Biology subjects

Mo, Z.

Publications and source records attributed to Mo, Z..

17 recordsLinked to original sources

bioRxiv2026

Identification of highly immunogenic endogenous dsRNAs from cellular MDA5 filaments

ADAR1 converts adenosine to inosine in endogenous double-stranded RNAs (dsRNAs) to prevent excessive MDA5-driven interferon-stimulated gene expression. The source of endogenous immunogenic dsRNAs remains enigmatic because only a small fraction of ADAR1 substrates activate MDA5, and cellular MDA5 filaments have not been isolated. Here, we couple affinity purification of cellular MDA5 filaments with RNA sequencing to define immunogenic endogenous dsRNAs. Greater than 84% of dsRNAs suppressed by combined DDX3X RNA helicase and ADAR1 base-editing activities were present in MDA5 filaments, compared to less than 1% of dsRNA substrates acted on by ADAR1 alone. Dual substrate dsRNAs consisted of inverted repeats embedded in 3-UTRs with high base-pair complementarity and longer intervening sequences between repeats, with a minor contribution coming from intermolecular dsRNAs formed by sense and antisense transcripts. Moreover, the majority of dual substrate immunogenic dsRNAs were hyperedited in DDX3X mutant cancers. This reveals the identity of endogenous immunogenic dsRNAs and quality control mechanisms underlying their suppression.

cell biology↗

bioRxiv2026

rDNA breaks activate dsRNA pattern recognition through sense-antisense transcription

Myriad DNA damaging chemo- and radio- therapies interfere with ribosomal RNA (rRNA) transcription and processing, yet the biological consequences of these phenomena remain unclear. Here we show that aberrant transcripts emanating from rDNA breaks engage double-stranded RNA pattern recognition receptors, melanoma differentiation-associated protein 5 (MDA5) and retinoic acid-inducible gene I (RIG-I) to activate immune signaling. rDNA damage abolishes full-length rRNA synthesis while generating truncated sense-antisense rRNA transcripts, whose accumulation is restrained by ATM and ATR kinase activities. Purification of the endogenous MDA5-filament coupled with sequencing identified complementary sense and antisense rRNA transcripts that terminate and initiate near the break site, respectively. This implicates aberrant rRNA species as a major source of damage induced endogenous ligands for dsRNA pattern recognition and establishes a mechanism by which nucleolar stress is coupled to immune signaling.

cell biology↗

bioRxiv2026

A Conserved Metabolic Oxidative Axis Underlies Immune Cell Cryo-vulnerability

Immunotherapy has emerged as a transformative approach for treating cancer and other diseases, yet its widespread deployment requires effective cryopreservation strategies to enable scalable global distribution. However, many immune cell types remain acutely vulnerable to freeze-thaw stress, and the underlying mechanisms of this cryo-vulnerability are not well defined. In this study, we combined metabolic flux analysis, ROS quantification, lipidomics, and preclinical xenograft models to investigate how metabolic state influences cryopreservation outcomes. We found that immune cell activation induces a metabolic shift characterized by elevated glucose utilization and excessive ROS production, leading to profound post-thaw loss of viability and function, as demonstrated by a [~]25% survival rate in natural killer (NK) cells. Targeted pretreatments--including inhibitors of glucose metabolism, antioxidants, and suppression of lipid peroxidation--restored post-thaw recovery to nearly 90% while preserving effector activity and antitumor efficacy. Similar protective effects were observed across {beta} T cells, {gamma}{delta} T cells, and macrophages, defining a conserved metabolic-oxidative pathway of cryo-vulnerability and offering applicable strategies to enhance immune cell preservation.

