SEC16A Variants Predispose to Chronic Pancreatitis by Impairing ER-to-Golgi Transport and Inducing ER Stress.

Chronic pancreatitis (CP) is a complex disease with genetic and environmental factors at play. Through trio exome sequencing, a de novo SEC16A frameshift variant in a Chinese teenage CP patient is identified. Subsequent targeted next-generation sequencing of the SEC16A gene in 1,061 Chinese CP patients and 1,196 controls reveals a higher allele frequency of rare nonsynonymous SEC16A variants in patients (4.90% vs 2.93%; odds ratio [OR], 1.71; 95% confidence interval [CI], 1.26-2.33). Similar enrichments are noted in a French cohort (OR, 2.74; 95% CI, 1.67-4.50) and in a biobank meta-analysis (OR, 1.16; 95% CI, 1.04-1.31). Notably, Chinese CP patients with SEC16A variants exhibit a median onset age 5 years earlier than those without (40.0 vs 45.0; p = 0.012). Functional studies using three CRISPR/Cas9-edited HEK293T cell lines show that loss-of-function SEC16A variants disrupt coat protein complex II (COPII) formation, impede secretory protein vesicles trafficking, and induce endoplasmic reticulum (ER) stress due to protein overload. Sec16a+/- mice, which demonstrate impaired zymogen secretion and exacerbated ER stress compared to Sec16a+/+, are further generated. In cerulein-stimulated pancreatitis models, Sec16a+/- mice display heightened pancreatic inflammation and fibrosis compared to wild-type mice. These findings implicate a novel pathogenic mechanism predisposing to CP.

Chrysanthemum lavandulifolium homolog ClCYCA2;1 modulates cell division in ray florets.

Morphology of ray florets in chrysanthemums is tightly associated with cell division and cell expansion, both of which require proper cell cycle progression. Here we identified a Chrysanthemum lavandulifolium homolog ClCYCA2;1, whose expression in ray florets is negatively correlated with petal width in C. lavandulifolium. Two TCP transcription factors in CYCLOIDEA2 (CYC2) family, ClCYC2a interacts with and stabilizes ClCYC2b and the latter can bind to the promoter of ClCYCA2;1 to activate its transcription. Overexpression of ClCYCA2;1 in C. lavandulifolium reduces the size of capitula and ray florets. Cytological analysis reveals that ClCYCA2;1 overexpression inhibits both cell division and cell expansion via repressing mitotic cell cycle in ray florets whose latitudinal development was more negatively influenced leading to increased ratios of petal length to width at later developmental stages. Yeast two hybrid library screening reveals multiple ClCYCA2;1 interacting proteins including ARP7, and silencing ClARP7 inhibits the development of ray florets. Co-immunoprecipitation assays confirm that ClCYCA2;1 can induce the degradation of ClARP7 to inhibit the development of ray florets. Taken together, our study constitutes a regulatory network containing ClCYC2b-ClCYCA2;1-ClARP7 in ray floret development via governing mitosis, which may facilitate breeding efforts targeted for novel ornamental traits of chrysanthemums.

Robustness of higher-order interdependent networks with reinforced nodes.

In reality, pairwise interactions are no longer sufficient to describe the higher-order interactions between nodes, such as brain networks, social networks, etc., which often contain groups of three or more nodes. Since the failure of one node in a high-order network can lead to the failure of all simplices in which it is located and quickly propagates to the whole system through the interdependencies between networks, multilayered high-order interdependent networks are challenged with high vulnerability risks. To increase the robustness of higher-order networks, in this paper, we proposed a theoretical model of a two-layer partial high-order interdependent network, where a proportion of reinforced nodes are introduced that can function and support their simplices and components, even losing connection with the giant component. We study the order parameter of the proposed model, including the giant component and functional components containing at least one reinforced node, via theoretical analysis and simulations. Rich phase transition phenomena can be observed by varying the density of 2-simplices and the proportion of the network's reinforced nodes. Increasing the density of 2-simplices makes a double transition appear in the network. The proportion of reinforced nodes can alter the type of second transition of the network from discontinuous to continuous or transition-free, which is verified on the double random simplicial complex, double scale-free simplicial complex, and real-world datasets, indicating that reinforced nodes can significantly enhance the robustness of the network and can prevent networks from abrupt collapse. Therefore, the proposed model provides insights for designing robust interdependent infrastructure networks.

Application of single cell sequencing technology in ovarian cancer research (review).

