Characterization of a Mouse Model of Inducible Frailty: The Humanized IL-6 Mouse

The cytokine interleukin-6 (IL-6) has pleiotropic effects in aging and is elevated in frail older adults. We have developed a conditional mouse model to better characterize the role of IL-6 in promoting frailty and age-related mitochondrial dysregulation. The human IL-6 (hIL-6) knock-in mouse (TetO-hIL6) was developed utilizing CRISPR/Cas9 technology with transgene donor vector containing a tetracycline response element promoter driving expression of hIL-6 cDNA. Male TetO-hIL6 mice were treated with doxycycline-containing water for six weeks starting at 8 months old. RNAseq analysis of whole blood demonstrated significant upregulation of pro-inflammatory related markers at 6 weeks compared to baseline and upregulated cell proliferation and metabolism pathways. Physical testing of TetO-hIL6 mice before and after hIL-6 induction demonstrated decreased grip strength (p =0.003), decreased running capacity (p = 0.02), and 40% increase in falls off of the treadmill (p = 0.001). Induced mice also demonstrated decreased basal body temperature (p < 0.001). Given the significant dysregulation of metabolism-related genes in RNAseq analysis and changes in basal body temperature following hIL-6 induction, we next performed untargeted metabolomics on plasma from mice at baseline and 6 weeks post-induction to better evaluate metabolic changes associated with hIL-6 elevation. We found changes in key serum metabolites, including circulating adenosine triphosphate (56% reduction, p = 0.02), pyruvate (35% reduction, p = 0.0006), alpha-ketoglutarate (47% reduction, p = 0.04), and succinate (306% increase, p = 0.001). The TetO-hIL6 mouse model allows for induction of hIL-6 at various timepoints across the lifespan and demonstrates features of a frailty phenotype.

The Accuracy of Wrist Skin Temperature in Detecting Ovulation Compared to Basal Body Temperature: Prospective Comparative Diagnostic Accuracy Study

Background As a daily point measurement, basal body temperature (BBT) might not be able to capture the temperature shift in the menstrual cycle because a single temperature measurement is present on the sliding scale of the circadian rhythm. Wrist skin temperature measured continuously during sleep has the potential to overcome this limitation. Objective This study compares the diagnostic accuracy of these two temperatures for detecting ovulation and to investigate the correlation and agreement between these two temperatures in describing thermal changes in menstrual cycles. Methods This prospective study included 193 cycles (170 ovulatory and 23 anovulatory) collected from 57 healthy women. Participants wore a wearable device (Ava Fertility Tracker bracelet 2.0) that continuously measured the wrist skin temperature during sleep. Daily BBT was measured orally and immediately upon waking up using a computerized fertility tracker with a digital thermometer (Lady-Comp). An at-home luteinizing hormone test was used as the reference standard for ovulation. The diagnostic accuracy of using at least one temperature shift detected by the two temperatures in detecting ovulation was evaluated. For ovulatory cycles, repeated measures correlation was used to examine the correlation between the two temperatures, and mixed effect models were used to determine the agreement between the two temperature curves at different menstrual phases. Results Wrist skin temperature was more sensitive than BBT (sensitivity 0.62 vs 0.23; P<.001) and had a higher true-positive rate (54.9% vs 20.2%) for detecting ovulation; however, it also had a higher false-positive rate (8.8% vs 3.6%), resulting in lower specificity (0.26 vs 0.70; P=.002). The probability that ovulation occurred when at least one temperature shift was detected was 86.2% for wrist skin temperature and 84.8% for BBT. Both temperatures had low negative predictive values (8.8% for wrist skin temperature and 10.9% for BBT). Significant positive correlation between the two temperatures was only found in the follicular phase (rmcorr correlation coefficient=0.294; P=.001). Both temperatures increased during the postovulatory phase with a greater increase in the wrist skin temperature (range of increase: 0.50 °C vs 0.20 °C). During the menstrual phase, the wrist skin temperature exhibited a greater and more rapid decrease (from 36.13 °C to 35.80 °C) than BBT (from 36.31 °C to 36.27 °C). During the preovulatory phase, there were minimal changes in both temperatures and small variations in the estimated daily difference between the two temperatures, indicating an agreement between the two curves. Conclusions For women interested in maximizing the chances of pregnancy, wrist skin temperature continuously measured during sleep is more sensitive than BBT for detecting ovulation. The difference in the diagnostic accuracy of these methods was likely attributed to the greater temperature increase in the postovulatory phase and greater temperature decrease during the menstrual phase for the wrist skin temperatures.

