Although a disease is defined as rare when it has a prevalence of less than 1:2000, the overall prevalence of rare diseases in the population is greater than 1%. Among potential organ donors, a similar frequency is observed. To date, guidelines have not been established, and operational decisions have been made empirically, case- by-case, based on the experience and expertise of clinicians. For this reason, the Italian Superior Health Council (CSS) has appointed a working Group to address "patients with a rare disease as potential organ donors," with the aim of devising recommendations for the management of transplant cases in which the donors have a rare disease. This group evaluated 493 diseases (10% of all rare diseases, including over 95% of patients with a rare disease) to deliver a technical report dealing with the suitability of organ donation and transplantation, with a focus on the organs most frequently used, including kidney, liver, heart, lung, and pancreas. This work has made it clear that a rare disease "per se" does not contraindicate organ donation at all. Indeed, in donors affected by a rare disease, almost 80% of the organs are suitable for transplantation, approximately 7% are unsuitable, and approximately 14% are suitable as non-standard with an acceptable risk.

Recent studies suggest a role for microRNAs in response to the mood stabilizer lithium and related phenotypes.

The HLA-DPB1 locus has been demonstrated to have a significant role on patients' outcome after allogeneic HSCT, and the so-called T-cell epitope (TCE) algorithm has been incorporated in international guidelines for the selection of unrelated donors. The purpose of the present study is to measure, through a national survey conducted on behalf of the Associazione Italiana di Immunogenetica e Biologia dei Trapianti (AIBT), the extent of awareness and use of HLA-DPB1 TCE-based algorithms during the donor search. 89% of the HLA laboratories answered to a short questionnaire and the results showed a progressive increase of the laboratories typing DPB1 in patients and their potential donors during the search (from 44% to 79% during the 2010-2019 period) as well as the application of a TCE-based algorithm for the donor choice whenever possible (from 24% to 65% during the same period). The DP-permissiveness status is detailed in the official HLA typing report by 12%, 32% and 50% of laboratories in 2010, 2015 and 2019, respectively. The present data indicate an encouraging raise in the awareness of the HLA-DPB1 role in unrelated donor selection; noteworthy, mentioning the TCE-based permissiveness status in the HLA typing report of each potential unrelated donor represents a notable mean to raise awareness among transplant physicians and to support them in their task of choosing the best donor. Nonetheless, despite the compelling evidence of the predictive ability of TCE-based algorithms, further efforts are still needed to extend its application to all transplant centers in Italy.

Motivation; This study presents a novel nonlinear model Which can Predict 10-Year carotid ultrasound image-based phenotypes by fusing nine traditional cardiovascular risk factors (ethnicity, gender, age, artery type, body mass index, hemoglobin Alc, hypertension, low-density lipoprotein, and smoking) with five types of carotid automated image phenotypes (three types of carotid intima-media thickness (IMT), wall variability, and total plaque area). Methodology: Two-step process was adapted: First, five baseline carotid irnage-based phenotypes were automatically measured using AtheroEdge (TM) (AtheroPoint (TM), CA, USA) system by two operators (novice arid experienced) and an expert. Second, based on the annual progression rates of clMT due to nine traditional cardiovascular risk factors, a novel nonlinear model was adapted for 10-year predictions of carotid phenotypes. Results: Institute review board (IRB) approved 204 Japanese patients' left/right common carotid artery (407 ultrasound scans) was collected with a mean age of 69 +/- 11 years. Age and hemoglobin were reported to have a high influence on the 10-year carotid phenotypes. Mean correlation coefficient (CC) between 10-year carotid image-based phenotype and age was improved by 39.35% in males and 25.38% in females. The area under the curves for the 10-year measurements of five phenotypes IMTave10yr, IMTmax(10yr), IMTmin10yr, IMTV10yr, and TPA(10yr) were 0.96, 0.94, 0.90, 1.0, and 1.0. Inter-operator variability between two operators showed significant CC (P < 0.0001). Conclusions: A nonlinear model was developed and validated by fusing nine conventional CV risk factors with current carotid image-based phenotypes for predicting the 10-year carotid ultrasound image-based phenotypes which may be used risk assessment.

