (+ 15.97%DNA damage; 95% CI 4.61 to 27.32; p = 0.006), with no significant within-group changes in MBD-T or PVD. Between-diet differences in change indicated greater increases in fecal TBARS following MBD (p = 0.010) and MBD-T (p = 0.037) compared with PVD, and a significantly greater increase in 4-HNE after MBD compared with PVD (p = 0.019). The FW Viability Index decreased significantly after MBD (p = 0.021). Differences in change between diets were also significant for circulating ferritin and inflammatory markers, which increased more after MBD compared with PVD (ferritin, IL-6, TNF-α), whereas MBD-T reduced TNF-α and PVD decreased IL-8, TNF-α, and ICAM. No significant between-diet differences in change were observed for fecal SCFAs or bile acids. In summary, over 12 weeks in a free-living setting, a MBD increased several mechanistic biomarkers associated with CRC, while α-tocopherol supplementation attenuated some adverse diet-related effects. In contrast, a PVD was associated with a more favorable biochemical and inflammatory profile. These findings reflect short-term modulation of mechanistic biomarkers rather than CRC outcomes. Trial Registration: ClinicalTrials.gov Identifier: NCT03416777. Registered 03/05/2018.