Stephen Lincoln

University of Connecticut

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Ranjan Srivastava

University of Connecticut

Bryan D. Cowan

University of Mississippi Medical Center

Cecil A. Long

American Society for Reproductive Medicine

Michael S. Opsahl

Posiva (Finland)

Joerg Graf

University of Connecticut

Steven D. Harris

Iowa State University

Mark R. Marten

University of Maryland, Baltimore County

Keith L. Blauer

Reproductive Science Center

Susan H. Black

Institute for Community Living

Jacquelynn Benjamino

Jackson Laboratory

Cooperative Institutions

Hudson Institute

John Wiley & Sons (United Kingdom)

Genetics and IVF Institute

University of Maryland, Baltimore County

Erasmus MC

National Institutes of Health

Erasmus University Rotterdam

University of Maryland, Baltimore

University of Louisville

Virginia Commonwealth University Medical Center

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Aggressive outpatient treatment of ovarian hyperstimulation syndrome with ascites using transvaginal culdocentesis and intravenous albumin minimizes hospitalization.

Journal of Assisted Reproduction and Genetics (2002)

Stephen Lincoln Michael S. Opsahl Keith L. Blauer Susan H. Black Joseph D. Schulman

Ovarian hyperstimulation syndrome

Controlled ovarian hyperstimulation

Outpatient clinic

10.1023/a:1014828027282

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Citations (31)

Luteal phase consequences of low-dose gonadotropin-releasing hormone agonist therapy in nonluteal-supported in vitro fertilization cycles

Fertility and Sterility (1995)

Cecil A. Long Victoria M. Sopelak Stephen Lincoln Bryan D. Cowan

Gonadotropin-releasing hormone agonist

Gonadotropin

10.1016/s0015-0282(16)57795-4

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Citations (9)

Metabolite Overproduction through Engineering and Optimization of Microbiome Composition Dynamics

Stephen Lincoln Jacquelynn Benjamino Joerg Graf Ranjan Srivastava

Although many advances have been made in genome sequencing for analyzing the composition of microbiomes, very few studies have attempted to learn and model their dynamics. Furthermore, no studies have attempted to exploit the dynamics of compositional changes of a microbiome for overproducing a metabolite of interest. This task proves to be computationally difficult at best and intractable at worst. The challenge is due to the complex, interdependent, and large number of highly non-linear interactions among members of a microbiome, as well as environmental factors, e.g. substrate. Here, we present a computationally tractable strategy using machine learning methods and stochastic optimization to characterize and potentially engineer a microbiome. In this work, an artificial neural network (ANN) is utilized to learn how six different lignocellulose food sources affect the temporal composition of the hindgut microbiome of Reticulitermes flavipes, the eastern subterranean termite. The learned dynamics from the ANN are optimized using either a genetic algorithm or artificial immune system approach. Specifically, the optimization objective is the maximization of the Rhodospirillales, an acetate producing order of bacteria, which will intrinsically maximize acetate production from the microbiome. The genetic algorithm and artificial immune system are compared for robustness and speed.

Robustness

Maximization

10.1145/2908961.2908999

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A prospective study on the association between red hair color and endometriosis in infertile patients

Fertility and Sterility (1995)

Steven H. Woodworth Manvinder Singh Marvin A. Yussman Joseph S. Sanfilippo Christine Cook

Cabello

10.1016/s0015-0282(16)57809-1

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Citations (45)

Altered secretion patterns and cell wall organization caused by loss of PodB function in the filamentous fungus Aspergillus nidulans

Scientific Reports (2018)

Karthik Boppidi Liliane Fraga Costa Ribeiro Sirasa Iambamrung Sidney M. Nelson Yan Wang

Filamentous fungi are widely used in the production of a variety of industrially relevant enzymes and proteins as they have the unique ability to secrete tremendous amounts of proteins. However, the secretory pathways in filamentous fungi are not completely understood. Here, we investigated the role of a mutation in the POlarity Defective (podB) gene on growth, protein secretion, and cell wall organization in Aspergillus nidulans using a temperature sensitive (Ts) mutant. At restrictive temperature, the mutation resulted in lack of biomass accumulation, but led to a significant increase in specific protein productivity. Proteomic analysis of the secretome showed that the relative abundance of 584 (out of 747 identified) proteins was altered due to the mutation. Of these, 517 were secreted at higher levels. Other phenotypic differences observed in the mutant include up-regulation of unfolded protein response (UPR), deformation of Golgi apparatus and uneven cell wall thickness. Furthermore, proteomic analysis of cell wall components in the mutant revealed the presence of intracellular proteins in higher abundance accompanied by lower levels of most cell wall proteins. Taken together, results from this study suggest the importance of PodB as a target when engineering fungal strains for enhanced secretion of valuable biomolecules.