Background Entropy is a thermodynamic variable statistically correlated with the disorder of a system. The hypothesis that entropy can be used to identify potentially unhealthy conditions was first suggested by Schrödinger, one of the founding fathers of quantum mechanics. Shannon later defined entropy as the quantity of information stored in a system. Shannon’s entropy has the advantage of being adaptable across a variety of disciplines, including genetic studies on complex immunogenetic systems such as the human leukocyte antigen (HLA) and killer-cell immunoglobulin-like receptor (KIR) systems. Methods In our study, entropy associated to the HLA and KIR systems was compared between a cohort of 619 Sardinian healthy controls and a group of 270 patients affected by multiple sclerosis (MS), the latter stratified into 81 patients with primary progressive multiple sclerosis (PPMS) and 189 patients with relapsing remitting multiple sclerosis (RRMS). Results The entropy associated to HLA four-loci haplotypes (A, B, C, DR) and combinations of two inhibitory KIR genes was significantly higher in patients affected by RRMS than in healthy controls. No significant differences were observed for patients with PPMS. By calculating the total HLA and KIR entropy ratio in each subject, it was possible to determine the individual risk of developing MS, particularly RRMS. Conclusions In addition to the standard statistical methods used to evaluate immunogenetic parameters associated to immune-mediated disease, the analysis of entropy measures the global disorder status deriving from these parameters. This innovative approach may represent a useful complementary tool to the risk assessment of immune-mediated disorders. Improved risk assessment is particularly important for family members of patients with MS. However, further investigation is warranted to confirm our findings and to evaluate the validity of the entropy-based method in other types of immune-mediated disorders.

Today, the 10-year cardiovascular risk largely relies on conventional cardiovascular risk factors (CCVRFs) and suffers from the effect of atherosclerotic wall changes. In this study, we present a novel risk calculator AtheroEdge Composite Risk Score (AECRS1.0), designed by fusing CCVRF with ultrasound image-based phenotypes. Ten-year risk was computed using the Framingham Risk Score (FRS), United Kingdom Prospective Diabetes Study 56 (UKPDS56), UKPDS60, Reynolds Risk Score (RRS), and pooled composite risk (PCR) score. AECRS1.0 was computed by measuring the 10-year five carotid phenotypes such as IMT (ave., max., min.), IMT variability, and total plaque area (TPA) by fusing eight CCVRFs and then compositing them. AECRS1.0 was then benchmarked against the five conventional cardiovascular risk calculators by computing the receiver operating characteristics (ROC) and area under curve (AUC) values with a 95% CI. Two hundred four IRB-approved Japanese patients’ left/right common carotid arteries (407 ultrasound scans) were collected with a mean age of 69 ± 11 years. The calculators gave the following AUC: FRS, 0.615; UKPDS56, 0.576; UKPDS60, 0.580; RRS, 0.590; PCRS, 0.613; and AECRS1.0, 0.990. When fusing CCVRF, TPA reported the highest AUC of 0.81. The patients were risk-stratified into low, moderate, and high risk using the standardized thresholds. The AECRS1.0 demonstrated the best performance on a Japanese diabetes cohort when compared with five conventional calculators.

The immunogenicity benefit of inactivated influenza vaccine (IIV) adjuvanted by squalene over non-adjuvanted aqueous IIV was explored in a meta-analysis involving 49 randomised trials published between 1999 and 2017, and 22,470 eligible persons of all age classes. Most vaccines contained 15 μg viral haemagglutinin per strain. Adjuvanted IIV mostly contained 9.75 mg squalene per dose. Homologous pre- and post-vaccination geometric mean titres (GMTs) of haemagglutination-inhibition (HI) antibody were recorded for 290 single influenza (sub-)type arms. The adjuvant effect was expressed as the ratio of post-vaccination GMTs between squalene-IIV and aqueous IIV (GMTR, 145 estimates). GMTRs > 1.0 favoured squalene-IIV over aqueous IIV. For all influenza (sub-)types, the adjuvant effect proved negatively associated with pre-vaccination GMT and mean age. The adjuvant effect appeared most pronounced in young children (mean age < 2.5 years) showing an average GMTR of 3.7 (95% CI: 2.5 to 5.5). With increasing age, GMTR values gradually decreased towards 1.4 (95% CI: 1.0 to 1.9) in older adults. Heterologous antibody titrations simulating mismatch between vaccine and circulating virus (30 GMTR estimates) again showed a larger adjuvant effect at young age. GMT values and their variances were converted to antibody-predicted protection rates using an evidence-based clinical protection curve. The adjuvant effect was expressed as the protection rate differences, which showed similar age patterns as corresponding GMTR values. However for influenza B, the adjuvant effect lasted longer than for influenza A, possibly due to a generally later influenza B virus exposure. Collectively, this meta-analysis indicates the highest benefit of squalene-IIV over aqueous IIV in young children and decreasing benefit with progressing age. This trend is similar for seasonal influenza (sub-)types and the 2009 pandemic strain, by both homologous and heterologous titration. The impact of pre-seasonal immunity on vaccine effectiveness, and its implications for age-specific vaccination recommendations, are discussed.

