Noble-Metal-Free High-Entropy Alloy Nanoparticles for Efficient Solar-Driven Photocatalytic CO2 Reduction.

Metal nanoparticle (NP) cocatalysts are widely investigated for their ability to enhance the performance of photocatalytic materials; however, their practical application is often limited by the inherent instability under light irradiation. This challenge has catalyzed interest in exploring high-entropy alloys (HEAs), which, with their increased entropy and lower Gibbs free energy, provide superior stability. In this study, 3.5 nm-sized noble-metal-free NPs composed of a FeCoNiCuMn HEA are successfully synthesized. With theoretic calculation and experiments, the electronic structure of HEA in augmenting the catalytic CO2 reduction has been uncovered, including the individual roles of each element and the collective synergistic effects. Then, their photocatalytic CO2 reduction capabilities are investigated when immobilized on TiO2. HEA NPs significantly enhance the CO2 photoreduction, achieving a 23-fold increase over pristine TiO2, with CO and CH4 production rates of 235.2 and 19.9 µmol g-1 h-1, respectively. Meanwhile, HEA NPs show excellent stability under simulated solar irradiation, as well high-energy X-ray irradiation. This research emphasizes the promising role of HEA NPs, composed of earth-abundant elements, in revolutionizing the field of photocatalysis.

Complete miscibility of immiscible elements at the nanometre scale.

Understanding the mixing behaviour of elements in a multielement material is important to control its structure and property. When the size of a multielement material is decreased to the nanoscale, the miscibility of elements in the nanomaterial often changes from its bulk counterpart. However, there is a lack of comprehensive and quantitative experimental insight into this process. Here we explored how the miscibility of Au and Rh evolves in nanoparticles of sizes varying from 4 to 1 nm and composition changing from 15% Au to 85% Au. We found that the two immiscible elements exhibit a phase-separation-to-alloy transition in nanoparticles with decreased size and become completely miscible in sub-2 nm particles across the entire compositional range. Quantitative electron microscopy analysis and theoretical calculations were used to show that the observed immiscibility-to-miscibility transition is dictated by particle size, composition and possible surface adsorbates present under the synthesis conditions.

Prediction of immune infiltration and prognosis for patients with cholangiocarcinoma based on a cuproptosis-related lncRNA signature.

Objective: Cholangiocarcinoma (CHOL) is a malignant disease that affects the digestive tract, and it is characterized by a poor prognosis. This research sought to explore the involvement of cuproptosis-related lncRNAs (CRLs) in the prognostic prediction and immune infiltration of cholangiocarcinoma. Methods: The expression profiles and clinical data of CHOL patients were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and CRLs were defined via co-expression analysis. Two molecular clusters distinguished by cuproptosis-related genes (CRGs) were produced. Then a risk signature consisted by four CRLs was formed, and all samples were separated into low- and high-risk groups using a risk score. Kaplan-Meier survival analysis, principal component analysis, differentially expressed analysis, immune cell infiltration analysis, and sensitivities analysis of chemotherapy drugs were conducted between the two groups. Simultaneously, the expression values of four lncRNAs confirmed by real-time PCR in our own 20 CHOL samples were brought into the risk model. Results: The CHOL samples could be differentiated into two molecular clusters, which displayed contrasting survival times. Additionally, patients with higher risk scores had significantly worse prognosis compared to those in the low-risk group. Furthermore, both immune infiltration and enrichment analysis revealed significant discrepancies in the tumor immune microenvironment (TIME) between different risk groups. Moreover, the predictive power and the correlation with CA19-9 and CEA of risk signature were validated in our own samples. Conclusion: We developed a risk signature which could serve as an independent prognostic factor and offer a promising prediction for not only prognosis but also TIME in CHOL patients.

Targeting ONECUT3 blocks glycolytic metabolism and potentiates anti-PD-1 therapy in pancreatic cancer.

