Neurovascular Coupling Analysis Based on Multivariate Variational Gaussian Process Convergent Cross-Mapping.

Neurovascular coupling (NVC) provides important insights into the intricate activity of brain functioning and may aid in the early diagnosis of brain diseases. Emerging evidences have shown that NVC could be assessed by the coupling between electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). However, this endeavor presents significant challenges due to the absence of standardized methodologies and reliable techniques for coupling analysis of these two modalities. In this study, we introduced a novel method, i.e., the collaborative multi-output variational Gaussian process convergent cross-mapping (CMVGP-CCM) approach to advance coupling analysis of EEG and fNIRS. To validate the robustness and reliability of the CMVGP-CCM method, we conducted extensive experiments using chaotic time series models with varying noise levels, sequence lengths, and causal driving strengths. In addition, we employed the CMVGP-CCM method to explore the NVC between EEG and fNIRS signals collected from 26 healthy participants using a working memory (WM) task. Results revealed a significant causal effect of EEG signals, particularly the delta, theta, and alpha frequency bands, on the fNIRS signals during WM. This influence was notably observed in the frontal lobe, and its strength exhibited a decline as cognitive demands increased. This study illuminates the complex connections between brain electrical activity and cerebral blood flow, offering new insights into the underlying NVC mechanisms of WM.

Corticospinal and corticoreticulospinal projections benefit motor behaviors in chronic stroke.

After corticospinal tract (CST) stroke, several motor deficits in the upper extremity (UE) emerge, including diminished muscle strength, motor control, and muscle individuation. Both the ipsilesional CST and contralesional corticoreticulospinal tract (CReST) innervate the paretic UE and may have different innervation patterns for the proximal and distal UE segments. These patterns may underpin distinct pathway relationships to separable motor behaviors. In this cross-sectional study of 15 chronic stroke patients and 28 healthy subjects, we examined two key questions: (1) whether segmental motor behaviors differentially relate to ipsilesional CST and contralesional CReST projection strengths, and (2) whether motor behaviors segmentally differ in the paretic UE. We measured strength, motor control, and muscle individuation in a proximal (biceps, BIC) and distal muscle (first dorsal interosseous, FDI) of the paretic UE. We measured the projection strengths of the ipsilesional CST and contralesional CReST to these muscles using transcranial magnetic stimulation (TMS). Stroke subjects had abnormal motor control and muscle individuation despite strength comparable to healthy subjects. In stroke subjects, stronger ipsilesional CST projections were linked to superior motor control in both UE segments, whereas stronger contralesional CReST projections were linked to superior muscle strength and individuation in both UE segments. Notably, both pathways also shared associations with behaviors in the proximal segment. Motor control deficits were segmentally comparable, but muscle individuation was worse for distal motor performance. These results suggest that each pathway has specialized contributions to chronic motor behaviors but also work together, with varying levels of success in supporting chronic deficits. Key points summary: Individuals with chronic stroke typically have deficits in strength, motor control, and muscle individuation in their paretic upper extremity (UE). It remains unclear how these altered behaviors relate to descending motor pathways and whether they differ by proximal and distal UE segment.In this study, we used transcranial magnetic stimulation (TMS) to examine projection strengths of the ipsilesional corticospinal tract (CST) and contralesional corticoreticulospinal tract (CReST) with respect to quantitated motor behaviors in chronic stroke.We found that stronger ipsilesional CST projections were associated with better motor control in both UE segments, whereas stronger contralesional CReST projections were associated with better strength and individuation in both UE segments. In addition, projections of both pathways shared associations with motor behaviors in the proximal UE segment.We also found that deficits in strength and motor control were comparable across UE segments, but muscle individuation was worse with controlled movement in the distal UE segment.These results suggest that the CST and CReST have specialized contributions to chronic motor behaviors and also work together, although with different degrees of efficacy.

Enhancing cross-subject EEG emotion recognition through multi-source manifold metric transfer learning.

