Integrated Brain Connectivity Analysis with fMRI, DTI, and sMRI Powered by Interpretable Graph Neural Networks.

Multimodal neuroimaging modeling has becomes a widely used approach but confronts considerable challenges due to heterogeneity, which encompasses variability in data types, scales, and formats across modalities. This variability necessitates the deployment of advanced computational methods to integrate and interpret these diverse datasets within a cohesive analytical framework. In our research, we amalgamate functional magnetic resonance imaging, diffusion tensor imaging, and structural MRI into a cohesive framework. This integration capitalizes on the unique strengths of each modality and their inherent interconnections, aiming for a comprehensive understanding of the brain's connectivity and anatomical characteristics. Utilizing the Glasser atlas for parcellation, we integrate imaging derived features from various modalities: functional connectivity from fMRI, structural connectivity from DTI, and anatomical features from sMRI within consistent regions. Our approach incorporates a masking strategy to differentially weight neural connections, thereby facilitating a holistic amalgamation of multimodal imaging data. This technique enhances interpretability at connectivity level, transcending traditional analyses centered on singular regional attributes. The model is applied to the Human Connectome Project's Development study to elucidate the associations between multimodal imaging and cognitive functions throughout youth. The analysis demonstrates improved predictive accuracy and uncovers crucial anatomical features and essential neural connections, deepening our understanding of brain structure and function.

Transcranial direct current stimulation over the right parietal cortex improves the depressive disorder: A preliminary study.

OBJECTIVE: The right posterior parietal cortex is the core brain region of emotional processing and executive control network in the human brain, and the function of the right posterior parietal cortex is decreased in patients with major depressive disorder. This study aims to preliminarily investigate whether the excitation of the right posterior parietal cortex by transcranial direct current stimulation (tDCS) could improve their clinical symptoms. METHODS: In this study, 12 patients with major depressive disorder were given tDCS treatment at Xuanwu Hospital of Capital Medical University and the First Hospital of Hebei Medical University. The stimulating electrode (anode) was placed on the patients' right parietal cortex, whereas the reference electrode (cathode) was placed on the patients' left mastoid. The stimulation intensity was set as 2.0 mA. The patients with depressive disorder were treated for 20 min at a time twice a day for 14 consecutive days. The severity of the clinical symptoms was evaluated using the Hamilton Depression Rating Scale-17 (HDRS-17) and the Hamilton Anxiety Rating Scale (HARS) at before and right after treatment. RESULTS: The HDRS-17 scores of patients with depressive disorder decreased significantly following the tDCS treatment compared with those before treatment (p < .001). Further analysis revealed that the patients' anxiety/somatization, cognitive deficit, retardation, and sleep disorder scores all decreased significantly after the tDCS treatment (p < .05), although there was no significant change in their weight. Moreover, the patients' HARS scores decreased significantly after the tDCS treatment when compared with those before treatment (p < .01). CONCLUSION: The right parietal cortex may be another key stimulation targets to improving the efficacy of tDCS treatment to the patients with major depressive disorder.

Current perspectives and trends of CD39-CD73-eAdo/A2aR research in tumor microenvironment: a bibliometric analysis.