BACKGROUND: Reprogramming glucose metabolism, also known as the Warburg effect (aerobic glycolysis), is a hallmark of cancers. Increased tumor glycolysis not only favors rapid cancer cell proliferation but reprograms the immune microenvironment to enable tumor progression. The transcriptional factor ONECUT3 plays key roles in the development of the liver and pancreas, however, limited is known about its oncogenic roles, particularly metabolic reprogramming. METHODS: Immunohistochemistry and Western blotting are applied to determine the expression pattern of ONECUT3 and its clinical relevance in pancreatic ductal adenocarcinoma (PDAC). Knockdown and overexpression strategies are employed to determine the in vitro and in vivo functions of ONECUT3. Chromatin immunoprecipitation, luciferase reporter assay, and gene set enrichment analysis are used to decipher the molecular mechanisms. RESULTS: The glycolytic metabolism is inversely associated with T-cell infiltration in PDAC. ONECUT3 is identified as a key regulator for PDAC glycolysis and CD8+ T-cell infiltration. Genetic silencing of ONECUT3 inhibits cell proliferation, promotes cell apoptosis, and reduces glycolytic metabolism as evidenced by glucose uptake, lactate production, and extracellular acidification rate. Opposite effects of ONECUT3 are observed in overexpression studies. ONECUT3 enhances aerobic glycolysis via transcriptional regulation of PDK1. Targeting ONECUT3 effectively suppresses tumor growth, increases CD8+ T-cell infiltration, and potentiates anti-PD-1 therapy in PDAC. Pharmacological inhibition of PDK1 also shows a synergistic effect with anti-PD-1 therapy. In clinical setting, ONECUT3 is closely associated with PDK1 expression and T-cell infiltration in PDAC and acts as an independent prognostic factor. CONCLUSIONS: Our study reveals a previous unprecedented regulatory role of ONECUT3 in PDAC glycolysis and provides in vivo evidence that increased glycolysis is linked to an immunosuppressive microenvironment. Moreover, targeting ONECUT3-PDK1 axis may serve as a promising therapeutic approach for the treatment of PDAC.

Interfacial Organization and Forces Arising from Epithelial-Cancerous Monolayer Interactions.

The interfacial interactions between epithelia and cancer cells have profound relevance for tumor development and metastasis. Through monolayer confrontation of MCF10A (nontumorigenic human breast epithelial cells) and MDA-MB-231 (human epithelial breast cancer cells) cells, we investigate the epithelial-cancerous interfacial interactions at the tissue level. We show that the monolayer interaction leads to competitive interfacial morphodynamics and drives an intricate spatial organization of MCF10A cells into multicellular finger-like structures, which further branch into multiple subfinger-like structures. These hierarchical interfacial structures penetrate the cancer monolayer and can spontaneously segregate or even envelop cancer cell clusters, consistent with our theoretical prediction. By tracking the substrate displacements via embedded fluorescent nanobeads and implementing nanomechanical modeling that combines atomic force microscopy and finite element simulations, we computed mechanical force patterns, including traction forces and monolayer stresses, caused by the monolayer interaction. It is found that the heterogeneous mechanical forces accumulated in the monolayers are able to squeeze cancer cells, leading to three-dimensional interfacial bulges or cell extrusion, initiating the p53 apoptosis signaling pathways of cancer cells. We reveal that intercellular E-cadherin and P-cadherin of epithelial cells differentially regulate the interfacial organization including migration speed, directionality, spatial correlation, F-actin alignment, and subcellular protrusions of MCF10A cells; whereas E-cadherin governs interfacial geometry that is relevant to force localization and cancer cell extrusion, P-cadherin maintains interfacial integrity that enables long-range force transmission. Our findings suggest that the collaborative molecular and mechanical behaviors are crucial for preventing epithelial tissues from undergoing tumor invasion.

Substrate nesting guides cyst morphogenesis of human pluripotent stem cells without 3D extracellular matrix overlay.

Understanding the principles underlying the self-organization of stem cells into tissues is fundamental for deciphering human embryo development. Here, we report that, without three-dimensional (3D) extracellular matrix (ECM) overlay, human pluripotent stem cells (hPSCs) cultured on two-dimensional soft elastic substrates can self-organize into 3D cysts resembling the human epiblast sac in a stiffness-dependent manner. Our theoretical modeling predicts that this cyst organization is facilitated and guided by the spontaneous nesting of the soft substrate, which results from the adhesion-dependent mechanical interaction between cells and substrate. Such substrate nesting is sufficient for the 3D assembly and polarization of hPSCs required for cyst organization, even without 3D ECM overlay. Furthermore, we identify that the reversible substrate nesting and cyst morphogenesis also require appropriate activation of ROCK-Myosin II pathway. This indicates a unique set of tissue morphomechanical signaling mechanisms that clearly differ from the canonical cystogenic mechanism previously reported in 3D ECM. Our findings highlight an unanticipated synergy between mechanical microenvironment and mechanotransduction in controlling tissue morphogenesis and suggest a mechanics-based strategy for generation of hPSCs-derived models for early human embryogenesis. STATEMENT OF SIGNIFICANCE: Soft substrates can induce the self-organization of human pluripotent stem cells (hPSCs) into cysts without three-dimensional (3D) extracellular matrix (ECM) overlay. However, the underlying mechanisms by which soft substrate guides cystogenesis are largely unknown. This study shows that substrate nesting, resulting from cell-substrate interaction, plays an important role in cyst organization, including 3D assembly and apical-basal polarization. Additionally, actomyosin contractility mediated by the ROCK-Myosin II pathway also contributes to the substrate deformation and cyst morphology. These findings demonstrate the interplay between the mechanical microenvironment and cells in tissue morphogenesis, suggesting a mechanics-based strategy in building hPSC-derived models for early human embryo development.

