The metabolism-related lncRNA signature predicts the prognosis of breast cancer patients.

Long non-coding RNAs (lncRNAs) involved in metabolism are recognized as significant factors in breast cancer (BC) progression. We constructed a novel prognostic signature for BC using metabolism-related lncRNAs and investigated their underlying mechanisms. The training and validation cohorts were established from BC patients acquired from two public sources: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The prognostic signature of metabolism-related lncRNAs was constructed using the least absolute shrinkage and selection operator (LASSO) cox regression analysis. We developed and validated a new prognostic risk model for BC using the signature of metabolism-related lncRNAs (SIRLNT, SIAH2-AS1, MIR205HG, USP30-AS1, MIR200CHG, TFAP2A-AS1, AP005131.2, AL031316.1, C6orf99). The risk score obtained from this signature was proven to be an independent prognostic factor for BC patients, resulting in a poor overall survival (OS) for individuals in the high-risk group. The area under the curve (AUC) for OS at three and five years were 0.67 and 0.65 in the TCGA cohort, and 0.697 and 0.68 in the GEO validation cohort, respectively. The prognostic signature demonstrated a robust association with the immunological state of BC patients. Conventional chemotherapeutics, such as docetaxel and paclitaxel, showed greater efficacy in BC patients classified as high-risk. A nomogram with a c-index of 0.764 was developed to forecast the survival time of BC patients, considering their risk score and age. The silencing of C6orf99 markedly decreased the proliferation, migration, and invasion capacities in MCF-7 cells. Our study identified a signature of metabolism-related lncRNAs that predicts outcomes in BC patients and could assist in tailoring personalized prevention and treatment plans.

Breakthrough of solid tumor treatment: CAR-NK immunotherapy.

As the latest and most anticipated method of tumor immunotherapy, CAR-NK therapy has received increasing attention in recent years, and its safety and high efficiency have irreplaceable advantages over CAR-T. Current research focuses on the application of CAR-NK in hematological tumors, while there are fewer studies on solid tumor. This article reviews the process of constructing CAR-NK, the effects of hypoxia and metabolic factors, NK cell surface receptors, cytokines, and exosomes on the efficacy of CAR-NK in solid tumor, and the role of CAR-NK in various solid tumor. The mechanism of action and the research status of the potential of CAR-NK in the treatment of solid tumor in clinical practice, and put forward the advantages, limitations and future problems of CAR-NK in the treatment of solid tumor.

Pore-Scale Study on Shale Oil-CO2-Water Miscibility, Competitive Adsorption, and Multiphase Flow Behaviors.

Due to the fracturing fluid imbibition and primary water, oil-water two-phase fluids generally exist in shale nanoporous media. The effects of water phase on shale oil recovery and geological carbon sequestration via CO2 huff-n-puff is non-negligible. Meanwhile, oil-CO2 miscibility after CO2 huff-n-puff also has an important effect on oil-water two-phase flow behaviors. In this work, by considering the oil-CO2 competitive adsorption behaviors and the effects of oil-CO2 miscibility on water wettability, an improved multicomponent and multiphase lattice Boltzmann method is proposed to study the effects of water phase on CO2 huff-n-puff. Additionally, the effects of oil-CO2 miscibility on oil-water flow behaviors and relative permeability are also discussed. The results show that due to Jamin's effect of water droplets in oil-wetting pores and the capillary resistance of bridge-like water phase in water-wetting pores, CO2 can hardly diffuse into the oil phase, causing a large amount of remaining oil. As water saturation increases, Jamin's effect and the capillary resistance become more pronounced, and the CO2 storage mass gradually decreases. Then, based on the results from molecular dynamics simulations, the influences of oil-CO2 miscibility on oil-water relative permeability in calcite nanoporous media are studied, and as the oil mass percentage in the oil-CO2 miscible system decreases, the oil/water relative permeability decreases/increases. The improved lattice Boltzmann model can be readily extended to quantitatively calculate geological CO2 storage mass considering water saturation and calculate the accurate oil-water relative permeability based on the real 3D digital core.

Entropy by Neighbor Distance as a New Measure for Characterizing Spatiotemporal Orders in Microscopic Collective Systems.