immunology↗

bioRxiv2025

The persistence and loss of hard selective sweeps amid ancient human admixture

The extent to which human adaptations have persisted throughout history despite strong eroding demographic events such as admixture, genetic drift, and fluctuations in selection pressures remains unknown. Understanding which adaptations were resilient to such forces may shed light on traits that were important for humans across time. Yet, detecting selection from ancient DNA is challenging due to severe degradation of the data and/or signal. Here we detect selective sweeps using a domain-adaptive neural network (DANN) trained on simulated data and applied to more than 800 ancient and modern Eurasian genomes spanning the last 7000 years. We show that the DANN can account for simulation misspecification, or discrepancies between simulations and real aDNA, improving the ability to detect sweeps in real data compared to standard convolutional neural networks or standard statistics. Application of the DANN to data recovered 16 known sweeps at loci including LCT, HLA, KITLG, and OCA2/HERC2, and revealed 32 novel sweeps. All identified sweeps were classified as hard, consistent with historically low population sizes. While some sweeps were lost over time, 14 sweeps at loci involved in functions including neuronal, reproductive, pigmentation, and signaling traits persisted from the earliest to the most recent time periods. In most cases, the most frequent haplotype remained at high frequency across time. Together, these results indicate that hard sweeps predominated in ancient Eurasians and that several ancient selective events were resilient to strong admixture events. Significance statementThe extent to which human adaptations have persisted despite strong eroding forces such as admixture, drift, or fluctuations in selection pressures remains unknown. Understanding which loci are particularly resilient to such forces may shed light on the traits that were important for humans across time. Using a domain-adaptive neural network that accounts for simulations with misspecified demography relative to the data, we discover several sweeps at loci encoding neuronal, reproductive, pigmentation, and signaling traits persisted from the earliest time periods to the present, revealing the resilience of these sweeps to strong admixture events. Moreover, we find that hard sweeps, driven by single beneficial mutations, dominated throughout human history, consistent with the historically low human population sizes.

evolutionary biology↗

bioRxiv2025

Circulating tumor cell heterogeneity and MMP9 expression in clinical correlation with breast cancer

ObjectivesThis study aimed to investigate the association between the heterogeneity of circulating tumor cell (CTC) subtypes and the expression patterns of matrix metalloproteinase 9 (MMP9) with clinicopathological parameters in breast cancer patients. The distribution of CTC subtypes, MMP9 expression levels, and their influence on tumor progression. MethodsA total of 303 breast cancer patients were enrolled in this study. The association between CTCs subtypes in peripheral blood, MMP9 expression and clinical or pathological data of patients were analyzed. ResultsThe number of mesenchymal CTCs increased significantly with the number of lymph node metastases (P < 0.05), and high MMP9 expression was positively correlated with lymph node involvement (P < 0.05). The proportion of intermediate to high MMP9 expression was significantly higher in mixed CTCs compared to epithelial and mesenchymal CTCs (P < 0.05). High MMP9 expression in tumor tissues was associated with increased CTCs production and induction of epithelial-mesenchymal transition (EMT) (P < 0.05), as well as an elevated number of MMP9-positive CTCs (P < 0.05). ConclusionsThese findings suggest that MMP9 is positively associated with CTCs production and EMT process, and MMP9 may contribute to tumor metastasis by promoting CTC shedding and EMT by degrading the extracellular matrix. We recommend compliance with the Mesh guidelines: https://www.ncbi.nlm.nih.gov/mesh/

cancer biology↗

bioRxiv2024

The Integrated Stress Response Suppresses PINK1-dependent Mitophagy by Preserving Mitochondrial Import Efficiency

Mitophagy is crucial for maintaining mitochondrial health, but how its levels adjust to different stress conditions remains unclear. In this study, we investigated the role of the DELE1-HRI axis of integrated stress response (ISR) in regulating mitophagy, a key mitochondrial stress pathway. Our findings show that the ISR suppresses mitophagy under non-depolarizing mitochondrial stress by positively regulating mitochondrial protein import, independent of ATF4 activation. Mitochondrial protein import is regulated by the rate of protein synthesis under both depolarizing and non-depolarizing stress. Without ISR, increased protein synthesis overwhelms the mitochondrial import machinery, reducing its efficiency. Under depolarizing stress, mitochondrial import is heavily impaired even with active ISR, leading to significant PINK1 accumulation. In contrast, non-depolarizing stress allows more efficient protein import in the presence of ISR, resulting in lower mitophagy. Without ISR, mitochondrial protein import becomes severely compromised, causing PINK1 accumulation to reach the threshold necessary to trigger mitophagy. These findings reveal a novel link between ISR-regulated protein synthesis, mitochondrial import, and mitophagy, offering potential therapeutic targets for diseases associated with mitochondrial dysfunction.

cell biology↗

bioRxiv2024

The effects of 17α-estradiol treatment on endocrine system revealed by single-nucleus transcriptomic sequencing of hypothalamus