Understanding the Structural Evolution of IrFeCoNiCu High-Entropy Alloy Nanoparticles under the Acidic Oxygen Evolution Reaction.

High-entropy alloy (HEA) nanoparticles are promising catalyst candidates for the acidic oxygen evolution reaction (OER). Herein, we report the synthesis of IrFeCoNiCu-HEA nanoparticles on a carbon paper substrate via a microwave-assisted shock synthesis method. Under OER conditions in 0.1 M HClO4, the HEA nanoparticles exhibit excellent activity with an overpotential of ∼302 mV measured at 10 mA cm-2 and improved stability over 12 h of operation compared to the monometallic Ir counterpart. Importantly, an active Ir-rich shell layer with nanodomain features was observed to form on the surface of IrFeCoNiCu-HEA nanoparticles immediately after undergoing electrochemical activation, mainly due to the dissolution of the constituent 3d metals. The core of the particles was able to preserve the characteristic homogeneous single-phase HEA structure without significant phase separation or elemental segregation. This work illustrates that under acidic operating conditions, the near-surface structure of HEA nanoparticles is susceptible to a certain degree of structural dynamics.

Chemical and Structural Evolution of AgCu Catalysts in Electrochemical CO2 Reduction.

Silver-copper (AgCu) bimetallic catalysts hold great potential for electrochemical carbon dioxide reduction reaction (CO2RR), which is a promising way to realize the goal of carbon neutrality. Although a wide variety of AgCu catalysts have been developed so far, it is relatively less explored how these AgCu catalysts evolve during CO2RR. The absence of insights into their stability makes the dynamic catalytic sites elusive and hampers the design of AgCu catalysts in a rational manner. Here, we synthesized intermixed and phase-separated AgCu nanoparticles on carbon paper electrodes and investigated their evolution behavior in CO2RR. Our time-sequential electron microscopy and elemental mapping studies show that Cu possesses high mobility in AgCu under CO2RR conditions, which can leach out from the catalysts by migrating to the bimetallic catalyst surface, detaching from the catalysts, and agglomerating as new particles. Besides, Ag and Cu manifest a trend to phase-separate into Cu-rich and Ag-rich grains, regardless of the starting catalyst structure. The composition of the Cu-rich and Ag-rich grains diverges during the reaction and eventually approaches thermodynamic values, i.e., Ag0.88Cu0.12 and Ag0.05Cu0.95. The separation between Ag and Cu has been observed in the bulk and on the surface of the catalysts, highlighting the importance of AgCu phase boundaries for CO2RR. In addition, an operando high-energy-resolution X-ray absorption spectroscopy study confirms the metallic state of Cu in AgCu as the catalytically active sites during CO2RR. Taken together, this work provides a comprehensive understanding of the chemical and structural evolution behavior of AgCu catalysts in CO2RR.

Immobilization of Actinobacillus succinogenes on nano- and micro-fiber membranes for efficient and robust production of succinic acid.

This work aimed to study the efficiency of nano- and micro- fiber membranes in immobilizing Actinobacillus succinogenes CCTCC M2012036 for succinic acid production. Among the four kinds of electrospun nanofiber membranes of cellulose acetate, chitosan, poly(vinyl alcohol) (PVA) and chitosan-PVA, the cellulose acetate nanofiber membrane-immobilized cells performed the best with a succinic acid concentration and yield to be 27.3 ± 3.5 g/L and 70.9 ± 5.8%. The cell-immobilized viscose microfiber membrane presented good reuse stability, and 17 batches of fermentation without activity loss were realized with the highest succinic acid yield of 83.20%. A microfiber membrane bioreactor was further constructed with the cell-immobilized viscose microfiber membrane to perform fermentation on a larger scale, and the concentration, yield and productivity of succinic acid were 73.20 g/L, 86.50% and 1.49 g/(L⋅h) using a fed-batch strategy, which were 124.30%, 127.60% and 124.2% of those obtained in the traditional fermenter. This study provided an approach for improving the practicality of biological succinic acid production.