Collective systems self-organize to form globally ordered spatiotemporal patterns. Finding appropriate measures to characterize the order in these patterns will contribute to our understanding of the principles of self-organization in all collective systems. Here we examine a new measure based on the entropy of the neighbor distance distributions in the characterization of collective patterns. We study three types of systems: a simulated self-propelled boid system, two active colloidal systems, and one centimeter-scale robotic swarm system. In all these systems, the new measure proves sensitive in revealing active phase transitions and in distinguishing steady states. We envision that the entropy by neighbor distance could be useful for characterizing biological swarms such as bird flocks and for designing robotic swarms.

Spatially resolved expression landscape and gene-regulatory network of human gastric corpus epithelium.

Molecular knowledge of human gastric corpus epithelium remains incomplete. Here, by integrated analyses using single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, and single-cell assay for transposase accessible chromatin sequencing (scATAC-seq) techniques, we uncovered the spatially resolved expression landscape and gene-regulatory network of human gastric corpus epithelium. Specifically, we identified a stem/progenitor cell population in the isthmus of human gastric corpus, where EGF and WNT signaling pathways were activated. Meanwhile, LGR4, but not LGR5, was responsible for the activation of WNT signaling pathway. Importantly, FABP5 and NME1 were identified and validated as crucial for both normal gastric stem/progenitor cells and gastric cancer cells. Finally, we explored the epigenetic regulation of critical genes for gastric corpus epithelium at chromatin state level, and identified several important cell-type-specific transcription factors. In summary, our work provides novel insights to systematically understand the cellular diversity and homeostasis of human gastric corpus epithelium in vivo.

Fast synthesis of large-area bilayer graphene film on Cu.

Bilayer graphene (BLG) is intriguing for its unique properties and potential applications in electronics, photonics, and mechanics. However, the chemical vapor deposition synthesis of large-area high-quality bilayer graphene on Cu is suffering from a low growth rate and limited bilayer coverage. Herein, we demonstrate the fast synthesis of meter-sized bilayer graphene film on commercial polycrystalline Cu foils by introducing trace CO2 during high-temperature growth. Continuous bilayer graphene with a high ratio of AB-stacking structure can be obtained within 20 min, which exhibits enhanced mechanical strength, uniform transmittance, and low sheet resistance in large area. Moreover, 96 and 100% AB-stacking structures were achieved in bilayer graphene grown on single-crystal Cu(111) foil and ultraflat single-crystal Cu(111)/sapphire substrates, respectively. The AB-stacking bilayer graphene exhibits tunable bandgap and performs well in photodetection. This work provides important insights into the growth mechanism and the mass production of large-area high-quality BLG on Cu.

Integrative single-cell multiomics analyses dissect molecular signatures of intratumoral heterogeneities and differentiation states of human gastric cancer.

Human gastric cancer is a highly lethal disease, but the underlying multiomic molecular signatures remain largely unclear. Here, we performed multi-regional sampling, parallel single-cell multiomics sequencing and integrated analyses of human gastric cancer. We identified common transcriptomic alterations of gastric cancer cells, such as aberrant down-regulation of genes associated with normal stomach function and up-regulation of KRT7, PI3, S100A4, etc. Surprisingly, aberrant and prevalent up-regulation of genes highly expressed in normal colorectal epithelial cells were also identified in cancer cells, which may be partially regulated by promoter chromatin accessibility and DNA methylation levels. We revealed the single-cell DNA methylome landscape of gastric cancer, and identified candidate DNA methylation biomarkers, such as hypermethylated promoters of TMEM240 and HAGLROS, and hypomethylated promoters of TRPM2-AS and HRH1. Additionally, the relationships between genetic lineages, DNA methylation and transcriptomic clusters were systematically revealed at single-cell level. We showed that DNA methylation heterogeneities were mainly among different genetic lineages of cancer cells. Moreover, we found that DNA methylation levels of cancer cells with poorer differentiation states tend to be higher than those of cancer cells with better differentiation states in the primary tumor within the same patient, although still lower than in normal gastric epithelial cells. Cancer cells with poorer differentiation states also prevalently down-regulated MUC1 expression and immune-related pathways, and had poor infiltration of CD8+ T cells. Our study dissected the molecular signatures of intratumoral heterogeneities and differentiation states of human gastric cancer using integrative single-cell multiomics analyses.

Characterisation of kapok fibre's biochar for arsenate adsorption removal from aqueous solution.