Transfer learning (TL) has demonstrated its efficacy in addressing the cross-subject domain adaptation challenges in affective brain-computer interfaces (aBCI). However, previous TL methods usually use a stationary distance, such as Euclidean distance, to quantify the distribution dissimilarity between two domains, overlooking the inherent links among similar samples, potentially leading to suboptimal feature mapping. In this study, we introduced a novel algorithm called multi-source manifold metric transfer learning (MSMMTL) to enhance the efficacy of conventional TL. Specifically, we first selected the source domain based on Mahalanobis distance to enhance the quality of the source domains and then used manifold feature mapping approach to map the source and target domains on the Grassmann manifold to mitigate data drift between domains. In this newly established shared space, we optimized the Mahalanobis metric by maximizing the inter-class distances while minimizing the intra-class distances in the target domain. Recognizing that significant distribution discrepancies might persist across different domains even on the manifold, to ensure similar distributions between the source and target domains, we further imposed constraints on both domains under the Mahalanobis metric. This approach aims to reduce distributional disparities and enhance the electroencephalogram (EEG) emotion recognition performance. In cross-subject experiments, the MSMMTL model exhibits average classification accuracies of 88.83 % and 65.04 % for SEED and DEAP, respectively, underscoring the superiority of our proposed MSMMTL over other state-of-the-art methods. MSMMTL can effectively solve the problem of individual differences in EEG-based affective computing.

Exploring the Prospects of Transcranial Electrical Stimulation (tES) as a Therapeutic Intervention for Post-Stroke Motor Recovery: A Narrative Review.

INTRODUCTION: Stroke survivors often have motor impairments and related functional deficits. Transcranial Electrical Stimulation (tES) is a rapidly evolving field that offers a wide range of capabilities for modulating brain function, and it is safe and inexpensive. It has the potential for widespread use for post-stroke motor recovery. Transcranial Direct Current Stimulation (tDCS), Transcranial Alternating Current Stimulation (tACS), and Transcranial Random Noise Stimulation (tRNS) are three recognized tES techniques that have gained substantial attention in recent years but have different mechanisms of action. tDCS has been widely used in stroke motor rehabilitation, while applications of tACS and tRNS are very limited. The tDCS protocols could vary significantly, and outcomes are heterogeneous. PURPOSE: the current review attempted to explore the mechanisms underlying commonly employed tES techniques and evaluate their prospective advantages and challenges for their applications in motor recovery after stroke. CONCLUSION: tDCS could depolarize and hyperpolarize the potentials of cortical motor neurons, while tACS and tRNS could target specific brain rhythms and entrain neural networks. Despite the extensive use of tDCS, the complexity of neural networks calls for more sophisticated modifications like tACS and tRNS.

Analyst optimism, information disclosure, and stock price collapse risk: Empirical insights from China's A-share market.

This study selects stock data of listed companies in China's A-share stock market from 2011 to 2020 as research samples. Using a fixed-effects model, it examines the impact of analyst optimism on stock price collapses and the moderating effect of information disclosure quality. Simultaneously, it conducts additional research to explore the potential transmission mechanisms involved. The main findings are as follows: Firstly, a positive correlation exists between analyst optimism and the risk of stock price collapse. Secondly, improving information disclosure quality of listed companies can enhance the positive impact of analyst optimism on the risk of stock price collapses and expedite the market's adjustment of overly optimistic valuations of listed companies. Additionally, analyst optimism can increase the risk of stock price collapses by affecting institutional ownership. These findings provide theoretical support for regulatory authorities to revise and improve the "information disclosure evaluation" system, regulate the analyst industry, guide analyst behavior, and encourage listed companies to enhance internal governance and improve information disclosure practices.

Comparison of ureteral stone measurements for predicting the efficacy of a single session of extracorporeal shockwave lithotripsy: one-, two-, and three-dimensional computed tomography measurements.

The objective of this study was to compare the value of one-, two- and three-dimensional computed tomography (CT) measurements for predicting the efficacy of a single session of extracorporeal shock wave lithotripsy (ESWL) in patients with a single ureteral stone. A total of 165 patients were included based on the inclusion and exclusion criteria. Different models were constructed using a combination of patients' clinical data and measurements obtained by manual sketching and automated extraction software. Multivariate logistic regression was used to develop the models. Receiver operating characteristic curves were used to assess the performance of the models. There was good interobserver agreement for all measurements in different dimensions (P < 0.001). We also found that hydronephrosis, the largest diameter, the largest area, volume, and mean CT value were significantly greater in the failure group than in the success group (P < 0.01). Furthermore, all sizes and CT measurement values were found to be independent predictors for predicting efficacy after one session of ESWL (P < 0.05). In addition, the multivariate logistic analysis showed that the area under the curve (AUC) for two-dimensional and three-dimensional measurements was superior to that of one-dimensional measurement (P < 0.01). However, when size alone was included as a measurable predictor, there was no significant difference in the AUC among the one-, two-, and three-dimensional measurements (P > 0.05). In summary, after adjusting for clinical data, two- and three-dimensional measurements combining ureteral stone size and CT values were found to be the best predictors of ESWL efficacy, and software-based three-dimensional measurements should be considered to avoid interobserver variability in clinical practice.

