Biology subjects

Ray, B.

Publications and source records attributed to Ray, B..

5 recordsLinked to original sources

bioRxiv2026

Microporous Immune-Isolating Capsule with Improved Diffusion for Restored Dynamic Bidirectional Hormone Signaling in a Murine Model of Premature Ovarian Insufficiency

Pediatric cancer survivors treated with gonadotoxic chemotherapy or radiation face lifelong premature ovarian insufficiency (POI), leading to elevated risk of cardiovascular disease, osteoporosis, and metabolic dysfunction. Pharmacological hormone replacement therapy (HRT) cannot replicate the pulsatile, bidirectional signaling of the hypothalamic-pituitary-gonadal (HPG) axis, leaving a critical therapeutic gap. Immune-isolating hydrogel capsules offer a promising strategy for the implantation of donor ovarian tissue without immunosuppression yet they require optimization for human applications. Here, we engineer a microporous immune-isolating capsule by incorporating thermosensitive gelatin microgels as sacrificial porogens. Microfluidic fabrication yielded monodisperse microgels that dissolved at 37{degrees}C generating disconnected micropores within a non-degradable poly(ethylene glycol) (PEG) matrix. Critically, the diffusion of FSH-scale analogs (40 kDa) increased by almost two-fold through the microporous capsules relative to nanoporous controls, while antibody-scale molecules (150 kDa) were blocked, demonstrating size-discriminating permeability. In ovariectomized mice implanted with encapsulated ovarian xenografts for 20 weeks, microporous capsules restored dynamic HPG-axis signaling evidenced by elevated levels of estradiol and progesterone, FSH suppression, and fluctuating hormone levels that resembled physiological patterns. Microporosity also improved graft viability, increasing stromal cellularity and reducing follicular apoptosis. These findings support microporous immune-isolating capsules as a platform for physiologically authentic therapy for POI.

bioengineering↗

bioRxiv2025

Restoration of ovarian endocrine function with encapsulated immune isolated human ovarian xenograft in ovariectomized mice

Anti-cancer treatments cause premature depletion of the non-renewable ovarian reserve of follicles, the source of key steroid hormones, leading to premature ovarian insufficiency (POI) in 50% of pediatric cancer survivors. Patients with POI, especially at the onset of pubertal development, experience significant endocrine complications, including delayed growth, elevated risks of obesity and diabetes, and accelerated cardiovascular, musculoskeletal and neurological disorders as adults. The only approved pharmacological treatment for POI is an off-label prescribed hormone replacement therapy, which does not replace physiologically functioning ovaries. To restore production of ovarian hormones and protect against immune-mediated injury, we developed a hydrogel-based capsule for implantation of donor ovarian tissue. We evaluated the restoration of ovarian endocrine function in ovariectomized immunodeficient (NOD scid gamma, NSG) mice implanted with encapsulated xenografts over 20 weeks through daily vaginal cytology, hormone measurements and histological analysis of explanted human xenografts. The encapsulated xenografts integrated into the murine hypothalamus-pituitary-gonad (HPG) axis responding to circulating murine gonadotropins and restoring ovarian endocrine function. As controls, we implanted non encapsulated human ovarian xenografts comparable in size. Without the need for exogeneous stimulation, the estrous cyclicity resumed in both groups of mice 12 weeks post implantation and all mice regularly cycled experiencing between 3 to 8 estrous cycles in 20 weeks. The levels of estradiol gradually increased reaching on average 50pg/mL 20 weeks post implantation. Morphological analysis of the encapsulated grafts revealed presence of large antral follicles, [~]3mm in diameter, consistent with regular cyclicity and measurable levels of circulating hormones. This work demonstrates that endocrine function of encapsulated human ovarian tissue was not affected by the encapsulation and integrated with the host physiology similarly to the non-encapsulated controls.

bioengineering↗

bioRxiv2023

Replication and Refinement of Brain Age Model for adolescent development.

The discrepancy between chronological age and estimated brain age, known as the brain age gap, may serve as a biomarker to reveal brain development and neuropsychiatric problems. This has motivated many studies focusing on the accurate estimation of brain age using different features and models, of which the generalizability is yet to be tested. Our recent study has demonstrated that conventional machine learning models can achieve high accuracy on brain age prediction during development using only a small set of selected features from multimodal brain imaging data. In the current study, we tested the replicability of various brain age models on the Adolescent Brain Cognitive Development (ABCD) cohort. We proposed a new refined model to improve the robustness of brain age prediction. The direct replication test for existing brain age models derived from the age range of 8-22 years onto the ABCD participants at baseline (9 to 10 years old) and year-two follow-up (11 to 12 years old) indicate that pre-trained models could capture the overall mean age failed precisely estimating brain age variation within a narrow range. The refined model, which combined broad prediction of the pre-trained model and granular information with the narrow age range, achieved the best performance with a mean absolute error of 0.49 and 0.48 years on the baseline and year-two data, respectively. The brain age gap yielded by the refined model showed significant associations with the participants information processing speed and verbal comprehension ability on baseline data.

neuroscience↗

bioRxiv2021

Decentralized Brain Age Estimation using MRI Data

Recent studies have demonstrated that neuroimaging data can be used to predict brain age, as it captures information about the neuroanatomical and functional changes the brain undergoes during development and the aging process. However, researchers often have limited access to neuroimaging data because of its challenging and expensive acquisition process, thereby limiting the effectiveness of the predictive model. Decentralized models provide a way to build more accurate and generalizable prediction models, bypassing the traditional data-sharing methodology. In this work, we propose a decentralized method for brain age estimation and evaluate it on three different feature sets, including both volumetric and voxelwise structural MRI data as well as resting functional MRI data. The results demonstrate that a decentralized brain age model can achieve similar performance compared to the models trained with all the data in one location.

neuroscience↗

bioRxiv2018

Mapping molecular HLA typing data to UNOS antigen equivalents for improved virtual crossmatch

BackgroundVirtual crossmatch utilizes HLA typing and antibody screen assay data as a part of organ offers in deceased donor allocation systems. Histocompatibility labs must convert molecular HLA typings to antigen equivalencies for entry into the United Network for Organ Sharing (UNOS) UNet system. While an Organ Procurement and Transplantation Network (OPTN) policy document provides general guidelines for conversion, the process is complex because no antigen mapping table is available. We present a UNOS antigen equivalency table for all IMGT/HLA alleles at the A, B, C, DRB1, DRB3/4/5, DQA1, and DQB1 loci.\n\nMethodsAn automated script was developed to generate a UNOS antigen equivalency table. Data sources used in the conversion algorithm included the World Marrow Donor Association(WMDA) antigen table, the HLA Dictionary, and UNOS-provided tables. To validate antigen mappings, we converted National Marrow Donor Program (NMDP) high resolution allele frequencies to antigen equivalents and compared with the UNOS Calculated Panel Reactive Antibodies (CPRA) reference panel.\n\nResultsNormalized frequency similarity scores between independent NMDP and UNOS panels for 4 US population categories (Caucasian, Hispanic, African American and Asian/Pacific Islander) ranged from 0.85 to 0.97, indicating correct antigen mapping. An open source web application (ALLele to ANtigen (\"ALLAN\")) and web services were also developed to map unambiguous and ambiguous HLA typing data to UNOS antigen equivalents based on NMDP population-specific allele frequencies (http://www.transplanttoolbox.org).\n\nConclusionsThis tool sets a foundation for using molecular HLA typing to compute the virtual crossmatch and may aid in reducing typing discrepancies in UNet.

bioinformatics↗