The biological characteristics of long cell-free DNA in spent embryos culture medium as noninvasive biomarker in in-vitro embryo selection.

An improved understanding of the cfDNA fragmentomics has proved it as a promising biomarker in clinical applications. However, biological characteristics of cfDNA in spent embryos culture medium (SECM) remain unsolved obstacles before the application in non-invasive in-vitro embryo selection. In this study, we developed a Tn5 transposase and ligase integrated dual-library construction sequencing strategy (TDual-Seq) and revealed the fragmentomic profile of cfDNA of all sizes in early embryonic development. The detected ratio of long cfDNA (>500 bp) was improved from 4.23 % by traditional NGS to 12.80 % by TDual-Seq. End motif analysis showed long cfDNA molecules have a more dominance of fragmentation intracellularly in apoptotic cells with higher predominance of G-end, while shorter cfDNA undergo fragmentation process both intracellularly and extracellularly. Moreover, the mutational pattern of cfDNA and the correlated GO biological process were well differentiated in cleavage and blastocyst embryos. Finally, we developed a multiparametric index (TQI) that employs the fragmentomic profiles of cfDNA, and achieved an area under the ROC curve of 0.927 in screening top quality embryos. TDual-Seq strategy has facilitated characterizing the fragmentomic profile of cfDNA of all sizes in SECM, which are served as a class of non-invasive biomarkers in the evaluation of embryo quality in in-vitro fertilization. And this improved strategy has opened up potential clinical utilities of long cfDNA analysis.

Transcriptome Study of rd1Mouse Brain and Association with Parkinson's Disease.

Degeneration of the retina is intrinsically associated with the pathogenesis and progression of neurodegenerative diseases. However, the cellular and molecular mechanisms underlying the association between neurodegeneration and retinal degeneration are still under exploration due to the complexity of the connectivity network of the nervous system. In this study, RNA-seq data from the brains of model retinitis pigmentosa (RP) mice and previously studied Parkinson's disease (PD) mice were analyzed to explore the commonalities between retinal degenerative and neurodegenerative diseases. Differentially expressed genes in RP were compared with neurodegenerative disease-related genes and intersecting genes were identified, including Cnr1 and Septin14. These genes were verified by quantitative real-time reverse transcription PCR and Western blotting experiments. The key proteins CNR1 and SEPTIN14 were found to be potential cotherapeutic targets for retinal degeneration and neurodegenerative disease. In conclusion, understanding the commonalities between retinal degenerative diseases and neurodegenerative processes in the brain will not only facilitate the interpretation of the underlying pathomechanisms but also contribute to early diagnosis and the development of new therapeutic strategies.

Anion Modulation of Ag-Imidazole Cuboctahedral Cage Microenvironments for Efficient Electrocatalytic CO2 Reduction.

How to achieve CO2 electroreduction in high efficiency is a current challenge with the mechanism not well understood yet. The metal-organic cages with multiple metal sites, tunable active centers, and well-defined microenvironments may provide a promising catalyst model. Here, we report self-assembly of Ag4L4 type cuboctahedral cages from coordination dynamic Ag+ ion and triangular imidazolyl ligand 1,3,5-tris(1-benzylbenzimidazol-2-yl) benzene (Ag-MOC-X, X=NO3, ClO4, BF4) via anion template effect. Notably, Ag-MOC-NO3 achieves the highest CO faradaic efficiency in pH-universal electrolytes of 86.1 % (acidic), 94.1 % (neutral) and 95.3 % (alkaline), much higher than those of Ag-MOC-ClO4 and Ag-MOC-BF4 with just different counter anions. In situ attenuated total reflection Fourier transform infrared spectroscopy observes formation of vital intermediate *COOH for CO2-to-CO conversion. The density functional theory calculations suggest that the adsorption of CO2 on unsaturated Ag-site is stabilized by C-H⋅⋅⋅O hydrogen-bonding of CO2 in a microenvironment surrounded by three benzimidazole rings, and the activation of CO2 is dependent on the coordination dynamics of Ag-centers modulated by the hosted anions through Ag⋅⋅⋅X interactions. This work offers a supramolecular electrocatalytic strategy based on Ag-coordination geometry and host-guest interaction regulation of MOCs as high-efficient electrocatalysts for CO2 reduction to CO which is a key intermediate in chemical industry process.

Theoretical comparison of fructose with methylglucoside for the production of formate and levulinate catalyzed by Brønsted acids in a methanol solution.