Direct Observation of Transient Structural Dynamics of Atomically Thin Halide Perovskite Nanowires.

Halide perovskite is a unique dynamical system, whose structural and chemical processes happening across different timescales have significant impact on its physical properties and device-level performance. However, due to its intrinsic instability, real-time investigation of the structure dynamics of halide perovskite is challenging, which hinders the systematic understanding of the chemical processes in the synthesis, phase transition, and degradation of halide perovskite. Here, we show that atomically thin carbon materials can stabilize ultrathin halide perovskite nanostructures against otherwise detrimental conditions. Moreover, the protective carbon shells enable atomic-level visualization of the vibrational, rotational, and translational movement of halide perovskite unit cells. Albeit atomically thin, protected halide perovskite nanostructures can maintain their structural integrity up to an electron dose rate of 10,000 e-/Å2·s while exhibiting unusual dynamical behaviors pertaining to the lattice anharmonicity and nanoscale confinement. Our work demonstrates an effective method to protect beam-sensitive materials during in situ observation, unlocking new solutions to study new modes of structure dynamics of nanomaterials.

Operando studies reveal active Cu nanograins for CO2 electroreduction.

Carbon dioxide electroreduction facilitates the sustainable synthesis of fuels and chemicals1. Although Cu enables CO2-to-multicarbon product (C2+) conversion, the nature of the active sites under operating conditions remains elusive2. Importantly, identifying active sites of high-performance Cu nanocatalysts necessitates nanoscale, time-resolved operando techniques3-5. Here, we present a comprehensive investigation of the structural dynamics during the life cycle of Cu nanocatalysts. A 7 nm Cu nanoparticle ensemble evolves into metallic Cu nanograins during electrolysis before complete oxidation to single-crystal Cu2O nanocubes following post-electrolysis air exposure. Operando analytical and four-dimensional electrochemical liquid-cell scanning transmission electron microscopy shows the presence of metallic Cu nanograins under CO2 reduction conditions. Correlated high-energy-resolution time-resolved X-ray spectroscopy suggests that metallic Cu, rich in nanograin boundaries, supports undercoordinated active sites for C-C coupling. Quantitative structure-activity correlation shows that a higher fraction of metallic Cu nanograins leads to higher C2+ selectivity. A 7 nm Cu nanoparticle ensemble, with a unity fraction of active Cu nanograins, exhibits sixfold higher C2+ selectivity than the 18 nm counterpart with one-third of active Cu nanograins. The correlation of multimodal operando techniques serves as a powerful platform to advance our fundamental understanding of the complex structural evolution of nanocatalysts under electrochemical conditions.

Topological defect-mediated morphodynamics of active-active interfaces.

Physical interfaces widely exist in nature and engineering. Although the formation of passive interfaces is well elucidated, the physical principles governing active interfaces remain largely unknown. Here, we combine simulation, theory, and cell-based experiment to investigate the evolution of an active-active interface. We adopt a biphasic framework of active nematic liquid crystals. We find that long-lived topological defects mechanically energized by activity display unanticipated dynamics nearby the interface, where defects perform "U-turns" to keep away from the interface, push the interface to develop local fingers, or penetrate the interface to enter the opposite phase, driving interfacial morphogenesis and cross-interface defect transport. We identify that the emergent interfacial morphodynamics stems from the instability of the interface and is further driven by the activity-dependent defect-interface interactions. Experiments of interacting multicellular monolayers with extensile and contractile differences in cell activity have confirmed our predictions. These findings reveal a crucial role of topological defects in active-active interfaces during, for example, boundary formation and tissue competition that underlie organogenesis and clinically relevant disorders.

Exploitation and Verification of a Stroma- and Metastasis-Associated Risk Prognostic Signature in Pancreatic Adenocarcinoma.

