How the First Year of the COVID-19 Pandemic Impacted Patients’ Hospital Admission and Care in the Vascular Surgery Divisions of the Southern Regions of the Italian Peninsula

Background: To investigate the effects of the COVID-19 lockdowns on the vasculopathic population. Methods: The Divisions of Vascular Surgery of the southern Italian peninsula joined this multicenter retrospective study. Each received a 13-point questionnaire investigating the hospitalization rate of vascular patients in the first 11 months of the COVID-19 pandemic and in the preceding 11 months. Results: 27 out of 29 Centers were enrolled. April-December 2020 (7092 patients) vs. 2019 (9161 patients): post-EVAR surveillance, hospitalization for Rutherford category 3 peripheral arterial disease, and asymptomatic carotid stenosis revascularization significantly decreased (1484 (16.2%) vs. 1014 (14.3%), p = 0.0009; 1401 (15.29%) vs. 959 (13.52%), p = 0.0006; and 1558 (17.01%) vs. 934 (13.17%), p < 0.0001, respectively), while admissions for revascularization or major amputations for chronic limb-threatening ischemia and urgent revascularization for symptomatic carotid stenosis significantly increased (1204 (16.98%) vs. 1245 (13.59%), p < 0.0001; 355 (5.01%) vs. 358 (3.91%), p = 0.0007; and 153 (2.16%) vs. 140 (1.53%), p = 0.0009, respectively). Conclusions: The suspension of elective procedures during the COVID-19 pandemic caused a significant reduction in post-EVAR surveillance, and in the hospitalization of asymptomatic carotid stenosis revascularization and Rutherford 3 peripheral arterial disease. Consequentially, we observed a significant increase in admissions for urgent revascularization for symptomatic carotid stenosis, as well as for revascularization or major amputations for chronic limb-threatening ischemia

Plant Physiological Analysis to Overcome Limitations to Plant Phenotyping.

Plant physiological status is the interaction between the plant genome and the prevailing growth conditions. Accurate characterization of plant physiology is, therefore, fundamental to effective plant phenotyping studies; particularly those focused on identifying traits associated with improved yield, lower input requirements, and climate resilience. Here, we outline the approaches used to assess plant physiology and how these techniques of direct empirical observations of processes such as photosynthetic CO2 assimilation, stomatal conductance, photosystem II electron transport, or the effectiveness of protective energy dissipation mechanisms are unsuited to high-throughput phenotyping applications. Novel optical sensors, remote/proximal sensing (multi- and hyperspectral reflectance, infrared thermography, sun-induced fluorescence), LiDAR, and automated analyses of below-ground development offer the possibility to infer plant physiological status and growth. However, there are limitations to such indirect approaches to gauging plant physiology. These methodologies that are appropriate for the rapid high temporal screening of a number of crop varieties over a wide spatial scale do still require calibration or validation with direct empirical measurement of plant physiological status. The use of deep-learning and artificial intelligence approaches may enable the effective synthesis of large multivariate datasets to more accurately quantify physiological characters rapidly in high numbers of replicate plants. Advances in automated data collection and subsequent data processing represent an opportunity for plant phenotyping efforts to fully integrate fundamental physiological data into vital efforts to ensure food and agro-economic sustainability

Plant Physiological Analysis to Overcome Limitations to Plant Phenotyping

Plant physiological status is the interaction between the plant genome and the prevailing growth conditions. Accurate characterization of plant physiology is, therefore, fundamental to effective plant phenotyping studies; particularly those focused on identifying traits associated with improved yield, lower input requirements, and climate resilience. Here, we outline the approaches used to assess plant physiology and how these techniques of direct empirical observations of processes such as photosynthetic CO2 assimilation, stomatal conductance, photosystem II electron transport, or the effectiveness of protective energy dissipation mechanisms are unsuited to high-throughput phenotyping applications. Novel optical sensors, remote/proximal sensing (multi- and hyperspectral reflectance, infrared thermography, sun-induced fluorescence), LiDAR, and automated analyses of below-ground development offer the possibility to infer plant physiological status and growth. However, there are limitations to such ‘indirect’ approaches to gauging plant physiology. These methodologies that are appropriate for the rapid high temporal screening of a number of crop varieties over a wide spatial scale do still require ‘calibration’ or ‘validation’ with direct empirical measurement of plant physiological status. The use of deep-learning and artificial intelligence approaches may enable the effective synthesis of large multivariate datasets to more accurately quantify physiological characters rapidly in high numbers of replicate plants. Advances in automated data collection and subsequent data processing represent an opportunity for plant phenotyping efforts to fully integrate fundamental physiological data into vital efforts to ensure food and agro-economic sustainability