Wilson's disease (WD) is an autosomal recessive disorder which is caused by poor excretion of copper in mammalian cells. In this review, various issues such as effective characterization of ATP7B genes, scope of gene network topology in genetic analysis, pattern recognition using different computing approaches and fusion possibilities in imaging and genetic dataset are discussed vividly. We categorized this study into three major sections: (A) WD genetics, (B) diagnosis guidelines and (3) treatment possibilities. We addressed the scope of advanced mathematical modelling paradigms for understanding common genetic sequences and dominating WD imaging biomarkers. We have also discussed current state-of-the-art software models for genetic sequencing. Further, we hypothesized that involvement of machine and deep learning techniques in the context of WD genetics and image processing for precise classification of WD. These computing procedures signify changing roles of various data transformation techniques with respect to supervised and unsupervised learning models.

Introduction/Background BRCA 1 and 2 mutated women have a 40–85% lifetime risk of developing breast cancer (BC) and 16–64% risk of ovarian cancer (OC). Literature data evaluating the role of pregnancies on risk of BC and OC in BRCA mutated patients are controversial. The objective of the present study is to evaluate the impact of pregnancy on cancer risk in a cohort of BRCA1/2 mutated patients. Methodology This is a retrospective study, conducted on a sample of 106 female patients, 83 (78%) with BRCA 1 mutation and 23 (22%) BRCA 2, involved in a follow-up program of two different divisions of the University of Cagliari. We evaluated the number of BC and OC and the age of cancer diagnosis correlating to the number of pregnancies. Results Of 106 patients, 39 (36,8%) patients did´t have diagnosis of cancer and 67 (63,2%) developed cancer: 48 BC, 12 OC and 7 both. Thirthy-nine (36,8%) women didn´t have pregnancy, 21 (19,8%) had one pregnancy, 27 (25,4%) had two pregnancies and 19 (17,9%) more than two pregnancies. The median age at the cancer diagnosis was 43,3 years (range 19–69 years). We found a significative difference on the age of cancer diagnosis in patients with two or more pregnancies (p-value <0,001). Patients with no or one pregnancy developed cancer at a median age of 38,3 years (range 19–59 ys), patients with two or more pregnancies at 49,5 ys (29–69 ys). Conclusion Our results seems to suggest a protective effect of pregnancy on the development of cancer in BRCA mutated women. Data show that two or more pregnancies significantly delay the development breast and ovarian cancer. Disclosure Nothing to disclose.

Lithium is the mainstay in the maintenance of bipolar disorder (BD) and the most efficacious pharmacological treatment in suicide prevention. Nevertheless, its use is hampered by a high interindividual variability and important side effects. Genetic and epigenetic factors have been suggested to modulate lithium response, but findings so far have not allowed identifying molecular targets with predictive value. In this study we used next generation sequencing to measure genome-wide miRNA expression in lymphoblastoid cell lines from BD patients excellent responders (ER, n = 12) and non-responders (NR, n = 12) to lithium. These data were integrated with microarray genome-wide expression data to identify pairs of miRNA/mRNA inversely and significantly correlated. Significant pairs were prioritized based on strength of association and in-silico miRNA target prediction analyses to select candidates for validation with qRT-PCR. Thirty-one miRNAs were differentially expressed in ER vs. NR and inversely correlated with 418 genes differentially expressed between the two groups. A total of 331 of these correlations were also predicted by in-silico algorithms. miR-320a and miR-155-3p, as well as three of their targeted genes (CAPNS1 (Calpain Small Subunit 1) and RGS16 (Regulator of G Protein Signaling 16) for miR-320, SP4 (Sp4 Transcription Factor) for miR-155-3p) were validated. These miRNAs and mRNAs were previously implicated in psychiatric disorders (miR-320a and SP4), key processes of the central nervous system (CAPNS1, RGS16, SP4) or pathways involved in mental illnesses (miR-155-3p). Using an integrated approach, we identified miRNAs and their targeted genes potentially involved in lithium response in BD.