Ovarian cancer is a malignant tumor of ovary. It has the characteristics of difficult early diagnosis, poor late curative effect and high recurrence rate. It is the biggest disease that seriously threatens women's health. Single cell sequencing technology refers to sequencing the genetic information carried by it at the single cell level to obtain the gene sequence, transcript, protein and epigenetic expression profile information of a certain cell type and conduct integrated analysis. It has unique advantages in the study of tumor occurrence and evolution, and can provide new methods for the study of ovarian cancer. This paper reviews the single cell sequencing technology and its application in ovarian cancer.

Association Between Visceral Obesity and Glycemic Control in Patients with Type 2 Diabetes Mellitus: A Retrospective Study.

Purpose: To investigate the association between visceral obesity and glycemic control in patients with type 2 diabetes mellitus. Patients and Methods: A retrospective analysis involved 714 patients diagnosed with type 2 diabetes mellitus from the National Metabolic Management Center from November 2021 to February 2024. Medical data included sociodemographic data, lifestyle behaviors, and anthropometric and biochemical measurements. Multivariate logistic regression analysis was used to analyze their associations. Results: Among the patients, 251 (35.2%) achieved good glycemic control (HbA1c < 7.0%). On univariate analysis, higher diastolic blood pressure, longer duration of type 2 diabetes mellitus, tobacco smoking, alcohol drinking, insulin treatment, higher levels of fasting plasma glucose, homeostasis model assessment of insulin resistance, triglyceride, total cholesterol, and low-density lipoprotein cholesterol, visceral obesity (visceral fat area ≥ 100cm2) and diabetic peripheral neuropathy were all positively correlated with poor glycemic control; female, older age, higher levels of C peptide and serum uric acid were inversely associated with poor glycemic control (all P < 0.05). On multivariate logistic regression analysis, the results suggested that higher diastolic blood pressure [OR: 1.021, 95% CI (1.002, 1.040), P = 0.030], insulin treatment [currently used: OR = 2.156, 95% CI (1.249, 3.724), P = 0.006], higher level of fasting plasma glucose [OR: 1.819, 95% CI (1.598, 2.069), P < 0.001], and visceral obesity [OR: 1.876, 95% CI (1.158, 3.038), P = 0.011] were risk factors for poor glycemic control. Conclusion: This study indicated that visceral obesity (visceral fat area ≥ 100cm2) is positively associated with poor glycemic control, and serves as an independent risk factor for poor glycemic control (HbA1c ≥ 7.0%) in patients with type 2 diabetes mellitus. Screening for visceral obesity should be emphasized, and targeted interventions should be taken to improve glycemic control in patients with type 2 diabetes mellitus.

Advances in research on the main nutritional quality of daylily, an important flower vegetable of Liliaceae.

Daylily (Hemerocallis citrina) is a perennial herb of the genus Hemerocallis of Liliaceae. It is also an economically important crop and is widely cultivated. Daylily has nutritional, medicinal and ornamental values. The research literature shows that daylily is a high-quality food raw material rich in soluble sugars, ascorbic acid, flavonoids, dietary fiber, carotenoids, mineral elements, polyphenols and other nutrients, which are effective in clearing heat and diuresis, resolving bruises and stopping bleeding, strengthening the stomach and brain, and reducing serum cholesterol levels. This article reviews the main nutrients of daylily and summarizes the drying process of daylily. In addition, due to the existence of active ingredients, daylily also has a variety of biological activities that are beneficial to human health. This article also highlights the nutritional quality of daylily, the research progress of dried vegetable rehydration technology and dried daylily. In the end, the undeveloped molecular mechanism and functional research status of daylily worldwide are introduced in order to provide reference for the nutritional quality research and dried processing industry of daylily.

Clinical Predictors of Nontuberculous Mycobacteria Lung Disease and Coisolates of Potential Pathogenic Microorganisms in Noncystic Fibrosis Bronchiectasis.

