Biology subjects

Ni, S.

Publications and source records attributed to Ni, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Benchmarking single-cell foundation models for aging biology

Single cell foundation models (scFMs) provide representations of cellular states, but their utility across biological questions in aging research remains unclear. We established a benchmark of cellular representations for aging research, evaluating ten general-purpose scFMs, three aging-specific models and conventional methods across five biological questions using more than 2.5 million single cell transcriptomes. Using frozen pretrained representations, Geneformer performed best among scFMs for chronological age prediction and age pseudotime concordance, although 2,000 highly variable genes achieved higher mean performance. Several scFMs captured positive molecular age shifts across three disease contexts, consistent with reported aging-associated changes. SCimilarity performed well for rare cellular state identification across out-of-distribution datasets, exceeding aging specific models and conventional baselines. At the gene level, scGPT showed the highest recovery of reference TF target interactions, including aging-related regulatory hubs. Overall, scFMs supported diverse aging analyses, but performance depended on the biological question, highlighting their utility for rare cellular state identification and regulatory analysis.

bioinformatics↗

bioRxiv2026

Repeat element-anchored enhancer-promoter interactions (REEPIs) shape the regulatory landscape of hormone-resistant breast cancer

Repeat elements (REs) comprise over half of the human genome and are increasingly recognized as regulatory components, yet their role in therapy resistance remains unclear. Here, we integrate CAGE and RADICL-seq to map regulatory elements and RNA-chromatin interactions in estrogen receptor-positive breast cancer cells (MCF7) and their long-term estrogen-deprived (LTED) derivatives. We identify repeat element-anchored enhancer-promoter interactions (REEPIs), defined by the presence of annotated REs at both enhancer and promoter sites. In LTED cells, REEPIs are enriched for ERV1 and ERVL elements and involve specific repeat pairings associated with transcription factor combinations such as SP1-SMAD3 and SP1-NFYC. At the gene level, these REEPIs are preferentially linked to genes involved in chromatin remodeling, DNA repair, and lineage plasticity. Our findings reveal a repeat-guided regulatory architecture associated with transcriptional adaptation in endocrine resistance and identify REEPIs as a previously underexplored component of regulatory reprogramming in hormone-resistant breast cancer.

cancer biology↗

bioRxiv2026

Probiotic-Directed Fermentation Reprograms the Metabolic Profile of a Traditional Mongolian Whole-Wheat Diet and Modulates Escherichia coli-Induced Gut Microbiota Dysbiosis

Traditional Mongolian fermented foods have been extensively utilized for dietary regulation and the promotion of gastrointestinal health. However, spontaneous fermentation remains inherently unpredictable, leading to significant variations in microbial community dynamics, metabolite accumulation, and the consistency and quality of the final product. Drawing on the traditional preparation of Mongolian acidic foods, this study established a controlled production strategy for whole-wheat probiotic fermented soup (WWPFS) by combining enzymatic pretreatment with probiotic-directed fermentation. Physicochemical characterization, 16S rRNA gene-based microbial community profiling, LC-MS/MS-based untargeted metabolomics, safety evaluation, and an Escherichia coli-induced gut microbiota dysbiosis model were employed to optimize and comprehensively characterize the fermentation process of WWPFS. The optimized process established a reproducible fermentation system consistently dominated by Lactobacillus and Bacillus across independent fermentation batches. Compared with traditional spontaneous fermentation, probiotic-directed fermentation remodeled the physicochemical properties of the whole-wheat matrix, including carbon, nitrogen, phosphorus, sulfur, and mineral composition, and facilitated the accumulation of putatively annotated LC-MS/MS features, including DL-lactate, 1,4-D-xylobiose, diacetyl, and phenyllactic-acid-related features derivatives. Acute oral and 28-day repeated-dose toxicity evaluations showed no treatment-related adverse effects within the tested dose range and study duration. In the Escherichia coli-induced gut microbiota dysbiosis mouse model, microbial richness, diversity, and community structure differed among the experimental groups, and both low- and high-dose WWPFS groups showed significant shifts in overall gut microbial community composition relative to the model group after multiple-testing correction, together with directional recovery of selected model-responsive bacterial genera. Cross-system integration identified coordinated response patterns between fermentation-derived metabolite features and model-responsive gut bacterial taxa, supporting a potential metabolite-microbiota link in WWPFS-mediated gut microbiota modulation. In summary, probiotic-directed fermentation improved the controllability of the traditional Mongolian fermented food production process, reshaped its metabolic profile, and enhanced its potential to modulate the gut microbiota. These findings provide experimental evidence supporting the modernization of traditional Mongolian fermented foods and the development of probiotic-based functional foods.

