Novel sample treatment method for the determination of free (E)-4-hydroxy-2-nonenal in meat products by liquid chromatography/tandem mass spectrometry using 4-hydroxy-2-nonenal-d3 as internal standard.

RATIONALE: (E)-4-Hydroxy-2-nonenal (HNE) is a reactive secondary product of lipid oxidation with biological significance. The analysis of HNE is a challenge due to its volatility and high activity. Developing sample preparation and analytical tools for the determination of free HNE is crucial for better understanding the actual level of free HNE in meat products. METHODS: Liquid nitrogen freezing, subzero-temperature extraction and derivatization were employed for meat sample treatment. Liquid chromatography/tandem mass spectrometry with electrospray ionization in negative ion mode was used for the determination of free HNE after isotope-coded derivatization. RESULTS: High repeatability and good recoveries with a limit of quantification as low as 0.25 pmol/g were found. Nineteen out of 24 samples, including chilled/processed meat products and meat-based instant foods, were found to contain free HNE with a range of 0.014-1.160 nmol/g. CONCLUSIONS: The proposed method showed satisfactory reliability, sensitivity and accuracy. We believe that such a sample preparation strategy will provide a powerful tool for better understanding the actual level of free HNE in meat products.

[Construction and application of modern research paradigm of new foreign introducing traditional Chinese medicine].

With the development of society, more and more foreign natural medicines have entered China, but they are faced with the problem that they are not given with the traditional Chinese medicine(TCM) properties when they are used with other TCM. When we carried out the research on introducing foreign natural plant resources to TCM, gradually, a new research model and field with original characteristics of TCM--the study of new foreign introducing TCM had been formed. In the process of it, we explored and summarized research rules to form the research paradigm, which will be conducive to the standardization and scientization of new foreign introducing TCM research. For the research of foreign introducing TCM, we analyzed the research background, reviewed the application history, sorted out the research status, elaborated the concept and summarized the research achievements. On this basis, we put forward the concept and system of the modern research paradigm of new foreign introducing TCM, studied and clarified the core elements, properties and research principles of this paradigm, and summarized the research contents and methods of new foreign introducing TCM. We interpreted the foundation of paradigm construction from multiple perspectives. The paradigm was the practical application of theoretical innovation of TCM. Under the guidance of it, more and more varieties of new foreign introducing TCM will be studied, the study will be more standardized, the conclusions will be more scientific and reliable, which will inspire and guide more researchers to focus on the research of new foreign introducing TCM, and the paradigm itself will be constantly improved. The construction and application of the paradigm will certainly accelerate the innovative research of foreign introducing TCM and play a historic role in promoting the enrichment of traditional Chinese medicine varieties.

Deep-learning model for predicting 30-day postoperative mortality.

BACKGROUND: Postoperative mortality occurs in 1-2% of patients undergoing major inpatient surgery. The currently available prediction tools using summaries of intraoperative data are limited by their inability to reflect shifting risk associated with intraoperative physiological perturbations. We sought to compare similar benchmarks to a deep-learning algorithm predicting postoperative 30-day mortality. METHODS: We constructed a multipath convolutional neural network model using patient characteristics, co-morbid conditions, preoperative laboratory values, and intraoperative numerical data from patients undergoing surgery with tracheal intubation at a single medical centre. Data for 60 min prior to a randomly selected time point were utilised. Model performance was compared with a deep neural network, a random forest, a support vector machine, and a logistic regression using predetermined summary statistics of intraoperative data. RESULTS: Of 95 907 patients, 941 (1%) died within 30 days. The multipath convolutional neural network predicted postoperative 30-day mortality with an area under the receiver operating characteristic curve of 0.867 (95% confidence interval [CI]: 0.835-0.899). This was higher than that for the deep neural network (0.825; 95% CI: 0.790-0.860), random forest (0.848; 95% CI: 0.815-0.882), support vector machine (0.836; 95% CI: 0.802-870), and logistic regression (0.837; 95% CI: 0.803-0.871). CONCLUSIONS: A deep-learning time-series model improves prediction compared with models with simple summaries of intraoperative data. We have created a model that can be used in real time to detect dynamic changes in a patient's risk for postoperative mortality.

