Blood type ABO and the cytokine profile of follicular fluid in women undergoing IVF/ET

OBJECTIVES

ABO blood type was hypothesised to be related to a number of infertility processes. There is still an open debate on ABO blood group's incompatibility and infertility. It was associated with ovarian reserve in women with subfertility. There is still not enough information on the influence of blood type and the immunology of follicular fluid (FF).

MATERIAL AND METHODS

78 patients were selected, who underwent in vitro fertilization (IVF) between April 2021 and January 2022. FF samples from each individual patient were taken on the day of ovarian puncture and stored at -80°C until immunological assessment. Concentration of chosen interleukins - IL-1α, IL-2, IL-4, IL-5, IL-6, IL-8 IL-10, IL-15, IL-1β, IL-18, IFN, LIF, TNFα, GCSF and PIBF-1 were measured using commercially available ELISA kits.

RESULTS

All assessed cytokines were present in the FF of exanimated patients. The concentration was compared to the blood type ABO of all women undergoing in vitro fertilization. No statistical relevance was found between blood type ABO and the concentration of GCSF, PIBF1, LIF, IL-15, IL-5, IL-8, IL-1 alfa, IL-1 beta, INF gamma, IL-2HS, IL-4HS, IL-6HS, IL-10HS in the FF obtained during ovarian puncture (p > 0,05). There was no statistically significant correlation between blood type ABO and the quality of embryo, and the positive pregnancy test in patients undergoing IVF/ET.

CONCLUSIONS

The blood type ABO does not influence the wide cytokine profile of FF obtained during ovarian puncture in women with infertility of different origin, as well as embryo quality and pregnancy rate.

Copper drives remodeling of metabolic state and progression of clear cell renal cell carcinoma

Copper (Cu) is an essential trace element required for mitochondrial respiration. Late-stage clear cell renal cell carcinoma (ccRCC) accumulates Cu and allocates it to mitochondrial cytochrome c oxidase. We show that Cu drives coordinated metabolic remodeling of bioenergy, biosynthesis and redox homeostasis, promoting tumor growth and progression of ccRCC. Specifically, Cu induces TCA cycle-dependent oxidation of glucose and its utilization for glutathione biosynthesis to protect against H 2 O 2 generated during mitochondrial respiration, therefore coordinating bioenergy production with redox protection. scRNA-seq determined that ccRCC progression involves increased expression of subunits of respiratory complexes, genes in glutathione and Cu metabolism, and NRF2 targets, alongside a decrease in HIF activity, a hallmark of ccRCC. Spatial transcriptomics identified that proliferating cancer cells are embedded in clusters of cells with oxidative metabolism supporting effects of metabolic states on ccRCC progression. Our work establishes novel vulnerabilities with potential for therapeutic interventions in ccRCC. Accumulation of copper is associated with progression and relapse of ccRCC and drives tumor growth.Cu accumulation and allocation to cytochrome c oxidase (CuCOX) remodels metabolism coupling energy production and nucleotide biosynthesis with maintenance of redox homeostasis.Cu induces oxidative phosphorylation via alterations in the mitochondrial proteome and lipidome necessary for the formation of the respiratory supercomplexes. Cu stimulates glutathione biosynthesis and glutathione derived specifically from glucose is necessary for survival of Cu Hi cells. Biosynthesis of glucose-derived glutathione requires activity of glutamyl pyruvate transaminase 2, entry of glucose-derived pyruvate to mitochondria via alanine, and the glutamate exporter, SLC25A22. Glutathione derived from glucose maintains redox homeostasis in Cu-treated cells, reducing Cu-H 2 O 2 Fenton-like reaction mediated cell death. Progression of human ccRCC is associated with gene expression signature characterized by induction of ETC/OxPhos/GSH/Cu-related genes and decrease in HIF/glycolytic genes in subpopulations of cancer cells. Enhanced, concordant expression of genes related to ETC/OxPhos, GSH, and Cu characterizes metabolically active subpopulations of ccRCC cells in regions adjacent to proliferative subpopulations of ccRCC cells, implicating oxidative metabolism in supporting tumor growth.