microbiology↗

bioRxiv2026

Pervasive Backdoor Vulnerabilities in Genomic Foundation Models

Genomic foundation models are increasingly used to interpret and design DNA sequences, yet their susceptibility to training-data manipulation remains poorly understood. Here we systematically evaluate backdoor poisoning across three model families, seven parameter scales ranging from 50 million to 7 billion, and 18 genomic classification tasks. We introduce two complementary 48-nucleotide triggers: a composition-matched synthetic sequence and a biologically grounded trigger derived from transposon terminal inverted repeats. Poisoning 5% of the training data induced high attack success rates across all tested models, with model-level median values ranging from 91.4% to 100%. Increasing parameter scale did not consistently improve resistance, whereas poisoning rate and trigger length had stronger effects on attack efficacy. Performance on unmodified sequences was generally preserved, with 79.4% of model - task - trigger configurations changing by no more than two percentage points, although larger task-specific losses occurred. We further developed a two-stage defense that combines single-nucleotide mutation-sensitivity screening with reference-database validation. Across 28 evaluated configurations, the method achieved 100% precision and a median recall of 92.95%, while localizing the trigger in nearly all detected poisoned sequences. These findings establish training-data poisoning as a pervasive and difficult-to-detect vulnerability in genomic foundation models and motivate stronger data-provenance controls, adversarial evaluation and post-training security auditing.

bioinformatics↗

bioRxiv2026

Systematic In Silico Off-Target Assessment of siRNAs: Integrated Tissue-Specific Scoring and Cross-Species Preclinical Model Selection with TargetSureR

Small interfering RNAs (siRNAs) have become a transformative class of nucleic acid therapeutics for clinical disease treatment, yet sequence-dependent off-target silencing continues to pose a major safety barrier that hinders their preclinical refinement and large-scale translational application. Existing bioinformatics tools only support partial off-target evaluation, either focusing on basic sequence optimization or simple seed-region scanning, and fail to deliver systematic, multi-dimensional and reproducible safety assessment for siRNA lead screening. To fill this gap, we developed TargetSureR, a lightweight, modular and CRAN-compatible open-source R package dedicated to full-process siRNA off-target risk profiling. This tool accommodates dual sequence-based and precomputed position-based inputs, integrates GTEx multi-tissue expression data and curated cancer, adverse-event and immune gene panels, and establishes a seven-dimensional scoring framework to stratify off-target risks into four hierarchical tiers. It further enables tissue-specific safety characterization and quantitative cross-species model selection, with an Ensembl API fallback mechanism ensuring high transcript annotation resolution. Built purely in R with no external shell dependencies, TargetSureR provides a standardized, robust and user-friendly workflow for systematic siRNA preclinical safety evaluation, and is freely available at https://github.com/nishuai/TargetSureR.

bioinformatics↗

bioRxiv2026

CESAR: High-Sensitivity Detection of Copy Number Variations in ctDNA Using Segmentation and Anchor Recalibration

BackgroundDetecting copy number variations (CNVs) in circulating tumor DNA (ctDNA) is crucial for the companion diagnosis and resistance monitoring of various solid tumors (e.g., NSCLC, Glioblastoma). However, when tumor-derived DNA fractions are extremely low (often <1%), traditional depth-based methods frequently fail due to non-linear sequencing depth fluctuations and probe-specific capture biases inherent to targeted Next-Generation Sequencing (NGS). MethodsWe developed CESAR (CNV Estimation with Segmentation and Anchor Recalibration), a computational tool for tumor-only CNV detection in targeted NGS panels. CESAR uses Circular Binary Segmentation (CBS) to re-partition target regions according to relative capture efficiency, then applies a data-driven "anchor" selection procedure that, for each target segment, identifies a personalized set of co-varying genomic segments. By selecting the anchor set that minimizes the coefficient of variation (CV) of the anchor-recalibrated depth ratio across a panel of normals, CESAR recalibrates the per-segment baseline and suppresses probe-specific technical noise. Copy-number status is then called from the deviation of the observed ratio against this trained baseline. ResultsUsing standard DNA reference materials, CESAR identified amplifications of MET, ERBB2, and EGFR at low tumor fractions. CESAR resolved focal alterations as subtle as 2.18 copies (a 1.09-fold change relative to the diploid baseline) while reporting no false-positive amplifications in diploid control regions. Applied to a clinical cohort of nine NSCLC ctDNA samples profiled on a 94-gene panel, CESAR successfully separated three MET-amplified samples from six matched negatives, where the standard CNVkit-based pipeline failed to distinguish them. In head-to-head benchmarking on identical data, CESAR reduced technical variance relative to the widely used CNVkit and more reproducibly resolved low-level copy-number gains, particularly in the depth-heterogeneous MET amplicon. ConclusionsCESAR provides a stable and sensitive framework for tumor-only CNV calling in liquid biopsies. On reference standards it outperforms CNVkit in bias and reproducibility, and on a clinical NSCLC cohort it recovered MET CNV abnormalities that a standard CNVkit pipeline missed. Validation on larger and more diverse cohorts is warranted.