Al-KBC was produced through the simple pyrolysis of Al-modified kapok fibres at high temperatures. Using the N2 adsorption Brunauer Emmett Teller (BET) process, Fourier transforms infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), the energy-dispersive X-ray spectroscopy (EDS) spectroscopy, and X-ray photoelectron spectroscopy (XPS), the sorbent changes and characteristics were analysed. As a result of Al's addition to the fibre's surface, Al-KBC exhibited superior As(V) adsorption performance compared to KBC due to better pore structures. Experiments on the kinetics of As(V) adsorption revealed that the adsorption followed the pseudo-second-order model and that intradiffusion was not the only factor governing the adsorption. Experiments with isotherms indicated that the adsorption mechanism corresponded to the Langmuir model, and the adsorption capacity Qm of Al-KBC at 25 °C was 483 µg/g. The thermodynamic experiments suggested that the adsorption reactions were spontaneous endothermic with a random approach at the adsorption interface. 25 mg/L of coexisting ions such as sulphate and phosphate reduced the sorbent As(V) removal ability to 65% and 39%. After seven cycles of adsorption/desorption, Al-KBC demonstrated satisfactory performance in terms of reusability, adsorbing 53% of 100 µg/L As(V) from the water. This novel BC can probably be used as a filter to purify groundwater with high As(V) concentration in the rural zone.

One Size Fits All: A Unified Traffic Predictor for Capturing the Essential Spatial-Temporal Dependency.

Traffic prediction is a keystone for building smart cities in the new era and has found wide applications in traffic scheduling and management, environment policy making, public safety, and so on. Instead of creating a traffic predictor for each city, this article focuses on designing a unified network model that could be directly applied for traffic prediction in any city, by learning the essential spatial-temporal dependencies, i.e., the mutual relationship between traffic and the corresponding fine-grained road network. To achieve this goal, this article proposes a joint knowledge-and data-driven mechanism that novelly divides dependencies into three kinds of correlations, i.e., road segment, intra-intersection, and inter-intersection correlation, which capture the microcosmic, middle, and macroscopic dependencies between traffic and the road network, respectively. Specifically, we first construct traffic datasets that could cover all road segments from real-world trajectory datasets, which makes it possible to model the whole road network as a graph, with the help of fine-grained road topology. Then, we propose meta road segment learner, connection-aware spatial-temporal graph convolutional network (GCN), and multiscale residual networks for capturing the microcosmic, middle, and macroscopic dependencies, respectively. Our experiments on three real-world datasets demonstrate that our proposed method could: 1) achieve better prediction accuracy compared with several approaches and 2) capture the mutual relationship between traffic and the fine-grained road network since our model trained only using data from the source city achieves good performance when it is directly applied for traffic prediction in the target city, without any fine-tuning. The codes will be made publicly available.

Research on Lower Limb Step Speed Recognition Method Based on Electromyography.

Wearable exoskeletons play an important role in people's lives, such as helping stroke and amputation patients to carry out rehabilitation training and so on. How to make the exoskeleton accurately judge the human action intention is the basic requirement to ensure that it can complete the corresponding task. Traditional exoskeleton control signals include pressure values, joint angles and acceleration values, which can only reflect the current motion information of the human lower limbs and cannot be used to predict motion. The electromyography (EMG) signal always occurs before a certain movement; it can be used to predict the target's gait speed and movement as the input signal. In this study, the generalization ability of a BP neural network and the timing property of a hidden Markov chain are used to properly fuse the two, and are finally used in the research of this paper. Experiments show that, using the same training samples, the recognition accuracy of the three-layer BP neural network is only 91%, while the recognition accuracy of the fusion discriminant model proposed in this paper can reach 95.1%. The results show that the fusion of BP neural network and hidden Markov chain has a strong solving ability for the task of wearable exoskeleton recognition of target step speed.

Analysis of rainwater storage and use recommendations: From the perspective of DBPs generation and their risks.

