Characteristics and phytotoxicity of hydrochar-derived dissolved organic matter: Effects of feedstock type and hydrothermal temperature.

The dissolved organic matter (DOM) with high mobility and reactivity plays a crucial role in soil. In this study, the characteristics and phytotoxicity of DOM released from the hydrochars prepared from different feedstocks (cow manure, corn stalk and Myriophyllum aquaticum) under three hydrothermal carbonization (HTC) temperatures (180, 200 and 220°C) were evaluated. The results showed that the hydrochars had high dissolved organic carbon content (20.15 to 37.65 mg/g) and its content showed a gradual reduction as HTC temperature increased. Three fluorescent components including mixed substance of fulvic acid-like and humic acid-like substances (C1, 30.92%-58.32%), UVA humic acid-like substance (C2, 25.27%-29.94%) and protein-like substance (C3, 11.74%-41.92%) were identified in hydrochar DOM by excitation emission matrix spectra coupled with parallel factor analysis. High HTC temperature increased the relative proportion of aromatic substances (C1+C2) and humification degree of hydrochar DOM from cow manure, while it presented adverse effects on the hydrochar DOM from corn stalk and Myriophyllum. aquaticum. The principal component analysis suggested that feedstock type and HTC temperature posed significant effects on the characteristics of hydrochar DOM. Additionally, seed germination test of all hydrochar DOM demonstrated that the root length was reduced by 8.88%-26.43% in contrast with control, and the germination index values were 73.57%-91.12%. These findings provided new insights into the potential environmental effects for hydrochar application in soil.

The Transcription Factor ZmMYB56 Regulates High CO2-Induced Stomatal Closure in Maize Seedlings by Regulating ZmHLT1 Expression.

Stomata are channels through which plants exchange H2O and CO2 with the external environment. The regulation of stomatal movement has significant impacts on plant growth, development and stress adaptation. Here, we present a maize R2R3 -MYB transcription factor, ZmMYB56, which regulates high CO2-induced stomatal closure in maize seedlings. ZmMYB56 is highly expressed in stomatal guard cells and is negatively regulated by CO2 and HCO3 -. Loss of ZmMYB56 function leads to insensitivity to high CO2. As a transcription factor, ZmMYB56 binds to a cis-acting element in the ZmHLT1 promoter and regulates its expression. ZmHLT1 plays a key role in CO2- induced maize stomatal movement, and its absence causes a severe weakening of maize's response to ambient CO2. ZmHLT1 expression is negatively regulated by bicarbonate, which does not occur in Zmmyb56 mutants, highlighting the significance of this regulatory relationship in plant responses to CO2 and HCO3 -. Taken together, these results show that ZmMYB56-regulated ZmHLT1 expression is important for high CO2-induced stomatal closure in maize. Our findings provide insight into genetic pathways that could be manipulated to improve maize growth and stress tolerance, especially under increasing atmospheric CO2 concentrations.

Ultrack: pushing the limits of cell tracking across biological scales.

Tracking live cells across 2D, 3D, and multi-channel time-lapse recordings is crucial for understanding tissue-scale biological processes. Despite advancements in imaging technology, achieving accurate cell tracking remains challenging, particularly in complex and crowded tissues where cell segmentation is often ambiguous. We present Ultrack, a versatile and scalable cell-tracking method that tackles this challenge by considering candidate segmentations derived from multiple algorithms and parameter sets. Ultrack employs temporal consistency to select optimal segments, ensuring robust performance even under segmentation uncertainty. We validate our method on diverse datasets, including terabyte-scale developmental time-lapses of zebrafish, fruit fly, and nematode embryos, as well as multi-color and label-free cellular imaging. We show that Ultrack achieves state-of-the-art performance on the Cell Tracking Challenge and demonstrates superior accuracy in tracking densely packed embryonic cells over extended periods. Moreover, we propose an approach to tracking validation via dual-channel sparse labeling that enables high-fidelity ground truth generation, pushing the boundaries of long-term cell tracking assessment. Our method is freely available as a Python package with Fiji and napari plugins and can be deployed in a high-performance computing environment, facilitating widespread adoption by the research community.

Failure Analysis of Ni-8YSZ Electrode under Reoxidation Based on the Real Microstructure.