bioinformatics↗

bioRxiv2026

Unleashed condensation by recurrent mutations of an epigenetic regulator promotes cancer

The pathological mechanisms and significance for the prevalent hotspot mutations in disordered protein regions are poorly understood. ASXL1 is an obligate co-factor for BAP1 in H2AK119 deubiquitination. ASXL1 mutations are very frequent in myeloid malignancies, and are mostly C-terminal truncating mutations concentrated in a specific disordered region of ASXL1. ASXL1 truncations are gain-of-function mutations that promote myeloid malignancies, but the underlying mechanisms remain poorly understood. Here we show that the frequently truncated mutants of ASXL1 possess an intrinsic property of forming phase-separated biomolecular condensates, and this property is normally suppressed by the frequently deleted regions. A disease-mutant of the endogenous ASXL1 in leukemia cells forms dynamic nuclear co-condensates with other endogenous factors important for gene activation. The ASXL1 disease-mutants can greatly enhance H2A deubiquitination activity of BAP1 in cells and in vitro reconstituted system, enhance myeloid leukemia cell growth, and promote leukemogenesis in a mouse transplant model by turning on myeloid leukemogenic transcriptional programs. However, substitution of residues important for condensation disrupted or impaired all these abilities, suggesting that the condensation property is crucially important for the ASXL1 mutants in promoting cancer. Moreover, we discover that the conserved negative charges in the highly disordered and frequently deleted region on ASXL1 suppress the condensation of the wild type ASXL1. Charge-neutralizing mutations in this region restores condensation of the full-length ASXL1, and are sufficient to turn ASXL1 into a leukemogenic protein. Biochemical, biophysical, and simulation analyses suggest the intramolecular interactions normally mask the N-terminal region in engaging intermolecular interactions required for phase separation, and disease truncations escape from the regulatory interactions and unleash the phase separation property to form nuclear hubs to promote expression of tumorigenic gene programs. Finally, by showing a striking correlation of the mutation frequencies with the condensation properties and leukemogenesis activity for a series of human patient mutations, we suggest that dysregulation of condensation is a central mechanism for ASXL1 mutations in promoting myeloid malignancies. This suggests that dysregulation of condensation may be a key mechanism for some of the prevalent hotspot disease mutations in the disordered proteomes.

biochemistry↗

bioRxiv2025

LISA: A Comprehensive R Package for Lentiviral Integration Site Analysis in Gene Therapy Safety Assessment

BackgroundGene therapy using integrating viral vectors has shown remarkable clinical success, but the random integration of vectors into the host genome poses potential safety concerns, particularly insertional mutagenesis. Common Integration Sites (CIS) near oncogenes significantly increase the risk of clonal expansion and malignant transformation. Current tools for integration site (IS) analysis lack comprehensive functionality for safety assessment, particularly in identifying risk-associated genomic regions and tracking clonal dynamics over time. ResultsWe developed LISA (Longitudinal Integration Site Analysis), a comprehensive R package specifically designed for gene therapy safety evaluation. LISA incorporates a novel approach that trains integration site profiles using cumulative curves derived from normal cell infusion samples and normal patient samples, with subsequent statistical testing to distinguish these normal samples from those with exceptional clonal expansion, thereby enabling effective identification of dominant clone formation. For longitudinal studies, LISA monitors fluctuations in clonal dynamics via Richness and Evenness metrics, and integrates this cumulative curve-based statistical testing approach into its early warning system to detect potentially dominant clones. Additionally, LISA features an optimized CIS detection algorithm with O (n log n) time complexity, achieved through chromosome-position encoding and a seed-site strategy, which facilitates efficient analysis of large-scale clinical datasets. The package also provides systematic functional annotations, including annotations for Safe Harbor regions, enhancer/promoter elements, and proximity to three curated gene sets: adverse event-associated genes (AE genes, n=36), cancer-related genes (n=980), and immune-related genes (n=2,485). Furthermore, it encompasses six categories of interactive visualizations and has been validated using real clinical data from gene therapy trials.

