Serum levels of stem cell factor for predicting embryo quality.

We evaluated whether serum stem cell factor (s-SCF) levels just prior to ovulation induction could indicate the ability to develop a top-quality (TQ) blastocyst by day 5. We investigated patients with normal ovarian reserve (NOR), polycystic ovary syndrome (PCOS), diminished ovarian reserve (DOR), or mild endometriosis. Our pilot research suggests a correlation between s-SCF levels and the ability to form TQ blastocysts in patients with mild endometriosis. This significant statistical difference (p < 0.05) was noted between mild endometriosis patients for whom a TQ blastocyst was obtained and those for whom it was not possible, as measured on the 8th day of stimulation and the day of oocyte retrieval. The mean SCF levels in the serum of these women on the 8th day were at 28.07 (± 2.67) pg/ml for the TQ subgroup and 53.32 (± 16.02) pg/ml for the non-TQ subgroup (p < 0.05). On oocyte retrieval day it was 33.47 (± 3.93) pg/ml and 52.23 (± 9.72) pg/ml (p < 0.05), respectively.

Evaluating the risk of endometriosis based on patients' self-assessment questionnaires.

BACKGROUND: Endometriosis is a condition that significantly affects the quality of life of about 10 % of reproductive-aged women. It is characterized by the presence of tissue similar to the uterine lining (endometrium) outside the uterus, which can lead lead scarring, adhesions, pain, and fertility issues. While numerous factors associated with endometriosis are documented, a wide range of symptoms may still be undiscovered. METHODS: In this study, we employed machine learning algorithms to predict endometriosis based on the patient symptoms extracted from 13,933 questionnaires. We compared the results of feature selection obtained from various algorithms (i.e., Boruta algorithm, Recursive Feature Selection) with experts' decisions. As a benchmark model architecture, we utilized a LightGBM algorithm, along with Multivariate Imputation by Chained Equations (MICE) and k-nearest neighbors (KNN), for missing data imputation. Our primary objective was to assess the model's performance and feature importance compared to existing studies. RESULTS: We identified the top 20 predictors of endometriosis, uncovering previously overlooked features such as Cesarean section, ovarian cysts, and hernia. Notably, the model's performance metrics were maximized when utilizing a combination of multiple feature selection methods. Specifically, the final model achieved an area under the receiver operator characteristic curve (AUC) of 0.85 on the training dataset and an AUC of 0.82 on the testing dataset. CONCLUSIONS: The application of machine learning in diagnosing endometriosis has the potential to significantly impact clinical practice, streamlining the diagnostic process and enhancing efficiency. Our questionnaire-based prediction approach empowers individuals with endometriosis to proactively identify potential symptoms, facilitating informed discussions with healthcare professionals about diagnosis and treatment options.

Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data.

Controlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient's genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched to groups of various MII oocyte counts using ranking, correspondence analysis, and self-organizing map methods. The gradient boosting machine technique was used to train models on a clinical dataset of 8,574 or a clinical-genetic dataset of 516 ovarian stimulations. The clinical-genetic model predicted the number of MII oocytes better than that based on clinical data. Anti-Müllerian hormone level and antral follicle count were the two most important predictors while a genetic feature consisting of sequence variants in the GDF9, LHCGR, FSHB, ESR1, and ESR2 genes was the third. The combined contribution of genetic features important for the prediction was over one-third of that revealed for anti-Müllerian hormone. Predictions of our clinical-genetic model accurately matched individuals' actual outcomes preventing over- or underestimation. The genetic data upgrades the personalized prediction of ovarian stimulation outcomes, thus improving the in vitro fertilization procedure.

Aberrant Mannosylated and Highly Fucosylated Glycoepitopes of Prostatic Acid Phosphatase as Potential Ligands for Dendritic-Cell Specific ICAM-Grabbing Nonintegrin (DC-SIGN) in Human Seminal Plasma-A Step towards Explaining Idiopathic Infertility.

Semen prostatic acid phosphatase (PAP) has been proposed as an endogenous ligand for dendritic cell-specific ICAM-3-grabbing nonintegrin (DC-SIGN), which plays a critical immuno-modulating role in maintaining homeostasis in the female reproductive tracts. In the current study, we assumed that semen PAP bears a set of fucosylated and mannosylated glycans, which may mediate the efficient binding of PAP to DC-SIGN. To investigate this hypothesis, we developed ELISA assays using Galanthus nivalis and Lotus tetragonolobus lectins capable of binding mannose-containing glycans or LewisX and LewisY motifs, respectively. In our assay with Galanthus nivalis, we detected that the relative reactivity of PAP mannose-presenting glycans in the normozoospermic idiopathic group was significantly higher than in the asthenozoospermic, oligozoospermic and oligoasthenozoospermic groups. Simultaneously, we observed slight differences in the relative reactivities of PAP glycans with Lotus tetragonolobus lectin among groups of patients with abnormal semen parameters. Subsequently, we examined whether DC-SIGN interacts with seminal plasma PAP glycans, and we detected a significantly higher relative reactivity in the normozoospermic group compared to the oligozoospermic group. Finally, we concluded that the significantly aberrant abundance of mannosylated functional groups of PAP among patients with semen disorders can suggest that PAP may thereby be engaged in modulating the immune response and promoting a tolerogenic response to male antigens in the female reproductive system.

Blood Antibody Titers and Adverse Reactions after BNT162b2 mRNA Vaccination.