The influence of ultrasound and adenosine 5'-monophosphate marination on tenderness and structure of myofibrillar proteins of beef

Objective: The aim was to investigate the influence of ultrasound and adenosine 5'-monophosphate (AMP) marination (UAMP) on tenderness and structure of myofibrillar proteins of beef. Methods: Five groups, the untreated meat (Control), deionized water marination (DW), ultrasound followed by DW (UDW), AMP marination (AMP), and ultrasound followed by AMP (UAMP) were studied. Myofibrillar fragmentation, cooking loss, shear force, thermograms, histological observation of meats and myofibrillar proteins properties were investigated in these different treatments. Results: The results showed that UAMP significantly increased MFI from 152 (control), 231 (AMP) and 307 (UDW) to 355 (P < 0.05), respectively. The lowest cooking loss, shear force and peak denaturation temperature were observed in UAMP. In histological observation, UDW and UAMP had more fragmented muscular bundles than the others. Furthermore, a drastic increase in α-helix and decrease in ß-sheet of myofibrillar proteins was observed in UAMP, implying the disaggregation of protein samples. The synchronous fluorescence spectra of myofibrillar proteins in UAMP suggested the combination of ultrasound and AMP could accelerate the unfolding molecular structure and destroying hydrophobic interactions. The results of circular dichroism and synchronous fluorescence spectra for myofibrillar proteins coincided with the microstructures of beef. Conclusion: The results indicate that ultrasound combined with AMP improved meat tenderness not only by disruption in muscle integrity, increasing water retention, but also altering their spatial structure of myofibrillar proteins.

Interaction of Hsp90 with phospholipid model membranes.

Heat shock protein 90 (Hsp90) is an essential molecular chaperone with versatile functions in cell homeostatic control under both normal and stress conditions. Hsp90 has been found to be expressed on the cell surface, but the mechanism of Hsp90 association to the membrane remains obscure. In this study, the direct interaction of Hsp90 and phospholipid vesicles was characterized, and the role of Hsp90 on membrane physical state was explored. Using surface plasmon resonance (SPR), we observed a strong interaction between Hsp90 and different compositions of lipid. Hsp90 had a preference to bind with more unsaturated phospholipid species and the affinity was higher with negatively charged lipids than zwitterionic lipids. Increasing the mole fraction of cholesterol in the phospholipid led to a decrease of binding affinity to Hsp90. Circular dichroism (CD) spectroscopy of Hsp90 in PC membranes showed more α-helix structure than in aqueous buffer. The differential scanning calorimeter (DSC) and fluorescence polarization results showed Hsp90 could affect the transition temperature and fluidity of the bilayer. We postulate from these results that the association between Hsp90 and membranes may involve both electrostatic and hydrophobic force, and constitute a possible mechanism that modulates membrane lipid order during thermal fluctuations.

BoostGAPFILL: improving the fidelity of metabolic network reconstructions through integrated constraint and pattern-based methods.

Motivation: Metabolic network reconstructions are often incomplete. Constraint-based and pattern-based methodologies have been used for automated gap filling of these networks, each with its own strengths and weaknesses. Moreover, since validation of hypotheses made by gap filling tools require experimentation, it is challenging to benchmark performance and make improvements other than that related to speed and scalability. Results: We present BoostGAPFILL, an open source tool that leverages both constraint-based and machine learning methodologies for hypotheses generation in gap filling and metabolic model refinement. BoostGAPFILL uses metabolite patterns in the incomplete network captured using a matrix factorization formulation to constrain the set of reactions used to fill gaps in a metabolic network. We formulate a testing framework based on the available metabolic reconstructions and demonstrate the superiority of BoostGAPFILL to state-of-the-art gap filling tools. We randomly delete a number of reactions from a metabolic network and rate the different algorithms on their ability to both predict the deleted reactions from a universal set and to fill gaps. For most metabolic network reconstructions tested, BoostGAPFILL shows above 60% precision and recall, which is more than twice that of other existing tools. Availability and Implementation: MATLAB open source implementation ( https://github.com/Tolutola/BoostGAPFILL ). Contacts: toyetunde@wustl.edu or muhan@wustl.edu . Supplementary information: Supplementary data are available at Bioinformatics online.

Differential expression of heat shock protein 90, 70, 60 in chicken muscles postmortem and its relationship with meat quality.