bioinformatics↗

bioRxiv2025

Decoding Prokaryotic Whole Genomes with a Product-Contextualized Large Language Model

Genomes encode the instructions for life, yet their interpretation requires models capable of capturing long-range genome-wide functional context at scale. Existing genomic foundation models have primarily focused on sequence-level representations, providing powerful tools for biological prediction while leaving complementary opportunities for function-level genome modeling. Here, we present GenSyntax, a function-level genome representation learning framework that models prokaryotic genomes as ordered sequences of gene-product descriptors. By treating gene products as semantic units, GenSyntax transforms annotated replicons into interpretable "genetic paragraphs" that capture genome-wide functional context. We trained GenSyntax on 49,250 annotated prokaryotic genomes and evaluated its ability across genome-scale tasks, including plasmid host prediction, gene-product disambiguation, genome contig ordering and gene essentiality prediction. Compared with general-purpose large language models and representative genomic foundation models, GenSyntax achieved competitive performance across multiple benchmarks, with independent external evaluations supporting its generalization beyond the original training datasets. GenSyntax embeddings also captured signals associated with microbial phenotypes, and gene essentiality predictions enabled exploratory design of minimal genomes. Together with the lightweight GenSyntax-Tiny model, GenSyntax provides a complementary, post-annotation framework for function-level analysis of prokaryotic genomes.

genomics↗

bioRxiv2024

Identify compound-protein interaction with knowledge graph embedding of perturbation transcriptomics

The emergence of perturbation transcriptomics provides a new perspective and opportunity for drug discovery, but existing analysis methods suffer from inadequate performance and limited applicability. In this work, we present PertKGE, a method designed to improve compound-protein interaction with knowledge graph embedding of perturbation transcriptomics. PertKGE incorporates diverse regulatory elements and accounts for multi-level regulatory events within biological systems, leading to significant improvements compared to existing baselines in two critical "cold-start" settings: inferring binding targets for new compounds and conducting virtual ligand screening for new targets. We further demonstrate the pivotal role of incorporating multi- level regulatory events in alleviating dataset bias. Notably, it enables the identification of ectonucleotide pyrophosphatase/phosphodiesterase-1 as the target responsible for the unique anti- tumor immunotherapy effect of tankyrase inhibitor K-756, and the discovery of five novel hits targeting the emerging cancer therapeutic target, aldehyde dehydrogenase 1B1, with a remarkable hit rate of 10.2%. These findings highlight the potential of PertKGE to accelerate drug discovery by elucidating mechanisms of action and identifying novel therapeutic compounds.

bioinformatics↗

bioRxiv2024

PackDock: a Diffusion Based Side Chain Packing Model for Flexible Protein-Ligand Docking

Structure-based drug design (SBDD) relies on accurate knowledge of protein structure and ligand-binding conformations. However, most of the static conformations obtained by advanced methods such as structural biology and de novo protein folding algorithms often dont meet the needs for drug design. We introduce PackDock, a flexible docking method that combines "conformation selection" and "induced fit" mechanisms in a two-stage docking pipeline. The core module of this method is PackPocket, which uses a diffusion model to explore the side-chain conformation space in ligand binding pockets, both with or without a ligand. We evaluate our method using several tests that reflect real-world application scenarios. (1) Side-chain packing and Re-docking experiments validate the ability of PackDock to predict accurate side-chain conformations and ligand conformations. (2) Cross-docking experiments with apo and non-homologous ligand-induced holo structures align with real docking scenarios, demonstrating PackDocks practical value. (3) Docking experiments with hypothetical models show that PackPocket can potentially conduct SBDD starting from protein sequence information only. Additionally, we found that PackDock can identify key amino acid conformation changes, which may provide insights for lead compound optimization. We demonstrate PackDock can accurately predict the complex conformations in various application scenarios, by combining the conformation selection theory and the induced fit theory, and by using the ability of PackPocket to accurately predict the side chain conformations in the pocket region. We believe this method can improve the usability of existing structures, providing a new perspective for the SBDD community.

