Definition Of Function Research Articles

Accelerating full-waveform inversion using source stacking: synthetic experiments at the global scale in a realistic 3-D earth model

SUMMARY The spectral element method is currently the method of choice for computing accurate synthetic seismic wavefields in realistic 3-D earth models at the global scale. However, it requires significantly more computational time, compared to normal mode-based approximate methods. Source stacking, whereby multiple earthquake sources are aligned on their origin time and simultaneously triggered, can reduce the computational costs by several orders of magnitude. We present the results of synthetic tests performed on a realistic radially anisotropic 3-D model, slightly modified from model SEMUCB-WM1 with three component synthetic waveform ‘data’ for a duration of 10 000 s, and filtered at periods longer than 60 s, for a set of 273 events and 515 stations. We consider two definitions of the misfit function, one based on the stacked records at individual stations and another based on station-pair cross-correlations of the stacked records. The inverse step is performed using a Gauss–Newton approach where the gradient and Hessian are computed using normal mode perturbation theory. We investigate the retrieval of radially anisotropic long wavelength structure in the upper mantle in the depth range 100–800 km, after fixing the crust and uppermost mantle structure constrained by fundamental mode Love and Rayleigh wave dispersion data. The results show good performance using both definitions of the misfit function, even in the presence of realistic noise, with degraded amplitudes of lateral variations in the anisotropic parameter ξ. Interestingly, we show that we can retrieve the long wavelength structure in the upper mantle, when considering one or the other of three portions of the cross-correlation time series, corresponding to where we expect the energy from surface wave overtone, fundamental mode or a mixture of the two to be dominant, respectively. We also considered the issue of missing data, by randomly removing a successively larger proportion of the available synthetic data. We replace the missing data by synthetics computed in the current 3-D model using normal mode perturbation theory. The inversion results degrade with the proportion of missing data, especially for ξ, and we find that a data availability of 45 per cent or more leads to acceptable results. We also present a strategy for grouping events and stations to minimize the number of missing data in each group. This leads to an increased number of computations but can be significantly more efficient than conventional single-event-at-a-time inversion. We apply the grouping strategy to a real picking scenario, and show promising resolution capability despite the use of fewer waveforms and uneven ray path distribution. Source stacking approach can be used to rapidly obtain a starting 3-D model for more conventional full-waveform inversion at higher resolution, and to investigate assumptions made in the inversion, such as trade-offs between isotropic, anisotropic or anelastic structure, different model parametrizations or how crustal structure is accounted for.

New Definition of Fractional Analytic Functions

New Definition of Fractional Analytic Functions

Comparison and analysis of various deep learning models for super-resolution reconstruction of turbulent flows

Single image super-resolution (SR) has become a promising research topic, with many deep learning-based models invented to reconstruct high-fidelity high-resolution (HR) images from low-resolution (LR) images. Motivated by a large amount of turbulent flow field data collected by experimental measurements and numerical simulation, researchers begin investigating the application of these data-driven deep learning models to conduct SR reconstruction of LR flow field data. Due to the limitations of experimental equipment and computing power, sometimes researchers can only obtain LR data. However, deep learning models can quickly reconstruct HR spatial-temporal turbulent data from LR data so that researchers can easily conduct further qualitative and quantitative analyses. This article reviews the development of flow field data SR reconstruction models and the problems encountered from the two aspects of network structure and loss function definition. Finally, we propose the research direction of applying the conditional generative adversarial network (cGAN) to turbulent flow SR reconstruction since seldom study has been conducted in this field.