OBJECTIVE: The aim of this study was to investigate the expression of heat shock protein (HSP) 90, 70, and 60 in chicken muscles and their possible relationship with quality traits of meat. METHODS: The breast muscles from one hundred broiler chickens were analyzed for drip loss and other quality parameters, and the levels of heat shock protein (HSP) 90, 70, and 60 were determined by immunoblots. RESULTS: Based on the data, chicken breast muscles were segregated into low (drip loss≤5%), intermediate (5%0.05). CONCLUSION: Results of this study suggests that higher levels of HSP90 and HSP60 may be advantageous for maintenance of cell function and reduction of water loss, and they could act as potential indicator for better water holding capacity of meat.

WUFlux: an open-source platform for 13C metabolic flux analysis of bacterial metabolism.

BACKGROUND: Flux analyses, including flux balance analysis (FBA) and 13C-metabolic flux analysis (13C-MFA), offer direct insights into cell metabolism, and have been widely used to characterize model and non-model microbial species. Nonetheless, constructing the 13C-MFA model and performing flux calculation are demanding for new learners, because they require knowledge of metabolic networks, carbon transitions, and computer programming. To facilitate and standardize the 13C-MFA modeling work, we set out to publish a user-friendly and programming-free platform (WUFlux) for flux calculations in MATLAB®. RESULTS: We constructed an open-source platform for steady-state 13C-MFA. Using GUIDE (graphical user interface design environment) in MATLAB, we built a user interface that allows users to modify models based on their own experimental conditions. WUFlux is capable of directly correcting mass spectrum data of TBDMS (N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide)-derivatized proteinogenic amino acids by removing background noise. To simplify 13C-MFA of different prokaryotic species, the software provides several metabolic network templates, including those for chemoheterotrophic bacteria and mixotrophic cyanobacteria. Users can modify the network and constraints, and then analyze the microbial carbon and energy metabolisms of various carbon substrates (e.g., glucose, pyruvate/lactate, acetate, xylose, and glycerol). WUFlux also offers several ways of visualizing the flux results with respect to the constructed network. To validate our model's applicability, we have compared and discussed the flux results obtained from WUFlux and other MFA software. We have also illustrated how model constraints of cofactor and ATP balances influence fluxome results. CONCLUSION: Open-source software for 13C-MFA, WUFlux, with a user-friendly interface and easy-to-modify templates, is now available at http://www.13cmfa.org /or ( http://tang.eece.wustl.edu/ToolDevelopment.htm ). We will continue documenting curated models of non-model microbial species and improving WUFlux performance.

The effect of adenosine 5'-monophosphate (AMP) on tenderness, microstructure and chemical-physical index of duck breast meat.

BACKGROUND: Adenosine 5'-monophosphate (AMP) is often used in meat and poultry soups as a flavor enhancer (flavor modifier), or as food additives for specific nutritional purposes. Our previous research as well as evidence from others showed that actomyosin could be dissociated into myosin and actin by AMP in extracted muscle solution. However, there is no report available on the application of AMP to dissociate actomyosin and to improve meat tenderness. The objectives of this study were to evaluate the effect of AMP on duck meat tenderness and other quality traits and to explore the mechanism of the action of AMP on meat tenderness. RESULTS: Duck breast muscle was treated with 0, 10, 20, 30, 40 mmol L(-1) AMP at 5 °C for 10 h and examined for shear force, microstructure, actomyosin dissociation, myofibril fragmentation index (MFI), pH, water content, cooking loss, CIE* color (L*, a*, b*), inosine monophosphate (IMP) and free amino acid (FAA) contents. Results showed that shear force, cooking loss, L* and b* of the muscles significantly decreased after AMP treatment (P < 0.05); actomyosin dissociation, MFI, pH, water content, fiber diameter, sarcomere length, IMP and ammonia significantly increased (P < 0.05); no significant change in a* or other FAA content was observed (P > 0.05), and muscle shrinkage in transverse and longitudinal directions were restrained after AMP treatment. CONCLUSION: The results suggest that AMP could notably improve meat tenderness, and this effect was probably mainly through increasing muscle pH, promoting actomyosin dissociation and disrupting the Z-line; meanwhile, the conversion of AMP to IMP may contribute to the flavor of meat.

Novel L-lactic acid biosensors based on conducting polypyrrole-block copolymer nanoparticles.