Examining the wound healing potential of curcumin-infused electrospun nanofibers from polyglutamic acid and gum arabic.

Advancements in medicine have led to continuous enhancements and innovations in wound dressing materials, making them pivotal in medical care. We used natural biological macromolecules, γ-polyglutamic acid and gum arabic as primary raw materials to create nanofibers laden with curcumin by blending electrostatic spinning technology in the current investigation. These nanofibers were meticulously characterized using fluorescence microscopy, scanning electron microscopy, Fourier transform infrared (FTIR) spectroscopy, differential scanning calorimetry (DSC), and X-ray diffraction (XRD). Our comprehensive analyses confirmed the successful encapsulation of curcumin within the nanofiber carrier and it has uniform diameter, good water absorption and mechanical properties. Subsequently, we evaluated the antimicrobial effects of these curcumin-loaded nanofibers against Staphylococcus aureus through an oscillating flask method. We created a mouse model with acute full-thickness skin defects to further investigate the wound healing potential. We conducted various biochemical assays to elucidate the mechanism of action. The results revealed that curcumin nanofibers profoundly impacted wound healing. They bolstered the expression of TGF-ß1 and VEGF and reduced the expression of inflammatory factors, leading to an accelerated re-epithelialization process, enhanced wound contraction, and increased regeneration of new blood vessels and hair follicles. Furthermore, these nanofibers positively influenced the proportion of three different collagen types. This comprehensive study underscores the remarkable potential of curcumin-loaded nanofibers to facilitate wound healing and lays a robust experimental foundation for developing innovative, natural product-based wound dressings.

Fraxin Ameliorates Ulcerative Colitis by Modulating Oxidative Stress, Inflammation and TLR4/NF-κB and MAPK Signaling Pathways.

Objective: UC is a chronic gastrointestinal disorder of uncertain etiology. However, effective therapeutic drug options for UC are relatively limited. Fraxin represents a principal active constituent within the traditional Chinese medicinal herb known as Cortex Fraxini or Qinpi. Nevertheless, the impact of Fraxin on UC remains uncharted. This study aims to explore the potential of Fraxin, a key component of Cortex Fraxini, in inhibiting DSS-induced intestinal inflammation in mice and to unravel the underlying mechanisms. Methods: In vitro experiment,the RAW264. 7 cells were induced by LPS as the model.In vivo experiment,the mice were induced by DSS as the animal model for a ten day experiment.The ELISA, western blots, measurement of oxidative stress markers and other relevant methods were used to discuss the effect of Fraxin on LPS-induced RAW264.7 cells and the inhibitory effect of Fraxin on intestinal inflammation induced by DSS in mice and underlying mechanisms. Results: Our findings indicated that Fraxin significantly reduced symptoms of UC, such as body weight loss, colonic length shortening, and histological damage. At the molecular level, it inhibited ROS generation, reduced pro-inflammatory cytokines, and regulated key pathways including TLR4/NF-κB and MAPK.The findings indicated that Fraxin diminished the expression of p-NF-κB and p-IκB, downregulated iNOS and COX-2 expression, and lessened p38, JNK and ERK phosphorylation. Conclusion: Taken together, Fraxin ameliorates UC by regulating oxidative stress, inflammation, and TLR4/NF-κB and MAPK pathways, and Fraxin may be a new treatment for UC. Our findings suggest that Fraxin could offer a novel therapeutic approach for UC, targeting oxidative stress and key inflammatory pathways.

CD19/CD20 dual-targeted chimeric antigen receptor-engineered natural killer cells exhibit improved cytotoxicity against acute lymphoblastic leukemia.

