Towards Feature-based ML-enabled Behaviour Location

Mapping behaviours to the features they relate to is a prerequisite for variability-intensive systems (VIS) reverse engineering. Manually providing this whole mapping is labour-intensive. In black-box scenarios, only execution traces are available (e.g., process mining). In our previous work, we successfully experimented with variant-based mapping using supervised machine learning (ML) to identify the variants responsible of the production of a given execution trace, and demonstrated that recurrent neural networks (RNNs) work well (above 80% accuracy) when trained on datasets in which we label execution traces with variants. However, this mapping (i) may not scale to large VIS because of combinatorial explosion and (ii) makes the internal ML representation hard to understand. In this short paper, we discuss the design of a novel approach: feature-based mapping learning

Corifollitropin alfa or rFSH treatment flexibility options for controlled ovarian stimulation: a post hoc analysis of the Engage trial

BACKGROUND: We sought to determine the impact of treatment flexibility on clinical outcomes in either a corifollitropin alfa or recombinant follicle-stimulating hormone (rFSH) protocol. METHODS: Post hoc analysis of a prospective, multicenter, randomized, double-blind, double-dummy non-inferiority clinical trial (Engage). Efficacy outcomes were assessed on patients from the Engage trial who started treatment on menstrual cycle day 2 versus menstrual cycle day 3, patients who received rFSH step-down or fixed-dose rFSH, patients who received rFSH on the day of human chorionic gonadotropin (hCG) compared with those who did not, and patients who received hCG when the criterion was reached versus those with a 1-day delay. RESULTS: The effect of each of the treatment flexibility options on ongoing pregnancy rate was not significant. The estimated difference (95% confidence interval) in ongoing pregnancy rate was -4.3% (-9.4%, 0.8%) for patients who started ovarian stimulation on cycle day 2 versus day 3, 1.8% (-4.1%, 7.6%) for patients who received hCG on the day the hCG criterion was met versus 1 day after, 3.2% (-2.1%, 8.6%) for patients who received rFSH on the day of hCG administration versus those who did not, and -5.8% (-13.0%, 1.4%) for patients who received a reduced versus fixed-dose of rFSH from day 8. CONCLUSIONS: Treatment flexibility of ovarian stimulation does not substantially affect the clinical outcome in patients’ treatment following initiation of ovarian stimulation with either corifollitropin alfa or with daily rFSH in a gonadotropin-releasing hormone antagonist protocol. TRIAL REGISTRATION: Trial was registered under ClinicalTrials.gov identifier NCT00696800

VaryMinions:Leveraging RNNs to Identify Variants in Event Logs

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VaryMinions:Leveraging RNNs to Identify Variants in Variability-intensive Systems’ Logs

From business processes to course management, variability-intensive software systems (VIS) are now ubiquitous. One can configure these systems’behaviour by activating options, e.g., to derive variants handling building permits across municipalities or implementing different functionalities (quizzes, forums) for a given course. These customisation facilities allow VIS to support distinct relevant customer requirements while taking advantage of reuse for common parts. Customisation thus allows realising both scope and scale economies. Behavioural differences amongst variants manifest themselves in event logs. To re-engineer this kind of system, one must know which variant(s) have produced which behaviour. Since variant information is barely present in logs, this paper supports this task by employing machine learning techniques to classify behaviours (event sequences) among variants. Specifically, we train Long Short Term Memory (LSTMs) and Gated Recurrent Units (GRUs) recurrent neural networks to relate event sequences with the variants they belong to on six different datasets issued from the configurable process and VIS domains. After having evaluated 20 different architectures of LSTM/GRU, our results demonstrate that it is possible to effectively learn the trace-to-variant mapping with high accuracy (at least 80% and up to 99%) and at scale, i.e., identifying 50 variants using 5000+ traces for each variant

Developmental stage on day-5 and fragmentation rate on day-3 can influence the implantation potential of top-quality blastocysts in IVF cycles with single embryo transfer

BACKGROUND: In IVF-ICSI cycles with single embryo transfer (SET), embryo selection for transfer is of crucial importance. The present study aimed to define which embryo parameters might be related to the implantation potential of advanced blastocysts. METHODS: Overall, in 203 cycles with SET, developmental characteristics of 93 implanted (group A) and 110 non-implanted (group B) advanced blastocysts of good quality were compared. The following developmental parameters were assessed in the two groups: normal fertilization, developmental stage on day 5, number of blastomeres on day 2 and on day 3, fragmentation rate on day 3, compaction on day 4 and cleavage pattern on day 2 and day 3. RESULTS: Expanded blastocysts compared to full blastocysts have higher implantation potential (56.5% vs. 29.3%, p < 0.05). In group B, a higher proportion of advanced blastocysts showed between 10% and 50% anucleated fragments on day 3 than in group A (23.6 vs 11.8, P = 0.03). Advanced blastocysts with >10–50% fragments on day 3 showed a significant lower implantation (29.7%) than those with ≤ 10%fragments (49.4%, P = 0.03). All the other parameters analysed were comparable for the two groups. CONCLUSION: Developmental stage on day 5 and fragmentation rate on day 3 were related to the implantation potential of advanced blastocysts and should also be taken into account in the selection of the best advanced blastocyst for transfer