As a vital freshwater resource, rainwater is usually stored in water cellars in arid regions to solve the daily drinking water problems of the population. However, the status of disinfection by-products (DBPs) generation in cellar water under intermittent disinfection conditions is unclear. Therefore, we investigated the formation and distribution characteristics of DBPs in cellar water under intermittent disinfection conditions for the first time. The results demonstrated that six categories of DBPs were selected for detection after chlorination, including trihalomethanes (THMs), haloacetic acids (HAAs), haloketones (HKs), haloacetonitriles (HANs), halonitromethanes (HNMs), and nitrosamines (NAs), among which HAAs, HKs, and HANs were the major DBPs. Only bromoacetic acid (MBAA), dichloroacetic acid (DCAA), and trichloroacetic acid (TCAA) showed an increasing trend of accumulation as the number of disinfections increased. Meanwhile, the precursor composition was gradually transformed from humic substances to amino acids, and both organic substances were the main precursors of HAAs. The health risk assessment showed that the main carcinogenic and non-carcinogenic risks of cellar water were contributed by NAs and HAAs, respectively, and children are more susceptible to the risks than adults. The best time to drink cellar water is after approximately 12 days of storage, when the total carcinogenic risk is the minimum.

Establishment and characterization of adult human gastric epithelial progenitor-like cell lines.

OBJECTIVE: Human gastric epithelial stem/progenitor cells are important for stomach homeostasis; however, the in vitro culture system of these cells remains immature. Although three-dimensional (3D) organoid culture has fundamentally changed the in vitro study of gastrointestinal tract, its use is limited by inaccessible luminal compartment, and difficulties of imaging and manipulation. To overcome these limitations of 3D organoid culture system, we established adult human gastric epithelial progenitor-like (hGEPL) cell lines using a novel robust monolayer cell culture system. MATERIALS AND METHODS: We established an in vitro gel-based monolayer culture system for normal human adult gastric epithelium, and compared it with traditional two-dimensional (2D) and 3D organoid culture systems using transcriptomics, immunofluorescence and cell viability experiments. At the same time, we used single-cell transcriptomics to compare the differences of the hGEPL cells in conditioned medium (Cond.) and in chemically defined medium (Chem.), the two most common media for organoid culture, in maintaining the stemness and proliferative activity of hGEPL cells. Finally, we explored the role of key niche factors in inducing hGEPL cell differentiation. RESULTS: The hGEPL cells were similar to the in vivo gastric epithelial stem/progenitor cells, which could stably proliferate in culture for a long time. Based on the established culture system, we explored signalling pathways that were important for the homeostasis of hGEPL cells. We found that after blocking the WNT signalling pathway or activating the BMP signalling pathway, hGEPL cells could differentiate into mucous surface cells. CONCLUSION: Our culture system of hGEPL cells from adults is robust and easy to operate, and has the transformative potential of personalized and precision medicine, laying a solid foundation for studying the self-renewal and differentiation potentials of gastric epithelial stem/progenitor cells as well as modelling of related gastric diseases.

One-Step Pyrolysis of Nitrogen-Containing Chemicals and Biochar Derived from Walnut Shells to Absorb Polycyclic Aromatic Hydrocarbons (PAHs).

The pyrolysis of biomass is an efficient means of utilizing biomass resources. Biomass can be converted into various high-performance chemicals and functional materials through pyrolysis. However, current pyrolysis technologies suffer from low conversion rates and single products, so the preparation of nitrogen compounds with high economic value remains a challenge. The walnut shell was soaked in three nitrogen-containing compound solutions before carbonization to produce high-value-added nitrogen-containing chemicals (with a nitrogen content of 59.09%) and biochar for the adsorption of polycyclic aromatic hydrocarbons (PAHs). According to biochar analysis, biochar has a porous structure with a specific surface area of 1161.30 m2/g and a high level of rocky desertification. The surface forms a dense pyrrole structure, and the structure produces π-π interactions with naphthalene molecules, exhibiting excellent naphthalene adsorption with a maximum capacity of 214.98 mg/g. This study provides an efficient, rapid, and environmentally friendly method for producing nitrogen-containing chemicals with high-added value and biochar.

Investigating the Overall Experience of Wearable Robots during Prototype-Stage Testing.

Wearable robots (WRs) might interact with humans in a similar manner to teammates to accomplish specific tasks together. However, the available data on WR user experience (UX) studies are limited, especially during the prototyping phase. Therefore, this study aims to examine the overall experience of WRs during the prototyping phase based on an exploratory research model. This theoretical model considered usability, hedonic quality, and attitude toward using WRs as key factors in explaining and predicting overall experience. To test the hypotheses inherent in the research model, quantitative empirical research was conducted and the data were analyzed by partial least squares structural equation modeling (PLS-SEM). The results from the PLS-SEM analysis revealed the significance level of correlations between the latent variables in the research model. The exploratory research model was able to explain up to 53.2% of the variance in the overall experience of using WRs, indicating medium predictive power. This research develops a new quantitative empirical research model that can be used to explain and predict the overall experience of interactive products such as WRs. Meanwhile, the model is needed during WR testing in the prototype phase.