For the conversion of fructose/methylglucoside (MG) into both methyl formate (MF) and methyl levulinate (MLev), the C-source of formate [HCOO]- remains unclear at the molecular level. Herein, reaction mechanisms catalyzed by [CH3OH2]+ in a methanol solution were theoretically investigated at the PBE0/6-311++G(d,p) level. For the conversion of fructose into MF and MLev, the formate [HCOO]- comes from the C1-atom of fructose, in which the rate-determining step lies in the reaction of 5-hydroxymethylfurfural (HMF) with CH3OH to yield MF and MLev. The reaction of fructose with CH3OH kinetically tends to generate HMF intermediates rather than yield (MF + MLev). When MG is dissolved in a methanol solution, its O2, O3, and O4 atoms are closer to the first layer of the solvent than O1, O5, and O6 atoms. For the dehydration of MG with methanol into MF and MLev, the formate [HCOO]- stems from the dominant C1- and secondary C3-atoms of MG. Kinetically, MG is ready to yield (MF + MLev), whereas fructose can induce the reaction to remain at the HMF intermediate, inhibiting the further conversion of HMF with CH3OH into MF and MLev. If MG isomerizes into fructose, the reaction will be more preferable for yielding HMF rather than (MF + MLev).

Transcriptomic and neuroimaging data integration enhances machine learning classification of schizophrenia.

Background: Schizophrenia is a polygenic disorder associated with changes in brain structure and function. Integrating macroscale brain features with microscale genetic data may provide a more complete overview of the disease etiology and may serve as potential diagnostic markers for schizophrenia. Objective: We aim to systematically evaluate the impact of multi-scale neuroimaging and transcriptomic data fusion in schizophrenia classification models. Methods: We collected brain imaging data and blood RNA sequencing data from 43 patients with schizophrenia and 60 age- and gender-matched healthy controls, and we extracted multi-omics features of macroscale brain morphology, brain structural and functional connectivity, and gene transcription of schizophrenia risk genes. Multi-scale data fusion was performed using a machine learning integration framework, together with several conventional machine learning methods and neural networks for patient classification. Results: We found that multi-omics data fusion in conventional machine learning models achieved the highest accuracy (AUC ~0.76-0.92) in contrast to the single-modality models, with AUC improvements of 8.88 to 22.64%. Similar findings were observed for the neural network, showing an increase of 16.57% for the multimodal classification model (accuracy 71.43%) compared to the single-modal average. In addition, we identified several brain regions in the left posterior cingulate and right frontal pole that made a major contribution to disease classification. Conclusion: We provide empirical evidence for the increased accuracy achieved by imaging genetic data integration in schizophrenia classification. Multi-scale data fusion holds promise for enhancing diagnostic precision, facilitating early detection and personalizing treatment regimens in schizophrenia.

Effect of Different Staining Methods on Brain Cryosections.

Staining frozen sections is often required to distinguish cell types for spatial transcriptomic studies of the brain. The impact of the staining methods on the RNA integrity of the cells becomes one of the limitations of spatial transcriptome technology with microdissection. However, there is a lack of systematic comparisons of different staining modalities for the pretreatment of frozen sections of brain tissue as well as their effects on transcriptome sequencing results. In this study, four different staining methods were analyzed for their effect on RNA integrity in frozen sections of brain tissue. Subsequently, differences in RNA quality in frozen sections under different staining conditions and their impact on transcriptome sequencing results were assessed by RNA-seq. As one of the most commonly used methods for staining pathological sections, HE staining seriously affects the RNA quality of frozen sections of brain tissue. In contrast, the homemade cresyl violet staining method developed in this study has the advantages of short staining time, low cost, and less RNA degradation. The homemade cresyl violet staining proposed in this study can be applied instead of HE staining as an advance staining step for transcriptome studies in frozen sections of brain tissue. In the future, this staining method may be suitable for wide application in brain-related studies of frozen tissue sections. Moreover, it is expected to become a routine step for staining cells before sampling in brain science.

From genetic associations to genes: methods, applications, and challenges.

Genome-wide association studies (GWASs) have identified numerous genetic loci associated with human traits and diseases. However, pinpointing the causal genes remains a challenge, which impedes the translation of GWAS findings into biological insights and medical applications. In this review, we provide an in-depth overview of the methods and technologies used for prioritizing genes from GWAS loci, including gene-based association tests, integrative analysis of GWAS and molecular quantitative trait loci (xQTL) data, linking GWAS variants to target genes through enhancer-gene connection maps, and network-based prioritization. We also outline strategies for generating context-dependent xQTL data and their applications in gene prioritization. We further highlight the potential of gene prioritization in drug repurposing. Lastly, we discuss future challenges and opportunities in this field.