The development of advanced nanomaterials for the highly efficient electrical detection of biological species has attracted great attention. Here, novel polypyrrole-Pluronic F127 nanoparticles (PPy-F127 NPs) with conducting and biocompatibility properties were synthesized and used to construct a L-lactic acid biosensor that could be applied in biochemical assays. The PPy-F127 NPs were characterized by transmission electron microscopy (TEM), elemental analysis and UV-vis spectroscopy. Lactate oxidase (LOx) structure variation on the PPy-F127 NPs was investigated by circular dichroism (CD). The cyclic voltammetric results indicated that LOx immobilized on the PPy-F127 NPs exhibited direct electron transfer reaction with a formal potential value (E(0)') of 0.154 V vs. SCE. Moreover, the biosensor had good electrocatalytic activity toward L-lactic acid with a wide linear range (0.015-37.5 mM) and a low detection limit of 0.0088 mM. The regression equation was I (µA) = 0.02353c (mM) + 1.4135 (R(2) = 0.9939). The L-lactic acid biosensor had a good anti-interference property towards uric acid (UA), ascorbic acid (AA), glucose and cysteine. The idea and method provide a promising platform for the rapid development of biosensors that can be used in the detection of biological species.

Analysis of abietic acid and dehydroabietic acid residues in raw ducks and cooked ducks.

Rosin was once widely used for removal of duck feathers in China and is still being used secretly in some poultry processing enterprises. Abietic acid (AA) and dehydroabietic acid (DHAA) are the major compounds of rosin. In the present study, 90 duck samples were collected for investigation of AA and DHAA residues. Abietic acid and DHAA were simultaneously detected in 13 out 40 raw ducks, 8 out of 26 water-boiled salted ducks, and 7 out of 24 roasted ducks, respectively. In positive samples, averages of AA were significantly higher than those of DHAA in positive samples of the 3 types of ducks (P < 0.05). Averages of AA and DHAA in positive raw ducks were significantly higher than those in positive roasted ducks (P < 0.05). The results indicated that almost one-third of raw ducks were defeathered by means of rosin-containing defeathering agent, and cooking processes could reduce the AA and DHAA residues to some extent, but could not eliminate them completely.

Refining Euclidean Obfuscatory Nodes Helps: A Joint-Space Graph Learning Method for Graph Neural Networks.

Many graph neural networks (GNNs) are inapplicable when the graph structure representing the node relations is unavailable. Recent studies have shown that this problem can be effectively solved by jointly learning the graph structure and the parameters of GNNs. However, most of these methods learn graphs by using either a Euclidean or hyperbolic metric, which means that the space curvature is assumed to be either constant zero or constant negative. Graph embedding spaces usually have nonconstant curvatures, and thus, such an assumption may produce some obfuscatory nodes, which are improperly embedded and close to multiple categories. In this article, we propose a joint-space graph learning (JSGL) method for GNNs. JSGL learns a graph based on Euclidean embeddings and identifies Euclidean obfuscatory nodes. Then, the graph topology near the identified obfuscatory nodes is refined in hyperbolic space. We also present a theoretical justification of our method for identifying obfuscatory nodes and conduct a series of experiments to test the performance of JSGL. The results show that JSGL outperforms many baseline methods. To obtain more insights, we analyze potential reasons for this superior performance.

A study on the catalytic domain of pork phospholipase A2: Enzymatic properties and hydrolysis characteristics of phosphatidylcholine and its hydroperoxide.

Endogenous phospholipase A2 (PLA2) plays an important role in phospholipids degradation during cured meat products manufacturing. The present study was undertaken to reveal more information about the endogenous PLA2 in muscles and its role in degradation of intramuscular phospholipids. With the catalytic domain of pork calcium-independent PLA2 (iPLA2cd), impacts of physic-chemical factors on the activity were investigated and substrate specificity of the enzyme were tested respectively. The optimum temperature and pH of pork iPLA2cd were 40 °C and 7.5, respectively. The iPLA2cd could be stimulated by adequate contents of NaCl and ATP, and inhibited by CaCl2 and NaNO2. For native phospholipids, the iPLA2cd was of a little higher affinity towards phosphatidylcholine (PC) than phosphatidylethanolamine (PE), phosphoserine (PS) and phosphatidylinositol (PI). The iPLA2cd could preferentially hydrolyze peroxidized PC over the native PC. The results would help better understand the degradation of phospholipids and the role played by endogenous enzymes during meat products manufacturing.

The application of large language models in medicine: A scoping review.

