Light Microscopy and Proteomic Patterns of Ovulation in Cervical Mucus.

There is an increasing number of couples interested in identifying the fertile window for the purpose of conceiving. From what has been published so far, it can be concluded that there are no reliable methods to predict ovulation, and, therefore, to predict the fertile window. Proteins of the cervical mucus (CM) could behave as biomarkers to allow the early and precise identification of ovulation. CM samples were collected from the lumen of the cervical canal from women of reproductive age, on three different days of the same menstrual cycle. Samples were first analyzed and classified by light microscopy. High-resolution mass spectrometry and bioinformatic analysis were performed afterwards to determine the in vivo changes of CM protein composition. CM underwent cyclical changes in its biophysical composition, which were evidenced by changes in the crystallographic patterns observed under the light microscope. The proteomic analysis revealed changes in the protein composition of CM along the cycle. Twenty-five out of the forty-eight total proteins identified could become potential biomarkers of ovulation. The coordinated changes in the composition of the CM around the time of ovulation could be happening to specifically grant access to a foreign body, such as the sperm might be.

Proteomic Markers in Cervical Mucus.

BACKGROUND: Cervical Mucus (CM) is a viscous fluid produced by the secretory cells of the cervical crypts. The CM undergoes modifications throughout the cycle that make it have different biochemical and biophysical characteristics, becoming a crucial element for the identification of ovulation. Since CM is rich in secreted proteins, it may represent moreover a source of biomarkers for female reproductive tract diseases. OBJECTIVE: This review is an attempt to collect relevant knowledge about the physicochemical properties and functions of the cervical mucus, including its important role as a clinical marker of female fertility, and draws attention to CM as a source of potential proteomic biomarkers. FINDINGS: All the assessed studies evidenced that the observation of the CM allows the identification of the days with the highest probability of pregnancy. CM proteome changes throughout the menstrual cycle have been revealed. Few proteomic studies on the constitutive protein composition of CM of fertile women have been conducted to date. In the CM of patients affected by endometriosis have been identified some proteins that could represent potential biomarkers of the disease. CONCLUSION: There is still limited knowledge about the physicochemical properties and functions of the CM and how these undergo to changes during menstrual cycle. CM is a reliable predictor of fertility. Further characterization of CM proteins would contribute to a better understanding of the key role they have on fertility, reproduction and biological regulation. CM may represent moreover a source of biomarkers for gynecological diseases.

FRAX® tool, the WHO algorithm to predict osteoporotic fractures: the first analysis of its discriminative and predictive ability in the Spanish FRIDEX cohort.

BACKGROUND: The WHO has recently published the FRAX® tool to determine the absolute risk of osteoporotic fracture at 10 years. This tool has not yet been validated in Spain. METHODS/DESIGN: A prospective observational study was undertaken in women in the FRIDEX cohort (Barcelona) not receiving bone active drugs at baseline. Baseline measurements: known risk factors including those of FRAX® and a DXA. Follow up data on self-reported incident major fractures (hip, spine, humerus and wrist) and verified against patient records. The calculation of absolute risk of major fracture and hip fracture was by FRAX® website. This work follows the guidelines of the STROBE initiative for cohort studies. The discriminative capacity of FRAX® was analyzed by the Area Under Curve (AUC), Receiver Operating Characteristics (ROC) and the Hosmer-Lemeshow goodness-of-fit test. The predictive capacity was determined using the ratio of observed fractures/expected fractures by FRAX® (ObsFx/ExpFx). RESULTS: The study subjects were 770 women from 40 to 90 years of age in the FRIDEX cohort. The mean age was 56.8 ± 8 years. The fractures were determined by structured telephone questionnaire and subsequent testing in medical records at 10 years. Sixty-five (8.4%) women presented major fractures (17 hip fractures). Women with fractures were older, had more previous fractures, more cases of rheumatoid arthritis and also more osteoporosis on the baseline DXA. The AUC ROC of FRAX® for major fracture without bone mineral density (BMD) was 0.693 (CI 95%; 0.622-0.763), with T-score of femoral neck (FN) 0.716 (CI 95%; 0.646-0.786), being 0.888 (CI 95%; 0.824-0.952) and 0.849 (CI 95%; 0.737-0.962), respectively for hip fracture. In the model with BMD alone was 0.661 (CI 95%; 0.583-0.739) and 0.779 (CI 95%; 0.631-0.929). In the model with age alone was 0.668 (CI 95%; 0.603-0.733) and 0.882 (CI 95%; 0.832-0.936). In both cases there are not significant differences against FRAX® model. The overall predictive value for major fracture by ObsFx/ExpFx ratio was 2.4 and 2.8 for hip fracture without BMD. With BMD was 2.2 and 2.3 respectively. Sensitivity of the four was always less than 50%. The Hosmer-Lemeshow test showed a good correlation only after calibration with ObsFx/ExpFx ratio. CONCLUSIONS: The current version of FRAX® for Spanish women without BMD analysed by the AUC ROC demonstrate a poor discriminative capacity to predict major fractures but a good discriminative capacity for hip fractures. Its predictive capacity does not adjust well because leading to underdiagnosis for both predictions major and hip fractures. Simple models based only on age or BMD alone similarly predicted that more complex FRAX® models.