Background and objective: Extracellular adenosine (eAdo) bridges tumor metabolism and immune regulation. CD39-CD73-eAdo/A2aR axis regulates tumor microenvironment (TME) and immunotherapy response. In the era of immunotherapy, exploring the impact of the CD39-CD73-eAdo/A2aR axis on TME and developing targeted therapeutic drugs to enhance the efficacy of immunotherapy are the current research hotspots. This study summarizes and explores the research trends and hotspots of the adenosine axis in the field of TME to provide ideas for further in-depth research. Methods: Literature information was obtained from the Web of Science core collection database. The VOS viewer and the bibliometric tool based on R were used to quantify and identify cooperation information and individual influence by analyzing the detailed information of the global annual publication volume, country/region and institution distribution, article authors and co-cited authors, and journal distribution of these articles. At the same time, the distribution of author keywords and the co-occurrence of author keywords, highly cited articles, and highly co-cited references of CD39-CD73-eAdo/A2aR in the field of TME were analyzed to determine research hotspots and trends. Result: 1,721 articles published in the past ten years were included in this study. Through bibliometric analysis, we found that (1) 69 countries and regions explored the effect of the CD39-CD73-eAdo/A2aR on TME, and the research was generally on the rise. Researchers in the United States dominated research in this area, with the highest total citation rate. China had the most significant number of publications. (2) Harvard University has published the most articles in this field. (3) 12,065 authors contributed to the publication of papers in this field, of which 23 published at least eight papers. STAGG J had significant academic influence, with 24 published articles and 2,776 citations. Co-cited authors can be clustered into three categories. Stagg J, Allard B, Ohta A, and Antonioli, L occupied a central position in the network. (4) 579 scholarly journals have published articles in this field. The journal FRONTIERS IN IMMUNOLOGY published the most significant number of papers, with 97 articles and a total of 2,317 citations, and the number of publications increased year by year. (5) "The ectonucleotidases CD39 and CD73: Novel checkpoint inhibitor targets" was the most frequently local cited article (163 times). The "A2A adenosine receptor protects tumors from antitumor T cells" was the most co-cited reference (224 times). (6) Through the analysis of author keywords, we found that the relationship between adenosine and immunotherapy was a core concept for many researchers in this field. Breast cancer, melanoma, colorectal cancer, ovarian cancer, glioblastoma, pancreatic cancer, hepatocellular carcinoma, and lung cancer were the most frequent cancer types in adenosine-related tumor studies. Immunotherapy, immunosuppression, immune checkpoint, and immune checkpoint inhibitors were the hot keywords in the research, reflecting the importance of the adenosine metabolic pathway in tumor immunotherapy. The keywords such as Immunogenic cell death, T cells, Sting, regulatory T cells, innate immunity, and immune infiltration demonstrated the pathways by which adenosine affected the TME. The famous author keywords in recent years have been immunotherapy, immunogenic cell death, inflammation, lung cancer, and gastric cancer. Conclusion: The effect of CD39-CD73-eAdo/A2aR on the infiltration and function of various immune cells in TME, tumor immunotherapy response, and patient prognosis has attracted the attention of researchers from many countries/regions. American scholars still dominate the research in this field, but Chinese scholars produce the most research results. The journal FRONTIERS IN IMMUNOLOGY has published the wealthiest research in the field. Stagg J was a highly influential researcher in this field. Further exploration of targeted inhibition of CD39-CD73-eAdo/A2aR alone or in combination with other immunotherapy, radiotherapy, and chemotherapy in treating various cancer types and developing effective clinical therapeutic drugs are continuous research hotspots in this field.

Notch1 signaling pathway promotes growth and metastasis of gastric cancer via modulating CDH5.

OBJECTIVE: To explore the underlying molecular mechanism of Notch1/cadherin 5 (CDH5) pathway in modulating in cell malignant behaviors of gastric cancer (GC). METHODS: We performed bioinformatic analyses to screen the potential target genes of Notch1 from cadherins in GC. Western blot and RT-PCR were conducted to detect CDH5 expression in GC tissues and cells. We utilized chromatin immunoprecipitation (CHIP) assays to assess the interaction of Notch1 with CDH5 gene. The effects of Notch1/CDH5 axis on the proliferation, invasion, migration and vasculogenic mimicry in GC cells were evaluated by EdU, wound healing, transwell, and tubule formation assays. RESULTS: Significantly increased CDH5 expression was found in GC tissues compared with paracancerous tissues and associated to clinical stage and poor overall survival (OS) in patients with GC. Notch1 positively regulate the expression of CDH5 in GC cells. CHIP assays validated that CDH5 was a direct target of Notch1. In addition, Notch1 upregulation enhanced the proliferation, migration, invasion and vasculogenic mimicry capacity of GC cells, which could be attenuated by CDH5 silencing. CONCLUSIONS: These results indicated Notch1 upregulation enhanced GC malignant behaviors by triggering CDH5, suggesting that targeting Notch1/CDH5 axis could be a potential therapeutic strategy for GC progression.

Explainable spatio-temporal graph evolution learning with applications to dynamic brain network analysis during development.

Modeling dynamic interactions among network components is crucial to uncovering the evolution mechanisms of complex networks. Recently, spatio-temporal graph learning methods have achieved noteworthy results in characterizing the dynamic changes of inter-node relations (INRs). However, challenges remain: The spatial neighborhood of an INR is underexploited, and the spatio-temporal dependencies in INRs' dynamic changes are overlooked, ignoring the influence of historical states and local information. In addition, the model's explainability has been understudied. To address these issues, we propose an explainable spatio-temporal graph evolution learning (ESTGEL) model to model the dynamic evolution of INRs. Specifically, an edge attention module is proposed to utilize the spatial neighborhood of an INR at multi-level, i.e., a hierarchy of nested subgraphs derived from decomposing the initial node-relation graph. Subsequently, a dynamic relation learning module is proposed to capture the spatio-temporal dependencies of INRs. The INRs are then used as adjacent information to improve the node representation, resulting in comprehensive delineation of dynamic evolution of the network. Finally, the approach is validated with real data on brain development study. Experimental results on dynamic brain networks analysis reveal that brain functional networks transition from dispersed to more convergent and modular structures throughout development. Significant changes are observed in the dynamic functional connectivity (dFC) associated with functions including emotional control, decision-making, and language processing.