This study aimed to measure, considering a prior history of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (SCV-negative/positive), antibodies titer using Elecsys Anti-SARS-CoV-2 S immunoassay (Roche Diagnostics, Mannheim, Germany), in a serum of healthcare workers (HCW) who received two doses of BNT162b2 vaccines. The local and systemic adverse reactions occurrence was checked with a self-reported questionnaire. A total of 60 SCV-negative HCW showed lower antibody titers than those presented by SCV-positive subjects (n = 7). The highest antibody level was detected 8 days after the second dose of vaccine administration. At the same time, the titer was higher in the SCV2 -positive than the SCV2-negative group and comparable after the first dose in those who became infected to the level after the second dose of those who did not. The local and systemic effects in the SCV2-negative and SCV2-positive groups appeared independent of the vaccine dose. After the second dose, systemic reactions were reported more often than the local adverse effects. Whether no effect was observed or whether the response was local or systemic, the antibody level in a specific group remains constant. These results can be helpful in the improvement of vaccination programs, controlling the occurrence of adverse and long-term effects of the vaccination.

Glyphosate dose modulates the uptake of inorganic phosphate by freshwater cyanobacteria.

The usefulness of glyphosate [N-(phosphonomethyl)glycine] as a source of nutritive phosphorus for species of halophilic cyanobacteria has been postulated for years. Our results indicate a stimulating effect of glyphosate on the growth of four out of five examined freshwater species, Anabaena variabilis (CCALA 007), Chroococcus minutus (CCALA 055), Fischerella cf. maior (CCALA 067) and Nostoc cf. muscorum (CCALA 129), in a manner dependent on the applied concentration. The most significant stimulation was observed at a dose of 0.1 mM glyphosate. The decrease in the amount of phosphonate, which correlated with microbial growth, demonstrated that glyphosate may play an important role in cyanobacterial nourishment. Surprisingly, the consumption of organic phosphorus did not start when concentrations of inorganic phosphate (PO43-) had fallen dramatically; instead, the assimilation of both types of phosphorus occurred simultaneously. The greatest decrease in the amount of glyphosate was observed during the first week. The uptake of the standard nutrient-phosphate (PO43-), was strongly dependent on the xenobiotic concentration. When a concentration of 0.1 mM glyphosate was used, the consumption of phosphate decreased in favour of glyphosate assimilation. Our study revealed for the very first time that the presence of inorganic phosphate significantly enhances the bioavailability of glyphosate. Statistical analysis confirmed that the nutritive usage of glyphosate and the absorption of phosphate are features associated with the herbicide concentration rather than features related to the species of freshwater cyanobacterium. This finding supports the thesis of an important role of organic phosphorus in the formation of cyanobacterial blooms and creates the opportunity of using these cyanobacteria to bind both organic and inorganic forms of phosphorus in microalgal biomasses.

Analytical insight into degradation processes of aminopolyphosphonates as potential factors that induce cyanobacterial blooms.

Aminopolyphosphonates (AAPs) are commonly used industrial complexones of metal ions, which upon the action of biotic and abiotic factors undergo a breakdown and release their substructures. Despite the low toxicity of AAPs towards vertebrates, products of their transformations, especially those that contain phosphorus and nitrogen, can affect algal communities. To verify whether such chemical entities are present in water ecosystems, much effort has been made in developing fast, inexpensive, and reliable methods for analyzing phosphonates. However, unfortunately, the methods described thus far require time-consuming sample pretreatment and offer relatively high values of the limit of detection (LOD). The aim of this study was to develop an analytical approach to study the environmental fate of AAPs. Four phosphonic acids, N,N-bis(phosphonomethyl)glycine (GBMP), aminotris(methylenephosphonic) acid (ATMP), hexamethylenediamine-N,N,N',N'-tetrakis(methylphosphonic) acid (HDTMP), and diethylenetriamine penta(methylenephosphonic) acid (DTPMP) were selected and examined in a water matrix. In addition, the susceptibility of these compounds to biotransformations was tested in colonies of five freshwater cyanobacteria-microorganisms responsible for the so-called blooms in the water. Our efforts to track the AAP decomposition were based on derivatization of N-alkyl moieties with p-toluenesulfonyl chloride (tosylation) followed by chromatographic (HPLC-UV) separation of derivatives. This approach allowed us to determine seven products of the breakdown of popular phosphonate chelators, in nanomolar concentrations and in one step. It should be noted that the LOD of four of those products, aminemethylphosphonic acid (AMPA), N-phosphomethyl glycine (NPMG), N-(methyl)aminemethanephosphonic acid (MAMPA), and N-(methyl) glycine (SAR), was set below the concentration of 50 nM. Among those substances, N-(methylamino)methanephosphonic acid (MAMPA) was identified for the first time as the product of decomposition of the examined aminopolyphosphonates.

Biodegradation of the aminopolyphosphonate DTPMP by the cyanobacterium Anabaena variabilis proceeds via a C-P lyase-independent pathway.

Cyanobacteria, the only prokaryotes capable of oxygenic photosynthesis, play a major role in carbon, nitrogen and phosphorus global cycling. Under conditions of increased P availability and nutrient loading, some cyanobacteria are capable of blooming, rapidly multiplying and possibly altering the ecological structure of the ecosystem. Because of their ability of using non-conventional P sources, these microalgae can be used for bioremediation purposes. Under this perspective, the metabolization of the polyphosphonate diethylenetriaminepenta(methylenephosphonic) acid (DTPMP) by the strain CCALA 007 of Anabaena variabilis was investigated using 31 P NMR analysis. Results showed a quantitative breakdown of DTPMP by cell-free extracts from cyanobacterial cells grown in the absence of any phosphonate. The identification of intermediates and products allowed us to propose a unique and new biodegradation pathway in which the formation of (N-acetylaminomethyl)phosphonic acid represents a key step. This hypothesis was strengthened by the results obtained by incubating cell-free extracts with pathway intermediates. When Anabaena cultures were grown in the presence of the phosphonate, or phosphorus-starved before the extraction, significantly higher biodegradation rates were found.