Modeling the Immune Response for Pathogenic and Nonpathogenic Orthohantavirus Infections in Human Lung Microvasculature Endothelial Cells.

Hantaviruses, genus Orthohantavirus, family Hantaviridae, order Bunyavirales, are negative-sense, single-stranded, tri-segmented RNA viruses that persistently infect rodents, shrews, and moles. Of these, only certain virus species harbored by rodents are pathogenic to humans. Infection begins with inhalation of virus particles into the lung and trafficking to the lung microvascular endothelial cells (LMVEC). The reason why certain rodent-borne hantavirus species are pathogenic has long been hypothesized to be related to their ability to downregulate and dysregulate the immune response as well as increase vascular permeability of infected endothelial cells. We set out to study the temporal dynamics of host immune response modulation in primary human LMVECs following infection by Prospect Hill (nonpathogenic), Andes (pathogenic), and Hantaan (pathogenic) viruses. We measured the level of RNA transcripts for genes representing antiviral, proinflammatory, anti-inflammatory, and metabolic pathways from 12 to 72 h with time points every 12 h. Gene expression analysis in conjunction with mathematical modeling revealed a similar profile for all three viruses in terms of upregulated genes that partake in interferon signaling (TLR3, IRF7, IFNB1), host immune cell recruitment (CXCL10, CXCL11, and CCL5), and host immune response modulation (IDO1). We examined secreted protein levels of IFN-ß, CXCL10, CXCL11, CCL5, and IDO in two male and two female primary HLMVEC donors at 48 and 60 h post infection. All three viruses induced similar levels of CCL5, CXCL10, and CXCL11 within a particular donor, and the levels were similar in three of the four donors. All three viruses induced different protein secretion levels for both IFN-ß and IDO and secretion levels differed between donors. In conclusion, we show that there was no difference in the transcriptional profiles of key genes in primary HLMVECs following infection by pathogenic and nonpathogenic hantaviruses, with protein secretion levels being more donor-specific than virus-specific.

Algorithms with Area under the Curve for Daily Urinary Estrone-3-Glucuronide and Pregnanediol-3-Glucuronide to Signal the Transition to the Luteal Phase.

Background and Objectives: Home fertility assessment methods (FAMs) for natural family planning (NFP) have technically evolved with the objective metrics of urinary luteinizing hormone (LH), estrone-3-glucuronide (E3G) and pregnanediol-3-glucuronide (PDG). Practical and reliable algorithms for timing the phase of cycle based upon E3G and PDG levels are mostly unpublished and still lacking. Materials and Methods: A novel formulation to signal the transition to the luteal phase was discovered, tested, and developed with a data set of daily E3G and PDG levels from 25 women, 78 cycles, indexed to putative ovulation (day after the urinary LH surge), Day 0. The algorithm is based upon a daily relative progressive change in the ratio, E3G-AUC/PDG-AUC, where E3G-AUC and PDG-AUC are the area under the curve for E3G and PDG, respectively. To improve accuracy the algorithm incorporated a three-fold cycle-specific increase of PDG. Results: An extended negative change in E3G-AUC/PDG-AUC of at least nine consecutive days provided a strong signal for timing the luteal phase. The algorithm correctly identified the luteal transition interval in 78/78 cycles and predicted the start day of the safe period as: Day + 2 in 10/78 cycles, Day + 3 in 21/78 cycles, Day + 4 in 28/78 cycles, Day + 5 in 15/78 cycles, and Day + 6 in 4/78 cycles. The mean number of safe luteal days with this algorithm was 10.3 ± 1.3 (SD). Conclusions: An algorithm based upon the ratio of the area under the curve for daily E3G and PDG levels along with a relative PDG increase offers another approach to time the phase of cycle. This may have applications for NFP/FAMs and clinical evaluation of ovarian function.

The Fertility Indicator Equation Using Serum Progesterone and Urinary Pregnanediol-3-Glucuronide for Assessment of Ovulatory to Luteal Phase Transition.