Water-Stable Ln-MOF as a multi-emitting luminescent sensor for the detection of metal ions and pharmaceuticals.

The development of innovative multi-emission sensors for the rapid and accurate detection of contaminants is both vital and challenging. In this study, utilizing two rigid ligands (H3ICA and H4BTEC), a series of water-stable bimetallic organic frameworks (EuTb-MOFs) were synthesized. Luminescent investigations have revealed that EuTb-MOF-1 exhibits prominent multiple emission peaks, attributed to the distinctive fluorescence characteristics of Eu(III) and Tb(III) ions. Therefore, EuTb-MOF-1 efficiently recognized various metal ions and pharmaceutical compounds through 2D decoded maps. Fe3+ and Pb2+ exhibited significant quenching effects on the luminescence of EuTb-MOF-1, which were attributed to the internal filtering effect and the interaction between Lewis basic sites within EuTb-MOF-1 and Pb2+ ions, respectively. Furthermore, EuTb-MOF-1 demonstrated high sensitivity to sulfonamide antibiotics, with detection limits of 0.037 µM for SMZ and 0.041 µM for SDZ, respectively. In addition, EuTb-MOF-1 was immobilized to prepare MOF-based test strips, enabling direct visual detection of sulfonamides as a portable sensor. With excellent water stability, multi-responsive recognition capabilities, and high sensitivity to specific analytes, EuTb-MOF-1 is a promising candidate for environmental contaminant detection in aquatic systems.

Isocitrate dehydrogenases 2-mediated dysfunctional metabolic reprogramming promotes intestinal cancer progression via regulating HIF-1A signaling pathway.

Changes in isocitrate dehydrogenases (IDH) lead to the production of the cancer-causing metabolite 2-hydroxyglutarate, making them a cause of cancer. However, the specific role of IDH in the progression of colon cancer is still not well understood. Our current study provides evidence that IDH2 is significantly increased in colorectal cancer (CRC) cells and actively promotes cell growth in vitro and the development of tumors in vivo. Inhibiting the activity of IDH2, either through genetic silencing or pharmacological inhibition, results in a significant increase in α-ketoglutarate (α-KG), indicating a decrease in the reductive citric acid cycle. The excessive accumulation of α-KG caused by the inactivation of IDH2 obstructs the generation of ATP in mitochondria and promotes the downregulation of HIF-1A, eventually inhibiting glycolysis. This dual metabolic impact results in a reduction in ATP levels and the suppression of tumor growth. Our study reveals a metabolic trait of colorectal cancer cells, which involves the active utilization of glutamine through reductive citric acid cycle metabolism. The data suggests that IDH2 plays a crucial role in this metabolic process and has the potential to be a valuable target for the advancement of treatments for colorectal cancer.

Far-infrared radiation and its therapeutic parameters: A superior alternative for future regenerative medicine?

In future regenerative medicine, far-infrared radiation (FIR) may be an essential component of optical therapy. Many studies have confirmed or validated the efficacy and safety of FIR in various diseases, benefiting from new insights into FIR mechanisms and the excellent performance of many applications. However, the lack of consensus on the biological effects and therapeutic parameters of FIR limits its practical applications in the clinic. In this review, the definition, characteristics, and underlying principles of the FIR are systematically illustrated. We outline the therapeutic parameters of FIR, including the wavelength range, power density, irradiation time, and distance. In addition, the biological effects, potential molecular mechanisms, and preclinical and clinical applications of FIR are discussed. Furthermore, the future development and applications of FIR are described in this review. By applying optimal therapeutic parameters, FIR can influence various cells, animal models, and patients, eliciting diverse underlying mechanisms and offering therapeutic potential for many diseases. FIR could represent a superior alternative with broad prospects for application in future regenerative medicine.

KPNA2 promotes the progression of gastric cancer by regulating the alternative splicing of related genes.