As a very basic flight mode, ascending flight is obviously of great importance to all kinds of manmade and natural fliers. Yet, for the most commonly seen fliers – insects, researches on this flight mode are rare. In this paper, we combined both experimental measurements and numerical simulations to investigate the kinematical characteristics, aerodynamic performance and power requirement of ascending flight in fruit flies (Drosophila virilis). The flies ascend at an advance ratio of about 0.12. The most significant characteristic of ascending flight is larger stroke amplitude compared to hovering, while the other kinematics is very similar. From an aerodynamics point of view, this increased stroke amplitude is needed to overcome the negative effects of "downwash flow", caused by the upward motion of the fly. Same as hovering, the ascending fruit flies utilize delayed stall and fast pitching-up mechanisms to generate the majority of the lift required for balancing the weight and body drag. By using a larger stroke-amplitude to overcome the negative effects of "downwash flow", larger energy cost (about 20%) than that of equivalent hovering is required.

Purpose of the Review Rheumatoid arthritis (RA) is a chronic, autoimmune disease which may result in a higher risk of cardiovascular (CV) events and stroke. Tissue characterization and risk stratification of patients with rheumatoid arthritis are a challenging problem. Risk stratification of RA patients using traditional risk factor–based calculators either underestimates or overestimates the CV risk. Advancements in medical imaging have facilitated early and accurate CV risk stratification compared to conventional cardiovascular risk calculators. Recent Finding In recent years, a link between carotid atherosclerosis and rheumatoid arthritis has been widely discussed by multiple studies. Imaging the carotid artery using 2-D ultrasound is a noninvasive, economic, and efficient imaging approach that provides an atherosclerotic plaque tissue–specific image. Such images can help to morphologically characterize the plaque type and accurately measure vital phenotypes such as media wall thickness and wall variability. Intelligence-based paradigms such as machine learning– and deep learning–based techniques not only automate the risk characterization process but also provide an accurate CV risk stratification for better management of RA patients. Summary This review provides a brief understanding of the pathogenesis of RA and its association with carotid atherosclerosis imaged using the B-mode ultrasound technique. Lacunas in traditional risk scores and the role of machine learning–based tissue characterization algorithms are discussed and could facilitate cardiovascular risk assessment in RA patients. The key takeaway points from this review are the following: (i) inflammation is a common link between RA and atherosclerotic plaque buildup, (ii) carotid ultrasound is a better choice to characterize the atherosclerotic plaque tissues in RA patients, and (iii) intelligence-based paradigms are useful for accurate tissue characterization and risk stratification of RA patients.

BACKGROUND:Behçet's disease (BD) is a polygenic immune-mediated disorder characterized by a close association with the HLA-B*51 allele. The HLA region has a strong linkage disequilibrium (LD) and carries several genetic variants (e.g. MIC-A, TNF-α genes) identified as associated to BD because of their LD with HLA-B*51. In fact, the HLA-B*51 is inherited as part of extended HLA haplotypes which are well preserved in patients with BD. Sardinian population is highly differentiated from other Mediterranean populations because of a distinctive genetic structure with very highly preserved HLA haplotypes.PATIENTS AND METHODS:In order to identify other genes of susceptibility to BD within the HLA region we investigated the distribution of human Allograft Inflammatory Factor-1 (AIF-1) gene variants among BD patients and healthy controls from Sardinia. Six (rs2736182; rs2259571; rs2269475; rs2857597; rs13195276; rs4711274) AIF-1 single nucleotide polymorphisms (SNPs) and related extended haplotypes have been investigated as well as their LD within the HLA region and with HLA-B*51. Overall, 64 BD patients, 43 HLA-B*51 positive healthy controls (HC) and 70 random HC were enrolled in the study.RESULTS:HLA-B*51 was the only allele with significantly higher frequency (pc = 0.0021) in BD patients (40.6%) than in HC (9.8%). The rs2259571T AIF-1 variant had a significantly reduced phenotypic, but not allelic frequency in BD patients (72.1%; pc = 0.014) compared to healthy population (91.3%). That was likely due to the LD between HLA-B*51 and rs2259571G (pc = 9E-5), even though the rs2259571G distribution did not significantly differ between BD patients and HC.CONCLUSION:No significant difference in distribution of AIF-1 SNPs haplotypes was observed between BD patients and HC and between HLA-B*51 positive BD patients and HLA-B*51 positive HC. Taken together, these results suggest that AIF-1 gene is not associated with susceptibility to BD in Sardinia.

Introduction: Human leukocyte antigen G (HLA-G) is an HLA class Ib molecule with immunomodulatory, immunosuppressive and tolerance-inducing functions. Altered HLA-G expression has been observed in various autoimmune diseases but no data exist in autoimmune hepatitis.