Characterization of acute-on-chronic liver diseases: A multicenter prospective cohort study.

BACKGROUND: Acute-on-chronic liver disease (AoCLD) accounts for the majority of patients hospitalized in the Department of Hepatology or Infectious Diseases. AIM: To explore the characterization of AoCLD to provide theoretical guidance for the accurate diagnosis and prognosis of AoCLD. METHODS: Patients with AoCLD from the Chinese Acute-on-Chronic Liver Failure (ACLF) study cohort were included in this study. The clinical characteristics and outcomes, and the 90-d survival rate associated with each clinical type of AoCLD were analyzed, using the Kaplan-Meier method and the log-rank test. RESULTS: A total of 3375 patients with AoCLD were enrolled, including 1679 (49.7%) patients with liver cirrhosis acute decompensation (LC-AD), 850 (25.2%) patients with ACLF, 577 (17.1%) patients with chronic hepatitis acute exacerbation (CHAE), and 269 (8.0%) patients with liver cirrhosis active phase (LC-A). The most common cause of chronic liver disease (CLD) was HBV infection (71.4%). The most common precipitants of AoCLD was bacterial infection (22.8%). The 90-d mortality rates of each clinical subtype of AoCLD were 43.4% (232/535) for type-C ACLF, 36.0% (36/100) for type-B ACLF, 27.0% (58/215) for type-A ACLF, 9.0% (151/1679) for LC-AD, 3.0% (8/269) for LC-A, and 1.2% (7/577) for CHAE. CONCLUSION: HBV infection is the main cause of CLD, and bacterial infection is the main precipitant of AoCLD. The most common clinical type of AoCLD is LC-AD. Early diagnosis and timely intervention are needed to reduce the mortality of patients with LC-AD or ACLF.

Prediction of Transcription Factor Binding Sites on Cell-Free DNA Based on Deep Learning.

Transcription factors (TFs) are important regulatory elements for vital cellular activities, and the identification of transcription factor binding sites (TFBS) can help to explore gene regulatory mechanisms. Research studies have proved that cfDNA (cell-free DNA) shows relatively higher coverage at TFBS due to the protection by TF from degradation by nucleases and short fragments of cfDNA are enriched in TFBS. However, there are still great difficulties in the noninvasive identification of TFBSs from experimental techniques. In this study, we propose a deep learning-based approach that can noninvasively predict TFBSs of cfDNA by learning sequence information from known TFBSs through convolutional neural networks. Under the addition of long short-term memory, our model achieved an area under the curve of 84%. Based on this model to predict cfDNA, we found consistent motifs in cfDNA fragments and lower coverage occurred upstream and downstream of these cfDNA fragments, which is consistent with a previous study. We also found that the binding sites of the same TF differ in different cell lines. TF-specific target genes were detected from cfDNA and were enriched in cancer-related pathways. In summary, our method of locating TFBSs from plasma has the potential to reflect the intrinsic regulatory mechanism from a noninvasive perspective and provide technical guidance for dynamic monitoring of disease in clinical practice.

Effectiveness and economic evaluation of rhTPO and rhIL-11 in the treatment of cancer therapy induced thrombocytopenia based on real-world research.

Objective: Based on real-world research, we aimed to evaluate the effectiveness and economy of recombinant human thrombopoietin (rhTPO) and recombinant human interleukin 11 (rhIL-11) in the treatment of cancer therapy induced thrombocytopenia (CTIT). Methods: We retrospectively collected clinical data of patients with CTIT who were treated with rhTPO or rhIL-11 in a single cancer hospital from January 2020 to December 2021. Propensity score matching (PSM) was applied to eliminate confounding factors. The measurements of effectiveness analysis were the platelet compliance rate, days of medication, days of compliance, highest platelet count after medication, platelet count elevation before and after medication, and the lowest platelet count after next-cycle cancer therapy. The economic evaluation was performed according to the results of the effectiveness evaluation. At the same time, patients were stratified according to type of tumor and grade of thrombocytopenia for subgroup analysis. Results: A total of 262 patients were collected and 174 patients were enrolled after PSM, 87 in the rhTPO group and 87 in the rhIL-11 group. In all patients, there were no significant differences in the platelet compliance rate, mean days of medication, median days of compliance, median highest platelet count after medication, and the median platelet count elevation before and after medication between the two groups (p > 0.05), but the median lowest platelet count after next-cycle cancer therapy in the rhTPO group was lower than that in the rhIL-11 group (p = 0.014). The subgroup analysis showed that the rhTPO group had longer mean days of medication than the rhIL-11 group in patients with hematological malignancies (p = 0.042), and a lower median lowest platelet count after next-cycle cancer therapy in patients with grade I/II thrombocytopenia than rhIL-11 group (p = 0.022), with no significant difference in other outcome indicators (p > 0.05). As there was no statistically significant difference in platelet compliance rate between the two groups, the cost-minimization analysis showed that the rhIL-11 group had lower treatment costs than the rhTPO group. Conclusion: RhTPO and rhIL-11 showed similar effectiveness in the treatment of CTIT, but rhIL-11 was more advantageous in economic cost.