Exotic C⁎-algebras of geometric groups

We consider a new class of potentially exotic group C*-algebras C⁎(PFp⁎(G)) for a locally compact group G, and its connection with the class of potentially exotic group C*-algebras CLp⁎(G) introduced by Brown and Guentner. Surprisingly, these two classes of C*-algebras are intimately related. By exploiting this connection, we show CLp⁎(G)=C⁎(PFp⁎(G)) for p∈(2,∞), and the C*-algebras CLp⁎(G) are pairwise distinct for p∈(2,∞) when G belongs to a large class of nonamenable groups possessing the Haagerup property and either the rapid decay property or Kunze-Stein phenomenon by characterizing the positive definite functions that extend to positive linear functionals of CLp⁎(G) and C⁎(PFp⁎(G)). This greatly generalizes earlier results of Okayasu (see [30]) and the second author (see [40]) on the pairwise distinctness of CLp⁎(G) for 2<p<∞ when G is either a noncommutative free group or the group SL(2,R), respectively.As a byproduct of our techniques, we present two applications to the theory of unitary representations of a locally compact group G. Firstly, we give a short proof of the well-known Cowling-Haagerup-Howe Theorem, which presents sufficient condition implying the weak containment of a cyclic unitary representation of G in the left regular representation of G (see [14]). Also we give a near solution to a 1978 conjecture of Cowling stated in [10]. This conjecture of Cowling states if G is a Kunze-Stein group and π is a unitary representation of G with cyclic vector ξ such that the mapG∋s↦〈π(s)ξ,ξ〉 belongs to Lp(G) for some 2<p<∞, then Aπ⊆Lp(G). We show Bπ⊆Lp+ϵ(G) for every ϵ>0 (recall Aπ⊆Bπ).

Catalyzing Cooling Tower Efficiency: A Novel Energy Performance Indicator and Functional Unit Including Climate and Cooling Demand Normalization

Energy and climate targets necessitate efficiency indicators to reflect resource-saving potentials. Prevailing indicators for cooling towers, however, often omit the effect of outside conditions. Hence, this study introduces an innovative indicator grounded in the energy efficiency ratio. Our proposed metric is the cost–benefit ratio between electricity demand and the thermodynamic minimum airflow. Thus, we call the novel indicator the airflow performance indicator. To validate its feasibility, we apply the indicator first to an extensive dataset encompassing 6575 cooling tower models and second to a year-long case study involving a data center’s wet cooling system. As a result, the energy performance indicator demonstrates that dry cooling requires eight times more minimum airflow at the median than evaporative cooling would, directly correlating to the fan power. Furthermore, efficiency benchmarks derived from the dataset of 6575 cooling tower models provide a comparative assessment of the case study. Defining the quantified benefit as minimum airflow additionally underscores the limitations of free cooling as the wet cooling system only partly covers the cooling demand, requiring chillers additionally. In conclusion, the indicator empowers the identification of energy-saving potentials in the selection, design, and operation of cooling towers. Moreover, the functional unit definition provides a foundation for future life cycle assessments of cooling towers, enhancing cooling tower efficiency and sustainability.

Adaptive prescribed finite-time asymptotic tracking control for switched systems with unknown initial conditions and full-state constraints

In this paper, an adaptive prescribed finite-time asymptotic tracking control problem is considered for the unknown nonlinear switched systems with unknown initial conditions and full-state constraints. A class of nonlinear mappings (NMs) and a new prescribed finite-time performance function (PFTPF) are introduced so that the control design is independent of initial conditions of the controlled states. Based on the neural network approximation approach, NMs, PFTPF and the Barbalat's lemma, an adaptive prescribed finite-time asymptotic tracking controller with full-state constraints is obtained. To avoid overlarge initial control input, the design method with zero initial control input is adopted, the definition of input tuning function (ITF) is expanded and its effectiveness is proved theoretically. As results, the full-state constraints and the boundedness of all the signals in the closed-loop system are guaranteed, and the tracking error of the system can converge to zero asymptotically. Finally, the effectiveness and superiority of the proposed scheme are verified by the simulation results.