This study systematically reviewed the application of large language models (LLMs) in medicine, analyzing 550 selected studies from a vast literature search. LLMs like ChatGPT transformed healthcare by enhancing diagnostics, medical writing, education, and project management. They assisted in drafting medical documents, creating training simulations, and streamlining research processes. Despite their growing utility in assisted diagnosis and improving doctor-patient communication, challenges persisted, including limitations in contextual understanding and the risk of over-reliance. The surge in LLM-related research indicated a focus on medical writing, diagnostics, and patient communication, but highlighted the need for careful integration, considering validation, ethical concerns, and the balance with traditional medical practice. Future research directions suggested a focus on multimodal LLMs, deeper algorithmic understanding, and ensuring responsible, effective use in healthcare.

Effects of different cooking regimes on the microstructure and tenderness of duck breast muscle.

BACKGROUND: Cooking has a great influence on meat tenderness, and we assumed that changes of tenderness in this process resulted from the liberation of actin and associated structural changes. Therefore, in this study, we investigated changes in the microstructure and tenderness when duck breast muscle were cooked to different internal endpoint temperatures (70, 80, 90, 95 °C) by three cooking regimes (conventional cooking, two-stage cooking and three-stage cooking). RESULTS: When duck breast muscle was cooked to an internal endpoint temperature of 70 °C, the three-stage cooking significantly decreased the Meullenet-Owens razor shear force (MORSF) value (P<0.05) and resulted in a longer sarcomere length (P<0.05) compared with the conventional cooking. However, further improvement of the tenderness and an increase in sarcomere length did not occur at higher internal endpoint temperatures. The two-stage cooking regime, with a much longer cooking time below 55 °C, also resulted in a lower MORSF value (P>0.05) and increased sarcomere length (P<0.05) at an internal endpoint temperature of 70 °C compared with the conventional cooking. Significant liberation of actin was also observed in duck meat cooked between 50 and 60 °C. CONCLUSION: The two- and three-stage cooking regimes with initial temperatures of 50-60 °C and endpoint temperature of 70 °C could improve tenderness of duck breast meat, which might be related to the liberation of actin. Three-stage cooking had the great advantages of improving meat tenderness and reducing cooking loss; therefore, this is to be recommended for further application and research.

Evaluation of the growth, adaption, and ecosystem services of two potentially-introduced urban tree species in Guangzhou under drought stress.

Under rapid urbanization and agglomeration of population, cities are facing various environmental challenges. As urban forests play a crucial role in mitigating native environmental problems and providing ecosystem services, cities might enhance their urban forest construction through multiple approaches, of which the introduction of exotic tree species could be an effective way. Under the background of constructing a high-quality forest city, Guangzhou was considering introducing a series of exotic tree species to improve the local urban greening, among which Tilia cordata Mill. and Tilia tomentosa Moench became the potential objects. As Guangzhou was reported to experience higher temperatures with less precipitation and face drought events with increasing frequency and intensity, whether the two tree species could survive in the dry environment required to be investigated profoundly. Thus, we launched a drought-simulation experiment and measured their above- and below-ground growth in 2020. In addition, their ecosystem services were also simulated and evaluated for their future adaption. Furthermore, a congeneric native tree species Tilia miqueliana Maxim was also measured in the same experiment as a comparison. Our results showed that Tilia miqueliana exhibited moderate patterns of growth and advantages in evapotranspiration and cooling. Besides, its investment in root development at horizontal level could account for its special strategy against drought stress. Tilia tomentosa's vigorous root growth could be the most positive behavior of coping with water deficit, which explained its maintenance of carbon fixation and implied a well adaption. Tilia cordata showed a complete decrease in above- and below-ground growth, especially for its fine root biomass. In addition, its ecosystem services were significantly reduced, reflecting a comprehensive failure when it faced a long-term scarcity of water. Therefore, it was necessary to supply sufficient water and under-ground space for their living in Guangzhou, especially for Tilia cordata. In the future, long-time observation of their growth under different stresses can be practical approaches to amplify their multiple ecosystem services.

Prediction and Verification of Potential Therapeutic Targets for Non-Responders to Infliximab in Ulcerative Colitis.

