Modeling the light-powered self-rotation of a liquid crystal elastomer fiber-based engine.

Self-oscillating systems possess the ability to convert ambient energy directly into mechanical work, and new types of self-oscillating systems are worth designing for practical applications in energy harvesters, engines and actuators. Taking inspiration from the four-stroke engine. A concept for a self-rotating engine is presented on the basis of photothermally responsive materials, consisting of a liquid crystal elastomer (LCE) fiber, a hinge and a turnplate, which can self-rotate under steady illumination. Based on the photo-thermal-mechanical model, a nonlinear theoretical model of the LCE-based engine under steady illumination is proposed to investigate its self-rotating behaviors. Numerical calculations reveal that the LCE-based engine experiences a supercritical Hopf bifurcation between the static regime and the self-rotation regime. The self-rotation of the LCE-based engine originates from the photothermally driven strain of the LCE fiber in illumination, and its continuous periodic motion is sustained by the correlation between photothermal energy and damping dissipation. The Hopf bifurcation conditions are also explored in detail, as well as the vital system parameters affecting self-rotation frequency. Compared to the abundant existing self-oscillating systems, this conceptual self-rotating LCE-based engine stands out due to its simple and lightweight structure, customizable dimensions and high speed, and it is expected to offer a broader range of design concepts applicable to soft robotics, energy harvesters, medical instruments, and so on.

A light-powered self-rotating liquid crystal elastomer drill.

Self-oscillating systems can directly convert ambient energy to mechanical work, and new type self-oscillating systems are worth designing for applications in energy harvesters, engines, and actuators. Taking inspiration from the hand drill, we have developed a novel self-rotating drill system, which is consist of a turnplate and a liquid crystal elastomer (LCE) fiber under steady illumination. To investigate the self-rotating behaviors of the LCE drill, we have proposed a nonlinear theoretical model of the LCE drill under steady illumination based on the well-established dynamic LCE model. Numerical calculation reveals that the LCE drill can undergo a supercritical Hopf bifurcation between the static regime and the self-rotation regime. The self-rotation of drill originates from the contraction of winding portion of LCE fiber in illumination at winding state, and its continuous periodic motion is sustained by the interrelation between light energy and damping dissipation. The Hopf bifurcation conditions are also investigated in detail, as well as the vital system parameters affecting its frequency and amplitude. In contrast to the abundant existing self-oscillating systems, this self-rotating drill stands out due to its simple and lightweight structure, customizable dimensions, and high speed, and thus facilitates the design of compact and integrated systems, enhancing their applicability in microdevices and systems. This bears great significance in fields like micro-robotics, micro-sensors, and medical instruments, enabling the realization of smaller and higher-performance devices.

DNA methylation heterogeneity attributable to a complex tumor immune microenvironment prompts prognostic risk in glioma.

Gliomas are malignant tumours of the human nervous system with different World Health Organization (WHO) classifications, glioblastoma (GBM) with higher grade and are more malignant than lower-grade glioma (LGG). To dissect how the DNA methylation heterogeneity in gliomas is influenced by the complex cellular composition of the tumour immune microenvironment, we first compared the DNA methylation profiles of purified human immune cells and bulk glioma tissue, stratifying three tumour immune microenvironmental subtypes for GBM and LGG samples from The Cancer Genome Atlas (TCGA). We found that more intermediate methylation sites were enriched in glioma tumour tissues, and used the Proportion of sites with Intermediate Methylation (PIM) to compare intertumoral DNA methylation heterogeneity. A larger PIM score reflected stronger DNA methylation heterogeneity. Enhanced DNA methylation heterogeneity was associated with stronger immune cell infiltration, better survival rates, and slower tumour progression in glioma patients. We then created a Cell-type-associated DNA Methylation Heterogeneity Contribution (CMHC) score to explore the impact of different immune cell types on heterogeneous CpG site (CpGct) in glioma tissues. We identified eight prognosis-related CpGct to construct a risk score: the Cell-type-associated DNA Methylation Heterogeneity Risk (CMHR) score. CMHR was positively correlated with cytotoxic T-lymphocyte infiltration (CTL), and showed better predictive performance for IDH status (AUC = 0.96) and glioma histological phenotype (AUC = 0.81). Furthermore, DNA methylation alterations of eight CpGct might be related to drug treatments of gliomas. In conclusion, we indicated that DNA methylation heterogeneity is associated with a complex tumour immune microenvironment, glioma phenotype, and patient's prognosis.