bioinformatics↗

bioRxiv2023

Landscape and functional repertoires of long noncoding RNAs in the pan-cancer tumor microenvironment using single-nucleus total RNA sequencing

Intratumor heterogeneity (ITH) plays crucial roles in tumor progression. However, the atlas of long noncoding RNAs (lncRNAs) in the context of ITH across multiple cancer types remains largely unexplored. Here, we analyze over 800,000 cells from ten different cancer types generated from the random-primed single-nucleus total RNA sequencing and provide a systematic landscape of lncRNAs in tumor microenvironment (TME) and malignant programs. Our study employe a robust cell annotation pipeline called scAnnotation, which allows us to identify 39 distinct cell types within the pan-cancer TME. By applying stringent criteria, we identify thousands of reliable marker genes, including both mRNAs and lncRNAs. Next, we identify sets of cell type-specific lncRNA-mRNA pairs by our LncPairs algorithm. Moreover, we identify nine expression meta-programs (MPs) associated with diverse biological processes in malignant cells across multiple cancer types. MP-specific lncRNA-transcription factor (TF) regulatory networks are further constructed and key lncRNAs and regulons that exert control over MP-specific gene expression are identified. The comprehensive atlas of lncRNAs in the pan-cancer context, coupled with the bioinformatics tools tailored for the random-primed datasets, is expected to accelerate advancements in the field of lncRNA research at the single-cell resolution.

cancer biology↗

bioRxiv2023

TranSiGen: Deep representation learning of chemical-induced transcriptional profile

With the advancement of high-throughput RNA sequencing technologies, the use of chemical-induced transcriptional profiling has greatly increased in biomedical research. However, the usefulness of transcriptomics data is limited by inherent random noise and technical artefacts that may cause systematical biases. These limitations make it challenging to identify the true signal of perturbation and extract knowledge from the data. In this study, we propose a deep generative model called Transcriptional Signatures Generator (TranSiGen), which aims to denoise and reconstruct transcriptional profiles through self-supervised representation learning.TranSiGen uses cell basal gene expression and compound molecular structure representation to infer the chemical-induced transcriptional profile. Results demonstrate the effectiveness of TranSiGen in learning and predicting differential expression genes. The representation derived from TranSiGen can also serve as an alternative phenotype information, with applications in ligand-based virtual screening, drug response prediction, and phenotype-based drug repurposing. We envisage that integrating TranSiGen into the drug discovery and mechanism research pipeline will promote the development of biomedicine.

bioinformatics↗

bioRxiv2023

DNA conserved across animals that controls genes for embryonic development

DNA that controls gene expression (e.g. enhancers, promoters) has seemed almost never to be conserved between distantly-related animals, like vertebrates and arthropods. This is mysterious, because development of such animals is partly organized by homologous genes with similar complex expression patterns, termed "deep homology". Here we report twenty-five regulatory DNA segments conserved across bilaterian animals, of which seven are also conserved in cnidaria (coral and sea anemone). They control developmental genes (e.g. Nr2f, Ptch, Rfx1/3, Sall, Smad6, Sp5, Tbx2/3), including six homeobox genes: Gsx, Hmx, Meis, Msx, Six1/2, and Zfhx3/4. The segments contain perfectly or near-perfectly conserved CCAAT boxes, E-boxes, and other sequences recognized by regulatory proteins. More such DNA conservation will surely be found soon, as more genomes are published and sequence comparison is optimized. This reveals a control system for animal development conserved since the Precambrian.

developmental biology↗

bioRxiv2022

An immune-suppressing protein in human endogenous retroviruses

Retroviruses are important contributors to disease and evolution in vertebrates. Sometimes, retrovirus DNA is heritably inserted in a vertebrate genome: an endogenous retrovirus (ERV). Vertebrate genomes have many such virus-derived fragments, usually with mutations disabling their original functions. Some primate ERVs appear to encode an overlooked protein. This protein is homologous to protein MC132 from Molluscum contagiosum virus, which is a human poxvirus, not a retrovirus. MC132 suppresses the immune system by targeting NF-{kappa}B, and it had no known homologs until now. The ERV homologs of MC132 in the human genome are mostly disrupted by mutations, but there is an intact copy on chromosome 4. We found homologs of MC132 in ERVs of apes, monkeys, and bushbaby, but not tarsiers, lemurs or non-primates. This suggests that some primate retroviruses had, or have, an extra immune-suppressing protein, which underwent horizontal genetic transfer between unrelated viruses.

