Role of Baseline Antral Follicle Count and Anti-Mullerian Hormone in Prediction of Cumulative Live Birth in the First In Vitro Fertilisation Cycle: A Retrospective Cohort Analysis

Objective

This retrospective study determined for the first time the role of baseline antral follicle count (AFC) and serum anti-Mullerian hormone (AMH) level in the first in-vitro fertilisation (IVF) cycle in predicting cumulative live birth from one stimulation cycle.

Methods

We studied 1,156 women (median age 35 years) undergoing the first IVF cycle. Baseline AFC and AMH level on the day before ovarian stimulation were analysed. The main outcome measure was cumulative live birth in the fresh plus all the frozen embryo transfers after the same stimulation cycle.

Results

Serum AMH was significantly correlated with AFC. Both AMH and AFC showed significant correlation with age and ovarian response in the stimulated cycle and total number of transferrable embryos. Baseline AFC and serum AMH were significantly higher in subjects attaining a live birth than those who did not in the fresh stimulated cycle, as well as those attaining cumulative live birth. There was a significant trend of higher cumulative live birth rate in women with higher AMH or AFC. However, logistic regression revealed that both AMH and AFC were not significant predictors of cumulative live birth after adjusting for age and number of embryos available for transfer. Considering only one single predictor, the areas under the ROC curves for AMH (0.646, 95% CI 0.616–0.675) and age (0.648, 95% CI 0.618–0.677) were slightly higher than that for AFC (0.617, 95% CI 0.587–0.647) in predicting cumulative live birth. However, a model combining AMH (with or without AFC) and age of the women only classified an addition of less than 2% of subjects correctly compared to the model with age alone.

Conclusion

Baseline AFC and serum AMH have only modest predictive performance on the occurrence of cumulative live birth, and may not give additional value on top of the women''s age.     

Intra-Peritoneal Hyperthermia Combining α-Galactosylceramide in the Treatment of Ovarian Cancer

The purpose of this study was to investigate the anti-tumor effect and potential mechanisms of i.p. hyperthermia in combination with α-galactosylceramide (α-GalCer) for the treatment of ovarian cancer. In this study, immuno-competent tumor models were established using murine ovarian cancer cell lines and treated with i.p. hyperthermia combining α-GalCer. Th1/Th2 cytokine expression profiles in the serum, NK cell cytotoxicity and phagocytic activities of dendritic cells (DCs) were assayed. We also analyzed the number of CD8⁺/IFN-γ⁺ tumor specific cytotoxic T cells, as well as the tumor growth based on depletion of lymphocyte sub-population. Therapeutic effect on those ovarian tumors was monitored by a non-invasive luminescent imaging system. Intra-peritoneal hyperthermia induced significant pro-inflammatory cytokines expression, and sustained the response of NK and DCs induced by α-GalCer treatment. The combination treatment enhanced the cytotoxic T lymphocyte (CTL) immune response in two mouse ovarian cancer models. This novel treatment modality by combination of hyperthermia and glycolipid provides a pronounced anti-tumor immune response and better survival. In conclusion, intra-peritoneal hyperthermia enhanced the pro-inflammatory cytokine secretion and phagocytic activity of DCs stimulated by α-GalCer. The subsequent CTL immune response induced by α-GalCer was further strengthened by combining with i.p. hyperthermia. Both innate and adaptive immunities were involved and resulted in a superior therapeutic effect in treating the ovarian cancer.     

Surface α-Enolase Promotes Extracellular Matrix Degradation and Tumor Metastasis and Represents a New Therapeutic Target

In previous research, we found α-enolase to be inversely correlated with progression-free and overall survival in lung cancer patients and detected α-enolase on the surface of lung cancer cells. Based on these findings, we hypothesized that surface α-enolase has a significant role in cancer metastasis and tested this hypothesis in the current study. We found that α-enolase was co-immunoprecipitated with urokinase-type plasminogen activator, urokinase-type plasminogen activator receptor, and plasminogen in lung cancer cells and interacted with these proteins in a cell-free dot blotting assay, which can be interrupted by α-enolase-specific antibody. α-Enolase in lung cancer cells co-localized with these proteins and was present at the site of pericellular degradation of extracellular matrix components. Treatment with antibody against α-enolase in vitro suppressed cell-associated plasminogen and matrix metalloproteinase activation, collagen and gelatin degradation, and cell invasion. Examination of the effect of treatment with shRNA plasmids revealed that down regulation of α-enolase decreases extracellular matrix degradation by and the invasion capacity of lung cancer cells. Adoptive transfer of α-enolase-specific antibody to mice resulted in accumulation of antibody in subcutaneous tumor and inhibited the formation of tumor metastasis in lung and bone. This study demonstrated that surface α-enolase promotes extracellular matrix degradation and invasion of cancer cells and that targeting surface α-enolase is a promising approach to suppress tumor metastasis.     