Ductus venosus opens in high-risk pregnancies without signs of increased central venous pressure

OBJECTIVES

It has been belived that changes in diastolic blood velocities in the fetal ductus venosus were due to increased central venous pressure secondary to increased fetal heart strain during hypoxia or heart failure. There have been recent reports of changes in ductus venosus blood velocity without signs of increased fetal heart strain. The aim of this evaluation was to compare blood velocity in the right hepatic vein as a marker of increased central venous pressure in relationship to changes in ductus venosus blood velocity.

MATERIAL AND METHODS

Fifty pregnancies suspected of fetal growth resitriction were evaluated by Doppler ultrasound. Blood velocity was recorded in the right hepatic vein, ducus venosus and in the umbilical vein. Placental blood flow was also recorded in the uterine and umbilical arteries as well as the fetal middle cerebral artery.

RESULTS

Increased umbilical artery pulsatility index was recorded in 19 fetuses and 20 has signes of brain sparing according to recordings in the middle cerebral artery. Abnormal blood velocity in the ductus venosus was recorded in 5 fetuses, none of these fetuses had an abnormal pulsatility in the right hepatic vein.

CONCLUSIONS

Opening of the ductus venosus is not only related to fetal cardiac strain. This might indicate that the ductus venosus does not primarily open due to increased central venous pressure in moderate fetal hypoxia. Increased fetal cardiac strain might be a late event in the process of chronic fetal hypoxia.

Influence of gestational diabetes in twin pregnancy on the condition of newborns and early neonatal complications

OBJECTIVES

Diabetes mellitus is the most common metabolic complication in pregnancy and increasing worldwide. In Europe, it occurs in 3-5% of pregnant women. The rate of twin pregnancy has been increased similarly to gestational diabetes mellitus (GDM). Twin pregnancy is associated with a higher complication rate compared to singleton pregnancy. The growing prevalence of GDM and twin pregnancy has given rise to their increasing concurrent presentation.

MATERIAL AND METHODS

The retrospective analysis included 212 twin-pregnant patients. The analysis excluded cases of miscarriage and early fetal death in the first trimester of pregnancy. The influence of GDM on the condition of newborns and mothers after delivery was analyzed. For statistical analysis R 3.6.2 software was used.

RESULTS

No statistically significant relationship between GDM and Non-GDM group and periparturient complications was found. Birth weight was significantly higher in the GDM G2 group. Apgar Score was the lowest in the GDM G1 group. In the group of larger newborns of the GDMG1 group respiratory distress syndrome (RDS) , a higher incidence of second-degree intracranial bleeding and grade II of preterm retinopathy were observed. There was no statistically significant relationship between GDM G1, GDM G2 and other neonatal complications.

CONCLUSIONS

In summary, our results indicate that GDM in twin pregnancy does not increase the risk of cesarean section but increases some neonatal complications. In conclusion women with twin pregnancies complicated by GDM require specialist care during pregnancy and childbirth should take place in a third-level reference center.

UQlust: combining profile hashing with linear-time ranking for efficient clustering and analysis of big macromolecular data

Background

Advances in computing have enabled current protein and RNA structure prediction and molecular simulation methods to dramatically increase their sampling of conformational spaces. The quickly growing number of experimentally resolved structures, and databases such as the Protein Data Bank, also implies large scale structural similarity analyses to retrieve and classify macromolecular data. Consequently, the computational cost of structure comparison and clustering for large sets of macromolecular structures has become a bottleneck that necessitates further algorithmic improvements and development of efficient software solutions.

Results

uQlust is a versatile and easy-to-use tool for ultrafast ranking and clustering of macromolecular structures. uQlust makes use of structural profiles of proteins and nucleic acids, while combining a linear-time algorithm for implicit comparison of all pairs of models with profile hashing to enable efficient clustering of large data sets with a low memory footprint. In addition to ranking and clustering of large sets of models of the same protein or RNA molecule, uQlust can also be used in conjunction with fragment-based profiles in order to cluster structures of arbitrary length. For example, hierarchical clustering of the entire PDB using profile hashing can be performed on a typical laptop, thus opening an avenue for structural explorations previously limited to dedicated resources. The uQlust package is freely available under the GNU General Public License at https://github.com/uQlust.