Seismic differential semblance-oriented migration velocity analysis — Status and the way forward

Differential semblance optimization (DSO) is a seismic waveform inversion approach. It has been developed to remove the limitation of conventional full-waveform inversion as a velocity model building tool when only reflected waves are available. It has connections with migration velocity analysis (MVA) techniques defined in the image domain to build macrovelocity models, with a split between the macromodel and the small-scale heterogeneities. Among the various DSO approaches, DSO-MVA has unique characteristics for velocity model building of complex structures, while ensuring the convergence to the global minimum in a local optimization approach: the wavefields are computed with the two-way wave equation operators, focusing panels are built in a survey-sinking mode, and the quality of the macrovelocity model is evaluated on common-image gathers in the subsurface-offset domain through a differential annihilator. We review the significant aspects that have been better understood over the past 15 years and discuss the way forward. The first identified issue has been the imprint of the small-scale heterogeneities on the macromodel update that is revealed with the use of wave equation-based Green’s functions and an ad hoc solution is subsequently developed by slightly modifying the definition of the objective function. A second important aspect has been the development of efficient approaches to compute the required quantitative migration based on approximate inverses to replace the previously used migrations. The issue of correctly interpreting the amplitudes has also moved into one of an improved model parameterization, i.e., from constant-density acoustics media to full acoustic media as a path toward fully viscoelastic media. Finally, we discuss the way forward with the challenges of extending DSO-MVA beyond the single scattering approximation, for processing diving waves and multiples, and also the challenge of numerical implementation, which remains critical even in two dimensions, for applicability to large-scale real data.

Outcomes of coronal pulpotomy on permanent first molars in children: a retrospective cohort study.

To investigate the survival probability of permanent first molars (PFMs) after coronal pulpotomy (CP) using two outcome definitions: success-focused and functional survival-focused, and to identify factors influencing tooth survival. A retrospective cohort study reviewing records of children undergoing CP with calcium silicate-based cements (CSCs) on PFMs. Each CP-treated PFM was classified as success, uncertain, failure, or censored. Survival probability was analyzed using Kaplan-Meier estimators. Success-focused definition considered failures and uncertain outcomes as events, while functional survival-focused definition considered only failures as events. Prognostic factors were analyzed using Cox regression analysis. Seventy-seven CP-treated PFMs with a follow-up period of 6-111months. Using the success-focused definition (two failures and 12 uncertain outcomes as events), survival probabilities were 93.1% (95% CI 84.3-97.1%) at 12months, 78.7% (95% CI 65.6-87.3%) at 36months, and 74.9% (95% CI 59.5-89.0%) at 60-111months. However, with the functional survival-focused definition, survival probabilities were 100% at 12months and 96.6% (95% CI 86.9-99.1%) at 24-111months. In multivariable analysis, proximal lesions increased failure risk compared to occlusal lesions (HR 17.17, 95% CI 2.18-135.31, p < 0.01), and resin composite restorations had higher failure risk than stainless steel crowns (HR 13.97, 95% CI 1.49-130.69, p < 0.05). CP using CSCs shows long-term survival potential as an alternative treatment for cariously exposed PFMs in children. Proximal lesions and resin composite restoration could contribute to the lower survival, indicating the need for careful consideration of restoration options and lesion location during treatment planning.

Semantic enrichment of building functions through geospatial data integration and ontological inference

The comprehensive definition of buildings in urban spatial databases (SDBs) and geographic information systems (GISs) is crucial for city management, considering their essential role in cities. Modern urban geospatial applications such as smart cities need a rich-information infrastructure, relying upon urban SDBs and GISs, powered by multiple data sources. In this respect, many geospatial techniques are available for acquiring geometric data of buildings, but their semantic definitions require extra effort. Today, volunteered geographic information (VGI) platforms are assumed to be alternative geospatial data sources and their integration with official datasets provides a new opportunity for the enrichment of urban geospatial datasets. In this context, geospatial semantic web technologies can contribute to the semantic enrichment process. This study presents a methodology for enriching various building datasets using GIS and geospatial semantic web technologies, enabling an enhanced definition of building functions. The proposed method makes use of an OpenStreetMap (OSM) dataset to obtain missing semantic information about building features. The enrichment process was implemented by transferring OSM point of interest (POI) values to associated OSM building features through the application of semantic web rule language (SWRL) rules. Furthermore, the same process was also applied to two additional official datasets at different levels of detail (TOPO1K and TOPO25K), which were subsequently incorporated into the geospatial ontology. The resulting geospatial ontology offers new opportunities for functional definition and logical rule-making for buildings, with the potential to uncover new classes and insights. In addition, it allows for the definition of terms and explanations in multiple languages, covering most of the OSM values used worldwide for selected tags to define building functions.

