Performance of a Modified, Three-Step Menstrual Cycle Tracking Method in Naturally Cycling Females

Effects of an agonist of gonadotrophin releasing hormone in cattle. I. Hormone concentrations and oestrous cycle length

Background and Objectives: Menstrual cycle tracking is essential for reproductive health and overall well-being. However, there is still an over-reliance on estimations that standard cycles are 28 days long, divided evenly between the follicular and luteal phases. Due to the variability of cycle length and cycle phase lengths, common methods of identifying where an individual is in their cycle are often inaccurate. This study used daily hormone monitoring obtained through a remote hormone-monitoring platform to evaluate hormone levels across a menstrual cycle to identify nuances in the follicular and luteal phases in individuals of different age groups. Materials and Methods: This study used a remote fertility testing system that quantitatively tracks luteinizing hormone (LH) and pregnanediol-3-glucuronide (PdG) through urine tests read by an AI-powered smartphone app. The study analyzed cycle data from 1233 users with a total of 4123 evaluated cycles. Daily levels for LH and PdG were monitored across multiple cycles. Results: This study determined that calculated cycle lengths tended to be shorter than user-reported cycle lengths. Significant differences were observed in cycle phase lengths between age groups, indicating that follicular phase length declines with age while luteal phase length increases. Finally, the study found that if an individual's age, first cycle day, and current hormone levels are known, population-level hormone data can be used to pinpoint which cycle phase and cycle day they are in with 95% confidence. Conclusions: At-home hormone monitoring technologies can allow patients and clinicians to track their cycles with greater precision than when relying on textbook estimations. The study's findings have implications for fertility planning, clinical management, and general health monitoring. Prior to this study, no standard existed for pinpointing where a person was in their cycle through only one measure of LH and PdG. These findings have the potential to fill significant gaps within reproductive healthcare and beyond.

In this paper, persistence characteristics of the Northern Hemisphere (NH) extratropical circulation have been studied. A simple method, based on the speed with which the atmosphere moves in the phase space (PSS, measured by 2-day lag distances), was adopted to partition the circulation data series into 5-day or longer quasi-stationary periods (QSP) and alternating transition periods (TP). The method is based on the assumptions that large-scale circulation regimes often develop abruptly and that during their development transient activity is either unchanged or enhanced. The partitioning results reveal that a whole cycle of QSP and TP on the hemisphere has an average duration of 20 days with considerable amount of variability. The average length of a QSP-TP cycle is not sensitive to changes of a relatively wide range in the PSS limit value employed in the method. In this range of limit values, the average length of the cycle changes less than 17%, while the ratio between the length of QSP and TP increases dramatically from 0.73 to 4.42. The partitioning results are statistically very similar for three complementary sectors of the hemisphere. However, we found very little synchronicity in the changes in the three sectors. The correlation between changes in any of the three sectors and on the whole hemisphere is at a much higher level, around 0.75. Although the length of the cycle on height values at individual grid points is in the range we can expect from a red-noise process, this cycle length is considerably (20%) shorter than that in a larger region or on the whole hemisphere. This is an indication that the persistence characteristics of larger-scale circulation, due to spatial interactions, show more persistence than, and cannot be well modeled by, a simple autoregressive process. Statistical tests indicate that the hemispheric QSPs are largely temporally uncorrelated and cannot be results of a random partitioning method. All these results suggest that the basic assumption about the regime-like behavior of the atmosphere is at least partially true: large-scale regime changes are indeed accompanied with higher speed of changes in the circulation phase space. Further evidence is presented that the circulation patterns in the phase space are distributed as a multivariate normal distribution in a phase-average sense (i.e., as a function of distance from the mean). Hence, the characteristic distance between neighboring circulation patterns is smaller close to the climate mean than farther away from it. As a consequence that had to be considered in this study, the day-to-day changes in the circulation (an inverse measure of persistence) are also smaller close to the climate mean. It is also argued that phase-average multinormality is the primary characteristic of the distribution of circulation patterns in the phase space and any secondary characteristic (local density maximum) should be searched for and interpreted in this context.