Background: In bronchiectasis, nontuberculous mycobacteria (NTM) lung disease (NTM-LD) is a well-known coexisting infection. However, microorganism coisolates and clinical NTM-LD predictors are poorly studied. Methods: Patients with bronchiectasis diagnosed by means of computed tomography between January 2017 and June 2020 were screened, using the date of computed tomography as the index date. Those with a major bronchiectasis diagnosis in ≥2 follow-up visits after the index date were enrolled in the study, and NTM-LD occurrence and its association with pneumonia and hospitalization within 1 year were analyzed. Results: Of the 2717 participants, 79 (2.9%) had NTM-LD diagnosed. The factors associated with NTM-LD included hemoptysis, postinfectious bronchiectasis, a tree-in-bud score ≥2, a modified Reiff score ≥4, and chronic obstructive pulmonary disease (adjusted odds ratios, 1.80, 2.36, 1.78, 2.95, and 0.51, respectively). Compared with patients in the non-NTM group, those with NTM-LD had higher rates of hospitalization (15.9% vs 32.9%; P < .001) and pneumonia (9.8% vs 20.3%; P = .003). Pseudomonas aeruginosa was the most common microorganism in those with NTM-LD and those in the non-NTM group (10.1% vs 7.8%; P = .40). However, compared with those in the non-NTM group, Acinetobacter baumannii and Escherichia coli were more prevalent in patients with NTM-LD (0.7% vs 3.8% [P = .03%] and 1.0% vs 3.8% [P = .05], respectively). Conclusions: Postinfectious bronchiectasis with hemoptysis, higher radiological involvement, and a tree-in-bud pattern were associated with NTM-LD risk. The rate of A baumannii and E coli coisolation was higher in bronchiectasis populations with NTM-LD.

Association between sarcopenia and frailty in middle-aged and elder population: Findings from the China health and retirement longitudinal study.

Background: The relationship between sarcopenia and frailty among middle-aged and elder adults remains unclear. This study conducted a cross-sectional and longitudinal analysis to investigate the association of sarcopenia and frailty in the middle-aged and elder Chinese population. Methods: Our data were drawn from the China Health and Retirement Longitudinal Study. Sarcopenia status was assessed according to the Asian Working Group for Sarcopenia 2019 criteria and categorised into: no sarcopenia, possible sarcopenia, sarcopenia, and severe sarcopenia. A 38-item deficit-accumulation frailty index was constructed to assess frailty trajectories at each visit. Generalised linear regression models were performed to analyse the cross-sectional associations between sarcopenia and frailty index. The Group-based trajectory modelling was adopted to identify potential frailty trajectories, and we then examined the associations of sarcopenia and frailty trajectories using logistic regression analysis. Results: A total of 13 218 participants were enrolled in the cross-sectional analysis and 4200 individuals were included in the longitudinal study. The cross-sectional study found that possible sarcopenia (regression coefficient (ß) = 0.76; 95% confidence interval (CI) = 0.64-0.87, P < 0.001), sarcopenia (ß = 0.56; 95% CI = 0.37-0.75, P < 0.001) and severe sarcopenia (ß = 1.35; 95% CI = 0.97-1.73, P < 0.001) were significantly associated with higher frailty index. The longitudinal study indicated that participants with possible sarcopenia (odds ratio (OR) = 2.46; 95% CI = 1.77-3.42, P < 0.001), sarcopenia (OR = 1.87; 95% CI = 1.27-2.74, P < 0.001) and severe sarcopenia (OR = 6.57; 95% CI = 3.14-13.77, P < 0.001) had a higher risk of accelerated progression of frailty compared to those with no sarcopenia. Conclusions: Possible sarcopenia, sarcopenia, and severe sarcopenia were associated with higher levels of frailty and accelerated progression of frailty. Therefore, clinical medical professionals should pay more attention to frailty status in individuals who have possible sarcopenia and sarcopenia.

Effective suppression of tumor growth and hepatic metastasis of neuroblastoma by NKT-stimulatory phenyl glycolipid.

Invariant natural killer T cell (iNKT) cells produce large amounts of cytokines in response to α-Galactosylceramide (α-GalCer) stimulation. An analog containing two phenyl rings on the acyl chain, C34, was previously found to be more Th1-biased than α-GalCer and triggered greater anticancer activities against breast cancer, melanoma and lung cancer in mice. Since liver is enriched in iNKT cells, we investigated anticancer efficacy of C34 on neuroblastoma with hepatic metastasis. C34 induced Th1-biased cytokine secretions in the liver, significantly suppressed neuroblastoma growth/metastasis and prolonged mouse survival. The anti-tumor efficacy might be attributed to greater expansions of hepatic NKT, NK, CD4+ T, and CD8+ T cells as well as reduction of the number of SSCloGr1intCD11b+ subset of myeloid-derived suppressor cells (MDSCs) in the liver of tumor-bearing mice, as compared to DMSO control group. C34 also upregulated expression of CD1d and CD11c, especially in the SSCloGr1intCD11b+ subset of MDSCs, which might be killed by C34-activated NKT cells, attributing to their reduced number. In addition, C34 also induced expansion of CD4+ T, CD8+ T, and NK cells, which might eliminate neuroblastoma cells. These immune-modulating effects of C34 might act in concert in the local milieu of liver to suppress the tumor growth. Further analysis of database of neuroblastoma revealed that patients with high CD11c expression in the monocytic MDSCs in the tumor had longer survival, suggesting the potential clinical application of C34 for treatment of neuroblastoma.