The 'microbiome counterattack': Insights on the soil and root-associated microbiome in diverse chickpea and lentil genotypes after an erratic rainfall event

Legumes maintain soil fertility thanks to their associated microbiota but are threatened by climate change that causes soil microbial community structural and functional modifications. The core microbiome associated with different chickpea and lentil genotypes was described after an unexpected climatic event. Results showed that chickpea and lentil bulk soil microbiomes varied significantly between two sampling time points, the first immediately after the rainfall and the second 2 weeks later. Rhizobia were associated with the soil of the more productive chickpea genotypes in terms of flower and fruit number. The root-associated bacteria and fungi were surveyed in lentil genotypes, considering that several parcels showed disease symptoms. The metabarcoding analysis revealed that reads related to fungal pathogens were significantly associated with one lentil genotype. A lentil core prokaryotic community common to all genotypes was identified as well as a genotype-specific one. A higher number of specific bacterial taxa and an enhanced tolerance to fungal diseases characterized a lentil landrace compared to the commercial varieties. This outcome supported the hypothesis that locally adapted landraces might have a high recruiting efficiency of beneficial soil microbes

Association of proinflammatory diet with low-grade inflammation: results from the Moli-sani study

Objectives: The association between diet and inflammation is well documented. Yet, no evidence exists on the relationship between the inflammatory potential of the diet and low-grade inflammation (LGI) as measured by a composite score of plasma and cellular biomarkers. The aim of this study was to assess the association between the Dietary Inflammatory Index (DII\uae) and LGI in a large population-based cohort. Methods: Cross-sectional analyses were conducted on data from 20 823 adults (age 6535 y; 48% male) without acute inflammation, who were recruited within the general population of the Moli-sani study from 2005 to 2010. LGI was measured by using a composite score (INFLA-score) including platelet and leukocyte counts, the granulocyte to lymphocyte ratio, and C-reactive protein. DII scores were computed based on dietary intake assessed by the EPIC food frequency questionnaire. Multivariable linear regression models were fit to produce adjusted regression coefficients and 95% confidence intervals (CIs). Results: Higher DII scores were associated with increased LGI (\u3b2 = 0.131; 95% CI, 0.089\u20130.174 for the highest versus lowest quintile of DII) after adjusting for age, sex, lifestyle, prevalence of chronic diseases, and health conditions. A higher DII score also was positively associated with each single biomarker of inflammation included in the INFLA-score, unhealthy behaviors (smoking, sedentary lifestyle), and insulin. Conclusions: Higher DII scores, indicating greater inflammatory potential of the diet, were directly associated with LGI, as measured by a composite score of plasma and cellular biomarkers of inflammation. These findings are consistent with the contributing role of diet-mediated inflammation in increasing risk for inflammation-related chronic diseases

Reduced mortality risk by a polyphenol-rich diet: An analysis from the Moli-sani study