This study examined the calendar records of 2149 menstrual cycles experienced by 592 health Swiss women in 1935-55 in order to assess the correlation between age and length of menstrual cycle. Qualitative changes in the menstrual cycle were observed in the adolescent maturity and climateric phases with adolescent women demostrating a descreasing range of variability and mean length of menstrual cycles and women in the climateric phase manifesting an increasing range of variability and average length of menstrual cycles. Overall 80% of the menstrual cycles analyzed fell into the 24-34 day range with an average cycle length of 29.2 days. Between ages 11-20 years the average length of the menstrual cycle decreased from 30-9 to 28.5 days and the standard deviation decreased parallel with the mean length of the cycle. From 21-28 years of age the average length of the cycle increased slightly and the standard deviation progressivey decreased indicating a rapid decrease in the frequency of long cycles. From 29-42 years of age the average cycle length decreased arallel with the continuous decrease of the standard deviation. Finally 43 years of age marked the onset of a simultaneous increase of the average length of the menstrual cycle and the standard deviation.

Ovarian function in crossbred beef heifers treated with dexamethasone

Background: Knowledge concerning value of menstrual cycle observation and its use to monitor procreative health is underestimated and limited in women's health promotion, education and health care. Academy of Pediatrics, Committee on Adolescence and , American College of Obstetricians and Gynecologists recommends starting to observe the forming cycle as early as puberty in order to pre-screen girls , from groups at risk of fertility disorders such as polycystic ovary syndrome. In view of the numerous reports on the increase in fertility problems, such a simple tool as self-observation of the menstrual cycle becomes particularly useful to learn about the natural rhythm of fertility and in the case of abnormalities, i.e. deviation from the typical course shortens the time to the first medical consultation. In Poland there are several non-governmental non-profit organizations, which through certified teachers of fertility awareness methods can professionally support the teaching of adolescents, adults and interested people working in the health service in the field of fertility awareness, health education and natural family planning.
 Aim of the presented study was to analyze 105 menstrual cycle observation charts among polish women not using contraception according to the principles of the symptom-thermal double-check method.
 Method: The study was performed using the method of documentation analysis, 105 menstrual cycle observation charts using the statistical package SPSS Statistica version 25. The level of p < 0.05 was considered statistically significant.
 Results: The average age of the women studied was 29 years. The majority of the women , i.e. more than 58%, were unmarried and childless (79.1%). The average length of the menstrual cycle was: 28.6 days. The average duration of the luteal phase was almost 13 days. The average length of days of highly fertile mucus was nearly 4 days. The average length of cycles of women over 35 years of age was: 28.88 days, while for women under 35 years of age. 28.48 days. The age of onset of the first menstrual period of the women studied varied between 10 and 17 years of age.
 Conclusions: The studied group of women was homogeneous in terms of the adopted eligibility criteria, i.e. they had typical cycles and did not use contraceptive methods. The examined parameters of the menstrual cycle, i.e.: the average length of the cycle , the course of the luteal phase and the average length of the occurrence of highly fertile mucus met the criteria for a normal cycle according to the symptom-thermal double-check method.

Data for the first 36 menstrual intervals immediately following menarche were analysed for 298 girls studied in Newcastle upon Tyne. The mean cycle length decreased from 49 . 5 days for the first cycle in 29.5 days for cycles 31-36. There was no clear seasonal pattern in cycle length. The standard deviation within subjects in the length of menstrual interval fell sharply from 23 . 3 days for cycles 1-6 to 10-7 days for cycles 7-12 and more slowly thereafter, reaching 5 . 5 days for cycles 31-36, and was not related to age at menarche. The proportion of short cycles (17 days or less) was relatively stable, but that of long cycles (57 days or more) decreased with cycle number from 27.4% for the first cycle to about 1% for cycles 31-36. The average length of menstrual flow was 5 . 5 days irrespective of age at menarche, cycle number of season. The standard deviation of menstrual flow within subjects fell from 1 . 5 days for cycles 1-6 to 0 . 8 days for cycles 25-36.

Zygotes were transferred, on the day of fertilization, from young and old rats with 4- or 6-day oestrous cycles into the ovarian bursa of young recipients with 4-day cycles, and zygotes from young rats with 4-day cycles were transferred into young and old recipients with 4- or 6-day cycles. Young rats with 4-day cycles served as controls for both donors and recipients. An increase in length of cycle or maternal age of donor caused an increase in unfertilized and/or abnormal eggs at the pronuclear stage (non-transferred zygotes). Increased age of donor or length of cycle decreased the implantation rate observed on Day 11 of pregnancy. Likewise, increased age of recipient or length of cycle decreased implantation rate observed on Day 11 of pregnancy. The increase in both age and length of cycle of donor or recipient caused the greatest decline in implantation rate and percentage of normal embryos observed on Day 11 of pregnancy.