Impact of three-dimensional reconstruction visualization technology on short-term and long-term outcomes after hepatectomy in patients with hepatocellular carcinoma: a propensity-score-matched and inverse probability of treatment-weighted multicenter study.

BACKGROUND: Three-dimensional reconstruction visualization technology (3D-RVT) is an important tool in the preoperative assessment of patients undergoing liver resection. However, it is not clear whether this technique can improve short-term and long-term outcomes in patients with hepatocellular carcinoma (HCC) compared with two-dimensional (2D) imaging. METHOD: A total of 3402 patients from five centers were consecutively enrolled from January 2016 to December 2020, and grouped based on the use of 3D-RVT or 2D imaging for preoperative assessment. Baseline characteristics were balanced using propensity score matching (PSM, 1:1) and stabilized inverse probability of treatment-weighting (IPTW) to reduce potential selection bias. The perioperative outcomes, long-term overall survival (OS), and recurrence-free survival (RFS) were compared between the two groups. Cox-regression analysis was used to identify the risk factors associated with RFS. RESULTS: A total of 1681 patients underwent 3D-RVT assessment before hepatectomy (3D group), while 1721 patients used 2D assessment (2D group). The PSM cohort included 892 patient pairs. In the IPTW cohort, there were 1608.3 patients in the 3D group and 1777.9 patients in the 2D group. In both cohorts, the 3D group had shorter operation times, lower morbidity and liver failure rates, as well as shorter postoperative hospital stays. The 3D group had more margins ≥10 mm and better RFS than the 2D group. The presence of tumors with a diameter ≥5 cm, intraoperative blood transfusion and multiple tumors were identified as independent risk factors for RFS, while 3D assessment and anatomical resection were independent protective factors. CONCLUSION: In this multicenter study, perioperative outcomes and RFS of HCC patients following 3D-RVT assessment were significantly different from those following 2D imaging assessment. Thus, 3D-RVT may be a feasible alternative assessment method before hepatectomy for these patients.

CylinGCN: Cylindrical structures segmentation in 3D biomedical optical imaging by a contour-based graph convolutional network.

Cylindrical organs, e.g., blood vessels, airways, and intestines, are ubiquitous structures in biomedical optical imaging analysis. Image segmentation of these structures serves as a vital step in tissue physiology analysis. Traditional model-driven segmentation methods seek to fit the structure by constructing a corresponding topological geometry based on domain knowledge. Classification-based deep learning methods neglect the geometric features of the cylindrical structure and therefore cannot ensure the continuity of the segmentation surface. In this paper, by treating the cylindrical structures as a 3D graph, we introduce a novel contour-based graph neural network for 3D cylindrical structure segmentation in biomedical optical imaging. Our proposed method, which we named CylinGCN, adopts a novel learnable framework that extracts semantic features and complex topological relationships in the 3D volumetric data to achieve continuous and effective 3D segmentation. Our CylinGCN consists of a multiscale 3D semantic feature extractor for extracting inter-frame multiscale semantic features, and a residual graph convolutional network (GCN) contour generator that combines the semantic features and cylindrical topological priors to generate segmentation contours. We tested the CylinGCN framework on two types of optical tomographic imaging data, small animal whole body photoacoustic tomography (PAT) and endoscopic airway optical coherence tomography (OCT), and the results show that CylinGCN achieves state-of-the-art performance. Code will be released at https://github.com/lzc-smu/CylinGCN.git.

Efficacy of Augmented Reality Combined with Indocyanine Green Fluorescence Imaging Guided Laparoscopic Segmentectomy for Hepatocellular Carcinoma.