Predicting Collision Cross-Section Values for Small Molecules through Chemical Class-Based Multimodal Graph Attention Network.

Libraries of collision cross-section (CCS) values have the potential to facilitate compound identification in metabolomics. Although computational methods provide an opportunity to increase library size rapidly, accurate prediction of CCS values remains challenging due to the structural diversity of small molecules. Here, we developed a machine learning (ML) model that integrates graph attention networks and multimodal molecular representations to predict CCS values on the basis of chemical class. Our approach, referred to as MGAT-CCS, had superior performance in comparison to other ML models in CCS prediction. MGAT-CCS achieved a median relative error of 0.47%/1.14% (positive/negative mode) and 1.40%/1.63% (positive/negative mode) for lipids and metabolites, respectively. When MGAT-CCS was applied to real-world metabolomics data, it reduced the number of false metabolite candidates by roughly 25% across multiple sample types ranging from plasma and urine to cells. To facilitate its application, we developed a user-friendly stand-alone web server for MGAT-CCS that is freely available at https://mgat-ccs-web.onrender.com. This work represents a step forward in predicting CCS values and can potentially facilitate the identification of small molecules when using ion mobility spectrometry coupled with mass spectrometry.

The Warburg Effect Revisited through Blood and Electron Flow.

The Warburg effect describes the propensity of many cancers to consume glucose avidly and convert it to lactate in the presence of oxygen. The benefit of the Warburg effect on cancer cells remains enigmatic, particularly because extracellular disposal of incompletely oxidized lactate is wasteful. However, lactate is not discarded from the body, but rather recycled as pyruvate for metabolism through the tricarboxylic acid cycle in oxidative tissues and cells. Hence, tissue and interorgan metabolism play important roles in tumor metabolism. The production of tumor lactate to be recycled elsewhere parallels the Cori cycle, in which lactate produced by muscle activity is shuttled to the liver, where it is converted to pyruvate and subsequently stored as glucose moieties in glycogen. This perspective will consider this organismal contextwhile discussing how glucose is used in tumors. We highlight several key articles published decades ago in Cancer Research that are foundational to our current understanding of cancer biology and metabolism.

Forensic bone age assessment of hand and wrist joint MRI images in Chinese han male adolescents based on deep convolutional neural networks.

In Chinese criminal law, the ages of 12, 14, 16, and 18 years old play a significant role in the determination of criminal responsibility. In this study, we developed an epiphyseal grading system based on magnetic resonance image (MRI) of the hand and wrist for the Chinese Han population and explored the feasibility of employing deep learning techniques for bone age assessment based on MRI of the hand and wrist. This study selected 282 Chinese Han Chinese males aged 6.0-21.0 years old. In the course of our study, we proposed a novel deep learning model for extracting and enhancing MRI hand and wrist bone features to enhance the prediction of target MRI hand and wrist bone age and achieve precise classification of the target MRI and regression of bone age. The evaluation metric for the classification model including precision, specificity, sensitivity, and accuracy, while the evaluation metrics chosen for the regression model are MAE. The epiphyseal grading was used as a supervised method, which effectively solved the problem of unbalanced sample distribution, and the two experts showed strong consistency in the epiphyseal plate grading process. In the classification results, the accuracy in distinguishing between adults and minors was 91.1%, and the lowest accuracy in the three minor classifications (12, 14, and 16 years of age) was 94.6%, 91.1% and 96.4%, respectively. The MAE of the regression results was 1.24 years. In conclusion, the deep learning model proposed enabled the age assessment of hand and wrist bones based on MRI.

In vitro evaluation of the impact of a bioceramic root canal sealer on the mechanical properties of tooth roots.