In this study, we investigated 17-estradiols role in lifespan extension from long-term administration. Pooled hypothalami from aged male Norway brown rats treated with 17-estradiol (O.T), aged male controls (O), and young male controls (Y) underwent single-nucleus transcriptomic sequencing (snRNA-seq). To evaluate the effects of 17-estradiol on aging neurons, supervised clustering of neurons based on neuropeptides and their receptors were used to evaluate the responses of each neuron subtype during aging and after 17-estradiol treatment. The elevated cellular metabolism, stress and decreased expression levels of pathways involved in synapse formation in neurons initiated by aging were significantly attenuated by 17-estradiol. Assessment of changes in neuron populations showed that neurons related to food intake, reproduction, blood pressure, stress response, and electrolyte balance were sensitive to 17-estradiol treatment. 17-estradiol treatment not only increased serum Oxytocin (Oxt), but also heightened the activity of hypothalamic-pituitary-gonadal (HPG) axis, as evidenced by significantly elevated levels of plasma Gnrh, total testosterone, and decreased estradiol. Elevated Gnrh1 was confirmed to be one of the causal effects mediating the role of 17-estradiol in energy homeostasis, neural synapse, and stress response. Notably, Crh neurons exhibited prominent stressed phenotype in O.T, distinct to appetite-stimulating neurons Agrp and Ghrl. Therefore, the HPG axis and energy metabolism may be key targets of 17-estradiol in male hypothalamus. Additionally, supervised clustering of neurons was shown to be a useful method for assessing treatment responses and cellular perturbation among different neuron subtypes in the hypothalamus.

neuroscience↗

bioRxiv2023

Comparison of chronic aerosol inhalation with combustible cigarette and e-cigarette on the psychiatric behaviors and neuroimmune profile in mice

With the worldwide use of electronic cigarettes (e-cigarettes) as a substitution for tobacco, the effects of e-cigarette vapor exposure on human health have been investigated. However, the comparison of long-term effects of aerosol inhalation with combustible cigarette and e-cigarette on the psychiatric behaviors has not been fully revealed. The present study examines the distinct effects of combustible cigarette and e-cigarette on anxiety, depression, cognition, and social behaviors. Here we found that the combustible cigarette induced the higher level of anxiety after long-term inhalation compared to the e-cigarettes with or without the tobacco flavor. Since the mechanism of action on the psychiatric behaviors entails the alterations on the neuroimmune-sensors and principal regulators such as glial cells, we further profiled the alterations of microglia and astrocytes by chronic inhalation of combustible tobacco cigarette, specifically the negative correlations between the IBA-1 level in the locus coeruleus (LC) and the latency to nest in VLT; as well as the GFAP level in LC and the open arm time in EPM were observed. Our current data provided an insight into the less impact of e-cigarettes on the anxiety-like behaviors and neuroimmune activation compared to combustible tobacco cigarettes which is not related to the flavor in e-cigarette, and the modulation on the neuroimmune signals in LC could be a therapeutic target for smoking-related anxiety.

animal behavior and cognition↗

bioRxiv2023

MiceVAPORDot: A novel automated approach for high-throughput behavioral characterization during E-cigarette exposure in mice

The prosperity of electronic nicotine delivery systems (ENDS) or e-cigarette use has been regarded to lead an increasing risk of nicotine addiction, especially among youth. Understanding and evaluating the behaviors induced by ENDS are fundamental to the study of neuropsychiatric effects of e-cigarettes. However, little is known regarding the behavioral features during e-cigarette exposure in mice. Current behavioral assessments for nicotine addiction are based on nicotine withdrawal-induced anxiety which can be only performed after ENDS exposures. Here we developed MiceVAPORDot, a novel high-throughput tool for automated in situ behavioral characterization during e-cigarette exposure. The integration of a deep learning-based animal pose tracking method by MiceVAPORDot allows precise characterization on behavioral phenotypes of e-vapor exposed mice, which were unable revealed by traditional evaluation methodology such as conditioned place preference and elevated plus maze tests. The behavioral fingerprints recognized by MiceVAPORDot can be used for high-throughput screening on incentive nature of e-cigarette flavors as well as medications for smoking cessation.

animal behavior and cognition↗

bioRxiv2023

High-Throughput Bioprinting of the Nasal Epithelium using Patient-derived Nasal Epithelial Cells