Conclusion

uQlust represents a drastic reduction in the computational complexity and memory requirements with respect to existing clustering and model quality assessment methods for macromolecular structure analysis, while yielding results on par with traditional approaches for both proteins and RNAs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1381-2) contains supplementary material, which is available to authorized users.

Fast geometric consensus approach for protein model quality assessment

Model quality assessment (MQA) is an integral part of protein structure prediction methods that typically generate multiple candidate models. The challenge lies in ranking and selecting the best models using a variety of physical, knowledge-based, and geometric consensus (GC)-based scoring functions. In particular, 3D-Jury and related GC methods assume that well-predicted (sub-)structures are more likely to occur frequently in a population of candidate models, compared to incorrectly folded fragments. While this approach is very successful in the context of diversified sets of models, identifying similar substructures is computationally expensive since all pairs of models need to be superimposed using MaxSub or related heuristics for structure-to-structure alignment. Here, we consider a fast alternative, in which structural similarity is assessed using 1D profiles, e.g., consisting of relative solvent accessibilities and secondary structures of equivalent amino acid residues in the respective models. We show that the new approach, dubbed 1D-Jury, allows to implicitly compare and rank N models in O(N) time, as opposed to quadratic complexity of 3D-Jury and related clustering-based methods. In addition, 1D-Jury avoids computationally expensive 3D superposition of pairs of models. At the same time, structural similarity scores based on 1D profiles are shown to correlate strongly with those obtained using MaxSub. In terms of the ability to select the best models as top candidates 1D-Jury performs on par with other GC methods. Other potential applications of the new approach, including fast clustering of large numbers of intermediate structures generated by folding simulations, are discussed as well.

Transcriptome of Pneumocystis carinii during fulminate infection: carbohydrate metabolism and the concept of a compatible parasite

Members of the genus Pneumocystis are fungal pathogens that cause pneumonia in a wide variety of mammals with debilitated immune systems. Little is known about their basic biological functions, including life cycle, since no species can be cultured continuously outside the mammalian lung. To better understand the pathological process, about 4500 ESTS derived from sequencing of the poly(A) tail ends of P. carinii mRNAs during fulminate infection were annotated and functionally characterized as unassembled reads, and then clustered and reduced to a unigene set with 1042 members. Because of the presence of sequences from other microbial genomes and the rat host, the analysis and compression to a unigene set was necessarily an iterative process. BLASTx analysis of the unassembled reads (UR) vs. the Uni-Prot and TREMBL databases revealed 56% had similarities to existing polypeptides at E values of<or=10(-6), with the remainder lacking any significant homology. The most abundant transcripts in the UR were associated with stress responses, energy production, transcription and translation. Most (70%) of the UR had similarities to proteins from filamentous fungi (e.g., Aspergillus, Neurospora) and existing P. carinii gene products. In contrast, similarities to proteins of the yeast-like fungi, Schizosaccharomyces pombe and Saccharomyces cerevisiae, predominated in the unigene set. Gene Ontology analysis using BLAST2GO revealed P. carinii dedicated most of its transcripts to cellular and physiological processes ( approximately 80%), molecular binding and catalytic activities (approximately 70%), and were primarily derived from cell and organellar compartments (approximately 80%). KEGG Pathway mapping showed the putative P. carinii genes represented most standard metabolic pathways and cellular processes, including the tricarboxylic acid cycle, glycolysis, amino acid biosynthesis, cell cycle and mitochondrial function. Several gene homologs associated with mating, meiosis, and sterol biosynthesis in fungi were identified. Genes encoding the major surface glycoprotein family (MSG), heat shock (HSP70), and proteases (PROT/KEX) were the most abundantly expressed of known P. carinii genes. The apparent presence of many metabolic pathways in P. carinii, sexual reproduction within the host, and lack of an invasive infection process in the immunologically intact host suggest members of the genus Pneumocystis may be adapted parasites and have a compatible relationship with their mammalian hosts. This study represents the first characterization of the expressed genes of a non-culturable fungal pathogen of mammals during the infective process.