BACKGROUND: Chimeric antigen receptor natural killer (CAR-NK) cells represent a promising advancement in CAR cell therapy, addressing limitations observed in CAR-T cell therapy. However, our prior study revealed challenges in CAR-NK cells targeting CD19 antigens, as they failed to eliminate CD19+ Raji cells in NSG tumor-bearing mice, noting down-regulation or loss of CD19 antigen expression in some Raji cells. In response, this study aims to enhance CD19 CAR-NK cell efficacy and mitigate the risk of tumor recurrence due to target antigen escape by developing CD19 and CD20 (CD19/CD20) dual-targeted CAR-NK cells. METHODS: Initially, mRNA encoding anti-CD19 CARs (FMC63 scFv-CD8α-4-1BB-CD3ζ) and anti-CD20 CARs (LEU16 scFv-CD8α-4-1BB-CD3ζ) was constructed via in vitro transcription. Subsequently, CD19/CD20 dual-targeted CAR-NK cells were generated through simultaneous electrotransfection of CD19/CD20 CAR mRNA into umbilical cord blood-derived NK cells (UCB-NK). RESULTS: Following co-electroporation, the percentage of dual-CAR expression on NK cells was 86.4% ± 1.83%, as determined by flow cytometry. CAR expression was detectable at 8 h post-electric transfer, peaked at 24 h, and remained detectable at 96 h. CD19/CD20 dual-targeted CAR-NK cells exhibited increased specific cytotoxicity against acute lymphoblastic leukemia (ALL) cell lines (BALL-1: CD19+CD20+, REH: CD19+CD20-, Jurkat: CD19-CD20-) compared to UCB-NK, CD19 CAR-NK, and CD20 CAR-NK cells. Moreover, CD19/CD20 dual-targeted CAR-NK cells released elevated levels of perforin, IFN-γ, and IL-15. Multiple activation markers such as CD69 and cytotoxic substances were highly expressed. CONCLUSIONS: The creation of CD19/CD20 dual-targeted CAR-NK cells addressed the risk of tumor escape due to antigen heterogeneity in ALL, offering efficient and safe 'off-the-shelf' cell products. These cells demonstrate efficacy in targeting CD20 and/or CD19 antigens in ALL, laying an experimental foundation for their application in ALL treatment.

Optimization of ultrasound-assisted extraction of Imperata cylindrica polysaccharides and evaluation of its anti-oxidant and amelioration of uric acid stimulated cell apoptosis.

An efficient, cost-effective and environmentally friendly ultrasound-assisted hot water method for Imperata cylindrica polysaccharide (ICPs) extraction was developed. According to the response surface results, the optimal ultrasonic time was 85 min, ultrasonic power was 192.75 W, temperature was 90.74 °C, liquid-solid ratio was 26.1, and polysaccharide yield was 28.50 %. The polysaccharide mainly consisted of arabinose (Ara), galactose (Gal), and glucose (Glc), with a molecular weight of 62.3 kDa. Ultrasound-assisted extraction of Imperata cylindrica polysaccharide (UICP) exhibited stronger anti-oxidant activity and ability to ameliorate cellular damage due to uric acid stimulation compared with traditional hot water extraction of Imperata cylindrica polysaccharide (ICPC-b). It also exhibited higher thermal stability, indicating its potential value for applications in the food industry.

Development and validation of a general-purpose ReaxFF reactive force field for earth material modeling.

ReaxFF reactive force field bridges the gap between nonreactive molecular simulations and quantum mechanical calculations and has been widely applied during the past two decades. However, its application to earth materials, especially those under high T-P conditions relevant to Earth's interior, is still limited due to the lack of available parameters. Here, we present the development and validation of a ReaxFF force field containing several of the most common elements in Earth's crust, i.e., Si/Al/O/H/Na/K. The force field was trained against a large data set obtained from density functional theory (DFT) calculations, including charges, bond/angle distortion curves, equation of states, ion migration energy profiles, and condensation reaction energies. Different coordination environments were considered in the training set. The fitting results showed that the current force field can well reproduce the DFT data (the Pearson correlation coefficient, Rp, is 0.95). We validated the force field on mineral-water interfaces, hydrous melts/supercritical geofluids, and bulk crystals. It was found that the current force field performed excellently in predicting the structural, thermodynamic, and transport properties of various systems (Rp = 0.95). Moreover, possible applications and future development have been discussed. The results obtained in this study suggest that the current force field holds good promise to model a wide range of processes and thus open opportunities to advance the application of ReaxFF in earth material modeling.

Three-stage transfer learning for motor imagery EEG recognition.

