Ancient DNA: genomic amplification of Roman and medieval bovine bones.

Cattle remains (bones and teeth) of both roman and medieval age were collected in the archaeological site of Ferento (Viterbo, Italy) with the aim of extracting and characterising nucleic acids. Procedures to minimize contamination with modern DNA and to help ancient DNA (aDNA) preservation of the archaeological remains were adopted. Different techniques to extract aDNA (like Phenol/chloroform extraction) from bovine bones were tested to identify the method that applies to the peculiar characteristics of the study site. Currently, aDNA investigation is mainly based on mtDNA, due to the ease of amplification of the small and high-copied genome and to its usefulness in evolutionary studies. Preliminary amplification of both mitochondrial and nuclear aDNA fragments from samples of Roman and medieval animals were performed and partial specific sequences of mitochondrial D-loop as well as of nuclear genes were obtained. The innovative amplification of nuclear aDNA could enable the analysis of genes involved in specific animal traits, giving insights of ancient economic and cultural uses, as well as providing information on the origin of modern livestock population

A machine-learning based bio-psycho-social model for the prediction of non-obstructive and obstructive coronary artery disease

Background: Mechanisms of myocardial ischemia in obstructive and non-obstructive coronary artery disease (CAD), and the interplay between clinical, functional, biological and psycho-social features, are still far to be fully elucidated. Objectives: To develop a machine-learning (ML) model for the supervised prediction of obstructive versus non-obstructive CAD. Methods: From the EVA study, we analysed adults hospitalized for IHD undergoing conventional coronary angiography (CCA). Non-obstructive CAD was defined by a stenosis < 50% in one or more vessels. Baseline clinical and psycho-socio-cultural characteristics were used for computing a Rockwood and Mitnitski frailty index, and a gender score according to GENESIS-PRAXY methodology. Serum concentration of inflammatory cytokines was measured with a multiplex flow cytometry assay. Through an XGBoost classifier combined with an explainable artificial intelligence tool (SHAP), we identified the most influential features in discriminating obstructive versus non-obstructive CAD. Results: Among the overall EVA cohort (n = 509), 311 individuals (mean age 67 ± 11 years, 38% females; 67% obstructive CAD) with complete data were analysed. The ML-based model (83% accuracy and 87% precision) showed that while obstructive CAD was associated with higher frailty index, older age and a cytokine signature characterized by IL-1β, IL-12p70 and IL-33, non-obstructive CAD was associated with a higher gender score (i.e., social characteristics traditionally ascribed to women) and with a cytokine signature characterized by IL-18, IL-8, IL-23. Conclusions: Integrating clinical, biological, and psycho-social features, we have optimized a sex- and gender-unbiased model that discriminates obstructive and non-obstructive CAD. Further mechanistic studies will shed light on the biological plausibility of these associations. Clinical trial registration: NCT02737982

Acute Delta Hepatitis in Italy spanning three decades (1991–2019): Evidence for the effectiveness of the hepatitis B vaccination campaign

Updated incidence data of acute Delta virus hepatitis (HDV) are lacking worldwide. Our aim was to evaluate incidence of and risk factors for acute HDV in Italy after the introduction of the compulsory vaccination against hepatitis B virus (HBV) in 1991. Data were obtained from the National Surveillance System of acute viral hepatitis (SEIEVA). Independent predictors of HDV were assessed by logistic-regression analysis. The incidence of acute HDV per 1-million population declined from 3.2 cases in 1987 to 0.04 in 2019, parallel to that of acute HBV per 100,000 from 10.0 to 0.39 cases during the same period. The median age of cases increased from 27 years in the decade 1991-1999 to 44 years in the decade 2010-2019 (p < .001). Over the same period, the male/female ratio decreased from 3.8 to 2.1, the proportion of coinfections increased from 55% to 75% (p = .003) and that of HBsAg positive acute hepatitis tested for by IgM anti-HDV linearly decreased from 50.1% to 34.1% (p < .001). People born abroad accounted for 24.6% of cases in 2004-2010 and 32.1% in 2011-2019. In the period 2010-2019, risky sexual behaviour (O.R. 4.2; 95%CI: 1.4-12.8) was the sole independent predictor of acute HDV; conversely intravenous drug use was no longer associated (O.R. 1.25; 95%CI: 0.15-10.22) with this. In conclusion, HBV vaccination was an effective measure to control acute HDV. Intravenous drug use is no longer an efficient mode of HDV spread. Testing for IgM-anti HDV is a grey area requiring alert. Acute HDV in foreigners should be monitored in the years to come

Infected pancreatic necrosis: outcomes and clinical predictors of mortality. A post hoc analysis of the MANCTRA-1 international study