Moving Domain Computational Fluid Dynamics to Interface with an Embryonic Model of Cardiac Morphogenesis

Peristaltic contraction of the embryonic heart tube produces time- and spatial-varying wall shear stress (WSS) and pressure gradients (∇P) across the atrioventricular (AV) canal. Zebrafish (Danio rerio) are a genetically tractable system to investigate cardiac morphogenesis. The use of Tg(fli1a:EGFP)^y1 transgenic embryos allowed for delineation and two-dimensional reconstruction of the endocardium. This time-varying wall motion was then prescribed in a two-dimensional moving domain computational fluid dynamics (CFD) model, providing new insights into spatial and temporal variations in WSS and ∇P during cardiac development. The CFD simulations were validated with particle image velocimetry (PIV) across the atrioventricular (AV) canal, revealing an increase in both velocities and heart rates, but a decrease in the duration of atrial systole from early to later stages. At 20-30 hours post fertilization (hpf), simulation results revealed bidirectional WSS across the AV canal in the heart tube in response to peristaltic motion of the wall. At 40-50 hpf, the tube structure undergoes cardiac looping, accompanied by a nearly 3-fold increase in WSS magnitude. At 110-120 hpf, distinct AV valve, atrium, ventricle, and bulbus arteriosus form, accompanied by incremental increases in both WSS magnitude and ∇P, but a decrease in bi-directional flow. Laminar flow develops across the AV canal at 20-30 hpf, and persists at 110-120 hpf. Reynolds numbers at the AV canal increase from 0.07±0.03 at 20-30 hpf to 0.23±0.07 at 110-120 hpf (p< 0.05, n=6), whereas Womersley numbers remain relatively unchanged from 0.11 to 0.13. Our moving domain simulations highlights hemodynamic changes in relation to cardiac morphogenesis; thereby, providing a 2-D quantitative approach to complement imaging analysis.     

Joint analysis of single-cell and bulk tissue sequencing data to infer intratumor heterogeneity

Many computational methods have been developed to discern intratumor heterogeneity (ITH) using DNA sequence data from bulk tumor samples. These methods share an assumption that two mutations arise from the same subclone if they have similar mutant allele-frequencies (MAFs), and thus it is difficult or impossible to distinguish two subclones with similar MAFs. Single-cell DNA sequencing (scDNA-seq) data can be very informative for ITH inference. However, due to the difficulty of DNA amplification, scDNA-seq data are often very noisy. A promising new study design is to collect both bulk and single-cell DNA-seq data and jointly analyze them to mitigate the limitations of each data type. To address the analytic challenges of this new study design, we propose a computational method named BaSiC (B ulk tumor a nd Si ngle C ell), to discern ITH by jointly analyzing DNA-seq data from bulk tumor and single cells. We demonstrate that BaSiC has comparable or better performance than the methods using either data type. We further evaluate BaSiC using bulk tumor and single-cell DNA-seq data from a breast cancer patient and several leukemia patients.     

A Bayesian multi-risks survival (MRS) model in the presence of double censorings

Semi-competing risks data include the time to a nonterminating event and the time to a terminating event, while competing risks data include the time to more than one terminating event. Our work is motivated by a prostate cancer study, which has one nonterminating event and two terminating events with both semi-competing risks and competing risks present as well as two censoring times. In this paper, we propose a new multi-risks survival (MRS) model for this type of data. In addition, the proposed MRS model can accommodate noninformative right-censoring times for nonterminating and terminating events. Properties of the proposed MRS model are examined in detail. Theoretical and empirical results show that the estimates of the cumulative incidence function for a nonterminating event may be biased if the information on a terminating event is ignored. A Markov chain Monte Carlo sampling algorithm is also developed. Our methodology is further assessed using simulations and also an analysis of the real data from a prostate cancer study. As a result, a prostate-specific antigen velocity greater than 2.0 ng/mL per year and higher biopsy Gleason scores are positively associated with a shorter time to death due to prostate cancer.     

Strategies for high-concentration drug substance manufacturing to facilitate subcutaneous administration: A review

To achieve the high protein concentrations required for subcutaneous administration of biologic therapeutics, numerous manufacturing process challenges are often encountered. From an operational perspective, high protein concentrations result in highly viscous solutions, which can cause pressure increases during ultrafiltration. This can also lead to low flux during ultrafiltration and sterile filtration, resulting in long processing times. In addition, there is a greater risk of product loss from the hold-up volumes during filtration operations. From a formulation perspective, higher protein concentrations present the risk of higher aggregation rates as the closer proximity of the constituent species results in stronger attractive intermolecular interactions and higher frequency of self-association events. There are also challenges in achieving pH and excipient concentration targets in the ultrafiltration/diafiltration (UF/DF) step due to volume exclusion and Donnan equilibrium effects, which are exacerbated at higher protein concentrations. This paper highlights strategies to address these challenges, including the use of viscosity-lowering excipients, appropriate selection of UF/DF cassettes with modified membranes and/or improved flow channel design, and increased understanding of pH and excipient behavior during UF/DF. Additional considerations for high-concentration drug substance manufacturing, such as appearance attributes, stability, and freezing and handling are also discussed. These strategies can be employed to overcome the manufacturing process challenges and streamline process development efforts for high-concentration drug substance manufacturing.