Overlapping Graph Clustering in Attributed Networks via Generalized Cluster Potential Game

Overlapping graph clustering is essential to understand the nature and behavior of real complex systems including human interactions, technical systems and transportation network. However, in addition of topological structure, many real-world networked systems contain spare factors, i.e., attributes of networks. Despite the considerable efforts that have been made in graph clustering, they only concentrate on the topological structure, which lack a profound understanding of cluster configuration on attributed graphs. To address this great challenge, in this article, we propose a new overlapping graph clustering algorithm by integrating the topological and attributive information into a cluster potential game (CPG). Firstly, a generalized definition of the utility function is provided, which measures the payoff of each node based on different node-to-cluster distance functions. It is worth mentioning that the model we proposed is able to associate with the classic ordinal potential game well. Then, we define the measures of both tightness and the homogeneity in each cluster, and introduce a novel two-way selection mechanism. The goal is to extend the flexibility of the cluster potential game, so that one can achieve a win-win situation between nodes and clusters. Finally, a distributed and heterogeneous multiagent system (DHMAS) is carefully designed based on a fast self-learning algorithm (SLA) for attributed overlapping graph clustering. Two series of experiments are implemented in multi-types datasets and the results verify the effectiveness and the scalability after the comparison with the most advanced approaches of literature.

Synthesizing Specifications

Every program should be accompanied by a specification that describes important aspects of the code's behavior, but writing good specifications is often harder than writing the code itself. This paper addresses the problem of synthesizing specifications automatically, guided by user-supplied inputs of two kinds: i) a query posed about a set of function definitions, and ii) a domain-specific language L in which the extracted property is to be expressed (we call properties in the language L-properties). Each of the property is a best L-property for the query: there is no other L-property that is strictly more precise. Furthermore, the set of synthesized L-properties is exhaustive: no more L-properties can be added to it to make the conjunction more precise. We implemented our method in a tool, Spyro. The ability to modify both the query and L provides a Spyro user with ways to customize the kind of specification to be synthesized. We use this ability to show that Spyro can be used in a variety of applications, such as mining program specifications, performing abstract-domain operations, and synthesizing algebraic properties of program modules.

The Communicative Function of Legal Transplants in Mixed Legal Systems

The article analyzes the definition of the communicative function of law from the point of view of legal communication between the dependent legal systems of the former colonies. In this context, the “evergreen issue” arises about legal transplantation, the legal transfer of norms and institutions and reception of nomadic legal constructs. The modern comparative lexicon uses three types of metaphors related to the interaction of legal systems and their law hybridization: anthropomorphic, communicative and mechanical metaphors. Among the best-known cases of legal transplantation, the authors pay attention to the spread of codes, the diffusion of common law, and the emergence of mixed legal systems. They explore the positivist concept of “legal transplants,” which appeared in comparative discourse thanks to the theory of Alan Watson. The article discusses the comparative opposition to this theory — the so-called cultural concept of legal transplants (transferists vs. culturalist debate), as well as the musical metaphor “legal transposition” and the process of diffusion of law in dependent legal systems. The practice of legal transplants in mixed common law systems and their application in practice are analyzed in national jurisdictions. The article shows criminal legal bijuridism and the process of the so-called “diffuse codification” in India, Canada, Australia and other British former colonies, which is an example of codistics communication of dissimilar political and legal cultures and circulation of model codes between them. In conclusion, attention is drawn to the discourse of the effectiveness, applicability and effectiveness of transplants. It is concluded that the success — failure discourse of legal transplants depends on the degree of communicativeness of transplanted and receptive constructs, their ability to “speak” in an understandable language for the host cultural environment of law.