bioinformatics↗

bioRxiv2022

Sensitization of Chrysosplenetin against Artemisinin Resistant Plasmodium berghei K173 via Blocking Host ABC Transporters Potentially Mediated by NF-κBB p52 or PXR/CAR Signaling Pathway

This study investigated if artemisinin-chrysosplenetin combination (ART-CHR) improved ART antimalarial efficacy against resistant Plasmodium berghei K173 via depressing host ABC transporter and potential molecular mechanism. Parasitaemia% and inhibition% were calculated and gene/protein expressions of ABC transporters or PXR/CAR/NF-{kappa}B p52 were detected by Western-blot and RT-qPCR. In vitro transcription of PXR/CAR was studied by dual-luciferase reporter assay. Our data indicated that ART-CHR improved ART efficacy against resistant parasites. P-gp inhibitor verapamil and CHR showed a stronger effect in killing resistant parasites while vehicle and Bcrp inhibitor novobiocin did not. ART activated intestinal ABCB1/ABCG2 and CHR inhibited them. ART decreased Bcrp protein whereas CHR increased it. ART ascended ABCC1/ABCC4/ABCC5 mRNA but ART-CHR descended them. CHR as well as rifampin (RIF) or 5-fluorouracil (5-FU) increased transcription levels of PXR/CAR while showed a versatile regulation on in vivo hepatic and enternal PXR/CAR in Mdr1a+/+ (WT) or Mdr1a-/- (KO) mice infected with sensitive or resistant parasites. Oppositely, hepatic and enteric N-{kappa}B p52 mRNA was conformably decreased in WT but increased in KO-resistant mice. NF-{kappa}B pathway should potentially involved in the mechanism of CHR on inhibiting ABC transporters and ART resistance while PXR/CAR play a more complicated role in this mechanism.

molecular biology↗

bioRxiv2021

The overlapping modular organization of human brain functional networks across the adult lifespan

Previous lifespan studies have demonstrated that the brain functional modular organization would change along with the adult lifespan. Yet, they assumed mutual exclusion among functional modules, ignoring convergent evidence for the existence of modular overlap. To reveal how age affects the overlapping functional modular organization, this study applied a detection algorithm requiring no prior knowledge of the resting-state fMRI data of a healthy cohort (N = 570, 18-88 years). Age-related regression analyses found a linear decrease in the overlapping modularity and the similarity of modular structure and overlapping node (i.e., region involved in multiple modules) distribution. The number of overlapping nodes increased with age, but the increment was distributed unevenly. In addition, across the adult lifespan and within each age group, the nodal overlapping probability consistently exhibited positive correlations with both functional gradient and flexibility. Further, we showed that the influence of age on memory-related cognitive performance might be explained by the change in the overlapping functional modular organization. Together, our results revealed age-related decreased segregation from the perspective of brain functional overlapping modular organization, providing new insight into the adult lifespan change in brain function and its influence on cognitive performance.

neuroscience↗

bioRxiv2021

High-speed widefield handheld swept-source OCT angiography with a VCSEL light source

Optical coherence tomography (OCT) and OCT angiography (OCTA) enable noninvasive structural and angiographic imaging of the eye. Portable handheld OCT/OCTA systems are required for imaging patients in the supine position. Examples include infants in the neonatal intensive care unit (NICU) and operating room (OR). The speed of image acquisition plays a pivotal role in acquiring high quality OCT/OCTA images, particularly with the handheld system, since both the operator hand tremor and subject motion can cause significant motion artifacts. In addition, having a large field of view and the ability of real-time data visualization are critical elements in rapid disease screening, reducing imaging time, and detecting peripheral retinal pathologies. The arrangement of optical components is less flexible in the handheld system due to the limitation of size and weight. In this paper, we introduce a 400-kHz, 55-degree field of view handheld OCT/OCTA system that has overcome many technical challenges as a portable OCT system as well as a high-speed OCTA system. We demonstrate imaging premature infants with retinopathy of prematurity (ROP) in the NICU, and patients with incontinentia pigmenti (IP) in the OR using our handheld OCT system. Our design may have potential for improving the diagnosis of retinal diseases and help provide a practical guideline for designing a flexible and portable OCT system.

bioengineering↗