Bacground/purpose: Endodontically treated teeth are more prone to vertical root fracture with the mechanical property changes to some extent during root canal treatment. This study aimed to investigate the effects of a bioceramic sealer on the mechanical properties of tooth roots. Materials and methods: Dentin discs were dried by two different methods (ethanol drying and paper points drying) and then filled with a BC sealer named iRoot SP. SEM and EDS were used to analyze the newly formed minerals in dentin tubules. Elastic modulus and hardness of the secondary dentin in areas proximal to the primary dentin (PD-SD) and areas proximal to canal or iRoot SP (SD-C/SD-iRoot SP) were measured using nanoindentation technique. The compressive strength of roots filled with iRoot SP were tested by compressive loading test. Results: (1) Penetration and mineralization: Paper points drying was more conducive to iRoot SP adhesion, spreading and penetration into the dentin tubules than 95% ethanol drying. (2) Micromechanical properties: After filling root canal with iRoot SP, the elastic modulus and hardness of SD-iRoot SP were higher than those of PD-SD (P = 0.001 and P = 0.000). (3) Fracture resistance: The compressive strength of the roots filled with iRoot SP was not significantly different from that of the roots unprepared and unfilled (P = 0.957), but was higher than that of the roots prepared and unfilled (P = 0.009). Conclusion: Excessive drying (95% ethanol drying method) is not conducive to the penetration and mineralization of the BC sealer iRoot SP into dentin tubules. The good bioactivity of iRoot SP was responsible for increasing the elastic modulus and hardness of dentin, which strengthened the prepared roots.

Research on 3D virtual vision matching based on interactive color segmentation.

Given the prevalent issues surrounding accuracy and efficiency in contemporary stereo-matching algorithms, this research introduces an innovative image segmentation-based approach. The proposed methodology integrates residual and Swim Transformer modules into the established 3D Unet framework, yielding the Res-Swim-UNet image segmentation model. The algorithm estimates the disparateness of segmented outputs by employing regression techniques, culminating in a comprehensive disparity map. Experimental findings underscore the superiority of the proposed algorithm across all evaluated metrics. Specifically, the proposed network demonstrates marked improvements, with IoU and mPA enhancements of 2.9% and 162%, respectively. Notably, the average matching error rate of the algorithm registers at 2.02%, underscoring its efficacy in achieving precise stereoscopic matching. Moreover, the model's enhanced generalization capability and robustness underscore its potential for widespread applicability.

A Plastic-Crystal Electrolyte Layer Promotes Interfacial Stability of Ni-Rich Oxide Cathode in Li6PS5Cl-Based All-Solid-State Rechargeable Li Batteries.

Unfavorable parasitic reactions between the Ni-rich layered oxide cathode and the sulfide solid electrolyte have plagued the realization of all-solid-state rechargeable Li batteries. The accumulation of inactive by-products (P2Sx, S, POx n- and SOx n-) at the cathode-sulfide interface impedes fast Li-ion transfer, which accounts for sluggish reaction kinetics and significant loss of cathode capacity. Herein, we proposed an easily scalable approach to stabilize the cathode electrochemistry via coating the cathode particles by a uniform, Li+-conductive plastic-crystal electrolyte nanolayer on their surface. The electrolyte, which simply consists of succinonitrile and Li bis(trifluoromethanesulphonyl)imide, serves as an interfacial buffer to effectively suppress the adverse phase transition in highly delithiated cathode materials, and the loss of lattice oxygen and generation of inactive oxygenated by-products at the cathode-sulfide interface. Consequently, an all-solid-state rechargeable Li battery with the modified cathode delivers high specific capacities of 168 mAh g-1 at 0.1 C and a high capacity retention >80 % after 100 cycles. Our work sheds new light on rational design of electrode-electrolyte interface for the next-generation high-energy batteries.

Visualization analysis of research frontiers and trends in the treatment of sciatic nerve injury.