RNA-binding proteins (RBPs) play critical roles in genome regulation. In this study, we explored the latent function of KPNA2, which is an essential member of the RBP family, in the regulation of alternative splicing (AS) in gastric cancer (GC). We analyzed the role of KPNA2 in regulating differential expression and AS via RNA sequencing (RNA-seq) and improved RNA immunoprecipitation sequencing (iRIP-seq). Clinical specimens were used to analyze the associations between KPNA2 expression and clinicopathological characteristics. CCK8 assays, transwell assays and wound healing assays were performed to explore the effect of KPNA2/WDR62 on GC cell progression. KPNA2 was shown to be highly expressed in GC cells and tissues and associated with lymph node metastases. KPNA2 promoted the proliferation, migration and invasion of GC cells and primarily regulated exon skipping, alternative 3's splice sites (A3SSs), alternative 5' splice sites (A5SSs), and cassette exons. We further revealed that KPNA2 participated in biological processes related to cell proliferation, and the immune response in GC via the regulation of transcription. In addition, KPNA2 preferentially bound to intron regions. Notably, KPNA2 regulated the A3SS AS mode of WDR62, and upregulation of WDR62 reversed the KPNA2 downregulation-induced inhibition of GC cell proliferation, migration and invasion. Finally, we discovered that the AS of immune-related molecules could be regulated by KPNA2. Overall, our results demonstrated for the first time that KPNA2 functions as an oncogenic splicing factor in GC that regulated the AS and differential expression of GC-related genes, and KPNA2 may be a potential target for GC treatment.

Risk of severe dengue during secondary infection: A population-based cohort study in Taiwan.

BACKGROUND: Dengue poses a significant public health concern. Secondary dengue infections with different dengue virus (DENV) serotypes have been linked to an increased risk of severe dengue. This study aimed to assess the risk of severe dengue during secondary infection in Taiwan. METHODS: A retrospective cohort study was conducted using Taiwan's National Health Insurance Research Database to identify dengue cases with secondary dengue infection born after 1944 from 2014 to 2015. Ten matched patients with primary infection were selected as controls using propensity score matching for each secondary dengue infection case. The odds ratio (OR) for severe dengue in secondary versus primary infections was calculated using conditional logistic regression. RESULTS: This study included 357 cases with secondary dengue infection and 3570 matched controls. The risk of severe dengue was found to be 7.8% in individuals with secondary infection, compared to 3.8% in those with primary dengue infection. Secondary infection significantly increased the risk of severe dengue (OR 2.13, 95% CI: 1.40-3.25, P = 0.0004). Notably, a significant association between secondary infection and severe dengue was observed only when the interval between the first and secondary infection was greater than two years (OR 3.19, 95% CI 2.04-5.00, P < 0.0001). CONCLUSION: Secondary dengue infection significantly increases the risk of severe disease in Taiwan, particularly when the interval between infections is over two years. Healthcare professionals should maintain heightened vigilance for individuals with a history of previous dengue infection, particularly if their initial diagnosis was more than two years prior.

CircCFL1 Promotes TNBC Stemness and Immunoescape via Deacetylation-Mediated c-Myc Deubiquitylation to Facilitate Mutant TP53 Transcription.

Triple-negative breast cancer (TNBC) is the most malignant subtype of breast cancer. TP53, which has a mutation rate of ≈70%-80% in TNBC patients, plays oncogenic roles when mutated. However, whether circRNAs can exert their effects on TNBC through regulating mutant TP53 has not been well evaluated. In this study, circCFL1, which is highly expressed in TNBC cells and tissues and has prognostic potential is identified. Functionally, circCFL1 promoted the proliferation, metastasis and stemness of TNBC cells. Mechanistically, circCFL1 acted as a scaffold to enhance the interaction between HDAC1 and c-Myc, further promoting the stability of c-Myc via deacetylation-mediated inhibition of K48-linked ubiquitylation. Stably expressed c-Myc further enhanced the expression of mutp53 in TNBC cells with TP53 mutations by directly binding to the promoter of TP53, which promoted the stemness of TNBC cells via activation of the p-AKT/WIP/YAP/TAZ pathway. Moreover, circCFL1 can facilitate the immune escape of TNBC cells by promoting the expression of PD-L1 and suppressing the antitumor immunity of CD8+ T cells. In conclusion, the results revealed that circCFL1 plays an oncogenic role by promoting the HDAC1/c-Myc/mutp53 axis, which can serve as a potential diagnostic biomarker and therapeutic target for TNBC patients with TP53 mutations.