Period tracker applications: What menstrual cycle information are they giving women?

Background: Period tracking applications (apps) allow women to track their menstrual cycles and receive a prediction for their period dates. The majority of apps also provide predictions of ovulation day and the fertile window. Research indicates apps are basing predictions on assuming women undergo a textbook 28-day cycle with ovulation occurring on day 14 and a fertile window between days 10 and 16. Objective: To determine how the information period tracker apps give women on their period dates, ovulation day and fertile window compares to expected results from big data. Methods: Five women’s profiles for 6 menstrual cycles were created and entered into 10 apps. Cycle length and ovulation day for the sixth cycle were Woman 1—Constant 28 day cycle length, ovulation day 16; Woman 2—Average 23 day cycle length, ovulation day 13; Woman 3—Average 28 day cycle length, ovulation day 17; Woman 4—Average 33 day cycle length, ovulation day 20; and Woman 5—Irregular, average 31 day cycle length, ovulation day 14. Results: The 10 period tracker apps examined gave conflicting information on period dates, ovulation day and the fertile window. For cycle length, the apps all predicted woman 1’s cycles correctly but for women 2–5, the apps predicted 0 to 8 days shorter or longer than expected. For day of ovulation, for women 1–4, of the 36 predictions, 3 (8%) were exactly correct, 9 predicted 1 day too early (25%) and 67% of predictions were 2–9 days early. For woman 5, most of the apps predicted a later day of ovulation. Conclusion: Period tracker apps should ensure they only give women accurate information, especially for the day of ovulation and the fertile window which can only be predicted if using a marker of ovulation, such as basal body temperature, ovulation sticks or cervical mucus.

The Accuracy of Wrist Skin Temperature in Detecting Ovulation Compared to Basal Body Temperature: Prospective Comparative Diagnostic Accuracy Study (Preprint)

BACKGROUND As a daily point measurement, basal body temperature (BBT) might not be able to capture the temperature shift in the menstrual cycle because a single temperature measurement is present on the sliding scale of the circadian rhythm. Wrist skin temperature measured continuously during sleep has the potential to overcome this limitation. OBJECTIVE This study compares the diagnostic accuracy of these two temperatures for detecting ovulation and to investigate the correlation and agreement between these two temperatures in describing thermal changes in menstrual cycles. METHODS This prospective study included 193 cycles (170 ovulatory and 23 anovulatory) collected from 57 healthy women. Participants wore a wearable device (Ava Fertility Tracker bracelet 2.0) that continuously measured the wrist skin temperature during sleep. Daily BBT was measured orally and immediately upon waking up using a computerized fertility tracker with a digital thermometer (Lady-Comp). An at-home luteinizing hormone test was used as the reference standard for ovulation. The diagnostic accuracy of using at least one temperature shift detected by the two temperatures in detecting ovulation was evaluated. For ovulatory cycles, repeated measures correlation was used to examine the correlation between the two temperatures, and mixed effect models were used to determine the agreement between the two temperature curves at different menstrual phases. RESULTS Wrist skin temperature was more sensitive than BBT (sensitivity 0.62 vs 0.23; <i>P</i>&lt;.001) and had a higher true-positive rate (54.9% vs 20.2%) for detecting ovulation; however, it also had a higher false-positive rate (8.8% vs 3.6%), resulting in lower specificity (0.26 vs 0.70; <i>P</i>=.002). The probability that ovulation occurred when at least one temperature shift was detected was 86.2% for wrist skin temperature and 84.8% for BBT. Both temperatures had low negative predictive values (8.8% for wrist skin temperature and 10.9% for BBT). Significant positive correlation between the two temperatures was only found in the follicular phase (<i>rmcorr</i> correlation coefficient=0.294; <i>P</i>=.001). Both temperatures increased during the postovulatory phase with a greater increase in the wrist skin temperature (range of increase: 0.50 °C vs 0.20 °C). During the menstrual phase, the wrist skin temperature exhibited a greater and more rapid decrease (from 36.13 °C to 35.80 °C) than BBT (from 36.31 °C to 36.27 °C). During the preovulatory phase, there were minimal changes in both temperatures and small variations in the estimated daily difference between the two temperatures, indicating an agreement between the two curves. CONCLUSIONS For women interested in maximizing the chances of pregnancy, wrist skin temperature continuously measured during sleep is more sensitive than BBT for detecting ovulation. The difference in the diagnostic accuracy of these methods was likely attributed to the greater temperature increase in the postovulatory phase and greater temperature decrease during the menstrual phase for the wrist skin temperatures.