During the operation of solid oxide fuel cells (SOFCs), the Ni-8YSZ anodes are subjected to thermal mismatch and reoxidation, accompanied by the risk of damage and failure. These damages and failures are generally induced by small defects at the microscopic level, leading to the degradation of the structural bearing capacity. Therefore, the distribution and quantification of the stresses in the real microstructure of Ni-8YSZ electrodes is essential. In this study, the real Ni-8YSZ microstructure was reconstructed based on nano-computed tomography, and the stress distribution of the real microstructure was analyzed based on the finite element method under reoxidation and different operating temperatures. The failure probability of 8YSZ at different degrees of reoxidation was evaluated according to the Weibull method, and the amount of damaged 8YSZ elements was statistically counted. The study results indicate a high level of stress in the thin necks and relatively sharp areas of the microstructure. The 8YSZ has a high failure probability at a reoxidation extent of 5-10%.

Blood-based DNA methylation and exposure risk scores predict PTSD with high accuracy in military and civilian cohorts.

BACKGROUND: Incorporating genomic data into risk prediction has become an increasingly popular approach for rapid identification of individuals most at risk for complex disorders such as PTSD. Our goal was to develop and validate Methylation Risk Scores (MRS) using machine learning to distinguish individuals who have PTSD from those who do not. METHODS: Elastic Net was used to develop three risk score models using a discovery dataset (n = 1226; 314 cases, 912 controls) comprised of 5 diverse cohorts with available blood-derived DNA methylation (DNAm) measured on the Illumina Epic BeadChip. The first risk score, exposure and methylation risk score (eMRS) used cumulative and childhood trauma exposure and DNAm variables; the second, methylation-only risk score (MoRS) was based solely on DNAm data; the third, methylation-only risk scores with adjusted exposure variables (MoRSAE) utilized DNAm data adjusted for the two exposure variables. The potential of these risk scores to predict future PTSD based on pre-deployment data was also assessed. External validation of risk scores was conducted in four independent cohorts. RESULTS: The eMRS model showed the highest accuracy (92%), precision (91%), recall (87%), and f1-score (89%) in classifying PTSD using 3730 features. While still highly accurate, the MoRS (accuracy = 89%) using 3728 features and MoRSAE (accuracy = 84%) using 4150 features showed a decline in classification power. eMRS significantly predicted PTSD in one of the four independent cohorts, the BEAR cohort (beta = 0.6839, p=0.006), but not in the remaining three cohorts. Pre-deployment risk scores from all models (eMRS, beta = 1.92; MoRS, beta = 1.99 and MoRSAE, beta = 1.77) displayed a significant (p < 0.001) predictive power for post-deployment PTSD. CONCLUSION: The inclusion of exposure variables adds to the predictive power of MRS. Classification-based MRS may be useful in predicting risk of future PTSD in populations with anticipated trauma exposure. As more data become available, including additional molecular, environmental, and psychosocial factors in these scores may enhance their accuracy in predicting PTSD and, relatedly, improve their performance in independent cohorts.

Reducing amplification cycles to improve the coverage of influenza A virus genome sequencing in heterosubtypic co-infection.

This study delineates the enhancement of a Reverse Transcription Polymerase Chain Reaction (RT-PCR) method for the amplification of the complete genome of the influenza A virus during heterosubtypic co-infection, relying on the amplification of intact gene segments. The precision of the method was assessed using all amplicons, which underwent both capillary electrophoresis and DNA sequencing. Five samples featuring co-infection of Influenza A viruses with H1N1 and H3N2 subtypes were evaluated. The improved strategy successfully amplified all eight segments of H3N2 strains in four samples, and the entire genome of H1N1 strains in three samples.

Are HPV Vaccines Well Accepted among Parents of Adolescent Girls in China? Trends, Obstacles, and Practical Implications for Further Interventions: A Five-Year Follow-Up Study.