Agarose amplification based sequencing characterization cell-free RNA in preimplantation spent embryo medium.

BACKGROUND: The cell-free RNA (cf-RNA) of spent embryo medium (SEM) has aroused a concern of academic and clinical researchers for its potential use in non-invasive embryo screening. However, comprehensive characterization of cf-RNA from SEM still presents significant technical challenges, primarily due to the limited volume of SEM. Hence, there is urgently need to a small input liquid volume and ultralow amount of cf-RNA library preparation method to unbiased cf-RNA sequencing from SEM. (75) RESULT: Here, we report a high sensitivity agarose amplification-based cf-RNA sequencing method (SEM-Acf) for human preimplantation SEM cf-RNA analysis. It is a cf-RNA sequencing library preparation method by adding agarose amplification. The agarose amplification sensitivity (0.005 pg) and efficiency (105.35 %) were increased than that of without agarose addition (0.45 pg and 96.06 %) by âˆ¼ 90 fold and 9.29 %, respectively. Compared with SMART sequencing (SMART-seq), the correlation of gene expression was stronger in different SEM samples by using SEM-Acf. The cf-RNA number of detected and coverage uniformity of 3' end were significantly increased. The proportion of 5' end adenine, alternative splicing events and short fragments (<400 bp) were increased. It is also found that 4-mer end motifs of cf-RNA fragments was significantly differences between different embryonic stage by day3 spent cleavage medium and day5/6 spent blastocyst medium. (141) SIGNIFICANCE: This study established an efficient SEM amplification and library preparation method. Additionally, we successfully described the characterizations of SEM cf-RNA in preimplantation embryo using SEM-Acf, including expression features and fragment lengths. SEM-Acf facilitates the exploration of cf-RNA as a noninvasive embryo screening biomarker, and opens up potential clinical utilities of small input liquid volume and ultralow amount cf-RNA sequencing. (59).

Avian ANP32A incorporated in avian influenza A virions promotes interspecies transmission by priming early viral replication in mammals.

Species-specific differences in acidic nuclear phosphoprotein 32 family member A (ANP32A) determine the restriction of avian-signature polymerase in mammalian cells. Mutations that evade this restriction, such as PB2-E627K, are frequently acquired when avian influenza A viruses jump from avian hosts to mammalian hosts. However, the mechanism underlying this adaptation process is still unclear. Here, we report that host factor ANP32 proteins can be incorporated into influenza viral particles through combination with the viral RNA polymerase (vPol) and then transferred into targeted cells where they support virus replication. The packaging of the ANP32 proteins into influenza viruses is dependent on their affinity with the vPol. Avian ANP32A (avANP32A) delivered by avian influenza A virions primes early viral replication in mammalian cells, thereby favoring the downstream interspecies transmission event by increasing the total amount of virus carrying adaptive mutations. Our study clarifies one role of avANP32A where it is used by avian influenza virus to help counteract the restriction barrier in mammals.

Deep-Cloud: A Deep Neural Network-Based Approach for Analyzing Differentially Expressed Genes of RNA-seq Data.

Presently, the field of analyzing differentially expressed genes (DEGs) of RNA-seq data is still in its infancy, with new approaches constantly being proposed. Taking advantage of deep neural networks to explore gene expression information on RNA-seq data can provide a novel possibility in the biomedical field. In this study, a novel approach based on a deep learning algorithm and cloud model was developed, named Deep-Cloud. Its main advantage is not only using a convolutional neural network and long short-term memory to extract original data features and estimate gene expression of RNA-seq data but also combining the statistical method of the cloud model to quantify the uncertainty and carry out in-depth analysis of the DEGs between the disease groups and the control groups. Compared with traditional analysis software of DEGs, the Deep-cloud model further improves the sensitivity and accuracy of obtaining DEGs from RNA-seq data. Overall, the proposed new approach Deep-cloud paves a new pathway for mining RNA-seq data in the biomedical field.