Background and Objectives: The Fertility Indicator Equation (FIE) has been shown to signal the fertile phase during the ovulatory menstrual cycle. It was hypothesized that this formulation, a product of two sequential normalized changes with a sign indicating direction of change, could be used to identify the transition from ovulatory to luteal phase with daily serum progesterone (P) and urinary pregnanediol-3-glucuronide (PDG) levels. Materials and Methods: Day-specific serum P levels from two different laboratories and day-specific urinary PDG levels from an additional two different laboratories were submitted for FIE analysis. These day-specific levels included mean or median, 5th, 10th, 90th and 95th percentile data. They were indexed to the day of ovulation, day 0, by ultrasonography, serum or urinary luteinizing hormone (LH). Results: All data sets showed a clear "cluster"-a periovulatory sequence of positive FIE values with a maximum. All clusters of +FIE signaled the transition from the ovulatory to luteal phase and were at least four days in length. The start day for the serum P and urinary PDG FIE clusters ranged from -3 to -1 and -3 to +2, respectively. The end day for serum P and PDG clusters went from +2 to +7 and +4 to +8, respectively. Outside these periovulatory FIE-P and FIE-PDG clusters, there were no consecutive positive FIE values. In addition, the maximum FIE-P and FIE-PDG values throughout the entire cycles were found in the clusters. Conclusions: FIE analysis with either daily serum P or urinary PDG levels provided a distinctive signature to recognize the periovulatory interval. The Fertility Indicator Equation served to robustly signal the transition from the ovulatory phase to the luteal phase. This may have applications in natural family planning especially with the recent emergence of home PDG tests.

A Novel Fertility Indicator Equation Using Estradiol Levels for Assessment of Phase of the Menstrual Cycle.

Background and Objectives: Urinary hormone home monitoring assays are now available for fertility awareness methods (FAMs) of family planning, but lack sensitivity and precision in establishing the start of the fertile phase. We hypothesized that with a suitable algorithm, daily serum or blood estradiol (E2) levels could serve as a better analyte to determine the phase of the ovulatory cycle and the fertile start day (FSD). Materials and Methods: Published day-specific serum E2 levels, indexed to the serum luteinizing hormone (LH) peak, were analyzed from three independent laboratories for a threshold for a FSD. A fertility indicator quation (FIE) was discovered and tested with these data and a FSD was determined using the mean or median and variance ranges of the day-specific E2 data. Results: The considerable variance of day-specific serum E2 levels made an absolute serum E2 indicator for phase of cycle problematic. However, a FIE was discovered which maps the day-specific E2 levels of the ovulatory cycle enabling the fertile phase and transition to the luteal phase to be signaled. In this equation, FIE(D) is the value of FIE on day, D, of the cycle and has both a magnitude and sign. The magnitude of FIE(D) is the product of the normalized change in day-specific E2 levels over two consecutive intervals, (D-2, D-1) and (D-1, D), multiplied by 100, and is formulated as: (E2 (on D-1) - E2 (on D-2))/E2 (on D-2) × (E2(on D) - E2 (on D-1))/E2 (on D-1) × 100. The sign of FIE(D) is either + or - or ind (indeterminate) and is assigned on the basis of the direction of this product. Using a FIE threshold of ≥2.5 as the start of the fertile phase, the FSDs were Day -5 or Day -6, with FSD Day -4 for an outlier set of E2 levels. The maximum FIE value ranged 9.5-27.8 and occurred most often on Day -2. An inflection point with a large change in FIE magnitude and change in sign from + to - always occurred at Day 0 for all sets of day-specific E2 data signaling transition to the luteal phase. Conclusions: The fertility indicator equation, a product of two sequential normalized changes in serum E2 levels with a sign indicating confidence in direction of change, is powerful in identifying the fertile phase and subsequent transition to the postovulatory phase and may serve as a useful algorithm for FAMs of family planning.

Cervical-Vaginal Mucin in Fertility Assessment: CA125 as a Predictor of the Fertile Phase of the Normal Menstrual Cycle.

: To evaluate the cervical-vaginal mucin, CA125, as a measure of fertility and possible method for natural family planning (NFP). Cervical-vaginal fluid (CVF) swab samples have been previously used to measure CA125, 'Qvaginal CA125 levels', as a function of time of cycle relative to Day 0, the first day of positive urine LH (luteinizing hormone). Data from 15 women, 20 cycles were used with an algorithm to establish the Fertile Start Day (FSD) for the cycles. The FSD was determined as either the second consecutive day of ≥20% Qvaginal CA125 rise or the first day of ≥400% rise. The interval, (FSD to Day +3), was used as the theoretical window of fertility, and conception rates assuming abstinence during this predicted period of fertility were computed using published day-specific probabilities of conception (PoC). The mean FSD was Day -4.8 ± 0.5 (SE), 95% CI (-5.9, -3.7). The estimated pregnancy failure rate (PFR) with abstinence during [FSD, +3] was 10.7% ± 2.0% (SE), 95% CI (6.9%, 14.8%); with exclusion of one cycle with very low levels of Qvaginal CA125, the estimated PFR was 9.8% ± 1.9%, 95% CI (6.3%, 13.8%). Furthermore, the day-specific Qvaginal CA125 values were normalized to the respective peak Qvaginal CA125 for each cycle, and a mean normalized day-specific Qvaginal CA125 plot was generated. The first derivative of the mean normalized day-specific Qvaginal CA125 plot showed a significant increase between Day -4.5 and Day -3.5, which correlated with the mean FSD. A Qvaginal CA125-based method holds promise as a means to identify the start of the fertile window and may prove useful in NFP, especially when combined with available home hormonal fertility awareness kits.