Aromatase inhibitors in post-menopausal endometriosis

Postmenopausal endometriosis is a rare clinical condition. The diagnosis and treatment of an endometriotic lesion in postmenopausal women is complicated. First line treatment choice should be surgical, given that there is a potential risk of malignancy. Medical treatment may be considered as second line or as an alternate first line treatment whenever surgery is contradicted and aims to alter the hormonal pathway leading to endometriosis progress. Different hormonal regimens have been administered to these patients, with conflicting however results. Aromatase inhibitors (AIs) represent one of the most recently used drugs for postmenopausal endometriosis. Clinical data for the use of (AIs) in postmenopausal patients is scarce. Up to date only 5 case reports are available regarding the use of these agents in postmenopausal women. Although definite conclusions may be premature, AIs appear to considerably improve patients' symptoms and reduce endometriotic lesions size. Nonetheless the subsequent induced reduction in estrogen production, leads to certain short-term and long-term adverse effects. Despite the limited available data, AIs appear to represent a new promising method which may improve symptoms and treat these patients, either as first line treatment, when surgery is contraindicated or as a second line for recurrences following surgical treatment. However, careful monitoring of patients' risk profile and further research regarding long-term effects and side-effects of these agents is essential prior implementing them in everyday clinical practice

Obstetric outcome in donor oocyte pregnancies: a matched-pair analysis

BACKGROUND: To investigate the obstetrical and perinatal impact of oocyte donation, a cohort of women who conceived after OD was compared with a matched control group of women who became pregnant through in vitro fertilisation with autologous oocytes (AO). METHODS: A matched-pair analysis has been performed at the Centre for Reproductive Medicine of the UZ Brussel, Dutch speaking Free University of Brussel. A total of 410 pregnancies resulted in birth beyond 20 weeks of gestation occurring over a period of 10 years, including 205 oocyte donation pregnancies and 205 ICSI pregnancies with autologous oocytes (AO). Patients in the OD group were matched on a one-to-one basis with the AO group in terms of age, ethnicity, parity and plurality. Matched groups were compared using paired t-tests for continuous variables and McNemar test for categorical variables. A conditional logistic regression analyses was performed adjusting for paternal age, age of the oocyte donor, number of embryos transferred, and singleton/twin pregnancy. RESULTS: Oocyte donation was associated with an increased risk of pregnancy induced hypertension (PIH) (matched OR: 1.502 CI: 1.024-2.204), and first trimester bleeding (matched OR: 1.493 CI: 1.036-2.15). No differences were observed between the two matched groups with regard to gestational age, mean birth weight and length, head circumference and Apgar scores. CONCLUSIONS: Oocyte donation is associated with an increased risk for PIH and first trimester bleeding independent of the recipients’ age, parity and plurality, and independent of the age of the donor or the partner. However, oocyte donation has no impact on the overall perinatal outcome

New candidate genes to predict pregnancy outcome in single embryo transfer cycles when using cumulus cell gene expression

Objective: To relate the gene expression in cumulus cells surrounding an oocyte to the potential of the oocyte, as evaluated by the embryo morphology (days 3 and 5) and pregnancy obtained in single-embryo transfer cycles. Design: Retrospective analysis of individual human cumulus complexes using quantitative real-time polymerase chain reaction for 11 genes. Setting: University hospital IVF center. Patient(s): Thirty-three intracytoplasmic sperm injection patients, of which 16 were pregnant (4 biochemical and 12 live birth). Intervention(s): Gene expression analysis in human cumulus complexes collected individually at pickup, allowing a correlation with the outcome of the corresponding oocyte. Multiparametric models were built for embryo morphology parameters and pregnancy prediction to find the most predictive genes. Main Outcome Measure(s): Gene expression profile of 99 cumulus complexes for 11 genes. Result(s): For embryo morphology prediction, TRPM7, ITPKA, STC2, CYP11A1, and HSD3B1 were often retained as informative. Models for pregnancy-biochemical or live birth-complemented or not with patient and cycle characteristics, always retained EFNB2 and CAMK1D together with STC1 or STC2. Positive and negative predictive values of the live birth models were &gt;85%. Conclusion(s): EFNB2 and CAMK1D are promising genes that could help to choose the embryo to transfer with the highest chance of a pregnancy. (Fertil Steril Ò 2012;98:432-9. Ó2012 by American Society for Reproductive Medicine.