Fast arsenate As(V) adsorption and removal from water using aluminium Al(III) fixed on Kapok fibres.

Arsenic (As) is among the most dangerous metalloids and is harmful to human wellbeing. In this laboratory study, Al(III)-modified kapok fibres (Al-Kapok) were used to remove As(V) from water. The sorbent was characterised using Fourier transform infrared spectroscopy (FT-IR) and scanning electron microscopy (SEM) combined with energy-dispersive X-ray spectroscopy (EDX). Batch experiments were performed to observe the performance of Al-Kapok in the removal of As(V) and to examine the effects of pH, temperature, adsorbent dose, and coexisting ions on the adsorption process. The surface of the sorbent changed after aluminium modification, and the results of the batch experiments showed that the adsorption of As(V) occurred mainly via endothermic-spontaneous chemisorption at the solution and solid interface of Al-Kapok. The As(V) removal efficiency was approximately 76%-84%, and it was slightly affected at pH levels below 8.0. Further study showed that the maximum adsorption capacity of Al-Kapok for As(V) was 118 µg/g at 30 °C and pH 6, and notable adverse effects were caused by the presence of SO42-and PO43-. It was also found that the boundary layer and film diffusion contributed more to As(V) adsorption. After five adsorption/desorption cycles, regeneration recovered approximately 92% of the adsorption capacity of Al-Kapok used. Overall, Al-Kapok appears to be a suitable adsorbent material for the purification of As-contaminated water.

Integrated wafer-scale ultra-flat graphene by gradient surface energy modulation.

The integration of large-scale two-dimensional (2D) materials onto semiconductor wafers is highly desirable for advanced electronic devices, but challenges such as transfer-related crack, contamination, wrinkle and doping remain. Here, we developed a generic method by gradient surface energy modulation, leading to a reliable adhesion and release of graphene onto target wafers. The as-obtained wafer-scale graphene exhibited a damage-free, clean, and ultra-flat surface with negligible doping, resulting in uniform sheet resistance with only ~6% deviation. The as-transferred graphene on SiO2/Si exhibited high carrier mobility reaching up ~10,000 cm2 V-1 s-1, with quantum Hall effect (QHE) observed at room temperature. Fractional quantum Hall effect (FQHE) appeared at 1.7 K after encapsulation by h-BN, yielding ultra-high mobility of ~280,000 cm2 V-1 s-1. Integrated wafer-scale graphene thermal emitters exhibited significant broadband emission in near-infrared (NIR) spectrum. Overall, the proposed methodology is promising for future integration of wafer-scale 2D materials in advanced electronics and optoelectronics.

Single-cell profiling reveals molecular basis of malignant phenotypes and tumor microenvironments in small bowel adenocarcinomas.

Small bowel adenocarcinomas (SBAs) are rare malignant tumors with a high mortality rate, and their molecular characteristics are still largely unexplored. Here we performed single-cell RNA sequencing for tumor samples from 12 SBA patients and predicted drug candidates for SBA. We identified four prevalent subtypes of malignant cells with distinct signatures including cell cycle program, mitochondria program, metabolism program and epithelial-mesenchymal transition (EMT) program. The progression relationships of these four subtypes of malignant cells were also revealed, which started from the cell cycle program, through the mitochondria program and then progressing into either the metabolism program or the EMT program. Importantly, ligand-receptor interaction pairs were found to be specifically enriched in pairs of EMT-program malignant cells and highly exhausted CD8+ T cells, suggesting that cancer cell subpopulations with EMT features may contribute most to the exhaustion of T cells. We also showed that the duodenal subtype of SBA exhibited molecular features more similar to gastric cancer whereas jejunal subtype of SBA more similar to colorectal cancer. Especially, we predicted specific drugs for SBA based on differential gene expression signatures between malignant cells and normal epithelial cells of SBA, and verified more potent inhibitory effects of volasertib and tozasertib for SBA cancer cells than conventional drugs of SBA at the same concentration, which provides new clues for treatments of SBA. In summary, our study provides a blueprint of the molecular signatures of both tumor cells and tumor microenvironment cells in SBA and reveals potential targets and drug candidates for its clinical treatments.