BACKGROUND: The internal anatomy of the liver is extremely complex. Laparoscopic anatomical segmentectomy requires reference to the position and alignment of intrahepatic vascular. However, the surface of the liver lacks anatomical landmarks and the liver segment boundaries cannot be identified with the naked eye. Augmented reality navigation (ARN) and indocyanine green fluorescence imaging (FI) are emerging navigation tools in liver resection. This study aimed to explore the efficacy and application value of laparoscopic anatomical segmentectomy guided by ARN combined with indocyanine green FI. STUDY DESIGN: Ninety-eight patients who were diagnosed with hepatocellular carcinoma and underwent laparoscopic anatomical segmentectomy from January 2018 to January 2022 were retrospectively analyzed. They were divided into the ARN-FI group (45 patients) and the non-ARN-FI group (53 patients) based on whether ARN combined with FI was applied during the operation. The differences in intraoperative and postoperative outcomes were compared. RESULTS: There was no significant difference in preoperative baseline data and postoperative complication rates between the 2 groups. Compared with the non-ARN-FI group, the ARN-FI group had much lower intraoperative blood loss (100 vs 200 mL, p = 0.005) and a lower incidence of remnant liver ischemia (13.3% vs 30.2%, p = 0.046). The 1- and 3-year disease-free survival rates in the ARN-FI and non-ARN-FI groups were 91.01% vs 71.15% and 70.01% vs 52.46%, respectively; the differences between the 2 groups were statistically significant (p = 0.047). CONCLUSIONS: The ARN-FI technology provides a more standardized approach for liver parenchyma section during laparoscopic liver resection, effectively minimizing intraoperative blood loss, reducing postoperative remnant liver ischemia, and improving oncological prognosis. This method is safe and feasible and has good clinical application prospects.

NIR-II Photoacoustic Imaging-Guided Oxygen Delivery and Controlled Release Improves Photodynamic Therapy for Hepatocellular Carcinoma.

Hypoxia, a prominent hallmark of hepatocellular carcinoma (HCC), undermines curative outcomes, elevates recurrence rates, and fosters metastasis, particularly during photodynamic therapy (PDT) in clinical settings. Studies indicate that alleviating tumor hypoxia enhances PDT efficacy. However, persistent challenges, including suboptimal oxygen delivery efficiency and absence of real-time feedback on blood oxygen fluctuations during PDT, considerably impede therapeutic efficacy in tumor treatment. This study addresses these issues using near-infrared-II (NIR-II) photoacoustic (PA) imaging for tumor-targeted oxygen delivery and controlled release. For this purpose, a biomimetic oxygen delivery system designated BLICP@O2 is developed, which utilizes hybrid tumor cell membranes and thermosensitive liposomes as oxygen carriers, incorporating the NIR-II dye IR1048, photosensitizer chlorin e6 (Ce6), and perfluorohexane. Upon sequential irradiation at 1064 and 690 nm, BLICP@O2 exhibits significant photothermal and photodynamic effects. Photothermal heating triggers oxygen release, enhancing the photodynamic effect of Ce6. Blood oxygen changes during PDT are tracked by multispectral PA imaging. Enhanced PDT efficacy, mediated by hypoxia relief, is convincingly demonstrated both in vitro and in vivo. This work presents an imaging-guided, dual-wavelength programmed cascaded treatment strategy for tumor-targeted oxygen delivery and controlled release, with real-time efficacy monitoring using PA imaging, offering valuable insights for overcoming challenges in PDT-based cancer therapy.

Unsupervised Fusion of Misaligned PAT and MRI Images via Mutually Reinforcing Cross-Modality Image Generation and Registration.

Photoacoustic tomography (PAT) and magnetic resonance imaging (MRI) are two advanced imaging techniques widely used in pre-clinical research. PAT has high optical contrast and deep imaging range but poor soft tissue contrast, whereas MRI provides excellent soft tissue information but poor temporal resolution. Despite recent advances in medical image fusion with pre-aligned multimodal data, PAT-MRI image fusion remains challenging due to misaligned images and spatial distortion. To address these issues, we propose an unsupervised multi-stage deep learning framework called PAMRFuse for misaligned PAT and MRI image fusion. PAMRFuse comprises a multimodal to unimodal registration network to accurately align the input PAT-MRI image pairs and a self-attentive fusion network that selects information-rich features for fusion. We employ an end-to-end mutually reinforcing mode in our registration network, which enables joint optimization of cross-modality image generation and registration. To the best of our knowledge, this is the first attempt at information fusion for misaligned PAT and MRI. Qualitative and quantitative experimental results show the excellent performance of our method in fusing PAT-MRI images of small animals captured from commercial imaging systems.