BACKGROUND: In 2020, the WHO proposed the global strategic goal of accelerating the elimination of cervical cancer (CC). One of the key strategies is that, by 2030, 90% of girls will complete HPV vaccination by age 15. In 2017, HPV vaccines were first marketed in China. OBJECTIVES: This study aimed to explore the changes in parents' knowledge about CC, HPV, HPV vaccines, and acceptance of HPV vaccination 5 years after the introduction of HPV vaccines into China. Associated factors and reasons for refusal by parents were also explored. METHODS: A school-based follow-up study was conducted among parents in China from May 2018 to May 2023. Comparison using Chi-square tests was performed to measure the changes. Univariate and multivariate analyses were used to explore factors associated with HPV vaccination among teenage girls. RESULTS: The overall cognitive level in terms of CC- and HPV-related knowledge among parents increased, and they expressed more willingness to vaccinate their daughter (35.4% in 2018 vs. 56.6% in 2023). The HPV vaccination rate among teenage girls remained at a low level (4.4% in 2018, 9.8% in 2023). The main obstacles reported by parents were limited knowledge (42.0%), scarcity of the HPV vaccine (29.2%), waiting until their daughter was older (27.5%), safety concerns (14.7%), high cost (9.0%), and effectiveness concerns (4.6%). Parents who are elderly, local residents, have received HPV vaccines themselves, have had experience of vaccinating their children with influenza vaccines, and have a higher knowledge level of CC, HPV and HPV vaccines are more likely to vaccinate their children with HPV vaccines. CONCLUSIONS: Although we observed an increment in parents' knowledge level in terms of CC, HPV, HPV vaccines, and HPV vaccine uptake over the past 5 years, the HPV vaccine coverage among girls still falls short of the WHO's 2030 target. Comprehensive intervention strategies, including tailored health education among adolescents and their parents, doctor recommendations, and providing financial subsidies or free HPV vaccines are needed in China.

Bridging the Gap: A Comprehensive Study on Traditional Chinese Medicine Strategies for Managing Adult Irritable Bowel Syndrome.

Recent studies have witnessed the incorporation of herbal medicine into the management of Disorders of Gut-Brain Interactions (DGBIs), reflecting a paradigm shift toward holistic healing modalities. However, there still exists a substantial gap in comprehending the utilization of Traditional Chinese Medicine (TCM) for Irritable Bowel Syndrome (IBS), particularly beyond the confines of China. This study endeavors to bridge this knowledge gap by meticulously identifying existing guidelines, critically reviewing TCM practices, and crafting contemporary treatment recommendations. We systematically searched several databases to retrieve related evidence in June 2023. Firstly, we employed the AGREE II tool to evaluate the recommended for use of TCM in the treatment of IBS, establishing a structured treatment selection hierarchy for different TCM patterns of IBS patients. Subsequently, we conducted an expert questionnaire to gain insights into the common treatment methods and medication choices practiced by clinical TCM doctors. Based on CM theory and experts' opinions, IBS with predominant Diarrheal (IBS-D) is divided into five Chinese medicine syndrome patterns, and IBS with predominant Constipation (IBS-C) is classified to four. A total of 22[Formula: see text]CM prescriptions were recommended for the management of IBS, 13 for IBS-D and 9 for IBS-C. The findings provide IBS patients with enhanced treatment choices while offering clinical physicians more specific treatment regimens. This research is the first to conduct a comprehensive study that combines guidelines with real clinical practices in the realm of TCM IBS treatment. This serves as a foundation for providing more personalized treatment options and improving the quality of life for patients.

Quantification of immiscible displacement in a rough-walled fracture through direct visualization.

Subsurface substance migration in the fractured rock aquifer is mainly controlled by fractures, and immiscible fluid-fluid displacement in fractures is important to many geophysical processes and engineering activities. Using a fracture-visualization system, we present the qualitative and quantitative assessment of fracture geometry associated with fluid movement and distribution in the rough fracture. Based on fracture geometry and statistical analysis, we first conducted a quantitative study of fracture surface roughness and aperture distribution. Then, fractal dimensions of displacement front and residual oil distribution were determined by image processing procedures. Influenced by wettability and micro-scale roughness, at the end of the displacement, residual oil saturation of molded sample is lower (6.45%-25.74%), and displacement pattern is more uniform, indicating that displacement effect is better. Due to smaller differences in residual oil saturation (9.08%) under different injection directions, the impact of wettability on the displacement process is greater than that of anisotropic roughness. Additionally, the fractal dimension of the displacement front increased under low injection rates initially but decreased when the rate was increased later. Overall, visualized temporal monitoring of experimental images enabled us to provide a preliminary assessment of the impact of anisotropic roughness and the material constituting the fracture wall on invading fluid saturation and the fractal dimension of the displacement front under various injection rates.

Cancer-associated fibroblasts derived fibronectin extra domain A promotes sorafenib resistance in hepatocellular carcinoma cells by activating SHMT1.