Copper acetate-facilitated transfer-free growth of high-quality graphene for hydrovoltaic generators.

Direct synthesis of high-quality graphene on dielectric substrates without a transfer process is of vital importance for a variety of applications. Current strategies for boosting high-quality graphene growth, such as remote metal catalyzation, are limited by poor performance with respect to the release of metal catalysts and hence suffer from a problem with metal residues. Herein, we report an effective approach that utilizes a metal-containing species, copper acetate, to continuously supply copper clusters in a gaseous form to aid transfer-free growth of graphene over a wafer scale. The thus-derived graphene films were found to show reduced multilayer density and improved electrical performance and exhibited a carrier mobility of 8500 cm2 V-1 s-1. Furthermore, droplet-based hydrovoltaic electricity generator devices based on directly grown graphene were found to exhibit robust voltage output and long cyclic stability, in stark contrast to their counterparts based on transferred graphene, demonstrating the potential for emerging energy harvesting applications. The work presented here offers a promising solution to organize the metal catalytic booster toward transfer-free synthesis of high-quality graphene and enable smart energy generation.

Single-cell genomic and transcriptomic landscapes of primary and metastatic colorectal cancer tumors.

BACKGROUND: Colorectal cancer (CRC) ranks as the second-leading cause of cancer-related death worldwide with metastases being the main cause of cancer-related death. Here, we investigated the genomic and transcriptomic alterations in matching adjacent normal tissues, primary tumors, and metastatic tumors of CRC patients. METHODS: We performed whole genome sequencing (WGS), multi-region whole exome sequencing (WES), simultaneous single-cell RNA-Seq, and single-cell targeted cDNA Sanger sequencing on matching adjacent normal tissues, primary tumors, and metastatic tumors from 12 metastatic colorectal cancer patients (n=84 for genomes, n=81 for exomes, n=9120 for single cells). Patient-derived tumor organoids were used to estimate the anti-tumor effects of a PPAR inhibitor, and self-renewal and differentiation ability of stem cell-like tumor cells. RESULTS: We found that the PPAR signaling pathway was prevalently and aberrantly activated in CRC tumors. Blocking of PPAR pathway both suppressed the growth and promoted the apoptosis of CRC organoids in vitro, indicating that aberrant activation of the PPAR signaling pathway plays a critical role in CRC tumorigenesis. Using matched samples from the same patient, distinct origins of the metastasized tumors between lymph node and liver were revealed, which was further verified by both copy number variation and mitochondrial mutation profiles at single-cell resolution. By combining single-cell RNA-Seq and single-cell point mutation identification by targeted cDNA Sanger sequencing, we revealed important phenotypic differences between cancer cells with and without critical point mutations (KRAS and TP53) in the same patient in vivo at single-cell resolution. CONCLUSIONS: Our data provides deep insights into how driver mutations interfere with the transcriptomic state of cancer cells in vivo at a single-cell resolution. Our findings offer novel knowledge on metastatic mechanisms as well as potential markers and therapeutic targets for CRC diagnosis and therapy. The high-precision single-cell RNA-seq dataset of matched adjacent normal tissues, primary tumors, and metastases from CRCs may serve as a rich resource for further studies.

Large-area transfer of two-dimensional materials free of cracks, contamination and wrinkles via controllable conformal contact.

The availability of graphene and other two-dimensional (2D) materials on a wide range of substrates forms the basis for large-area applications, such as graphene integration with silicon-based technologies, which requires graphene on silicon with outperforming carrier mobilities. However, 2D materials were only produced on limited archetypal substrates by chemical vapor deposition approaches. Reliable after-growth transfer techniques, that do not produce cracks, contamination, and wrinkles, are critical for layering 2D materials onto arbitrary substrates. Here we show that, by incorporating oxhydryl groups-containing volatile molecules, the supporting films can be deformed under heat to achieve a controllable conformal contact, enabling the large-area transfer of 2D films without cracks, contamination, and wrinkles. The resulting conformity with enhanced adhesion facilitates the direct delamination of supporting films from graphene, providing ultraclean surfaces and carrier mobilities up to 1,420,000 cm2 V-1 s-1 at 4 K.