Objective: To visualize and analyze the literature related to sciatic nerve injury treatment from January 2019 to December 2023, and summarize the current status, hotspots, and development trends of research in this field. Methods: Using CiteSpace and VOSviewer software, we searched the Web of Science database for literature related to the treatment of sciatic nerve injury. Then we analyzed and plotted visualization maps to show the number of publications, countries, institutions, authors, keywords, references, and journals. Results: A total of 2,653 articles were included in the English database. The annual number of publications exceeded 230, and the citation frequency increased yearly. The United States and China were identified as high-influence nations in this field. Nantong University was the leading institution in terms of close cooperation among institutions. The authors Wang Yu had the highest number of publications and were highly influential in this field. Keyword analysis and reference Burst revealed a research focus on nerve regeneration and neuropathic pain, which involve regenerative medicine and neural tissue engineering. Chronic pain resulting from sciatic nerve injury often manifests alongside anxiety, depression, cognitive-behavioral disorders, and other issues. Interventions such as stem cells, electrical stimulation, electroacupuncture, total joint replacement, pharmacological interventions, gene therapy, nerve conduits, chitosan scaffolds, and exercise promote nerve repair and alleviate pain. Schwann cells have been the focus of much attention in nerve repair and regeneration. Improving the outcome of sciatic nerve injury is a current research challenge and focus in this field. Based on keyword Burst, nerve conduits and grafts may become a potential research hotspot in the treatment of sciatic nerve injury. Conclusion: This visual analysis summarizes research trends and developments of sciatic nerve injury treatment and predicts potential research frontiers and hot directions.

Application of Medical Statistical and Machine Learning Methods in the Age Estimation of Living Individuals.

In the study of age estimation in living individuals, a lot of data needs to be analyzed by mathematical statistics, and reasonable medical statistical methods play an important role in data design and analysis. The selection of accurate and appropriate statistical methods is one of the key factors affecting the quality of research results. This paper reviews the principles and applicable principles of the commonly used medical statistical methods such as descriptive statistics, difference analysis, consistency test and multivariate statistical analysis, as well as machine learning methods such as shallow learning and deep learning in the age estimation research of living individuals, and summarizes the relevance and application prospects between medical statistical methods and machine learning methods. This paper aims to provide technical guidance for the age estimation research of living individuals to obtain more scientific and accurate results.

Application of multimodality perception scene construction based on Internet of Things (IoT) technology in art teaching.

Numerous impediments beset contemporary art education, notably the unidimensional delivery of content and the absence of real-time interaction during instructional sessions. This study endeavors to surmount these challenges by devising a multimodal perception system entrenched in Internet of Things (IoT) technology. This system captures students' visual imagery, vocalizations, spatial orientation, movements, ambient luminosity, and contextual data by harnessing an array of interaction modalities encompassing visual, auditory, tactile, and olfactory sensors. The synthesis of this manifold information about learning scenarios entails strategically placing sensors within physical environments to facilitate intuitive and seamless interactions. Utilizing digital art flower cultivation as a quintessential illustration, this investigation formulates tasks imbued with multisensory channel interactions, pushing the boundaries of technological advancement. It pioneers advancements in critical domains such as visual feature extraction by utilizing DenseNet networks and voice feature extraction leveraging SoundNet convolutional neural networks. This innovative paradigm establishes a novel art pedagogical framework, accentuating the importance of visual stimuli while enlisting other senses as complementary contributors. Subsequent evaluation of the usability of the multimodal perceptual interaction system reveals a remarkable task recognition accuracy of 96.15% through the amalgamation of Mel-frequency cepstral coefficients (MFCC) speech features with a long-short-term memory (LSTM) classifier model, accompanied by an average response time of merely 6.453 seconds-significantly outperforming comparable models. The system notably enhances experiential fidelity, realism, interactivity, and content depth, ameliorating the limitations inherent in solitary sensory interactions. This augmentation markedly elevates the caliber of art pedagogy and augments learning efficacy, thereby effectuating an optimization of art education.

NRDE2 deficiency impairs homologous recombination repair and sensitizes hepatocellular carcinoma to PARP inhibitors.

To identify novel susceptibility genes for hepatocellular carcinoma (HCC), we performed a rare-variant association study in Chinese populations consisting of 2,750 cases and 4,153 controls. We identified four HCC-associated genes, including NRDE2, RANBP17, RTEL1, and STEAP3. Using NRDE2 (index rs199890497 [p.N377I], p = 1.19 × 10-9) as an exemplary candidate, we demonstrated that it promotes homologous recombination (HR) repair and suppresses HCC. Mechanistically, NRDE2 binds to the subunits of casein kinase 2 (CK2) and facilitates the assembly and activity of the CK2 holoenzyme. This NRDE2-mediated enhancement of CK2 activity increases the phosphorylation of MDC1 and then facilitates the HR repair. These functions are eliminated almost completely by the NRDE2-p.N377I variant, which sensitizes the HCC cells to poly(ADP-ribose) polymerase (PARP) inhibitors, especially when combined with chemotherapy. Collectively, our findings highlight the relevance of the rare variants to genetic susceptibility to HCC, which would be helpful for the precise treatment of this malignancy.