A Light-Powered Liquid Crystal Elastomer Roller.

Achieving and controlling the desired movements of active machines is generally accomplished through precise control of artificial muscles in a distributed and serialized manner, which is a significant challenge. The emerging motion control strategy based on self-oscillation in active machines has unique advantages, including directly harvesting energy from constant ambient light, and it has no need for complex controllers. Inspired by the roller, we have innovatively developed a self-rolling roller that consists of a roller and a liquid crystal elastomer (LCE) fiber. By utilizing a well-established dynamic LCE model and subjecting it to constant illumination, we have investigated the dynamic behavior of the self-rolling roller. Based on numerical calculations, it has been discovered that the roller, when subjected to steady illumination, exhibits two distinct motion regimes: the static regime and the self-rolling regime. The self-rolling regime, characterized by continuous periodic rolling, is sustained by the interaction between light energy and damping dissipation. The continuous periodic rolling observed in the self-rolling regime is maintained through the interplay between the dissipation of damping and the absorption of light energy. In the static state, the rolling angle of the roller begins to decrease rapidly and then converges to zero. Detailed investigations have been conducted to determine the critical conditions required to initiate self-rolling, as well as the essential system parameters that influence its frequency and amplitude. The proposed self-rolling roller has superiorities in its simple structure, light weight, alternative to manual labor, and speediness. This advancement is expected to inspire greater design diversity in micromachines, soft robotics, energy harvesters, and similar areas.

Symmetric Kondo Lattice States in Doped Strained Twisted Bilayer Graphene.

We use the topological heavy fermion (THF) model and its Kondo lattice (KL) formulation to study the possibility of a symmetric Kondo (SK) state in twisted bilayer graphene. Via a large-N approximation, we find a SK state in the KL model at fillings ν=0,±1,±2 where a KL model can be constructed. In the SK state, all symmetries are preserved and the local moments are Kondo screened by the conduction electrons. At the mean-field level of the THF model at ν=0,±1,±2,±3 we also find a similar symmetric state that is adiabatically connected to the symmetric Kondo state. We study the stability of the symmetric state by comparing its energy with the ordered (symmetry-breaking) states found in [H. Hu et al., Phys. Rev. Lett. 131, 026502 (2023).PRLTAO0031-900710.1103/PhysRevLett.131.026502, Z.-D. Song and B. A. Bernevig, Phys. Rev. Lett. 129, 047601 (2022).PRLTAO0031-900710.1103/PhysRevLett.129.047601] and find the ordered states to have lower energy at ν=0,±1,±2. However, moving away from integer fillings by doping the light bands, our mean-field calculations find the energy difference between the ordered state and the symmetric state to be reduced, which suggests the loss of ordering and a tendency toward Kondo screening. In order to include many-body effects beyond the mean-field approximation, we also performed dynamical mean-field theory calculations on the THF model in the nonordered phase. The spin susceptibility follows a Curie behavior at ν=0,±1,±2 down to ∼2 K where the onset of screening of the local moment becomes visible. This hints to very low Kondo temperatures at these fillings, in agreement with the outcome of our mean-field calculations. At noninteger filling ν=±0.5,±0.8,±1.2 dynamical mean-field theory shows deviations from a 1/T susceptibility at much higher temperatures, suggesting a more effective screening of local moments with doping. Finally, we study the effect of a C_{3z}-rotational-symmetry-breaking strain via mean-field approaches and find that a symmetric phase (that only breaks C_{3z} symmetry) can be stabilized at sufficiently large strain at ν=0,±1,±2. Our results suggest that a symmetric Kondo phase is strongly suppressed at integer fillings, but could be stabilized either at noninteger fillings or by applying strain.