: The identification of high-risk patients in the early stages of infected pancreatic necrosis (IPN) is critical, because it could help the clinicians to adopt more effective management strategies. We conducted a post hoc analysis of the MANCTRA-1 international study to assess the association between clinical risk factors and mortality among adult patients with IPN. Univariable and multivariable logistic regression models were used to identify prognostic factors of mortality. We identified 247 consecutive patients with IPN hospitalised between January 2019 and December 2020. History of uncontrolled arterial hypertension (p = 0.032; 95% CI 1.135-15.882; aOR 4.245), qSOFA (p = 0.005; 95% CI 1.359-5.879; aOR 2.828), renal failure (p = 0.022; 95% CI 1.138-5.442; aOR 2.489), and haemodynamic failure (p = 0.018; 95% CI 1.184-5.978; aOR 2.661), were identified as independent predictors of mortality in IPN patients. Cholangitis (p = 0.003; 95% CI 1.598-9.930; aOR 3.983), abdominal compartment syndrome (p = 0.032; 95% CI 1.090-6.967; aOR 2.735), and gastrointestinal/intra-abdominal bleeding (p = 0.009; 95% CI 1.286-5.712; aOR 2.710) were independently associated with the risk of mortality. Upfront open surgical necrosectomy was strongly associated with the risk of mortality (p < 0.001; 95% CI 1.912-7.442; aOR 3.772), whereas endoscopic drainage of pancreatic necrosis (p = 0.018; 95% CI 0.138-0.834; aOR 0.339) and enteral nutrition (p = 0.003; 95% CI 0.143-0.716; aOR 0.320) were found as protective factors. Organ failure, acute cholangitis, and upfront open surgical necrosectomy were the most significant predictors of mortality. Our study confirmed that, even in a subgroup of particularly ill patients such as those with IPN, upfront open surgery should be avoided as much as possible. Study protocol registered in ClinicalTrials.Gov (I.D. Number NCT04747990)

GWAS meta-analysis of over 29,000 people with epilepsy identifies 26 risk loci and subtype-specific genetic architecture

Epilepsy is a highly heritable disorder affecting over 50 million people worldwide, of which about one-third are resistant to current treatments. Here we report a multi-ancestry genome-wide association study including 29,944 cases, stratified into three broad categories and seven subtypes of epilepsy, and 52,538 controls. We identify 26 genome-wide significant loci, 19 of which are specific to genetic generalized epilepsy (GGE). We implicate 29 likely causal genes underlying these 26 loci. SNP-based heritability analyses show that common variants explain between 39.6% and 90% of genetic risk for GGE and its subtypes. Subtype analysis revealed markedly different genetic architectures between focal and generalized epilepsies. Gene-set analyses of GGE signals implicate synaptic processes in both excitatory and inhibitory neurons in the brain. Prioritized candidate genes overlap with monogenic epilepsy genes and with targets of current antiseizure medications. Finally, we leverage our results to identify alternate drugs with predicted efficacy if repurposed for epilepsy treatment

Efficient CFD evaluation of the NPSH for centrifugal pumps

This paper provides the reader with guidelines for the definition of coarse but effective meshes on reduced computational domains in order to accurately evaluate the drop curves and the NPSH3%of centrifugal pumps by means of CFD. The procedure has been validated against experimental data, carried out on single stages of multi-stage centrifugal pumps, and numerical data obtained by a monodimensional model. Thanks to the proposed procedure, without any detriment to the accuracy, a significant computational cost reduction has been experienced with respect to simulations performed on complete stages

Slip Factor Correction in 1-D Performance Prediction Model for PaTs

In recent years, pumps operated as turbines (PaTs) have been gaining the interest of industry and academia. For instance, PaTs can be effectively used in micro hydropower plants (MHP) and water distribution systems (WDS). Therefore, further efforts are necessary to investigate their fluid dynamic behavior. Compared to conventional turbines, a lower number of blades is employed in PaTs, lowering their capability to correctly guide the flow, hence reducing the Euler’s work; thus, the slip phenomenon cannot be neglected at the outlet section of the runner. In the first part of the paper, the slip phenomenon is numerically investigated on a simplified geometry, evidencing the dependency of the lack in guiding the flow on the number of blades. Then, a commercial double suction centrifugal pump, characterized by the same specific speed, is considered, evaluating the dependency of the slip on the flow rate. In the last part, a slip factor correlation is introduced based on those CFD simulations. It is shown how the inclusion of this parameter in a 1-D performance prediction model allows us to reduce the performance prediction errors with respect to experiments on a pump with a similar specific speed by 5.5% at design point, compared to no slip model, and by 8% at part-loads, rather than using Busemann and Stodola formulas

Development of a 1-D Performance Prediction Model for Pumps as Turbines

Pumps as turbines (PaTs) are becoming more and more attractive in Small Hydropower. PaTs are considered a cost-effective alternative to conventional turbines as long as their turbine characteristic curves can be predicted. Indeed, manufacturers need of a tool that could support them to predict the turbine mode performance from the knowledge of pump characteristics, in order to be competitive on the market. In this framework, a new 1-D prediction model is proposed for manufacturers in order to predict the entire characteristic of a PaT, by taking into account detailed geometrical information of the machine, hydraulic losses and the influence of the flow deflection with respect to the outlet blade angle of the runner during turbine operation

How to Improve the Performance Prediction of a Pump as Turbine by Considering the Slip Phenomenon

Nowadays Pumps working as Turbines (PaT) are devices widely used to perform energy recovery in hydraulic grids, thus improving their overall efficiency, and to build small hydropower plants. In this work, a centrifugal pump has been numerically investigated in turbine operating mode by means of the open-source CFD code OpenFOAM with emphasis on the flow field at the runner outlet. Due to the reduced number of blades in a PaT, the mean outlet relative velocity angle differs from the blade angle. In order to account for this phenomenon, the slip factor is introduced. The slip factor is investigated and its application to a 1D model is shown in order to highlight the improvement in predicting the characteristic curve of a centrifugal pump used in reverse mode as a turbine (PaT) especially at its part-load