Objectives: The effect of the polyphenol content of the human diet on mortality risk is not yet fully understood. The aim of this study was to evaluate the association of a polyphenol-rich diet with mortality rate and a possible mediation effect by inflammation, in what we believe to be a novel, holistic approach. Methods: We analyzed 21 302 participants (10 980 women and 10 322 men, aged 6535 y) from the Moli-sani cohort. The participants were followed up for a median of 8.3 y. The European Prospective Investigation into Cancer and Nutrition food frequency questionnaire (FFQ) was used for dietary assessment. Flavonol, flavone, flavanone, flavanol, anthocyanin, isoflavone, and lignan intakes were calculated using European Food Information Resource\u2014Bioactive Substances in Food Information Systems and the polyphenol antioxidant content (PAC)-score was constructed to assess the total content of these nutrients in the diet. Results: Participants included in the highest quintile of intake of various polyphenol classes and subclasses presented a significant lower all-cause mortality risk compared with those in the lowest group of consumption (hazard ratio [HR] < 1; P < 0.05). Cox regression analyses adjusted for potential confounders indicated that participants in higher quintiles of PAC-score had lower all-cause mortality risk (HR <1; P < 0.05). When cause-specific mortality rates were considered, similar effects were observed for cardiocerebrovascular and cancer mortality (HR <1; P < 0.05). Conclusions: The polyphenol content of the diet was associated with reduced mortality risk in a Mediterranean population, possibly through an antiinflammatory mechanism

Mean platelet volume is associated with lower risk of overall and non-vascular mortality in a general population: Results from the Moli-sani study

Larger mean platelet volume (MPV) has been associated with adverse health outcomes in high-risk populations or patients with cardiovascular disease (CVD). We tested the association of MPV with mortality in a prospective cohort study including 17,402 subjects randomly recruited from an adult general population within the Moli-sani study (2005-2010). Two distinct subgroups (with or without CVD at baseline) were subsequently analysed. Hazard ratios (HR) were calculated using multivariable Cox-proportional hazard models. Over a median follow up of eight years (137,547 person-years), 925 all-cause deaths occurred (330 vascular, 351 cancer and 244 other deaths). In a multivariable model, the highest MPV quintile (mean MPV=10.0 fL), as compared to the lowest one, was associated with reduced risk of overall mortality (HR=0.79; 95 % confidence interval 0.64-0.98), cancer death (HR=0.70; 0.49-1.00) and death from other non-vascular/non cancer causes (HR=0.55; 0.36-0.84) but not with vascular mortality. The inverse association with overall death appeared even stronger in the subgroup without CVD at baseline (HR=0.64; 0.50-0.81). In contrast, within 920 subjects reporting a previous CVD event, larger MPV was associated with higher risk of total mortality (HR=1.69; 1.05-2.72; p for interaction=0.048) and with a trend of risk for other cause-specific deaths. In conclusion, larger MPV is associated with lower risk of overall and non-vascular death in subjects apparently free from CVD, but appears to be a predictive marker of death in patients with CVD history. The latter is a likely effect modifier of the association between MPV and death

Moderate Alcohol Consumption Is Associated With Lower Risk for Heart Failure But Not Atrial Fibrillation

Objectives The aim of this study was to assess the hypothesis that alcohol consumption is associated with onset of atrial fibrillation (AF) and/or heart failure (HF). Background The connection between ethanol intake and AF or HF remains controversial. Methods The study population was 22,824 AF- or HF-free subjects (48% men, age \ue2\u89\ua535 years) randomly recruited from the general population included in the Moli-sani study, for whom complete data on HF, AF, and alcohol consumption were available. The cohort was followed up to December 31, 2015, for a median of 8.2 years (183,912 person-years). Incident cases were identified through linkage to the Molise regional archive of hospital discharges. Hazard ratios were calculated using Cox proportional hazard models and cubic spline regression. Results A total of 943 incident cases of HF and 554 of AF were identified. In comparison with never drinkers, both former and occasional drinkers showed comparable risk for developing HF. Drinking alcohol in the range of 1 to 4 drinks/day was associated with a lower risk for HF, with a 22% maximum risk reduction at 20 g/day, independent of common confounders. In contrast, no association of alcohol consumption with onset of AF was observed. Very similar results were obtained after restriction of the analyses to regular or only wine drinkers or according to sex, age, social status, or adherence to the Mediterranean diet. Conclusions Consumption of alcohol in moderation was associated with a lower incidence of HF but not with development of AF