Resistance to sorafenib, an effective first-line treatment for advanced hepatocellular carcinoma (HCC), greatly compromised the prognosis of patients. The extracellular matrix is one of the most abundant components of the tumor microenvironment. Beyond acting as a physical barrier, it remains unclear whether cell interactions and signal transduction mediated by the extracellular matrix contribute to sorafenib resistance. With the analysis of primary HCC organoid RNA-seq data combined with in vivo and in vitro experiments validation, we discovered that fibronectin extra domain A (FN-EDA) derived from cancer-associated fibroblasts played a critical role in sorafenib resistance. Mechanistically, FN-EDA stimulates the up-regulation of the key one-carbon metabolism enzyme SHMT1 in HCC cells via the TLR4/NF-κB signaling pathway, thereby countering the oxidative stress induced by sorafenib. Moreover, we reinforced the clinical significance of our discoveries by conducting in vivo assays with an immunodeficiency subcutaneous xenograft tumor model, which was established using primary cancer-associated fibroblasts derived from clinical HCC tissues, and through the analysis of HCC samples obtained from The Cancer Genome Atlas (TCGA) database. Our findings suggest that targeting the FN-EDA/SHMT1 pathway could be a potential strategy to improve sorafenib responsiveness in HCC patients.

N6-methyladenosine transcriptome-wide profiles of maize kernel development.

Maize (Zea mays L.) kernel development is a complex and dynamic process involving cell division and differentiation, into a variety of cell types. Epigenetic modifications, including DNA methylation, play a pivotal role in regulating this process. N6-methyladenosine modification is a universal and dynamic post-transcriptional epigenetic modification that is involved in the regulation of plant development. However, the role of N6-methyladenosine in maize kernel development remains unknown. In this study, we have constructed transcriptome-wide profiles for maize kernels at various stages of early development. Utilizing a combination of MeRIP-seq and RNA-seq analysis, we identified a total of 11,170, 10,973, 11,094, 11,990, 12,203 and 10,893 N6-methyladenosine peaks in maize kernels at 0, 2, 4, 6, 8, and 12 days after pollination, respectively. These N6-methyladenosine modifications were primarily deposited at the 3'-UTRs and were associated with the conserved motif-UGUACA. Additionally, we found that conserved N6-methyladenosine modification are involved in the regulation of genes that are ubiquitously expressed during kernel development. Further analysis revealed that N6-methyladenosine peak intensity was negatively correlated with the mRNA abundance of these ubiquitously expressed genes. Meanwhile, we employed phylogenetic analysis to predict potential regulatory proteins involved in maize kernels development and identified several that participate in the regulation of N6-methyladenosine modifications. Collectively, our results suggest the existence of a novel post-transcriptional epigenetic modification mechanism involved in the regulation of maize kernels development, thereby providing a novel perspective for maize molecular breeding.

Effects and mechanisms of harmine on ameliorating ethanol-induced memory impairment.

ETHNOPHARMACOLOGICAL RELEVANCE: Peganum harmala L., a traditional Uyghur ethnic medicine widely used in China, is commonly used in the treatment of conditions such as hemiplegia, forgetfulness, cough, and asthma. Harmine and other ß-carboline alkaloids, one of the main active ingredients in P. harmala, have exhibited various pharmacological activities, including anti-Alzheimer's, antidepressant, anti-inflammatory, and antioxidant effects. However, the effects and underlying mechanisms of harmine on improving ethanol-induced memory impairment remain unclear. AIM OF THE STUDY: This study aimed to investigate the effects of harmine on ameliorating ethanol-induced memory impairment, and to explore potential mechanisms. MATERIALS AND METHODS: Ethanol (30%, i. g.) was used to induce memory impairment model. The effect of harmine on memory impairment was evaluated by Morris water maze (MWM). The histopathological analysis, immunofluorescence staining, RT-qPCR and UHPLC-MS/MS methods were performed to further investigate the underlying mechanisms. RESULTS: MWM experiments showed that harmine significantly improved ethanol-induced spatial learning memory deficit. Harmine exhibited anti-inflammatory effect by downregulating inflammatory factors such as IL-6, IL-1ß and tumor necrosis factor-α (TNF-α) induced by ethanol. Harmine also upregulated brain-derived neurotrophic factor (BDNF) levels to exert neuroprotective effect. Moreover, harmine protected neuronal cells and increased the protein expression of myelin basic protein (MBP). The cellular results indicated that harmine protected SH-SY5Y cells from ethanol-induced cytotoxicity and upregulated the relative mRNA expression of synaptosome associated protein 25 (SNAP25), syntaxin 1 A (STX1A), vesicle associated membrane protein 2 (VAMP2), synaptotagmin 1 (SYT1) and synaptophysin (SYP). CONCLUSIONS: Harmine improved ethanol-induced memory impairment by ameliorating inflammation, increasing BDNF levels, promoting synaptic vesicle fusion, protecting myelin sheath, and modulating neurotransmitter levels. These findings provided a scientific basis for development of therapeutic drugs for alcohol-induced memory impairments and other related disorders.