Risks of anxiety disorders, depressive disorders, and sleep disorders in patients with dengue fever: A nationwide, population-based cohort study.

BACKGROUND: Dengue virus (DENV) infection, a common mosquito-borne disease, has been linked to several mental disorders like depression and anxiety. However, the temporal risk of these disorders after DENV infection is not well studied. METHODS: This population-based cohort study encompassed 45,334 recently lab-confirmed dengue patients in Taiwan spanning 2002 to 2015, matched at a 1:5 ratio with non-dengue individuals based on age, gender, and residence (n = 226,670). Employing subdistribution hazard regression analysis, we assessed the immediate (<3 months), intermediate (3-12 months), and prolonged (>12 months) risks of anxiety disorders, depressive disorders, and sleep disorders post DENV infection. Corrections for multiple comparisons were carried out using the Benjamini-Hochberg procedure. RESULTS: A significant increase in depressive disorder risk across all timeframes post-infection was observed (<3 months [aSHR 1.90, 95% CI 1.20-2.99], 3-12 months [aSHR 1.68, 95% CI 1.32-2.14], and >12 months [aSHR 1.14, 95% CI 1.03-1.25]). Sleep disorder risk was higher only during 3-12 months (aSHR 1.55, 95% CI 1.18-2.04). No elevated anxiety disorder risk was found. Subgroup analysis of hospitalized dengue patients showed increased risk of anxiety disorders within 3 months (aSHR 2.14, 95% CI 1.19-3.85) and persistent risk of depressive disorders across all periods. Hospitalized dengue patients also had elevated sleep disorder risk within the first year. CONCLUSION: Dengue patients exhibited significantly elevated risks of depressive disorders in both the short and long term. However, dengue's impact on sleep disorders and anxiety seems to be short-lived. Further research is essential to elucidate the underlying mechanisms.

Effects of endogenous testosterone on oscillatory activity during verbal working memory in youth.

Testosterone levels sharply rise during the transition from childhood to adolescence and these changes are known to be associated with changes in human brain structure. During this same developmental window, there are also robust changes in the neural oscillatory dynamics serving verbal working memory processing. Surprisingly, whereas many studies have investigated the effects of chronological age on the neural oscillations supporting verbal working memory, none have probed the impact of endogenous testosterone levels during this developmental period. Using a sample of 89 youth aged 6-14 years-old, we collected salivary testosterone samples and recorded magnetoencephalography during a modified Sternberg verbal working memory task. Significant oscillatory responses were identified and imaged using a beamforming approach and the resulting maps were subjected to whole-brain ANCOVAs examining the effects of testosterone and sex, controlling for age, during verbal working memory encoding and maintenance. Our primary results indicated robust testosterone-related effects in theta (4-7 Hz) and alpha (8-14 Hz) oscillatory activity, controlling for age. During encoding, females exhibited weaker theta oscillations than males in right cerebellar cortices and stronger alpha oscillations in left temporal cortices. During maintenance, youth with greater testosterone exhibited weaker alpha oscillations in right parahippocampal and cerebellar cortices, as well as regions across the left-lateralized language network. These results extend the existing literature on the development of verbal working memory processing by showing region and sex-specific effects of testosterone, and are the first results to link endogenous testosterone levels to the neural oscillatory activity serving verbal working memory, above and beyond the effects of chronological age.

Evaluating drug withdrawal syndrome risks through food and drug administration adverse event reporting system: a comprehensive disproportionality analysis.

Objective: The study aims to identify the drugs associated with drug withdrawal syndrome in the Food and Drug Administration Adverse Event Reporting System (FAERS) and estimate their risks of causing withdrawal syndrome. Methods: All the data were collected from FAERS from the first quarter of 2004 to the third quarter of 2023. Disproportionality analyses of odds ratio (ROR) and proportional reported ratio were conducted to identify potential adverse effects signal of drug withdrawal syndrome. Results: A total of 94,370 reports related to withdrawal syndrome from the data. The top 50 drugs with most frequency reported were analyzed, and 29 exhibited a positive signal based on the number of reports. The top three categories of drugs with positive signals included opioids, antidepressant drugs and antianxiety drugs. Other classifications included opioid antagonist, muscle relaxant, antiepileptic drugs, analgesics, hypnotic sedative drugs and antipsychotic drugs. Conclusion: Our analysis of FAERS data yielded a comprehensive list of drugs associated with withdrawal syndrome. This information is vital for healthcare professionals, including doctors and pharmacists, as it aids in better recognition and management of withdrawal symptoms in patients undergoing treatment with these medications.

