Publications by authors named "Y Cohen"

Study Objective: To evaluate the impact of Asherman's Syndrome (AS) following hysteroscopic adhesiolysis on reproductive outcomes and the time to achieve pregnancy in infertile women undergoing in vitro fertilization (IVF) treatment.

Design: Case control study.

Setting: Tertiary university-affiliated medical center.

Patients: Fifty-one infertile women who were treated for AS and underwent IVF (study group) matched for age and etiology of infertility with non-AS controls at a 1:1 ratio.

Interventions: Medical records search, chart review, and phone survey were used to assess reproductive outcomes.

Main Outcome Measures: A multivariate logistic regression analyses was used to assess live birth, accounting for patient age at stimulation cycle start, parity, number of embryo's transferred and endometrial thickness. A survival analysis was performed to assess the times that had lapsed from interventions to conception.

Results: The study group of 51 women included 38 (74.5%) with moderate-to-severe disease. The mean number of embryo transfers (ET) per woman was similar for the study and control groups (4.9±4.6 vs. 6.22±4.3, respectively, p=.78). The controls had a significantly higher mean endometrial thickness before ET (8.7±1.8 mm vs. 6.95±1.7 mm, p=.001). The overall time to achieve live birth was significantly longer in women with AS (p=0.022). In a logistic regression analysis, the presence of moderate-to-severe AS was shown to be independent factors for achieving a live birth (adjusted odds ratio 0.174, 95% confidence interval [CI] 0.032-0.955, p=.004). Women with AS who had live births had a significantly thicker mean endometrial thickness (8.2±1.4 mm vs 6.9±1.2, p=.001).

Conclusions: Moderate and severe AS has a detrimental effect upon reproductive performance in infertile women. Endometrial thickness is an important predictor for live births among women with AS who undergo IVF.

Enzymes are well known for their catalytic abilities, some even reaching "catalytic perfection" in the sense that the reaction they catalyze has reached the physical bound of the diffusion rate. However, our growing understanding of enzyme superfamilies has revealed that only some share a catalytic chemistry while others share a substrate-handle binding motif, for example, for a particular phosphate group. This suggests that some families emerged through a "substrate-handle-binding-first" mechanism ("binding-first" for brevity) instead of "chemistry-first" and we are, therefore, left to wonder what the role of non-catalytic binders might have been during enzyme evolution. In the last of their eight seminal, back-to-back articles from 1976, John Albery and Jeremy Knowles addressed the question of enzyme evolution by arguing that the simplest mode of enzyme evolution is what they defined as "uniform binding" (parallel stabilization of all enzyme-bound states to the same degree). Indeed, we show that a uniform-binding proto-catalyst can accelerate a reaction, but only when catalysis is already present, that is, when the transition state is already stabilized to some degree. Thus, we sought an alternative explanation for the cases where substrate-handle-binding preceded any involvement of a catalyst. We find that evolutionary starting points that exhibit negative catalysis can redirect the reaction's course to a preferred product without need for rate acceleration or product release; that is, if they do not stabilize, or even destabilize, the transition state corresponding to an undesired product. Such a mechanism might explain the emergence of "binding-first" enzyme families like the aldolase superfamily.

Anemia is a major complication of end-stage kidney disease (ESKD). Erythropoiesis-stimulating agents and intravenous (IV) iron are the current backbone of anemia treatment in ESKD. Iron overload induced by IV iron is a potential clinical problem in dialysis patients. We compared the pharmacokinetics of liver accumulation of iron sucrose, currently used worldwide, with two third-generation IV irons (ferric carboxymaltose and iron isomaltoside). We hypothesized that better pharmacokinetics of newer irons could improve the safety of anemia management in ESKD. Liver iron concentration (LIC) was analyzed in 54 dialysis patients by magnetic resonance imaging under different modalities of iron therapy. LIC increased significantly in patients treated with 1.2 g or 2.4 g IV iron sucrose ( < 0.001, Wilcoxon test), whereas no significant increase was observed in patients treated with ferric carboxymaltose or iron isomaltoside ( > 0.05, Wilcoxon-test). Absolute differences in LIC reached 25 μmol/g in the 1.2 g iron sucrose group compared with only 5 μmol/g in the 1 g ferric carboxymaltose and 1 g iron isomaltoside groups ( < 0.0001, Kruskal-Wallis test). These results suggest the beneficial consequences of using ferric carboxymaltose or iron isomaltoside on liver structure in ESKD due to their pharmacokinetic ability to minimize iron overload.

Mutations to the genes encoding the RNA polymerase core enzyme (RNAPC) and additional housekeeping regulatory genes were found to be involved in adaptation, in the context of numerous evolutionary experiments, in which bacteria were exposed to diverse selective pressures. This provides a conundrum, as the housekeeping genes that were so often mutated in response to these diverse selective pressures tend to be among the genes that are most conserved in their sequences across the bacterial phylogeny. In order to further examine this apparent discrepancy, we characterized the precise positions of the RNAPC involved in adaptation to a large variety of selective pressures. We found that RNAPC lab adaptations tended to occur at positions displaying traits associated with higher selective constraint. Specifically, compared to other RNAPC positions, positions involved in adaptation tended to be more conserved in their sequences within bacteria, were more often located within defined protein domains, and were located closer to the complex's active site. Higher sequence conservation was also found for resource exhaustion adaptations occurring within additional housekeeping genes. Combined, our results demonstrate that the positions that change most readily in response to well-defined selective pressures exerted in lab environments are often also those that evolve most slowly in nature.

Longitudinal 'omics analytical methods are extensively used in the evolving field of precision medicine, by enabling 'big data' recording and high-resolution interpretation of complex datasets, driven by individual variations in response to perturbations such as disease pathogenesis, medical treatment or changes in lifestyle. However, inherent technical limitations in biomedical studies often result in the generation of feature-rich and sample-limited datasets. Analyzing such data using conventional modalities often proves to be challenging since the repeated, high-dimensional measurements overload the outlook with inconsequential variations that must be filtered from the data in order to find the true, biologically relevant signal. Tensor methods for the analysis and meaningful representation of multiway data may prove useful to the biological research community by their advertised ability to tackle this challenge. In this study, we present tcam-a new unsupervised tensor factorization method for the analysis of multiway data. Building on top of cutting-edge developments in the field of tensor-tensor algebra, we characterize the unique mathematical properties of our method, namely, 1) preservation of geometric and statistical traits of the data, which enable uncovering information beyond the inter-individual variation that often takes over the focus, especially in human studies. 2) Natural and straightforward out-of-sample extension, making tcam amenable for integration in machine learning workflows. A series of re-analyses of real-world, human experimental datasets showcase these theoretical properties, while providing empirical confirmation of tcam's utility in the analysis of longitudinal 'omics data.