Clinical characteristics and risk stratification for late-onset herpes zoster following allogeneic hematopoietic stem cell transplantation.

The incidence of herpes zoster (HZ) in allogeneic hematopoietic stem cell transplantation (allo-HSCT) recipients is significantly higher than that of the general public. Although routine antiviral prophylaxis is recommended, late-onset HZ has been highlighted, yet limited information is known about its clinical features and predictors. Here, we conducted a retrospective nested case-control study to identify patients with late-onset HZ, defined as a diagnosis of HZ after 1 year of transplantation, among allo-HSCT recipients between 2012 and 2017 at Peking University People's Hospital. Three controls were matched for each patient. A total of 201 patients developed late-onset HZ. Age over 20 years, absence of neutrophil engraftment by 14 days, mental disorders, immunosuppressant use at 1 year, and a peripheral CD4+/CD8+ ratio ≥0.5 at 1 year were independent risk factors, among which the CD4+/CD8+ ratio demonstrated good discriminative power for predicting late-onset HZ. For patients with a CD4+/CD8+ ratio <0.5, patient age, neutrophil engraftment time, mental disorders, and immunosuppressant use were potential risk factors. A stratification algorithm was accordingly established, classifying the transplant recipients into three risk groups. Whether the algorithm could facilitate the administration of posttransplant antiviral prophylaxis merits further validation.

Dry hydroclimates in the late Palaeocene-early Eocene hothouse world.

Extreme global warming can produce hydroclimate changes that remain poorly understood for sub-tropical latitudes. Late Palaeocene-early Eocene (LPEE; ~58-52 Ma) proto-Mediterranean zones of the western Tethys offer opportunities to assess hydroclimate responses to massive carbon cycle perturbations. Here, we reconstruct LPEE hydroclimate conditions of these regions and find that carbon cycle perturbations exerted controls on orbitally forced hydroclimate variability. Long-term (~6 Myr) carbon cycle changes induced a gradual precipitation/moisture reduction, which was exacerbated by some short-lived (<200 kyr) carbon cycle perturbations that caused rapid warming and exceptionally dry conditions in western Tethyan continental areas. Hydroclimate recovery following the greatest short-lived global warming events took ~24-27 kyr. These observations support the notion that anthropogenically driven warming can cause widespread aridification with impacts that may last tens of thousands of years.

Global burden of gynaecological cancers in 2022 and projections to 2050.

Background: The incidence and mortality of gynaecological cancers can significantly impact women's quality of life and increase the health care burden for organisations globally. The objective of this study was to evaluate global inequalities in the incidence and mortality of gynaecological cancers in 2022, based on The Global Cancer Observatory (GLOBOCAN) 2022 estimates. The future burden of gynaecological cancers (GCs) in 2050 was also projected. Methods: Data regarding to the total cases and deaths related to gynaecological cancer, as well as cases and deaths pertaining to different subtypes of GCs, gathered from the GLOBOCAN database for the year 2022. Predictions for the number of cases and deaths in the year 2050 were derived from global demographic projections, categorised by world region and Human Development Index (HDI). Results: In 2022, there were 1 473 427 new cases of GCs and 680 372 deaths. The incidence of gynecological cancer reached 30.3 per 100 000, and the mortality rate hit 13.2 per 100 000. The age-standardised incidence of GCs in Eastern Africa is higher than 50 per 100 000, whereas the age-standardised incidence in Northern Africa is 17.1 per 100 000. The highest mortality rates were found in East Africa (ASMR (age-standardised mortality rates) of 35.3 per 100 000) and the lowest in Australia and New Zealand (ASMR of 8.1 per 100 000). These are related to the endemic areas of HIV and HPV. Very High HDI countries had the highest incidence of GCs, with ASIR (age-standardised incidence rates) of 34.8 per 100 000, and low HDI countries had the second highest incidence rate, with an ASIR of 33.0 per 100 000. Eswatini had the highest incidence and mortality (105.4 per 100 000; 71.1 per 100 000) and Yemen the lowest (5.8 per 100 000; 4.4 per 100 000). If the current trends in morbidity and mortality are maintained, number of new cases and deaths from female reproductive tract tumours is projected to increase over the next two decades. Conclusions: In 2022, gynaecological cancers accounted for 1 473 427 new cases and 680 372 deaths globally, with significant regional disparities in incidence and mortality rates. The highest rates were observed in Eastern Africa and countries with very high and low HDI, with Eswatini recording the most severe statistics. If current trends continue, the number of new cases and deaths from gynaecological cancers is expected to rise over the next two decades, highlighting the urgent need for effective interventions.