Functional and ecological diversification of underground organs in Solanum.

The evolution of geophytes in response to different environmental stressors is poorly understood largely due to the great morphological variation in underground plant organs, which includes species with rhizomatous structures or underground storage organs (USOs). Here we compare the evolution and ecological niche patterns of different geophytic organs in Solanum L., classified based on a functional definition and using a clade-based approach with an expert-verified specimen occurrence dataset. Results from PERMANOVA and Phylogenetic ANOVAs indicate that geophytic species occupy drier areas, with rhizomatous species found in the hottest areas whereas species with USOs are restricted to cooler areas in the montane tropics. In addition, rhizomatous species appear to be adapted to fire-driven disturbance, in contrast to species with USOs that appear to be adapted to prolonged climatic disturbance such as unfavorable growing conditions due to drought and cold. We also show that the evolution of rhizome-like structures leads to changes in the relationship between range size and niche breadth. Ancestral state reconstruction shows that in Solanum rhizomatous species are evolutionarily more labile compared to species with USOs. Our results suggest that underground organs enable plants to shift their niches towards distinct extreme environmental conditions and have different evolutionary constraints.

Rotating Target Detection Method of Concrete Bridge Crack Based on YOLO v5

Crack detection is a critical and essential aspect of concrete bridge maintenance and management. Manual inspection often falls short in meeting the demands of large-scale crack detection in terms of cost, efficiency, accuracy, and data management. To address the challenges faced by existing generic object detection algorithms in achieving high accuracy or efficiency when detecting cracks with large aspect ratios, overlapping structures, and clear directional characteristics, this paper presents improvements to the YOLO v5 model. These enhancements include the introduction of angle regression variables, the definition of a new loss function, the integration of PSA-Neck and ECA-Layer attention mechanism modules into the network architecture, consideration of the contribution of each node’s features to the network, and the addition of skip connections within the same feature scale. This results in a novel crack image rotation object detection algorithm named “R-YOLO v5”. After training the R-YOLO v5 model for 300 iterations on a dataset comprising 1628 crack images, the model achieved an mAP@0.5 of 94.03% on the test set, which is significantly higher than other rotation object detection algorithms such as SASM, S2A Net, Re Det, as well as the horizontal-box YOLO v5 model. Furthermore, R-YOLO v5 demonstrates clear advantages in terms of model size (4.17 MB) and detection speed (0.01 s per image). These results demonstrate that the designed model effectively detects cracks in concrete bridges and exhibits robustness, minimal memory usage, making it suitable for real-time crack detection on small devices like smartphones or drones. Additionally, the rotation object detection improvement strategy discussed in this study holds potential applicability for enhancing other object detection algorithms.

Probability thermodynamics and probability quantum field

We introduce probability thermodynamics and probability quantum fields. By probability we mean that there is an unknown operator, physical or nonphysical, whose eigenvalues obey a certain statistical distribution. Eigenvalue spectra define spectral functions. Various thermodynamic quantities in thermodynamics and effective actions in quantum field theory are all spectral functions. In the scheme, eigenvalues obey a probability distribution, so a probability distribution determines a family of spectral functions in thermodynamics and quantum field theory. This leads to probability thermodynamics and probability quantum fields determined by a probability distribution. In constructing spectral functions, we encounter a problem. The conventional definition of spectral functions applies only to lower bounded spectra. In our scheme, however, there are two types of spectra: lower bounded spectra, corresponding to the probability distribution with nonnegative random variables, and the lower unbounded spectra, corresponding to probability distributions with negative random variables. To take the lower unbounded spectra into account, we generalize the definition of spectral functions by analytical continuation. In some cases, we encounter divergences. We remove the divergence by a renormalization procedure. In virtue of spectral theory in physics, we generalize some concepts in probability theory. For example, the moment-generating function in probability theory does not always exist. We redefine the moment-generating function as the generalized heat kernel introduced in this paper, which makes the concept definable when the definition in probability theory fails. We construct examples corresponding to some probability distributions. Thermodynamic quantities, vacuum amplitudes, one-loop effective actions, and vacuum energies for various probability distributions are presented.