Motor imagery (MI) paradigms have been widely used in neural rehabilitation and drowsiness state assessment. The progress in brain-computer interface (BCI) technology has emphasized the importance of accurately and efficiently detecting motor imagery intentions from electroencephalogram (EEG). Despite the recent breakthroughs made in developing EEG-based algorithms for decoding MI, the accuracy and efficiency of these models remain limited by technical challenges posed by cross-subject heterogeneity in EEG data processing and the scarcity of EEG data for training. Inspired by the optimal transport theory, this study aims to develop a novel three-stage transfer learning (TSTL) method, which uses the existing labeled data from a source domain to improve classification performance on an unlabeled target domain. Notably, the proposed method comprises three components, namely, the Riemannian tangent space mapping (RTSM), source domain transformer (SDT), and optimal subspace mapping (OSM). The RTSM maps a symmetric positive definite matrix from the Riemannian space to the tangent space to minimize the marginal probability distribution drift. The SDT transforms the source domain to a target domain by finding the optimal transport mapping matrix to reduce the joint probability distribution differences. The OSM finally maps the transformed source domain and original target domain to the same subspace to further mitigate the distribution discrepancy. The performance of the proposed method was validated on two public BCI datasets, and the average accuracy of the algorithm on two datasets was 72.24% and 69.29%. Our results demonstrated the improved performance of EEG-based MI detection in comparison with state-of-the-art algorithms.

Comprehensive molecular analyses of a 7-m6A-related lncRNAs signature for prognosis, tumor immunity and therapeutic effect in patients with hepatocellular carcinoma.

Hepatocellular carcinoma is the most common form of liver tumor. m6A modification and noncoding RNA show indispensable roles in HCC. We sought to establish and verify an appropriate m6A-related long noncoding RNA prognostic tool for predicting hepatocellular carcinoma progression. We extracted the RNA expression levels and the clinicopathologic data from GTEx and TCGA databases. Multivariate Cox regression analysis and receiver operating characteristic curves were performed to test the model's predictive ability. We further built a nomogram for overall survival according to the risk score and clinical features. A competing endogenous RNA network and Gene Ontology assessment were implemented to identify related biological mechanisms and processes. By bioinformatics analysis, a risk model comprising GABPB1-AS1, AC025580.1, LINC01358, AC026356.1, AC009005.1, HCG15, and AC026368.1 was built to offer a prognostic prediction for hepatocellular carcinoma independently. The prognostic tool could better prognosticate hepatocellular carcinoma patients' survival than other clinical characteristics. Then, a nomogram with risk score and clinical characteristics was created, which had strong power to calculate the survival probability in hepatocellular carcinoma. The immune-associated processes involving the differentially expressed genes between the two subgroups were displayed. Analyses of prognosis, clinicopathological characteristics, tumor mutation burden, immune checkpoint molecules, and drug response showed significant differences among the two risk subtypes, hinting that the model could appraise the efficacy of immunotherapy and chemotherapy. The tool can independently predict the prognosis in patients with hepatocellular carcinoma, which benefits drug selection in hepatocellular carcinoma patients.

Exposure to bisphenol A affects transcriptome-wide N6-methyladenine methylation in ovarian granulosa cells.

Bisphenol A (BPA) is an endocrine disruptor of potential reproductive toxicities. Increasingly research elucidated that BPA exposure to the environment would change the epigenetic modifications of transcriptome, but the mechanism by which BPA affects m6A methylation in interfering with female reproductive health remains uncertain. Therefore, this study preliminarily proposed and tested the hypothesis that BPA exposure alters the m6A modification level in transcripts in female ovarian granulosa cells. After BPA was exposed to granulosa cells for 24 h, RNA methylation related regulatory genes (such as METTL3, METTL14, ALKBH5, FTO) and the global m6A levels showed significant differences. Next, we applied MERIP-seq analysis to obtain information on the genome-wide m6A modification changes and identified 1595 differentially methylated mRNA transcripts, and 50 differentially methylated lncRNA transcripts. Further joint analysis of gene common expression showed that 33 genes were hypermethylated and up-regulated, 71 were hypermethylated and down-regulated, 49 were hypomethylated and up-regulated, and 20 were hypomethylated and down-regulated. Enriched Gene Ontology (GO) and biological pathway analysis revealed that these unique genes were mainly enriched in lipid metabolism, cell proliferation, and apoptosis related pathways. Six of these genes (mRNAs IMPA1, MCOLN1, DCTN3, BRCA2, and lncRNAs MALAT1, XIST) were validated using RT-qPCR and IGV software. Through comprehensive analysis of epitranscriptome and protein-protein interaction (PPI) data, lncRNAs MALAT1 and XIST are expected to serve as new markers for BPA interfering with the female reproductive system. In brief, these data show a novel and necessary connection between the damage of BPA exposure on female ovarian granulosa cells and RNA methylation modification.

Ultrasonic-assisted synthesis of lignin-based ultrasmall silver nanoparticles for photothermal-mediated sterilization.