Augmented Reality Navigation Plus Indocyanine Green Fluorescence Imaging Can Accurately Guide Laparoscopic Anatomical Segment 8 Resection.

BACKGROUND: Laparoscopic anatomical Segment 8 (S8) resection is a highly challenging hepatectomy. Augmented reality navigation (ARN), which could be combined with indocyanine green (ICG) fluorescence imaging, has been applied in various complex liver resections and may also be applied in laparoscopic anatomical S8 resection. However, no study has explored how to apply ARN plus ICG fluorescence imaging (ARN-FI) in laparoscopic anatomical S8 resection, or explored its accuracy. PATIENTS AND METHODS: This study is a post hoc analysis that included 31 patients undergoing laparoscopic anatomical S8 resection from the clinical NaLLRFI trial, and the resected liver volume was measured in each patient. The perioperative parameters of safety and feasibility, as well as the accuracy analysis outcomes were compared. RESULTS: There were 16 patients in the ARN-FI group and 15 patients underwent conventional laparoscopic hepatectomy without ARN or fluorescence imaging (non-ARN-FI group). There was no significant difference in baseline characteristics between the two groups. Compared with the non-ARN-FI group, the ARN-FI group had lower intraoperative bleeding (median 125 vs. 300 mL, P = 0.003). No significant difference was observed in other postoperative short-term outcomes. Accuracy analysis indicated that the actual resected liver volume (ARLV) in the ARN-FI group was more accurate. CONCLUSIONS: ARN-FI was associated with less intraoperative bleeding and more accurate resection volume. These techniques may address existing challenges and provide rational guidance for laparoscopic anatomical S8 resection.

Kondo Lattice Model of Magic-Angle Twisted-Bilayer Graphene: Hund's Rule, Local-Moment Fluctuations, and Low-Energy Effective Theory.

We apply a generalized Schrieffer-Wolff transformation to the extended Anderson-like topological heavy fermion (THF) model for the magic-angle (θ=1.05°) twisted bilayer graphene (MATBLG) [Phys. Rev. Lett. 129, 047601 (2022)PRLTAO0031-900710.1103/PhysRevLett.129.047601], to obtain its Kondo lattice limit. In this limit localized f electrons on a triangular lattice interact with topological conduction c electrons. By solving the exact limit of the THF model, we show that the integer fillings ν=0,±1,±2 are controlled by the heavy f electrons, while ν=±3 is at the border of a phase transition between two f-electron fillings. For ν=0,±1,±2, we then calculate the Ruderman-Kittel-Kasuya-Yosida (RKKY) interactions between the f moments in the full model and analytically prove the SU(4) Hund's rule for the ground state which maintains that two f electrons fill the same valley-spin flavor. Our (ferromagnetic interactions in the) spin model dramatically differ from the usual Heisenberg antiferromagnetic interactions expected at strong coupling. We show the ground state in some limits can be found exactly by employing a positive semidefinite "bond-operators" method. We then compute the excitation spectrum of the f moments in the ordered ground state, prove the stability of the ground state favored by RKKY interactions, and discuss the properties of the Goldstone modes, the (reason for the accidental) degeneracy of (some of) the excitation modes, and the physics of their phase stiffness. We develop a low-energy effective theory for the f moments and obtain analytic expressions for the dispersion of the collective modes. We discuss the relevance of our results to the spin-entropy experiments in TBG.

Coupled topological flat and wide bands: Quasiparticle formation and destruction.

Flat bands amplify correlation effects and are of extensive current interest. They provide a platform to explore both topology in correlated settings and correlation physics enriched by topology. Recent experiments in correlated kagome metals have found evidence for strange-metal behavior. A major theoretical challenge is to study the effect of local Coulomb repulsion when the band topology obstructs a real-space description. In a variant to the kagome lattice, we identify an orbital-selective Mott transition in any system of coupled topological flat and wide bands. This was made possible by the construction of exponentially localized and Kramers-doublet Wannier functions, which, in turn, leads to an effective Kondo-lattice description. Our findings show how quasiparticles are formed in such coupled topological flat-wide band systems and, equally important, how they are destroyed. Our work provides a conceptual framework for the understanding of the existing and emerging strange-metal properties in kagome metals and beyond.