Background: Infliximab (IFX) has been widely used in ulcerative colitis (UC) patients. However, the subsequent effective treatment of IFX non-response in UC patients remains a challenge. This study aims to predict potential therapeutic targets for non-responders by performing a bioinformatic analysis of the data in the Gene Expression Omnibus (GEO) database and validation by biopsies. Methods: Colonic mucosal biopsies expression profiles of IFX-treated UC patients (GSE73661, GSE16879) were utilized to predict potential therapeutic targets. Bioinformatics analyses were used to explore potential biological mechanisms. CytoHubba was performed to screen hub genes. We used a validation dataset and colonic mucosal biopsies of UC patients to validate hub genes. Results: A total of 147 DEGs were identified (119 upregulated genes and 28 downregulated genes). GSEA showed that DEGs in GSE73661 were enriched in the pathways of the cytokine-cytokine receptor, the chemokine, and the adhesion molecules system. Based on the PPI network analysis, we identified four hub genes (and the transcription factor NF-κB). Then, we validate the expression of hub genes by reverse transcription-polymerase chain reaction (RT-PCR). We found higher expression of IL-6, IL1B, CXCL8, and CCL2 in non-responders compared to responders. Conclusion: In summary, four potential targets (IL-6, IL1B, CXCL8, and CCL2) were finally identified by performing a bioinformatics analysis of the datasets in the GEO database. Their expression was confirmed in colonic mucosal biopsies of patients with UC. These results can help to further explore the mechanism of non-responders to IFX in UC and to provide potential targets for their subsequent treatment.

Comparison of biochemical characteristics and gel properties of chicken myofibrillar protein affected by heme-iron and nonheme-iron oxidizing systems.

In this study, the effect of hemin and non-heme iron on the biochemical and gelling properties of chicken myofibrillar protein (MP) was compared. Results revealed that free radicals from hemin incubated MP were significantly higher than that in FeCl3 incubated samples (P < 0.05), and had higher ability to initiate protein oxidation. The carbonyl content, surface hydrophobicity, random coil increased with oxidant concentration, whereas the total sulfhydryl and α-helix content decreased in both oxidizing systems. The turbidity and particle size were increased after oxidant treatment, indicating oxidation promoted the cross-linking and aggregation of protein, and the degree of aggregation was higher in hemin treated MP compared with that incubated with FeCl3. The biochemical changes of MP resulted in an uneven and loose gel network structure, which significantly reduced the gel strength and water holding capacity (WHC) of the gel.

Lipidomic profile changes of yellow-feathered chicken meat during thermal processing based on UPLC-ESI-MS approach.

In this work, ultra-performance liquid chromatography-electrospray ionization mass spectrometry (UPLC-ESI-MS) was applied to compare the lipidomics profile of chicken breast meat heated to various temperatures. A total of 445 lipids including phospholipids, diacylglycerols, triacylglycerols, glycoglycerolipids, and sphingolipids were detected in chicken muscle. Significant decreases in a list of characteristic unsaturated phospholipid species including phosphatidylcholine, phosphatidylethanolamine, phosphatidylglycerol and phosphatidylinositol were identified after heating, suggesting the occurrence of lipid oxidation, while significant increases in characteristic lysophospholipid species were found with increasing heating temperature, which were mainly derived from hydrolysis of phospholipids. Moreover, ether phospholipid and neutral lipid species exhibited remarkable changes during the heating process, and monoalk(en)yl diacylglycerol was first identified in chicken meat. The findings could contribute to the improved understanding of key lipids and biochemical reactions engaged in the heating of meat products.

Highly accurate disease diagnosis and highly reproducible biomarker identification with PathFormer.

Biomarker identification is critical for precise disease diagnosis and understanding disease pathogenesis in omics data analysis, like using fold change and regression analysis. Graph neural networks (GNNs) have been the dominant deep learning model for analyzing graph-structured data. However, we found two major limitations of existing GNNs in omics data analysis, i.e., limited-prediction/diagnosis accuracy and limited-reproducible biomarker identification capacity across multiple datasets. The root of the challenges is the unique graph structure of biological signaling pathways, which consists of a large number of targets and intensive and complex signaling interactions among these targets. To resolve these two challenges, in this study, we presented a novel GNN model architecture, named PathFormer, which systematically integrate signaling network, priori knowledge and omics data to rank biomarkers and predict disease diagnosis. In the comparison results, PathFormer outperformed existing GNN models significantly in terms of highly accurate prediction capability (~30% accuracy improvement in disease diagnosis compared with existing GNN models) and high reproducibility of biomarker ranking across different datasets. The improvement was confirmed using two independent Alzheimer's Disease (AD) and cancer transcriptomic datasets. The PathFormer model can be directly applied to other omics data analysis studies.