PO-02-184 MAPPING-GUIDED ATRIAL LEAD PLACEMENT DETERMINES OPTIMAL CONDUCTION ACROSS BACHMANN’S BUNDLE: A RATIONALE FOR PATIENT-TAILORED PACING THERAPY

The paper deals with the heterogeneous degradation process of the system with gradual and instantaneous failures. For the case when the times in the degradation stages are independent and distributed exponentially with different parameters, analytical expressions are obtained for the probability of a failure on the regeneration cycle, average time before the failure on the cycle, the average cycle length with and without failure, the average total cycle length. For the case of arbitrary distributions in highly reliable systems, where failure is a rare event, an simulation splitting algorithm is proposed to speed up the construction of regeneration cycles. The results of experiments obtained by the splitting and Monte-Carlo methods are presented and compared with analytical solutions

To identify smartphone menstrual cycle tracking applications (apps) and evaluate their accuracy, features, and functionality. In this systematic evaluation, we searched the Apple iTunes store for free menstrual cycle tracking apps for patient use. We considered an application accurate if menstrual cycle predictions were based on average cycle lengths of at least three previous cycles, ovulation (when included) was predicted at 13-15 days before the start of the next cycle, and the application contained no misinformation. We modified the APPLICATIONS Scoring System to evaluate the features and functionality of accurate apps. Our search criteria yielded 1,116 apps; 108 remained after excluding duplicate, non-English, nonmenstrual cycle tracking, and priced apps. We further eliminated 88 that did not meet inclusion or accuracy criteria. Of the 20 accurate, free apps, 80% contained information for conception and 50% for contraception. Common features and functionality included password protection (55%); no requirement for Internet connectivity (80%); no advertisements (65%); in-application technical support (70%); medical disclaimers (65%); health education (55%); tracking of menstrual flow (70%), symptoms (70%), and intercourse (75%); alerts for next menses (65%) and fertility (55%); and cycle length information (75%). Forty percent were available for Android. Usefulness for fertility medications (15%), professional involvement (5%), and cited literature (5%) were rare. Most free smartphone menstrual cycle tracking apps for patient use are inaccurate. Few cite medical literature or health professional involvement. We list accurate apps to aid health care providers in understanding the key components they can use to evaluate and recommend apps for patients.

Luteal Inhibition in the Bovine as a Result of Oxytocin Injections, Uterine Dilatation, and Intrauterine Infusions of Seminal and Preputial Fluids

The capacity of rat oocytes to mature in vitro was studied in relationship to the stages of the 4- and 5-day estrous cycles and to the time of day. Antral oocytes obtained from animals on regular 4- and 5-day cycles were placed in culture under standard conditions either in the morning or in the evening and examined with a dissecting microscope ∿10 h later for the stage of maturation, i.e., intact nucleus or germinal vesicle (GV), germainal vesicle breakdown (GVB), or extruded polar body (PB). Three relationships were studied: oocyte maturation was compared 1) between days of the same cycle for each AM and PM culture period (day-to-day changes without regard to diurnal changes); 2) between AM and PM cultures within each cycle length (diurnal variations); and 3) between similar days of the 4-and 5-day estrous cycles (cycle length dependency). There were no differences in the total number of oocytes maturing (GVB + PB) or in the percentage of immature oocytes at the end of the incubation period. PB formation varied from low values on estrus and metestrus to peak values on diestrus and proestrus in both cycles when oocytes were placed in culture in the morning. GVB formation was the reverse of PB formation. The differences between days within the same cycle generally were not evident when oocyte culture was initiated in the evening. When morning and evening maturation rates were compared in the 4-day cycle (diurnal variations), PB formation was higher in the morning of diestrus compared with the evening of metestrus or diestrus and higher in the morning of proestrus than in the evening of diestrus or proestrus. A similar but less pronounced rhythm in PB formation was evident in the 5-day cycle in which PB formation was higher in the evening as opposed to the morning of metestrus. GVB also exhibited 12 h fluctuations and was the opposite of PB formation in both cycles. When morning and evening PB formation and GVB were contrasted for comparable days of the two cycles, the two cycles had a similar pattern of maturation prior to proestrus but diverged within 2 days after the gonadotropic surge. The results support the conclusion that rat oocyte maturation in vitro varies with the stage and length of the estrous cycle and with the time of day.