Genomic, transcriptomic, and epigenomic analysis of a medicinal snake, Bungarus multicinctus, to provides insights into the origin of Elapidae neurotoxins.

The many-banded krait, Bungarus multicinctus, has been recorded as the animal resource of JinQianBaiHuaShe in the Chinese Pharmacopoeia. Characterization of its venoms classified chief phyla of modern animal neurotoxins. However, the evolutionary origin and diversification of its neurotoxins as well as biosynthesis of its active compounds remain largely unknown due to the lack of its high-quality genome. Here, we present the 1.58 Gbp genome of B. multicinctus assembled into 18 chromosomes with contig/scaffold N50 of 7.53 Mbp/149.8 Mbp. Major bungarotoxin-coding genes were clustered within genome by family and found to be associated with ancient local duplications. The truncation of glycosylphosphatidylinositol anchor in the 3'-terminal of a LY6E paralog released modern three-finger toxins (3FTxs) from membrane tethering before the Colubroidea divergence. Subsequent expansion and mutations diversified and recruited these 3FTxs. After the cobra/krait divergence, the modern unit-B of ß-bungarotoxin emerged with an extra cysteine residue. A subsequent point substitution in unit-A enabled the ß-bungarotoxin covalent linkage. The B. multicinctus gene expression, chromatin topological organization, and histone modification characteristics were featured by transcriptome, proteome, chromatin conformation capture sequencing, and ChIP-seq. The results highlighted that venom production was under a sophisticated regulation. Our findings provide new insights into snake neurotoxin research, meanwhile will facilitate antivenom development, toxin-driven drug discovery and the quality control of JinQianBaiHuaShe.

UMRFormer-net: a three-dimensional U-shaped pancreas segmentation method based on a double-layer bridged transformer network.

Background: Methods based on the combination of transformer and convolutional neural networks (CNNs) have achieved impressive results in the field of medical image segmentation. However, most of the recently proposed combination segmentation approaches simply treat transformers as auxiliary modules which help to extract long-range information and encode global context into convolutional representations, and there is a lack of investigation on how to optimally combine self-attention with convolution. Methods: We designed a novel transformer block (MRFormer) that combines a multi-head self-attention layer and a residual depthwise convolutional block as the basic unit to deeply integrate both long-range and local spatial information. The MRFormer block was embedded between the encoder and decoder in U-Net at the last two layers. This framework (UMRFormer-Net) was applied to the segmentation of three-dimensional (3D) pancreas, and its ability to effectively capture the characteristic contextual information of the pancreas and surrounding tissues was investigated. Results: Experimental results show that the proposed UMRFormer-Net achieved accuracy in pancreas segmentation that was comparable or superior to that of existing state-of-the-art 3D methods in both the Clinical Proteomic Tumor Analysis Consortium Pancreatic Ductal Adenocarcinoma (CPTAC-PDA) dataset and the public Medical Segmentation Decathlon dataset (self-division). UMRFormer-Net statistically significantly outperformed existing transformer-related methods and state-of-the-art 3D methods (P<0.05, P<0.01, or P<0.001), with a higher Dice coefficient (85.54% and 77.36%, respectively) or a lower 95% Hausdorff distance (4.05 and 8.34 mm, respectively). Conclusions: UMRFormer-Net can obtain more matched and accurate segmentation boundary and region information in pancreas segmentation, thus improving the accuracy of pancreas segmentation. The code is available at https://github.com/supersunshinefk/UMRFormer-Net.

Perioperative and Disease-Free Survival Outcomes after Hepatectomy for Centrally Located Hepatocellular Carcinoma Guided by Augmented Reality and Indocyanine Green Fluorescence Imaging: A Single-Center Experience.