Fecundability in relation to use of mobile computing apps to track the menstrual cycle

STUDY QUESTION To what extent does the use of mobile computing apps to track the menstrual cycle and the fertile window influence fecundability among women trying to conceive? SUMMARY ANSWER After adjusting for potential confounders, use of any of several different apps was associated with increased fecundability ranging from 12% to 20% per cycle of attempt. WHAT IS KNOWN ALREADY Many women are using mobile computing apps to track their menstrual cycle and the fertile window, including while trying to conceive. STUDY DESIGN, SIZE, DURATION The Pregnancy Study Online (PRESTO) is a North American prospective internet-based cohort of women who are aged 21–45 years, trying to conceive and not using contraception or fertility treatment at baseline. PARTICIPANTS/MATERIALS, SETTING, METHODS We restricted the analysis to 8363 women trying to conceive for no more than 6 months at baseline; the women were recruited from June 2013 through May 2019. Women completed questionnaires at baseline and every 2 months for up to 1 year. The main outcome was fecundability, i.e. the per-cycle probability of conception, which we assessed using self-reported data on time to pregnancy (confirmed by positive home pregnancy test) in menstrual cycles. On the baseline and follow-up questionnaires, women reported whether they used mobile computing apps to track their menstrual cycles (‘cycle apps’) and, if so, which one(s). We estimated fecundability ratios (FRs) for the use of cycle apps, adjusted for female age, race/ethnicity, prior pregnancy, BMI, income, current smoking, education, partner education, caffeine intake, use of hormonal contraceptives as the last method of contraception, hours of sleep per night, cycle regularity, use of prenatal supplements, marital status, intercourse frequency and history of subfertility. We also examined the impact of concurrent use of fertility indicators: basal body temperature, cervical fluid, cervix position and/or urine LH. MAIN RESULTS AND THE ROLE OF CHANCE Among 8363 women, 6077 (72.7%) were using one or more cycle apps at baseline. A total of 122 separate apps were reported by women. We designated five of these apps before analysis as more likely to be effective (Clue, Fertility Friend, Glow, Kindara, Ovia; hereafter referred to as ‘selected apps’). The use of any app at baseline was associated with 20% increased fecundability, with little difference between selected apps versus other apps (selected apps FR (95% CI): 1.20 (1.13, 1.28); all other apps 1.21 (1.13, 1.30)). In time-varying analyses, cycle app use was associated with 12–15% increased fecundability (selected apps FR (95% CI): 1.12 (1.04, 1.21); all other apps 1.15 (1.07, 1.24)). When apps were used at baseline with one or more fertility indicators, there was higher fecundability than without fertility indicators (selected apps with indicators FR (95% CI): 1.23 (1.14, 1.34) versus without indicators 1.17 (1.05, 1.30); other apps with indicators 1.30 (1.19, 1.43) versus without indicators 1.16 (1.06, 1.27)). In time-varying analyses, results were similar when stratified by time trying at study entry (&lt;3 vs. 3–6 cycles) or cycle regularity. For use of the selected apps, we observed higher fecundability among women with a history of subfertility: FR 1.33 (1.05–1.67). LIMITATIONS, REASONS FOR CAUTION Neither regularity nor intensity of app use was ascertained. The prospective time-varying assessment of app use was based on questionnaires completed every 2 months, which would not capture more frequent changes. Intercourse frequency was also reported retrospectively and we do not have data on timing of intercourse relative to the fertile window. Although we controlled for a wide range of covariates, we cannot exclude the possibility of residual confounding (e.g. choosing to use an app in this observational study may be a marker for unmeasured health habits promoting fecundability). Half of the women in the study received a free premium subscription for one of the apps (Fertility Friend), which may have increased the overall prevalence of app use in the time-varying analyses, but would not affect app use at baseline. Most women in the study were college educated, which may limit application of results to other populations. WIDER IMPLICATIONS OF THE FINDINGS Use of a cycle app, especially in combination with observation of one or more fertility indicators (basal body temperature, cervical fluid, cervix position and/or urine LH), may increase fecundability (per-cycle pregnancy probability) by about 12–20% for couples trying to conceive. We did not find consistent evidence of improved fecundability resulting from use of one specific app over another. STUDY FUNDING/COMPETING INTEREST(S) This research was supported by grants, R21HD072326 and R01HD086742, from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, USA. In the last 3 years, Dr L.A.W. has served as a fibroid consultant for AbbVie.com. Dr L.A.W. has also received in-kind donations from Sandstone Diagnostics, Swiss Precision Diagnostics, FertilityFriend.com and Kindara.com for primary data collection and participant incentives in the PRESTO cohort. Dr J.B.S. reports personal fees from Swiss Precision Diagnostics, outside the submitted work. The remaining authors have nothing to declare. TRIAL REGISTRATION NUMBER N/A.