The development and validation of the experiential avoidance rating scale (EARS): A self-report questionnaire that might actually measure experiential avoidance

Serious concerns have been raised regarding the validity of popular experiential avoidance measures. We developed a new “experiential avoidance rating scale” (EARS) to address some of the psychometric concerns with existing measures. Candidate items were generated according to the original functional contextual definition of experiential avoidance and reviewed by experts and public members for content validity and readability. Items then underwent validation involving n = 3628 participants. Exploratory factor analyses (n = 1069) identified six items with good underlying common variance. Confirmatory factor analyses from college student (n = 1068) and community samples (n = 1413) demonstrated excellent fit. In all samples, the EARS demonstrated evidence of content, factorial, concurrent, convergent, and discriminant validity. The EARS also demonstrated evidence of incremental validity by predicting significant additional variance above-and-beyond neuroticism and extant experiential avoidance measures in depression, anxiety, post-traumatic stress, alcohol use problems, and general mental health measures. Measurement invariance analyses indicated that the EARS demonstrated residual (strict) invariance between cisgender men and women; clinical and non-clinical participants; White Non-Hispanic, White Hispanic, Black, and Asian participants; and heterosexual and bisexual individuals. We suggest that the EARS be further investigated as a brief measure of experiential avoidance in additional studies, particularly with clinical populations. We also discuss areas of future psychometric study and implications.

Middle school students' development of an understanding of the concept of function using an applet with no algebraic representations

AbstractMiddle school students (n = 144) worked with an applet specially designed to introduce the concept of function without using algebraic representations. The purpose of the study was to examine whether the applet would help students understand function as a relationship between a set of inputs and a set of outputs and to begin to develop a definition of function based on that relationship. Results indicate that, by focusing on consistency of the outputs, the students, at a rate of approximately 80%, are able to distinguish functions from nonfunctions. Also, students showed some promise in recognizing constant functions as functions, a known area of common misconceptions. Students' main conceptual difficulty, likely caused by the context, was accepting nonintuitive outputs even if those outputs were consistent.

Compound learning adaptive neural network optimal backstepping control of uncertain fractional-order predator–prey systems

Reinforcement learning as an effective strategy is widely utilized in optimal control. However, when updating critic–actor weight vectors based on the square of Bellman residual, it often leads to substantial computational complexity. This paper formulates a compound learning optimal backstepping control programme that can efficaciously reduce the computational burden for fractional-order predator–prey systems (FOPPS) with uncertainties. To economize resource, a reinforcement learning technology is adopted to realize the optimal control in view of neural networks under identifier–critic–actor structure. To address the computational complexity issue raised above, a simple positive definite function is proposed to update critic–actor weight vectors. Fractional-order filters are utilized to estimate virtual signals and their fractional-order derivatives for tackling the “explosion of complexity” problem existing in the conventional backstepping technology. Simultaneously, to enhance the approximation accuracy of uncertainties in FOPPS, a compound learning updating law is built by using tracking error and prediction error. In accordance with the stability analysis, the formulated scheme ensures that the output of FOPPS can track the reference signal with the expected accuracy and all signals are bounded. Eventually, a numerical simulation is presented to validate the effectiveness of the proposed control strategy.