BACKGROUND: Laparoscopic hepatectomy for centrally located hepatocellular carcinoma is challenging to perform. Augmented reality navigation (ARN) and fluorescence imaging are currently safe and reproducible techniques for hepatectomy, but the efficacy results for centrally located hepatocellular carcinoma have not been reported. This study aimed to evaluate the efficacy of an ARN system combined with fluorescence imaging (ARN-FI) in laparoscopic hepatectomy for centrally located hepatocellular carcinoma. STUDY DESIGN: This was a post hoc analysis of an original nonrandomized clinical trial that was designed to evaluate the feasibility and efficacy of ARN-FI for laparoscopic liver resection. A total of 76 patients were consecutively enrolled from June 2018 to June 2021, of which 42 underwent laparoscopic hepatectomy using ARN-FI (ARN-FI group), and the other 34 who did not use ARN-FI guidance (non-ARN-FI group). Perioperative outcomes and disease-free survival were compared between the 2 groups. RESULTS: Compared with the non-ARN-FI group, the ARN-FI group had less intraoperative blood loss (median 275 vs 300 mL, p = 0.013), lower intraoperative transfusion rate (14.3% vs 64.7%, p < 0.01), shorter postoperative hospital stay (median 8 vs 9 days, p = 0.005), and lower postoperative complication rate (35.7% vs 61.8%, p = 0.024). There was no death in the perioperative period and follow-up period. There was no significant difference in overall disease-free survival between the 2 groups (p = 0.16). CONCLUSIONS: The ARN system and fluorescence imaging may be of value in improving the success rate of surgery, reducing postoperative complications, accelerating postoperative recovery, and shortening postoperative hospital stay.

How does mandatory energy conversion affect sustainable development: Perspectives of regional heterogeneity and efficiency decomposition.

Clean energy conversion is a core approach and development trend to tackle climate change, while the severe drawbacks such as supply deficiency and cost increase restrict regional sustainable development. This paper employs a natural experiment of coal-to-gas conversion of the Chinese government to study the effect of such policy on regional sustainable development, as well as the underlying mechanism. Based on a city-level dataset from 2006 to 2019, this paper measure green total factor productivity (GTFP) using data envelopment analysis (DEA) combined with the Malmquist‒Luenberger productivity index. Then, this paper evaluates the impact of the CTG policy in pilot cities using the Difference-in-Difference (DID) with Propensity Score Matching (PSM) approach. This paper finds that the CTG policy increased the GTFP of the pilot cities by 2.25% (0.0229/1.02). A series of robustness tests confirmed the findings. Subsequent mechanism analysis shows that the CTG policy increases the GTFP of pilot cities mainly by increasing technical efficiency. In addition, the mechanism of the CTG policy's impact differs between central and noncentral cities. In particular, the CTG policy increases the technological innovation indicator (TC) of provincial capital cities by 2.35% while it increases the technical efficiency indicator (EC) of other cities by 1.89%, which proves the Porter effect in provincial capital cities. Finally, several implications are provided for policymakers to promote other types of renewable energy.

Revisiting the gravity laws of inter-city mobility in megacity regions.

Inter-city mobility is one of the most important issues in the UN Sustainable Development Goals, as it is essential to access the regional labour market, goods and services, and to constrain the spread of infectious diseases. Although the gravity model has been proved to be an effective model to describe mobility among settlements, knowledge is still insufficient in regions where dozens of megacities interact closely and over 100 million people reside. In addition, the existing knowledge is limited to overall population mobility, while the difference in inter-city travel with different purposes is unexplored on such a large geographic scale. We revisited the gravity laws of inter-city mobility using the 2.12 billion trip chains recorded by 40.48 million mobile phone users' trajectories in the Jing-Jin-Ji Region, which contains China's capital Beijing. Firstly, unlike previous studies, we found that non-commuting rather than commuting is the dominant type of inter-city mobility (89.3%). Non-commuting travellers have a travel distance 42.3% longer than commuting travellers. Secondly, we developed more accurate gravity models for the spatial distribution of inter-city commuting and non-commuting travel. We also found that inter-city mobility has a hierarchical structure, as the distribution of inter-city travel volume follows Zipf's law. In particular, the hierarchy of non-commuting travel volume among the cities is more in line with an ideal Zipf distribution than commuting travel. Our findings contribute to new knowledge on basic inter-city mobility laws, and they have significant applications for regional policies on human mobility.