Improving Generalization and Personalization in Model-Heterogeneous Federated Learning.

Conventional federated learning (FL) assumes the homogeneity of models, necessitating clients to expose their model parameters to enhance the performance of the server model. However, this assumption cannot reflect real-world scenarios. Sharing models and parameters raises security concerns for users, and solely focusing on the server-side model neglects clients' personalization requirements, potentially impeding expected performance improvements of users. On the other hand, prioritizing personalization may compromise the generalization of the server model, thereby hindering extensive knowledge migration. To address these challenges, we put forth an important problem: How can FL ensure both generalization and personalization when clients' models are heterogeneous? In this work, we introduce FedTED, which leverages a twin-branch structure and data-free knowledge distillation (DFKD) to address the challenges posed by model heterogeneity and diverse objectives in FL. The employed techniques in FedTED yield significant improvements in both personalization and generalization, while effectively coordinating the updating process of clients' heterogeneous models and successfully reconstructing a satisfactory global model. Our empirical evaluation demonstrates that FedTED outperforms many representative algorithms, particularly in scenarios where clients' models are heterogeneous, achieving a remarkable 19.37% enhancement in generalization performance and up to 9.76% improvement in personalization performance.

StaRS: Learning a Stable Representation Space for Continual Relation Classification.

Relation classification (RC) aims to detect the semantic relation between two annotated entities in a piece of sentence, serving as an essential task in automatic knowledge graph construction. Due to the emergence of new relations, there is a recent trend to train RC models in continual settings. To overcome the catastrophic forgetting problem in continual learning, existing research is devoted in a two-stage training paradigm, fast adaptation to novel relations, and memory replay for all historical relations. These memory-replay-based methods explore different techniques to mitigate the forgetting problem of continual RC (CRC) models during the memory replay stage. However, we find that the representation space undergoes distortion due to the incoming of fresh relations in the fast adaptation phase. To address this issue, we propose using a knowledge distillation strategy and designing a margin loss, aiming to maintain the stability of the RC model during adaptation to new relations. In addition, in the second stage, with a limited number of typical memory instances available, we introduce a self-contrastive learning objective to facilitate learning a balanced decision boundary for RC. Through training in two stages, our objective is to acquire a stable representation space to encode instances for CRC. We experimentally demonstrate the superiority of our model over competing methods in various settings, and the results suggest that our tailored designs can achieve better performance in CRC.

Enhancing homology-directed repair efficiency with HDR-boosting modular ssDNA donor.

Despite the potential of small molecules and recombinant proteins to enhance the efficiency of homology-directed repair (HDR), single-stranded DNA (ssDNA) donors, as currently designed and chemically modified, remain suboptimal for precise gene editing. Here, we screen the biased ssDNA binding sequences of DNA repair-related proteins and engineer RAD51-preferred sequences into HDR-boosting modules for ssDNA donors. Donors with these modules exhibit an augmented affinity for RAD51, thereby enhancing HDR efficiency across various genomic loci and cell types when cooperated with Cas9, nCas9, and Cas12a. By combining with an inhibitor of non-homologous end joining (NHEJ) or the HDRobust strategy, these modular ssDNA donors achieve up to 90.03% (median 74.81%) HDR efficiency. The HDR-boosting modules targeting an endogenous protein enable a chemical modification-free strategy to improve the efficacy of ssDNA donors for precise gene editing.