Aspergillus nidulans

Secretory protein

Filamentous fungus

Fungal protein

10.1038/s41598-018-29615-z

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Citations (6)

Extended clomiphene citrate (CC) and prednisone for the treatment of chronic anovulation resistant to CC alone

Fertility and Sterility (1997)

John D. Isaacs Stephen Lincoln Bryan D. Cowan

Anovulation

Clomifene

Regimen

10.1016/s0015-0282(97)81359-3

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Citations (37)

High-Order Multiple Gestations Can Be Limited by Controlling the Number of Completely Intact Embryos Transferred in Frozen-Thawed Embryo Transfer (FET) Cycles

Fertility and Sterility (2000)

Michael S. Opsahl M.E. Geltinger Susan H. Black Keith L. Blauer Stephen Lincoln

10.1016/s0015-0282(00)00994-8

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Citations (0)

Serum cotinine is a better predictor of successful in vitro fertilization than smoking history

Journal of the Society for Gynecologic Investigation (1998)

Riddle Ke B FRAZIER Stephen Lincoln William H. Kutteh

Cotinine

Smoking history

10.1016/s1071-5576(97)86274-0

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Citations (2)

The expression of human chorionic gonadotropin/human luteinizing hormone receptors in ectopic human endometrial implants.

The Journal of Clinical Endocrinology & Metabolism (1992)

Stephen Lincoln Zhenmin Lei Ch.V. Rao Marvin A. Yussman

Our laboratory previously demonstrated that normal human endometrium contains hCG/human LH receptors. Since ectopic endometrial implants in endometriosis arise directly at least in part from uterine endometrium, we investigated whether the implants continue the expression of these receptors. The presence of hCG/LH receptor mRNA and/or immunoreactive receptor protein in ectopic endometrial implants on pelvic peritoneum, uterine endometrium, and unaffected or normal peritoneum from patients with (n = 12) and without (n = 14) clinically apparent endometriosis was examined by in situ hybridization and immunocytochemistry analyses. The results showed that the peritoneal biopsies with visible or microscopic endometrial implants contain receptor mRNA and receptor protein. The glands contain more receptor mRNA and receptor protein than stromal cells in implants similar to uterine endometrium from patients with or without endometriosis. However, there is no consistent difference in the expression of receptors in implants compared to uterine endometria from patients with or without endometriosis. Contrary to ectopic endometrial implants, unaffected or normal peritoneum contain neither receptor mRNA nor receptor protein. In summary, we conclude that ectopic endometrial implants contain hCG/LH receptor mRNA and receptor protein, which suggests new possibilities in the medical treatment of endometriosis.

Human chorionic gonadotropin

10.1210/jcem.75.4.1400884

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Citations (29)

Metabolic Design And Engineering Through Ant Colony Optimization

Stephen Lincoln Ian S. Rogers Ranjan Srivastava

Due to the vast search space of all possible combinations of reaction knockouts in Escherichia coli, determining the best combination of knockouts for over-production of a metabolite of interest is a computationally expensive task. Ant colony optimization (ACO) applied to genome-scale metabolic models via flux balance analysis (FBA) provides a means by which such a solution space may feasibly be explored. In previous work, the Minimization of Metabolic Adjustment (MoMA) objective function for FBA was used in conjunction with ACO to identify the best gene knockouts for succinic acid production. In this work, algorithmic and biological constraints are introduced to further reduce the solution space. We introduce Stochastic Exploration Edge Reduction Ant Colony Optimization, or STEER-ACO. Algorithmically, ACO is modified to refine its search space over time allowing for greater initial coverage of the solution space while ultimately honing on a high quality solution. Biologically, a heuristic is introduced allowing the maximum number of knockouts to be no greater than five. Beyond this number, cellular viability becomes suspect. Results using this approach versus previous methods are reported.

Gene knockout

Metabolic Engineering

Flux Balance Analysis

10.1145/2739480.2754817

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Citations (0)