Impairment and Disability Identity and Perceptions of Trust, Respect, and Fairness

Most studies use impaired functioning alone to specify populations with disabilities. However, some people with functional impairments do not identify as disabled. With functional status-based definitions, studies have shown disparate care quality for people with disabilities. To examine whether impairment and disability identity have different associations with perceived health care experiences and explore factors associated with disability identification. This cross-sectional study used a nationally representative survey of US adults conducted from April 20 through May 31, 2021, and analyzed between June 1 and August 31, 2022. Survey participants were 1822 English- or Spanish-speaking adults responding either online or via telephone. Using 8 survey questions, participants were grouped according to presence of impairment and disability identity. Likert scale measures of trust, respect, and fairness (henceforth, procedural justice measures) were dichotomized. Sociodemographic characteristics and rates of procedural justice responses were compared across groups. Multivariable logistic regressions adjusting for baseline characteristics were performed to (1) estimate associations of impairment and disability identity with perceptions of procedural justice and (2) explore factors associated with disability identification. Analyses applied survey weights. Of 6126 individuals invited to participate, 1854 (30.3%) completed the survey. Thirty-two were excluded due to unreportable gender, for a final analytic sample of 1822 participants. Participants with impairments (n = 816; mean [SD] age, 48.1 [17.0] years; 51.2% women, 48.8% men) had worse perceptions on 7 of 10 procedural justice measures (crude) compared with those without impairments (n = 1006; mean [SD] age, 49.6 [18.1] years, 55.1% female, 44.9% male). Among respondents with impairments, those who did (n = 340) vs did not (n = 476) identify as disabled gave better ratings for clinician communication efforts (a lot of effort, 38.8% vs 31.0%) and having health goals understood (understood very or fairly well, 77.2% vs 70.1%) but gave worse ratings for respect (almost never felt inferior or talked down to, 66.1% vs 59.1%). Disability identification was associated with more reports of unfair treatment (31.0% vs 22.4%; adjusted odds ratio, 1.65; 95% CI, 1.12-2.42) and of being unafraid to ask questions or disagree (50.5% vs 40.1%; adjusted odds ratio, 1.51; 95% CI, 1.04-20.19). Income and employment were associated with disability identification. In this cross-sectional survey study of US adults, health care perceptions differed between groups defined by impairment status and disability identity. These findings suggest that, alongside functional measures, health systems should capture disability identity to better address disparities for people with impairments.

Tissue adhesive indocyanine green-locking granular gel-mediated photothermal therapy combined with checkpoint inhibitor for preventing postsurgical recurrence and metastasis of colorectal cancer.

Developing effective therapy to inhibit postoperative recurrence and metastasis of colorectal cancer (CRC) is challenging and significant to reduce mortality and morbidity. Here, a granular hydrogel, assembled from gelatin microgels by dialdehyde starch and interpenetrated with in situ polymerized poly(sulfobetaine methacrylate-co-N-isopropylacrylamide) (P(SBMA-co-NIPAM)), is prepared to load and lock Food and Drug Administration (FDA)-approved indocyanine green (ICG) with definite photothermal function and biosafety for photothermal therapy (PTT) combining with checkpoint inhibitor. The presence of P(SBMA-co-NIPAM) endows granular hydrogel with high retention to water-soluble ICG, preventing easy diffusion and rapid scavenging of ICG. The ICG-locking granular hydrogel can be spread and adhered onto the surgery site at wet state in vivo, exerting a persistent and stable PTT effect. Combined with αPD-L1 treatment, ICG-locking granular hydrogel-mediated PTT can eradicate postsurgery residual and metastatic tumors, and prevent long-term tumor recurrence. Further mechanistic studies indicate that combination treatment effectively promotes dendritic cells maturation in lymph nodes, enhances the number and infiltration of CD8+ T and CD4+ T cells in tumor tissue, and improves memory T cell number in spleen, thus activating the antitumor immune response. Overall, ICG-locking gel-mediated PTT is expected to exhibit broad clinical applications in postoperative treatment of cancers, like CRC.