Pancreatic adenocarcinoma (PAAD), one of the most malignant tumors, not only has abundant mesenchymal components, but is also characterized by an extremely high metastatic risk. The purpose of this study was to construct a model of stroma- and metastasis-associated prognostic signature, aiming to benefit the existing clinical staging system and predict the prognosis of patients. First, stroma-associated genes were screened from the TCGA database with the ESTIMATE algorithm. Subsequently, transcriptomic data from clinical tissues in the RenJi cohort were screened for metastasis-associated genes. Integrating the two sets of genes, we constructed a risk prognostic signature by Cox and LASSO regression analysis. We then obtained a risk score by a quantitative formula and divided all samples into high- and low-risk groups based on the scores. The results demonstrated that patients with high-risk scores have a worse prognosis than those with low-risk scores, both in the TCGA database and in the RenJi cohort. In addition, tumor mutation burden, chemotherapeutic drug sensitivity and immune infiltration analysis also exhibited significant differences between the two groups. In exploring the potential mechanisms of how stromal components affect tumor metastasis, we simulated different matrix stiffness in vitro to explore its effect on EMT key genes in PAAD cells. We found that cancer cells stimulated by high matrix stiffness may trigger EMT and promote PAAD metastasis.

Unified multiscale theory of cellular mechanical adaptations to substrate stiffness.

Rigidity of the extracellular matrix markedly regulates many cellular processes. However, how cells detect and respond to matrix rigidity remains incompletely understood. Here, we propose a unified two-dimensional multiscale framework accounting for the chemomechanical feedback to explore the interrelated cellular mechanosensing, polarization, and migration, which constitute the dynamic cascade in cellular response to matrix stiffness but are often modeled separately in previous theories. By combining integrin dynamics and intracellular force transduction, we show that substrate stiffness can act as a switch to activate or deactivate cell polarization. Our theory quantitatively reproduces rich stiffness-dependent cellular dynamics, including spreading, polarity selection, migration pattern, durotaxis, and even negative durotaxis, reported in a wide spectrum of cell types, and reconciles some inconsistent experimental observations. We find that a specific bipolarized mode can determine the optimal substrate stiffness, which enables the fastest cell migration rather than the largest traction forces that cells apply on the substrate. We identify that such a mechanical adaptation stems from the force balance across the whole cell. These findings could yield universal insights into various stiffness-mediated cellular processes within the context of tissue morphogenesis, wound healing, and cancer invasion.

Research on Cement Slurry Using Silica Fume Instead of Fly Ash.

Ordinary cement is not environmentally friendly, has high cost and lacks superior performance. Many scholars use various admixtures to adjust the properties of cement slurry, but admixtures are usually not environmentally friendly, and it is difficult to ensure that the properties after deployment meet engineering requirements. In this study, a variety of admixtures were obtained using the environmental protection method, and the optimal mixing ratio was analyzed by combining the entropy weight method and the Taguchi grey relational analysis method. The developed cement slurry was compared with conventional slurry from both macroscopic and microscopic aspects. Aiming at the problem that previous scholars lacked the engineering feasibility verification of the developed slurry, this study combined the constitutive equation regression analysis method, discrete element numerical simulation and other methods to study various actual engineering conditions. The results show that the optimal mix ratio of silica fume cement slurry has good permeability characteristics under the conditions of different roughness, grouting pressure and confining pressure. At the same time, under different geological temperatures and different erosive liquid states, the cement slurry stone body shows good properties of reinforcement materials.

Predicted mouse interactome and network-based interpretation of differentially expressed genes.

The house mouse or Mus musculus has become a premier mammalian model for genetic research due to its genetic and physiological similarities to humans. It brought mechanistic insights into numerous human diseases and has been routinely used to assess drug efficiency and toxicity, as well as to predict patient responses. To facilitate molecular mechanism studies in mouse, we present the Mouse Interactome Database (MID, Version 1), which includes 155,887 putative functional associations between mouse protein-coding genes inferred from functional association evidence integrated from 9 public databases. These putative functional associations are expected to cover 19.32% of all mouse protein interactions, and 26.02% of these function associations may represent protein interactions. On top of MID, we developed a gene set linkage analysis (GSLA) web tool to annotate potential functional impacts from observed differentially expressed genes. Two case studies show that the MID/GSLA system provided precise and informative annotations that other widely used gene set annotation tools, such as PANTHER and DAVID, did not. Both MID and GSLA are accessible through the website http://mouse.biomedtzc.cn.

Revealing the Phase Separation Behavior of Thermodynamically Immiscible Elements in a Nanoparticle.