HvMPK4 phosphorylates HvWRKY1 to enhance its suppression of barley immunity to powdery mildew fungus.

Mitogen-activated protein kinase (MAPK) cascades play important roles in disease resistance in model plant species. However, the functions of MAPK signaling pathways in crop disease resistance are largely unknown. Here we report the function of HvMKK1-HvMPK4-HvWRKY1 module in barley immune system. HvMPK4 is identified to play a negative role in barley immune response against Bgh, as virus-induced gene silencing of HvMPK4 results in enhanced disease resistance whilst stably overexpressing HvMPK4 leads to super-susceptibility to Bgh infection. Furthermore, the barley MAPK kinase HvMKK1 is found to specifically interact with HvMPK4, and the activated HvMKK1DD variant specifically phosphorylates HvMPK4 in vitro. Moreover, the transcription factor HvWRKY1 is identified to be a downstream target of HvMPK4 and phosphorylated by HvMPK4 in vitro in the presence of HvMKK1DD. Phosphorylation assay coupled with mutagenesis analyses identifies S122, T284, and S347 in HvWRKY1 as the major residues phosphorylated by HvMPK4. HvWRKY1 is phosphorylated in barley at the early stages of Bgh infection, which enhances its suppression on barley immunity likely due to enhanced DNA-binding and transcriptional repression activity. Our data suggest that the HvMKK1-HvMPK4 kinase pair acts upstream of HvWRKY1 to negatively regulate barley immunity against powdery mildew.

The Effects of Age and Reading Experience on the Lifespan Neurodevelopment for Reading Comprehension.

Reading comprehension is a vital cognitive skill that individuals use throughout their lives. The neurodevelopment of reading comprehension across the lifespan, however, remains underresearched. Furthermore, factors such as maturation and experience significantly influence functional brain development. Given the complexity of reading comprehension, which incorporates lower-level word reading process and higher-level semantic integration process, our study aims to investigate how age and reading experience influence the neurobiology underpinning these two processes across the lifespan. fMRI data of 158 participants aged from 7 to 77 years were collected during a passive word viewing task and a sentence comprehension task to engage the lower- and higher-level processes, respectively. We found that the neurodevelopment of the lower-level process was primarily influenced by age, showing increased activation and connectivity with age in parieto-occipital and middle/inferior frontal lobes related to morphological-semantic mapping while decreased activation in the temporoparietal regions linked to phonological processing. However, the brain function of the higher-level process was primarily influenced by reading experience, exhibiting a greater reliance on the frontotemporal semantic network with enhanced sentence-level reading performance. Furthermore, reading experience did not significantly affect the brain function of children, but had a positive effect on young adults in the lower-level process and on middle-aged and older adults in the higher-level process. These findings indicate that the brain function for lower- and higher-level processes of reading comprehension is differently affected by maturation and reading experience, and the experience effect is contingent on age regarding the two processes.

Vulval superficial myofibroblastoma with lymphocytic and eosinophilic infiltrate.

We present the case of a vulval superficial myofibroblastoma with a lymphocytic and eosinophilic rim in a woman in her late 20s. The tumour presented in pregnancy as a cystic lesion with pain and increasing size. While the histopathology of superficial myofibroblastomas has been well defined in the literature, to our knowledge, there has been no documentation of the presence of an inflammatory infiltrate of lymphocytes and eosinophils surrounding and within the tumour. This may potentially act as a diagnostic or prognostic reference.

Possible association between cerebral white matter atrophy and impaired performance of activities of daily living in patients with Parkinson's disease.