Human nasal epithelial cells (hNECs) are an essential cell source for the reconstruction of the respiratory pseudostratified columnar epithelium composed of multiple cell types in the context of infection studies and disease modeling. Hitherto, manual seeding has been the dominant method for creating nasal epithelial tissue models. However, the manual approach is slow, low-throughput and has limitations in terms of achieving the intricate 3D structure of the natural nasal epithelium in a uniform manner. 3D Bioprinting has been utilized to reconstruct various epithelial tissue models, such as cutaneous, intestinal, alveolar, and bronchial epithelium, but there has been no attempt to use of 3D bioprinting technologies for reconstruction of the nasal epithelium. In this study, for the first time, we demonstrate the reconstruction of the nasal epithelium with the use of primary hNECs deposited on Transwell inserts via droplet-based bioprinting (DBB), which enabled high-throughput fabrication of the nasal epithelium in Transwell inserts of 24-well plates. DBB of nasal progenitor cells ranging from one-tenth to one-half of the cell seeding density employed during the conventional cell seeding approach enabled a high degree of differentiation with the presence of cilia and tight-junctions over a 4-week air-liquid interface culture. Single cell RNA sequencing of these cultures identified five major epithelial cells populations, including basal, suprabasal, goblet, club, and ciliated cells. These cultures recapitulated the pseudostratified columnar epithelial architecture present in the native nasal epithelium and were permissive to respiratory virus infection. These results denote the potential of 3D bioprinting for high-throughput fabrication of nasal epithelial tissue models not only for infection studies but also for other purposes such as disease modeling, immunological studies, and drug screening.

bioengineering↗

bioRxiv2023

Domain-adaptive neural networks improve supervised machine learning based on simulated population genetic data

Investigators have recently introduced powerful methods for population genetic inference that rely on supervised machine learning from simulated data. Despite their performance advantages, these methods can fail when the simulated training data does not adequately resemble data from the real world. Here, we show that this "simulation mis-specification" problem can be framed as a "domain adaptation" problem, where a model learned from one data distribution is applied to a dataset drawn from a different distribution. By applying an established domain-adaptation technique based on a gradient reversal layer (GRL), originally introduced for image classification, we show that the effects of simulation mis-specification can be substantially mitigated. We focus our analysis on two state-of-the-art deep-learning population genetic methods--SIA, which infers positive selection from features of the ancestral recombination graph (ARG), and ReLERNN, which infers recombination rates from genotype matrices. In the case of SIA, the domain adaptive framework also compensates for ARG inference error. Using the domain-adaptive SIA (dadaSIA) model, we estimate improved selection coefficients at selected loci in the 1000 Genomes CEU population. We anticipate that domain adaptation will prove to be widely applicable in the growing use of supervised machine learning in population genetics. Author SummaryPopulation genetic simulation is a powerful tool in the study of evolution. A number of supervised machine learning methods have been developed that take advantage of inexpensive simulations as training data. Despite their outstanding performance in benchmarks, these models can fail when the simulated training data deviate from the real data. In this work, we employed domain adaptation techniques to address this "simulation mis-specification" problem by training the machine learning model jointly with simulated and real data. We performed extensive benchmark experiments to demonstrate the improvement of the domain-adaptive models over standard machine learning models in the presence of different types of mis-specification. In addition, we applied dadaSIA, a domain-adaptive selection inference model, to improve the estimates of selection coefficients at selected loci in a European population. The domain adaptation framework proposed in our work is widely applicable to models relying on synthetic training data and therefore opens the door to many more applications in population genetics.

genetics↗

bioRxiv2021

A spatiotemporal steroidogenic regulatory network in human fetal adrenal glands and gonads

Human fetal adrenal glands produce substantial amounts of dehydroepiandrosterone (DHEA), which is one of the most important precursors of sex hormones. However, the underlying biological mechanism remains largely unknown. Herein, we sequenced human fetal adrenal glands and gonads from 7 to 14 GW via the 10x Genomics single-cell transcriptome techniques and reconstructed their location information by Spatial Transcriptome, conducted COOL-seq for the MC2R+ inner zone steroidogenic cells during the time window of sex differentiation (8-12GW). We found that relative to gonads, adrenal glands begin to synthesize steroids early. The coordination among steroidogenic cells and multiple nonsteroidogenic cells promotes adrenal cortex construction and steroid synthesis. Notably, during the time window of sex differentiation (8-12 GW), key enzyme gene expression shifts to accelerate DHEA synthesis in males and cortisol synthesis in females. Furthermore, high SST+ expressions in the adrenal gland and testis amplify androgen synthesis in males. Our research highlights the robustness of the action of fetal adrenal glands on gonads to modify the process of sexual differentiation.

