Advanced molecular approaches in male infertility diagnosis†.

In the recent years a special attention has been given to a major health concern namely to male infertility, defined as the inability to conceive after 12 months of regular unprotected sexual intercourse, taken into account the statistics that highlight that sperm counts have dropped by 50-60% in recent decades. According to the WHO, infertility affects approximately 9% of couples globally, and the male factor is believed to be present in roughly 50% of cases, with exclusive responsibility in 30%. The aim of this article is to present an evidence-based approach for diagnosing male infertility that includes finding new solutions for diagnosis and critical outcomes, retrieving up-to-date studies and existing guidelines. The diverse factors that induce male infertility generated in a vast amount of data that needed to be analyzed by a clinician before a decision could be made for each individual. Modern medicine faces numerous obstacles as a result of the massive amount of data generated by the molecular biology discipline. To address complex clinical problems, vast data must be collected, analyzed, and used, which can be very challenging. The use of artificial intelligence (AI) methods to create a decision support system can help predict the diagnosis and guide treatment for infertile men, based on analysis of different data as environmental and lifestyle, clinical (sperm count, morphology, hormone testing, karyotype, etc.), and "omics" bigdata. Ultimately, the development of AI algorithms will assist clinicians in formulating diagnosis, making treatment decisions, and predicting outcomes for assisted reproduction techniques.

Functional variants of ERAP1 gene are associated with HLA-B27 positive spondyloarthritis.

We investigated two nonsynonymous variants (rs30187 and rs27044) of ERAP1 gene in HLA-B27 positive individuals (150 spondyloarthritis and 108 controls) and in general ankylosing spondylitis (AS) patients (n = 137) vs random controls (n = 139). Both single nucleotide polymorphisms (SNPs) were associated with the risk of spondyloarthritis [odds ratio (OR) 1.80, 95% confidence interval (CI) 1.24-2.62, P = 0.001 for rs30187, OR 1.58, 95% CI 1.07-2.34, P = 0.02 for rs27044]. The CC haplotype was a protective factor (P = 0.002), while the TG haplotype was a risk factor (P = 0.01) for spondyloarthritis. The SNP rs30187 was also associated with the risk of HLA-B27+ AS. For the general group of AS, the carriers of minor alleles showed an increased risk for the disease (OR 1.92, 95% CI 1.17-3.13 for rs30187, OR 1.74, 95% CI 1.08-2.80 for rs27044). This is the first study that shows the association of ERAP1 gene variants and haplotypes with HLA-B27 positive spondyloarthritis.

HLA-C locus and genetic susceptibility to psoriatic arthritis in Romanian population.

We determined the distribution of human leukocyte antigen-C (HLA-C) allelic groups in a cohort of psoriatic arthritis (PsA) patients and a control population of Romanian ethnicity. A nominal association of HLA-C*06 with susceptibility to PsA was observed [P = 0.014, p(corr) > 0.05, odds ratio (OR) 2.1, 95% confidence interval (CI) 1.08-4.46]. When subanalyzing data according to PsA clinical phenotypes, association was noticed between HLA-C*06 and PsA with psoriasis onset before 40 years (p(corr) = 0.013, OR 3.7, 95% CI 1.58-9). This first report from Romania confirmed the association of HLA-C*06 with type I psoriasis in PsA patients. Other study findings, such as the relationship between HLA-C*06 and spondylitis or the protective effect of HLA-C*07 for the polyarthritis clinical phenotype of PsA, are of preliminary character and require verification.

Distribution of HLA-B27 in Romanian spondyloarthritides patients.

The analysis of 310 Romanian spondyloarthritides patients confirmed the association of the HLA-B27 marker with the susceptibility to different diseases of this group. For ankylosing spondylitis, the HLA-B27 frequency in Romanian patients (72.1%) was similar to that found in several regions in the Mediterranean area.

Optimization of immunochemical methods for intracellular protein detection.

Given the possibility that cell kinetics and p53 status may be important determinants of chemotherapeutical efficacy, the aim of the present study was to determine the optimal methods and conditions for qualitative and quantitative intracellular proteins detection. Bradford assay is the better choice for protein concentration detection because it is more sensitive and more rapid than Sheffield assay despite the fact that it utilizes a higher amount of samples. The direct staining method for flow-cytometrical detection of intracellular proteins is more rapid as compared to the indirect staining one, also providing information about protein expression during cell cycle phases, but it is low sensitive for protein expression estimation and is prohibitive for masked intracellular proteins like PCNA. More than that, it can be performed with both fixed and freshly isolated cells as compared to the indirect staining method, but the last one provides advantages by signal amplification and by its availability of using it for a large number of intracellular proteins detection.