A Deep Dynamic Causal Learning Model to Study Changes in Dynamic Effective Connectivity during Brain Development.

OBJECTIVE: Brain dynamic effective connectivity (dEC), characterizes the information transmission patterns between brain regions that change over time, which provides insight into the biological mechanism underlying brain development. However, most existing methods predominantly capture fixed or temporally invariant EC, leaving dEC largely unexplored. METHODS: Herein we propose a deep dynamic causal learning model specifically designed to capture dEC. It includes a dynamic causal learner to detect time-varying causal relationships from spatio-temporal data, and a dynamic causal discriminator to validate these findings by comparing original and reconstructed data. RESULTS: Our model outperforms established baselines in the accuracy of identifying dynamic causalities when tested on the simulated data. When applied to the Philadelphia Neurodevelopmental Cohort, the model uncovers distinct patterns in dEC networks across different age groups. Specifically, the evolution process of brain dEC networks in young adults is more stable than in children, and significant differences in information transfer patterns exist between them. CONCLUSION: This study highlights the brain's developmental trajectory, where networks transition from undifferentiated to specialized structures with age, in accordance with the improvement of an individual's cognitive and information processing capability. SIGNIFICANCE: The proposed model consists of the identification and verification of dynamic causality, utilizing the spatio-temporal fusing information from fMRI. As a result, it can accurately detect dEC and characterize its evolution over age.

Application of HFO and scaling analysis of neuronal oscillations in the presurgical evaluation of focal epilepsy.

PURPOSE: To explore the utility of high frequency oscillations (HFO) and long-range temporal correlations (LRTCs) in preoperative assessment of epilepsy. METHODS: MEG ripples were detected in 59 drug-resistant epilepsy patients, comprising 5 with parietal lobe epilepsy (PLE), 21 with frontal lobe epilepsy (FLE), 14 with lateral temporal lobe epilepsy (LTLE), and 19 with mesial temporal lobe epilepsy (MTLE) to identify the epileptogenic zone (EZ). The results were compared with clinical MEG reports and resection area. Subsequently, LRTCs were quantified at the source-level by detrended fluctuation analysis (DFA) and life/waiting -time at 5 bands for 90 cerebral cortex regions. The brain regions with larger DFA exponents and standardized life-waiting biomarkers were compared with the resection results. RESULTS: Compared to MEG sensor-level data, ripple sources were more frequently localized within the resection area. Moreover, source-level analysis revealed a higher proportion of DFA exponents and life-waiting biomarkers with relatively higher rankings, primarily distributed within the resection area (p<0.01). Moreover, these two LRCT indices across five distinct frequency bands correlated with EZ. CONCLUSION: HFO and source-level LRTCs are correlated with EZ. Integrating HFO and LRTCs may be an effective approach for presurgical evaluation of epilepsy.

OsNLP3 enhances grain weight and reduces grain chalkiness in rice.

Grain weight, a key determinant of yield in rice (Oryza sativa L.), is governed primarily by genetic factors, whereas grain chalkiness, a detriment to grain quality, is intertwined with environmental factors such as mineral nutrients. Nitrogen (N) is recognized for its effect on grain chalkiness, but the underlying molecular mechanisms remain to be clarified. This study revealed the pivotal role of rice NODULE INCEPTION-LIKE PROTEIN 3 (OsNLP3) in simultaneously regulating grain weight and grain chalkiness. Our investigation showed that loss of OsNLP3 leads to a reduction in both grain weight and dimension, in contrast to the enhancement observed with OsNLP3 overexpression. OsNLP3 directly suppresses the expression of OsCEP6.1 and OsNF-YA8, which were identified as negative regulators associated with grain weight. Consequently, two novel regulatory modules, OsNLP3-OsCEP6.1 and OsNLP3-OsNF-YA8, were identified as key players in grain weight regulation. Notably, the OsNLP3-OsNF-YA8 module not only increases grain weight but also mitigates grain chalkiness in response to N. This research clarifies the molecular mechanisms that orchestrate grain weight through the OsNLP3-OsCEP6.1 and OsNLP3-OsNF-YA8 modules, highlighting the pivotal role of the OsNLP3-OsNF-YA8 module in alleviating grain chalkiness. These findings reveal potential targets for simultaneous enhancement of rice yield and quality.