systems biology↗

bioRxiv2021

SIA: Selection Inference Using the Ancestral Recombination Graph

Detecting signals of selection from genomic data is a central problem in population genetics. Coupling the rich information in the ancestral recombination graph (ARG) with a powerful and scalable deep learning framework, we developed a novel method to detect and quantify positive selection: Selection Inference using the Ancestral recombination graph (SIA). Built on a Long Short-Term Memory (LSTM) architecture, a particular type of a Recurrent Neural Network (RNN), SIA can be trained to explicitly infer a full range of selection coefficients, as well as the allele frequency trajectory and time of selection onset. We benchmarked SIA extensively on simulations under a European human demographic model, and found that it performs as well or better as some of the best available methods, including state-of-the-art machine-learning and ARG-based methods. In addition, we used SIA to estimate selection coefficients at several loci associated with human phenotypes of interest. SIA detected novel signals of selection particular to the European (CEU) population at the MC1R and ABCC11 loci. In addition, it recapitulated signals of selection at the LCT locus and several pigmentation-related genes. Finally, we reanalyzed polymorphism data of a collection of recently radiated southern capuchino seedeater taxa in the genus Sporophila to quantify the strength of selection and improved the power of our previous methods to detect partial soft sweeps. Overall, SIA uses deep learning to leverage the ARG and thereby provides new insight into how selective sweeps shape genomic diversity.

genetics↗

bioRxiv2021

Emerging SARS-CoV-2 mutation hotspots associated with clinical outcomes

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing coronavirus disease 2019 (COVID-19) pandemic. Understanding the influence of mutations in the SARS-CoV-2 gene on clinical outcomes and related factors is critical for treatment and prevention. Here, we analyzed 209,551 high-coverage complete virus sequences and 321 RNA-seq samples to mine the mutations associated with clinical outcome in the SARS-CoV-2 genome. Several important hotspot variants were found to be associated with severe clinical outcomes. Q57H variant in ORF3a protein were found to be associated with higher mortality rate, and was high proportion in severe cases (39.36%) and 501Y.V2 strains (100%) but poorly proportional to asymptomatic cases (10.04%). T265I could change nsp2 structure and mitochondrial permeability, and evidently higher in severe cases (20.12%) and 501Y.V2 strains (100%) but lower in asymptomatic cases (1.43%). Additionally, R203K and G204R could decrease the flexibility and immunogenic property of N protein with high frequency among severe cases, VUI 202012/01 and 484K.V2 strains. Interestingly, the SARS-CoV-2 genome was more susceptible to mutation because of the high frequency of nt14408 mutation (which located in RNA polymerase) and the high expression levels of ADAR and APOBEC in severe clinical outcomes. In conclusion, several important mutation hotspots in the SARS-CoV-2 genome associated with clinical outcomes was found in our study, and that might correlate with different SARS-CoV-2 mortality rates.

bioinformatics↗

bioRxiv2020

The wheat 55K SNP-based exploration of loci for spikelet number per spike from a tetraploid wheat (Triticum turgidum L.) recombinant inbred line population derived from a Chinese landrace Ailanmai and a wild emmer accession

The spikelet number per spike (SNS) is a primary factor determining wheat yield. Common wheat breeding reduces the genetic diversity among elite germplasm resources, leading to a detrimental effect on future wheat production. It is, therefore, necessary to explore new genetic resources for SNS to increase wheat yield. A tetraploid landrace Ailanmai x wild emmer wheat recombinant inbred line (RIL) population was used to construct a genetic map using the wheat 55K single nucleotide polymorphism (SNP) array. The linkage map containing 1150 bin markers with a total genetic distance of 2411.8 cM was obtained. Based on phenotypic data from eight environments and best linear unbiased prediction (BLUP) values, five quantitative trait loci (QTL) for SNS were identified, explaining 6.71-29.40% of the phenotypic variation. Two of them, QSns.sau-AM-2B.3 and QSns.sau-AM-3B.2, were detected as the major and novel QTL. Their effects were further validated in two additional F2 populations using tightly linked Kompetitive Allele-Specific PCR (KASP) markers. Potential candidate genes within the physical intervals of corresponding QTL were predicted to participate in inflorescence development and spikelet formation. Genetic associations between SNS and other agronomic traits were also detected and analyzed. This study demonstrates the feasibility of wheat 55K SNP array developed for common wheat in genetic mapping of tetraploid population and shows the potential application of wheat related species in wheat improvement programs.

