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Effective subset selection from complex oligonucleotide libraries is crucial for genomics, synthetic biology, and DNA data storage. The polymerase chain reaction, foundational for amplifying target subsets is limited by primer design and length for specificity, which constrains the scalability of oligo libraries and increases the synthesis burden for primers. We introduce an oligo subset selection methodology that utilizes sequence-specific cyclic nucleotide synthesis and blocking of the template oligos. This approach eliminates the need for primers for selective hybridization and enables the encoding and selection of hundreds of subsets with barcode lengths of fewer than five nucleotides. Moreover, cyclic selection enables a hierarchical data structure in the oligo library, enhancing the programmability. This advancement offers a scalable and cost-effective solution for handling complex oligo libraries.
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http://dx.doi.org/10.1038/s41467-025-56856-0 | DOI Listing |
JAACAP Open
September 2025
Columbia University, New York, New York.
Objective: The serotonin system has long been implicated in autism spectrum disorder. A previous study reported lower whole blood serotonin (WB5-HT) concentrations in the mothers of children with more severe autism. This study attempted to replicate this finding in an independent cohort.
View Article and Find Full Text PDFAm J Respir Cell Mol Biol
September 2025
Univ. of Pennsylvania, Medicine, Philadelphia, Pennsylvania, United States.
Lymphangioleiomyomatosis (LAM) is a rare lung disease caused by hyperactivation of the mechanistic/mammalian target of rapamycin 1 (mTORC1) growth pathway in a subset of mesenchymal lung cells. Histopathologically, LAM lesions have been described as immature smooth muscle-like cells positive for the immature melanocytic marker HMB45/PMEL/gp100 and phosphorylated ribosomal protein S6 (pS6). Advances in single cell sequencing (scRNA-seq) technology allowed us to group LAM cells according to their expression of cancer stem cell (CSC) genes and identify three clusters: a high CSC-like state (SLS), an intermediate state, and a low CSC-like inflammatory state (IS).
View Article and Find Full Text PDFPLoS One
September 2025
Information Technologies and Programming Faculty, ITMO University, Saint Petersburg, Russia.
In the paper we consider the well-known Influence Maximization (IM) and Target Set Selection (TSS) problems for Boolean networks under Deterministic Linear Threshold Model (DLTM). The main novelty of our paper is that we state these problems in the context of pseudo-Boolean optimization and solve them using evolutionary algorithms in combination with the known greedy heuristic. We also propose a new variant of (1 + 1)-Evolutionary Algorithm, which is designed to optimize a fitness function on the subset of the Boolean hypercube comprised of vectors of a fixed Hamming weight.
View Article and Find Full Text PDFPLoS One
September 2025
Smart Manufacturing and Artificial Intelligence, Micron Memory Malaysia Sdn. Bhd., Batu Kawan, Penang, Malaysia.
Advances in data collection have resulted in an exponential growth of high-dimensional microarray datasets for binary classification in bioinformatics and medical diagnostics. These datasets generally possess many features but relatively few samples, resulting in challenges associated with the "curse of dimensionality", such as feature redundancy and an elevated risk of overfitting. While traditional feature selection approaches, such as filter-based and wrapper-based approaches, can help to reduce dimensionality, they often struggle to capture feature interactions while adequately preserving model generalization.
View Article and Find Full Text PDFInt J Cancer
September 2025
Department of Medical Oncology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
A subset of rectal cancer (RC), <5%, exhibits mismatch repair deficiency (dMMR); the remaining are classified as proficient (pMMR). Reported evidence on differences between dMMR and pMMR RC is limited. In this nationwide Dutch study, we compared patients with dMMR and pMMR stage II/III RC based on patient and tumor characteristics, treatment patterns, and associated outcomes.
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