Enhanced recognition of protein transmembrane domains with prediction-based structural profiles

MOTIVATION

Membrane domain prediction has recently been re-evaluated by several groups, suggesting that the accuracy of existing methods is still rather limited. In this work, we revisit this problem and propose novel methods for prediction of alpha-helical as well as beta-sheet transmembrane (TM) domains. The new approach is based on a compact representation of an amino acid residue and its environment, which consists of predicted solvent accessibility and secondary structure of each amino acid. A recently introduced method for solvent accessibility prediction trained on a set of soluble proteins is used here to indicate segments of residues that are predicted not to be accessible to water and, therefore, may be 'buried' in the membrane. While evolutionary profiles in the form of a multiple alignment are used to derive these simple 'structural profiles', they are not used explicitly for the membrane domain prediction and the overall number of parameters in the model is significantly reduced. This offers the possibility of a more reliable estimation of the free parameters in the model with a limited number of experimentally resolved membrane protein structures.

RESULTS

Using cross-validated training on available sets of structurally resolved and non-redundant alpha and beta membrane proteins, we demonstrate that membrane domain prediction methods based on such a compact representation outperform approaches that utilize explicitly evolutionary profiles and multiple alignments. Moreover, using an external evaluation by the TMH Benchmark server we show that our final prediction protocol for the TM helix prediction is competitive with the state-of-the-art methods, achieving per-residue accuracy of approximately 89% and per-segment accuracy of approximately 80% on the set of high resolution structures used by the TMH Benchmark server. At the same time the observed rates of confusion with signal peptides and globular proteins are the lowest among the tested methods. The new method is available online at http://minnou.cchmc.org.

POLYVIEW: a flexible visualization tool for structural and functional annotations of proteins

The POLYVIEW visualization server can be used to generate protein sequence annotations, including secondary structures, relative solvent accessibilities, functional motifs and polymorphic sites. Two-dimensional graphical representations in a customizable format may be generated for both known protein structures and predictions obtained using protein structure prediction servers. POLYVIEW may be used for automated generation of pictures with structural and functional annotations for publications and proteomic on-line resources.

AVAILABILITY

http://polyview.cchmc.org.

[Evaluation of incidence of Chlamydia trachomatis infections among the group of infertile women diagnosed by laparoscopy, and based on properties of Chlamydia trachomatis in the cervical canal, peritoneal fluid and ovarian cyst puncture]

The number of 75 patients who underwent diagnostic et operative laparoscopy was analysed. The percentage of infection cases caused by Chlamydia Trachomatis was 9.33% investigations proved correlation between fallopian tube factor and infection. It seems that pelvic infection not always undergoes with infection of uterine cervix.

Hybrid Neural-global Minimization Method of Logical Rule Extraction

Methodology of extraction of optimal sets of logical rules using neural networks and global minimization procedures has been developed. Initial rules are extracted using density estimation neural networks with rectangular functions or multilayered perceptron (MLP) networks trained with constrained backpropagation algorithm, transforming MLPs into simpler networks performing logical functions. A constructive algorithm called CMLP2LN is proposed, in which rules of increasing specificity are generated consecutively by adding more nodes to the network. Neural rule extraction is followed by optimization of rules using global minimization techniques. Estimation of confidence of various sets of rules is discussed. The hybrid approach to rule extraction has been applied to a number of benchmark and real life problems with very good results.

[Laparoscopic evaluation of small pelvic adhesions in female patients treated for infertility]

The range and nature of adhesions found out by means of laparoscopy was analysed in patients diagnosed because of infertility. 38% of patients had laparotomy performed previously. Adhesions concerned 47% of the reproductive organ, although in nearly the same percentage intestine and greater omentum were involved. In 13 (31%) patients occurrence of endometriosis focus was discovered. In the area of Fallopian tube--ovary there were most often non-vascularized, thin adhesions and solid adhesions in the area of Douglas sinus.