Lignin-based silver nanoparticles have been considered a promising antimicrobial material. However, it remains challenging to prepare ultra-small size silver nanoparticles sustainably with superior antibacterial performance. In this work, we modified ethanol-extracted lignin (EL) with carboxymethyl groups and further synthesized ultra-small particle size (3.8 ± 0.1 nm) nanosilver incorporated carboxymethyl lignin complexes (AgNPs@CEL) using ultrasonic technology. Due to the outstanding antibacterial properties of the ultra-small size nanosilver, AgNPs@CEL could cause 5.3 and 5.4 log10 CFU/mL reduction against E. coli and S. aureus in 5 min. Meanwhile, AgNPs@CEL exhibited remarkable photothermal antibacterial performance, which caused 6.2 and 6.1 log10 CFU/mL reduction of E. coli and S. aureus, with NIR irradiation for 5 min. Furthermore, the composite films prepared by doping only 0.5 wt% AgNPs@CEL into ethyl cellose could achieve a bactericidal rate more than 99.99 %. This study provides a new insight into design of controlled particle size lignin-based antibacterial nanosilver materials in a sustainable manner and holds promise for applications in antibacterial fields.

Ultrasonographic changes and impact factors of diaphragmatic function in patients with obstructive sleep apnea-hypopnea syndrome.

PURPOSE: Diaphragmatic impairment has been reported in obstructive sleep apnea-hypopnea syndrome (OSAHS) patients. However, the risk factors of diaphragmatic dysfunction are unclear. This study was conducted to evaluate the diaphragmatic function and to investigate impact factors of ultrasonographic changes of the diaphragm in OSAHS patients. METHODS: This cross-sectional study recruited 150 snoring patients. All patients were divided into the control group (AHI < 5/h, n = 20), the mild-to-moderate OSAHS group (5/h ≤ AHI ≤ 30/h, n = 61), and the severe OSAHS group (AHI > 30/h, n = 69). Diaphragmatic thickness at function residual capacity (TFRC) and total lung capacity (TTLC) were measured by two-dimensional ultrasound, and the diaphragmatic excursion during tidal and deep breath was measured by M-mode ultrasound. The diaphragmatic thickening fraction (TF) was calculated. Spearman analysis and multiple linear stepwise regression analysis were conducted to analyze the impact factors of diaphragmatic function. RESULTS: TFRC in the control group, mild-to-moderate OSAHS group, and severe OSAHS group was 1.23 (1.10, 1.39) mm, 1.60 (1.43, 1.85) mm, and 1.90 (1.70, 2.25) mm; TTLC was 2.75 (2.53, 2.93) mm, 3.25 (2.90, 3.55) mm, and 3.60 (3.33, 3.90) mm, and TF was 119.23% (102.94, 155.97), 96.55% (74.34, 119.11), and 85.29% (60.68,101.22). There were across-group significant differences in TFRC, TTLC, and TF (P < 0.05). The oxygen desaturation index was the influencing factor of TFRC, TTLC, and TF (P < 0.05). CONCLUSION: The diaphragm is thickened and diaphragmatic contractility is decreased in OSAHS patients. Nocturnal intermittent hypoxia is a risk factor for diaphragmatic hypertrophy and impaired diaphragmatic contractility.

GINv2.0: a comprehensive topological network integrating molecular interactions from multiple knowledge bases.

Knowledge bases have been instrumental in advancing biological research, facilitating pathway analysis and data visualization, which are now widely employed in the scientific community. Despite the establishment of several prominent knowledge bases focusing on signaling, metabolic networks, or both, integrating these networks into a unified topological network has proven to be challenging. The intricacy of molecular interactions and the diverse formats employed to store and display them contribute to the complexity of this task. In a prior study, we addressed this challenge by introducing a "meta-pathway" structure that integrated the advantages of the Simple Interaction Format (SIF) while accommodating reaction information. Nevertheless, the earlier Global Integrative Network (GIN) was limited to reliance on KEGG alone. Here, we present GIN version 2.0, which incorporates human molecular interaction data from ten distinct knowledge bases, including KEGG, Reactome, and HumanCyc, among others. We standardized the data structure, gene IDs, and chemical IDs, and conducted a comprehensive analysis of the consistency among the ten knowledge bases before combining all unified interactions into GINv2.0. Utilizing GINv2.0, we investigated the glycolysis process and its regulatory proteins, revealing coordinated regulations on glycolysis and autophagy, particularly under glucose starvation. The expanded scope and enhanced capabilities of GINv2.0 provide a valuable resource for comprehensive systems-level analyses in the field of biological research. GINv2.0 can be accessed at: https://github.com/BIGchix/GINv2.0 .