genetics↗

bioRxiv2020

Genome-wide association study of TP53 R249S mutation in hepatocellular carcinoma with aflatoxin B1 exposure and hepatitis B virus infection in Guangxi

Background/AimsDietary aflatoxin B1 (AFB1) exposure, which induces DNA damage and codon 249 mutation of the TP53 gene, is one of the major risk factors for hepatocellular carcinoma (HCC). Hepatitis B virus (HBV) infection and AFB1 exert synergistic effects to promote carcinogenesis and TP53 R249S mutation in HCC. MethodsA genome-wide association study (GWAS) was conducted on 485 cases of HCC with chronic HBV infection, followed by a two-stage replication study on 270 cases with chronic HBV infection. Susceptibility variants for the TP53 R249S mutation in HCC were identified based on both GWAS and replication analysis. The associations of identified variants with expression levels of their located genes were validated in 20 paired independent samples. ResultsOur results showed that TP53 R249S was significantly associated with ADAMTS18 rs9930984 (adjusted P = 4.84x10-6), WDR49 rs75218075 (adjusted P = 7.36 x 10-5) and SLC8A3 rs8022091 (adjusted P = 0.042). Additionally, ADAMTS18 mRNA expression was significantly higher in HCC tissue, compared with paired non-tumor tissue (P = 0.041) and patients carrying the TT genotype at rs9930984 showed lower ADAMTS18 expression in non-tumor tissue, compared with those carrying the GT genotype (P = 0.0028). ConclusionsTP53 expression is significantly associated with R249S mutation in HCC. Our collective results suggest that rs9930984, rs75218075 and rs8022091 are associated with susceptibility to the R249S mutation in cases of HCC exposed to AFB1 and HBV infection.

genetics↗

bioRxiv2020

Association between ocular biometrical parameters and diabetic retinopathy in Chinese adults with type 2 diabetes mellitus

PurposeTo investigate the association between ocular biometrical parameters and diabetic retinopathy (DR) in ocular treatment naive patients with diabetes. MethodsThis cross-sectional study recruited type 2 diabetes mellitus patients with no history of ocular treatment in Guangzhou, China. The ocular biometrical parameters were obtained by Lenstar, including corneal diameter, central corneal thickness (CCT), corneal curvature (CC), anterior chamber depth (ACD), lens thickness (LT), and axial length (AL). The lens power and axial length-to-cornea radius ratio (AL/CR ratio) were calculated. Spherical equivalent (SE) was determined by auto-refraction after pupil dilation. Multivariate logistic regression analyses were performed to explore the associations of ocular biometry with any DR and vision threatening DR (VTDR). ResultsA total of 1838 patients were included in the final analysis, involving 145 5(79.2%) patients without DR and 383(20.8%) patients with DR. After adjusting confounding factors, any DR was independently associated with AL (OR = 0.84 per 1 mm increase, 95%CI: 0.74, 0.94), lens power (OR = 0.9951 per 1 D increase, 95%CI: 0.9904, 0.9998), and AL/CR ratio (OR = 0.26 per 1 increase, 95%CI: 0.10-0.70). Similarly, the presence of VTDR was independently related to AL (OR = 0.67 per 1 mm increase, 95%CI: 0.54-0.85), lens power (OR = 0.99 per 1 D increase, 95%CI: 0.98, 0.997), and AL/CR ratio (OR = 0.04 per 1 increase, 95%CI: 0.01, 0.25). The CC, corneal diameter, and refractive status were not significantly correlated with presence of DR or VTDR. ConclusionLonger AL, deeper ACD, higher lens power, and higher AL/CR ratio may be protective factors against DR. Considering the high prevalence of myopia in the Chinese juvenile population, it is worth paying attention to how the incidence of DR in this generation may change over time.

pathology↗