An empirical saddlepoint approximation method for producing smooth survival and hazard functions under interval-censoring.

We devise a new method to produce smooth estimates of baseline survival and hazard functions for incomplete data observed subject to interval-censoring, that can in principle be viewed as being nonparametric. The key idea is to start from the nonparametric maximum likelihood estimate, and to then construct an empirical moment generating function for the underlying data generating mechanism, which is subsequently inverted via a saddlepoint approximation in order to obtain smooth distributional estimates. Unlike the typical spline-based and other semiparametric methods that have thus far been devised for the same purpose, the proposed approach is unencumbered by the choice of tuning parameters. Simulation studies show that in terms of integrated squared error, the method is very close in performance to the parametric gold standard, and should generally be preferred over the well-established spline-based approach implemented in R package logspline. The methodology is illustrated on some publicly available real datasets, and its implications and limitations are discussed.

Linear regression model for predicting patient-specific total skeletal spongiosa volume for use in molecular radiotherapy dosimetry.

UNLABELLED: The toxicity of red bone marrow is widely considered to be a key factor in restricting the activity administered in molecular radiotherapy to suboptimal levels. The assessment of marrow toxicity requires an assessment of the dose absorbed by red bone marrow which, in many cases, requires knowledge of the total red bone marrow mass in a given patient. Previous studies demonstrated, however, that a close surrogate-spongiosa volume (combined tissues of trabecular bone and marrow)-can be used to accurately scale reference patient red marrow dose estimates and that these dose estimates are predictive of marrow toxicity. Consequently, a predictive model of the total skeletal spongiosa volume (TSSV) would be a clinically useful tool for improving patient specificity in skeletal dosimetry. METHODS: In this study, 10 male and 10 female cadavers were subjected to whole-body CT scans. Manual image segmentation was used to estimate the TSSV in all 13 active marrow-containing skeletal sites within the adult skeleton. The age, total body height, and 14 CT-based skeletal measurements were obtained for each cadaver. Multiple regression was used with the dependent variables to develop a model to predict the TSSV. RESULTS: Os coxae height and width were the 2 skeletal measurements that proved to be the most important parameters for prediction of the TSSV. The multiple R(2) value for the statistical model with these 2 parameters was 0.87. The analysis revealed that these 2 parameters predicted the estimated the TSSV to within approximately +/-10% for 15 of the 20 cadavers and to within approximately +/-20% for all 20 cadavers in this study. CONCLUSION: Although the utility of spongiosa volume in estimating patient-specific active marrow mass has been shown, estimation of the TSSV in active marrow-containing skeletal sites via patient-specific image segmentation is not a simple endeavor. However, the alternate approach demonstrated in this study is fairly simple to implement in a clinical setting, as the 2 input measurements (os coxae height and width) can be made with either pelvic CT scanning or skeletal radiography.

CT volumetry of the skeletal tissues.

Computed tomography (CT) is an important and widely used modality in the diagnosis and treatment of various cancers. In the field of molecular radiotherapy, the use of spongiosa volume (combined tissues of the bone marrow and bone trabeculae) has been suggested as a means to improve the patient-specificity of bone marrow dose estimates. The noninvasive estimation of an organ volume comes with some degree of error or variation from the true organ volume. The present study explores the ability to obtain estimates of spongiosa volume or its surrogate via manual image segmentation. The variation among different segmentation raters was explored and found not to be statistically significant (p value >0.05). Accuracy was assessed by having several raters manually segment a polyvinyl chloride (PVC) pipe with known volumes. Segmentation of the outer region of the PVC pipe resulted in mean percent errors as great as 15% while segmentation of the pipe's inner region resulted in mean percent errors within approximately 5%. Differences between volumes estimated with the high-resolution CT data set (typical of ex vivo skeletal scans) and the low-resolution CT data set (typical of in vivo skeletal scans) were also explored using both patient CT images and a PVC pipe phantom. While a statistically significant difference (p value <0.002) between the high-resolution and low-resolution data sets was observed with excised femoral heads obtained following total hip arthroplasty, the mean difference between high-resolution and low-resolution data sets was found to be only 1.24 and 2.18 cm3 for spongiosa and cortical bone, respectively. With respect to differences observed with the PVC pipe, the variation between the high-resolution and low-resolution mean percent errors was a high as approximately 20% for the outer region volume estimates and only as high as approximately 6% for the inner region volume estimates. The findings from this study suggest that manual segmentation is a reasonably accurate and reliable means for the in vivo estimation of spongiosa volume. This work also provides a foundation for future studies where spongiosa volumes are estimated by various raters in more comprehensive CT data