Phase-separation is commonly observed in multimetallic nanomaterials, yet it is not well understood how immiscible elements distribute in a thermodynamically stable nanoparticle. Herein, we studied the phase-separation of Au and Rh in nanoparticles using electron microscopy and tomography techniques. The nanoparticles were thermally annealed to form thermodynamically stable structures. HAADF-STEM and EDS characterizations reveal that Au and Rh segregate into two domains while their miscibility is increased. Using aberration-corrected HAADF-STEM and atomic electron tomography, we show that the increased solubility of Au in Rh is achieved by forming Au clusters and single atoms inside the Rh domains and on the Rh surface. Furthermore, based on the three-dimensional reconstruction of a AuRh nanoparticle, we can visualize the uneven interface that is embedded in the nanoparticle. The results advance our understanding on the nanoscale thermodynamic behavior of metal mixtures, which is crucial for the optimization of multimetallic nanostructures for many applications.

HIR V2: a human interactome resource for the biological interpretation of differentially expressed genes via gene set linkage analysis.

To facilitate biomedical studies of disease mechanisms, a high-quality interactome that connects functionally related genes is needed to help investigators formulate pathway hypotheses and to interpret the biological logic of a phenotype at the biological process level. Interactions in the updated version of the human interactome resource (HIR V2) were inferred from 36 mathematical characterizations of six types of data that suggest functional associations between genes. This update of the HIR consists of 88 069 pairs of genes (23.2% functional interactions of HIR V2 are in common with the previous version of HIR), representing functional associations that are of strengths similar to those between well-studied protein interactions. Among these functional interactions, 57% may represent protein interactions, which are expected to cover 32% of the true human protein interactome. The gene set linkage analysis (GSLA) tool is developed based on the high-quality HIR V2 to identify the potential functional impacts of the observed transcriptomic changes, helping to elucidate their biological significance and complementing the currently widely used enrichment-based gene set interpretation tools. A case study shows that the annotations reported by the HIR V2/GSLA system are more comprehensive and concise compared to those obtained by the widely used gene set annotation tools such as PANTHER and DAVID. The HIR V2 and GSLA are available at http://human.biomedtzc.cn.

Universal Statistical Laws for the Velocities of Collective Migrating Cells.

Migratory dynamics of collective cells is central to the morphogenesis of biological tissues. The statistical distribution of cell velocities in 2D confluent monolayers is measured through large-scale and long-term experiments of various cell types lying on different substrates. A linear relation is discovered between the variability and the mean of cell speeds during the jamming process of confluent cell monolayers, suggesting time-invariant distribution profile of cell velocities. It is further found that the probability density function of cell velocities obeys the non-canonical q-Gaussian statistics, regardless of cell types and substrate stiffness. It is the Tsallis entropy, instead of the classical Boltzmann-Gibbs entropy, that dictates the universal statistical laws of collective cell migration. The universal statistical law stems from cell-cell interactions, as demonstrated by the wound healing experiments. This previously unappreciated finding provides a linkage between cell-level heterogeneity and tissue-level ensembles in embryonic development and tumor growth.

Predicted rat interactome database and gene set linkage analysis.

Rattus norvegicus, or the rat, has been widely used as animal models for a diversity of human diseases in the last 150 years. The rat, as a disease model, has the advantage of relatively large body size and highly similar physiology to humans. In drug discovery, rat models are routinely used in drug efficacy and toxicity assessments. To facilitate molecular pharmacology studies in rats, we present the predicted rat interactome database (PRID), which is a database of high-quality predicted functional gene interactions with balanced sensitivity and specificity. PRID integrates functional gene association data from 10 public databases and infers 305 939 putative functional associations, which are expected to include 13.02% of all rat protein interactions, and 52.59% of these function associations may represent protein interactions. This set of functional interactions may not only facilitate hypothesis formulation in molecular mechanism studies, but also serve as a reference interactome for users to perform gene set linkage analysis (GSLA), which is a web-based tool to infer the potential functional impacts of a set of changed genes observed in transcriptomics analyses. In a case study, we show that GSLA based on PRID may provide more precise and informative annotations for investigators to understand the physiological mechanisms underlying a phenotype and lead investigators to testable hypotheses for further studies. Widely used functional annotation tools such as Gene Ontology (GO) analysis, and Database for Annotation, Visualization and Integrated Discovery (DAVID) did not provide similar insights. Database URL: http://rat.biomedtzc.cn.