Can algorithms using wrist temperature, available on compatible models of iPhone and Apple Watch, retrospectively estimate the day of ovulation and predict the next menses start day? Algorithms using wrist temperature can provide retrospective ovulation estimates and next menses start day predictions for individuals with typical or atypical cycle lengths. Wrist skin temperature is affected by hormonal changes associated with the menstrual cycle and can be used to estimate the timing of cycle events. We conducted a prospective cohort study of 262 menstruating females (899 menstrual cycles) aged 14 and older who logged their menses, performed urine LH testing to define day of ovulation, recorded daily basal body temperature (BBT), and collected overnight wrist temperature. Participants contributed between 2 and 13 menstrual cycles. Algorithm performance was evaluated for three algorithms: one for retrospective ovulation day estimate in ongoing cycles (Algorithm 1), one for retrospective ovulation day estimate in completed cycles (Algorithm 2), and one for prediction of next menses start day (Algorithm 3). Each algorithm's performance was evaluated under multiple scenarios, including for participants with all typical cycle lengths (23-35 days) and those with some atypical cycle lengths (<23, >35 days), in cycles with the temperature change of ≥0.2°C typically associated with ovulation, and with any temperature change included. Two hundred and sixty participants provided 889 cycles. Algorithm 1 provided a retrospective ovulation day estimate in 80.5% of ongoing menstrual cycles of all cycle lengths with ≥0.2°C wrist temperature signal with a mean absolute error (MAE) of 1.59 days (95% CI 1.45, 1.74), with 80.0% of estimates being within ±2 days of ovulation. Retrospective ovulation day in an ongoing cycle (Algorithm 1) was estimated in 81.9% (MAE 1.53 days, 95% CI 1.35, 1.70) of cycles for participants with all typical cycle lengths and 77.7% (MAE 1.71 days, 95% CI 1.42, 2.01) of cycles for participants with atypical cycle lengths. Algorithm 2 provided a retrospective ovulation day estimate in 80.8% of completed menstrual cycles with ≥0.2°C wrist temperature signal with an MAE of 1.22 days (95% CI 1.11, 1.33), with 89.0% of estimates being within ±2 days of ovulation. Wrist temperature provided the next menses start day prediction (Algorithm 3) at the time of ovulation estimate (89.4% within ±3 days of menses start) with an MAE of 1.65 (95% CI 1.52, 1.79) days in cycles with ≥0.2°C wrist temperature signal. There are several limitations, including reliance on LH testing to identify ovulation, which may mislabel some cycles. Additionally, the potential for false retrospective ovulation estimates when no ovulation occurred reinforces the idea that this estimate should not be used in isolation. Algorithms using wrist temperature can provide retrospective ovulation estimates and next menses start day predictions for individuals with typical or atypical cycle lengths. Apple is the funding source for this manuscript. Y.W., C.Y.Z., J.P., S.Z., and C.L.C. own Apple stock and are employed by Apple. S.M. has research funding from Apple for a separate study, the Apple Women's Health Study, including meeting and travel support to present research findings related to that separate study. A.M.Z.J., D.D.B., B.A.C., and J.P. had no conflicts of interest. NCT05852951.

Cycle frequency, length, and vaginal cytology were measured longitudinally in three cohorts of singly housed virgin mice staggered across a 3-year interval. The age profiles of these parameters were qualitatively similar, but quantitatively different, among cohorts. Cycle frequency was initially low (Phase I), due to prolonged cycles and late-starting cycles, and did not peak (Phase II) until mice were 3-5 months old. Phase II lasted for 7-10 months, depending on the cohort. Thereafter cycle frequency declined steadily (Phase III). The average age of cessation of cyclicity varied among cohorts, occurring between 13 and 16 months of age. Age changes in cycle length paralleled those of cycle frequency. During Phase II, median cycle length was less than 5 days and variance was lowest. During Phases I and III, variance was about twofold greater and median cycle length was greater than 5 days. Although median cycle length remained stable for several months during Phase II, the peak period of 4-day cycles was much shorter. In all cohorts, 4-day cycles did not peak until 7-8 months of age and began to decline by 9 months. The decrease in 4-day cycles was associated with a progressive lengthening of cycles-first from 4 to 5 days, then to longer cycles. The fraction of cycles with extended cornification (greater than 2 days) increased with advancing age from less than 0.35 during the initial period of cycle lengthening to a maximum of 0.60. The observation that the initial phase o cycle prolongation was not usually associated with extended cornification is consistent with earlier evidence that this period is characterized by a delayed, rather than prolonged, preovulatory rise of estradiol. However, the increased fraction of prolonged cycles with extended cornification at later ages suggests that the preovulatory elevation of estradiol may ultimately be prolonged.