A study on relation between Pitta Pradhan Prakriti females and ovulation with the help of basal body temperature method

Prakriti indicates the predominance of natural Doshas which may interfere with the normal human physiology. The day of Ovulation may have some relation with Prakriti of females. In this competitive era females are facing many problems related to their menstruation such as painful menses, irregular menses, etc. in their adolescent age without any specific pathology in their reproductive system, which may cause problems related to infertility. Thus the present study enlightens the relation between Pitta Pradhan Prakriti females and Ovulation with the help of Basal Body Temperature method (BBT method). Methodology: To record the day of Ovulation in 30 Pitta Pradhan Prakriti females, basal body temperature method was selected. For confirmation, USG of ten females was done. Applications of proposed thought: In Pitta Pradhan Prakriti females by BBT method, we can observe that, whether the Ovulation is early or late as compared to normal 14th day of Ovulation and what are the effects of Pittadhikya on menstrual symptoms. Knowing the day of Ovulation will be helpful for identifying safe period and danger period. Conclusion: Pitta Pradhan Prakriti was found in 30 females. Vinishaya of Prakriti was done by percentage method and also by gradation method; grades were given on the basis of six Gunas. Day of Ovulation by B.B.T. method in Pitta Pradhan females was found to be the 14th and 15th day of menstrual cycle. Temperature rise on the day of Ovulation was found in the range 0.5°F - 0.7°F. By USG method, 90% results were matching related to day of Ovulation by BBT method.

The Use of NFP When Pregnancy Is Contraindicated?

The Sacred Congregation for the Doctrine of the Faith has declared the moral liceity of hysterectomy when certain medical criteria are met but does not exclude other options, “for example, recourse to infertile periods or total abstinence.” Consequently, there may be couples who prefer to use natural family planning (NFP) methods. We shall refer to these in this article. The efficacy of NFP methods is determined by knowing the day of ovulation. To that end, three parameters are used: the presence and consistency of cervical mucus, measurement of the basal body temperature, and the determination of particular hormones in urine. Of the NFP methods used, the so-called sympto-thermal method seems to be the most effective. It has been concluded that the postovulatory or luteal phase of the female menstrual cycle is the safest time to avoid pregnancy if the couple has sexual intercourse during this period. Nevertheless, the use of NFP methods has limitations if the length of the cycles varies, there are fluctuations in the basal temperature, or when there are vaginal infections. Urinary hormone levels can also be altered by the use of antibiotics or psychotropic drugs. In general, however, it can be concluded that NFP methods, if used in the conditions mentioned herein, offer a high degree of reliability, similar to that of artificial contraceptive methods. Accordingly, if pregnancy must be avoided in the medical circumstances to which the Congregation for the Doctrine of the Faith refers, NFP methods can effectively replace hysterectomy, thereby circumventing the medical difficulties of this practice. Summary: The Sacred Congregation for the Doctrine of the Faith has declared the moral liceity of hysterectomy when certain medical criteria are met but does not exclude other options, “for example, recourse to infertile periods or total abstinence.” Consequently, there may be couples who prefer to use natural family planning (NFP) methods. We shall refer to these in this article. In general, it can be concluded that NFP methods, if used in the conditions mentioned herein, offer a high degree of reliability, similar to that of artificial contraceptive methods. Accordingly, if pregnancy must be avoided in the medical circumstances to which the Congregation for the Doctrine of the Faith refers, NFP methods can effectively replace hysterectomy, thereby circumventing the medical difficulties of this practice.