INTRODUCTION: The contribution of brain abnormalities in patients with Parkinson's disease (PD) to impaired functional status remains uncertain. Our study assessed whether global and regional brain structural abnormalities are associated with impaired performance of activities of daily living (ADL) in PD patients. MATERIAL AND METHODS: A retrospective analysis was conducted of 46 patients with PD, recruited prospectively from a movement disorder clinic. Motor impairment and disability were assessed using the Hoehn and Yahr (H-Y) scale and Unified Parkinson's Disease Rating Scale Part III (UPDRS-III). Cognitive status was evaluated with Montreal Cognitive Assessment (MoCA). The performance of ADL was indexed by the sum score of the Physical Self-Maintenance Scale (PSMS) and Lawton Instrumental ADL scale. Brain magnetic resonance imaging (MRI) was performed to assess white matter hyperintensities and medial temporal lobe atrophy (MTLA). Global brain atrophy, indexed by the relative grey matter volume (RGM), relative white matter volume (RWM) and average cortical thickness of the whole brain, was quantified by voxel-based morphometry (VBM). RESULTS: The ADL score (where higher scores indicate poorer performance) negatively correlated with RWM (where greater volume indicates less severe atrophy; r = -0.41, p = 0.004) and RGM (where greater volume indicates less severe atrophy; r = -0.43, p = 0.003) but not with the average cortical thickness ( r = -0.16, p = 0.29). With ADL score as the dependent variable in a linear regression model, H-Y stage and RWM significantly correlated with the ADL score after adjusting for age and MoCA score, and together accounted for 51% of the variance therein. RGM was not significantly correlated with the ADL score after adjusting for age and MoCA score. CONCLUSIONS: Cerebral white matter atrophy may be associated with the performance of ADL in patients with PD, indicating an important role of white matter impairment in their functional status.

Joint analysis of GWAS and multi-omics QTL summary statistics reveals a large fraction of GWAS signals shared with molecular phenotypes.

Molecular quantitative trait loci (xQTLs) are often harnessed to prioritize genes or functional elements underpinning variant-trait associations identified from genome-wide association studies (GWASs). Here, we introduce OPERA, a method that jointly analyzes GWAS and multi-omics xQTL summary statistics to enhance the identification of molecular phenotypes associated with complex traits through shared causal variants. Applying OPERA to summary-level GWAS data for 50 complex traits (n = 20,833-766,345) and xQTL data from seven omics layers (n = 100-31,684) reveals that 50% of the GWAS signals are shared with at least one molecular phenotype. GWAS signals shared with multiple molecular phenotypes, such as those at the MSMB locus for prostate cancer, are particularly informative for understanding the genetic regulatory mechanisms underlying complex traits. Future studies with more molecular phenotypes, measured considering spatiotemporal effects in larger samples, are required to obtain a more saturated map linking molecular intermediates to GWAS signals.

Cooperative Catalysis Mechanism of Brønsted and Lewis Acids from Al(OTf)3 with Methanol for ß-Cellobiose-to-Fructose Conversion: An Experimental and Theoretical Study.

Al-containing catalysts, e.g., Al(OTf)3, show good catalytic performance toward the conversion of cellulose to fructose in methanol solution. Here, we report the catalytic isomerization and alcoholysis mechanisms for the conversion of cellobiose to fructose at the PBE0/6-311++G(d,p), aug-cc-pVTZ theoretical level, combining the relevant experimental verifications of electrospray ionization mass spectrometry (ESI-MS), high-performance liquid chromatography (HPLC), and the attenuated total reflection-infrared (ATR-IR) spectra. From the alcoholysis of Al(OTf)3 in methanol solution, the catalytically active species involves both the [CH3OH2]+ Brønsted acid and the [Al(CH3O)(OTf)(CH3OH)4]+ Lewis acid. There are two reaction pathways, i.e., one through glucose (glycosidic bond cleavage followed by isomerization, w-G) and another through cellobiulose (isomerization followed by glycosidic bond cleavage, w-L). The Lewis acid ([Al(CH3O)(OTf)(CH3OH)4]+) is responsible for the aldose-ketose tautomerization, while the Brønsted acid ([CH3OH2]+) is in charge of ring-opening, ring-closure, and glycosidic bond cleavage. For both w-G and w-L, the rate-determining steps are related to the intramolecular [1,2]-H shift between C1-C2 for the aldose-ketose tautomerization catalyzed by the [Al(CH3O)(OTf)(CH3OH)4]+ species. The Lewis acid ([Al(CH3O)(OTf)(CH3OH)4]+) exhibits higher catalytic activity toward the aldose-ketose tautomerization of glycosyl-chain-glucose to glycosyl-chain-fructose than that of chain-glucose to chain-fructose. Besides, the Brønsted acid ([CH3OH2]+) shows higher catalytic activity toward the glycosidic bond cleavage of cellobiulose than that of cellobiose. Kinetically, the w-L pathway is predominant, whereas the w-G pathway is minor. The theoretically proposed mechanism has been experimentally testified. These insights may advance on the novel design of the catalytic system toward the conversion of cellulose to fructose.