Albumin-seeking dyes with adjustable assemblies in situ enable programmable imaging windows and targeting tumor imaging.

Cyanine dyes are widely used organic probes for in vivo imaging due to their tunable fluorescence. They can form complexes with endogenous albumin, resulting in enhanced brightness and photostability. However, this binding is uncontrollable and irreversible, leading to considerable nonspecific background signals and unregulated circulation time. Methods: Here, we connect varying numbers of 4-(4-iodophenyl) butanoic acid (IP) as albumin-binding moieties (ABM) to the cyanine dye, enabling dynamic and controllable binding with albumin. Meanwhile, we provide a blocking method to completely release the dye from covalent capture with albumin, resulting in specific targeting fluorescence. Furthermore, we evaluate the pharmacokinetics and tumor targeting of the developed dyes. Results: The engineered dyes can dynamically and selectively bind with multiple albumins to change the in situ size of assemblies and circulation time, providing programmable regulation over the imaging time window. The nucleophilic substitution of meso-Cl with water-soluble amino acids or targeting peptides for IP-engineered dye further addresses the nonspecific signals caused by albumin, allowing for adjustable angiography time and efficient tumor targeting. Conclusion: This study rationalizes the binding modes of dyes and proteins, applicable to a wide range of near-infrared (NIR) dyes for improving their in vivo molecular imaging.

Functions of nonsuicidal self-injury and repeated nonsuicidal self-injury among adolescents: A moderating role of addictive features.

OBJECTIVE: The high prevalence and addictive features of nonsuicidal self-injury (NSSI) in adolescents have been documented, but the role of addictive features in the process from NSSI functions to behaviour remains unclear. The major aim of this study was to investigate the effect of addictive features on NSSI functions and the severity of repeated NSSI. METHODS: A total of 10,781 students from primary and middle schools in Chengdu and Karamay were invited to participate in the online cross-sectional survey, and 10,501 completed the survey. Two self-report questionnaires, the Ottawa Self-Injury Inventory (OSI) and the Adolescent Self-Harm Scale (ASHS), were used to collect data from all participants. RESULTS: Among the students, 23.45% and 6.64% reported having engaged in NSSI at least once or at least five times in the past year. Being a girl, being an only child, and being in a single-parent family were significantly associated with more severe NSSI. Addictive features have high value for predicting repeated NSSI. In addition to their significant independent/direct additive effects, addictive features mediated and moderated the relationship between NSSI functions and increased severity of NSSI in adolescents. DISCUSSION AND CONCLUSIONS: The findings suggest that addictive features play a critical role in the development of repeated NSSI in adolescents, which indicates that addiction models may partially explain the mechanism underlying increased severity of NSSI. This may enhance understanding of the reasons for repeated NSSI and inform interventions for repeated NSSI among adolescents.

A combined nanotherapeutic approach targeting farnesoid X receptor, ferroptosis, and fibrosis for nonalcoholic steatohepatitis treatment.

Obeticholic acid (OCA), a farnesoid X receptor (FXR) agonist with favorable effects on fatty and glucose metabolism, has been considered the leading candidate drug for nonalcoholic steatohepatitis (NASH) treatment. However, its limited effectiveness in resolving liver fibrosis and lipotoxicity-induced cell death remains a major drawback. Ferroptosis, a newly recognized form of cell death characterized by uncontrolled lipid peroxidation, is involved in the progression of NASH. Nitric oxide (NO) is a versatile biological molecule that can degrade extracellular matrix. In this study, we developed a PEGylated thiolated hollow mesoporous silica nanoparticles (MSN) loaded with OCA, as well as a ferroptosis inhibitor liproxsatin-1 and a NO donor S-nitrosothiol (ONL@MSN). Biochemical analyses, histology, multiplexed flow cytometry, bulk-tissue RNA sequencing, and fecal 16S ribosomal RNA sequencing were utilized to evaluate the effects of the combined nanoparticle (ONL@MSN) in a mouse NASH model. Compared with the OCA-loaded nanoparticles (O@MSN), ONL@MSN not only protected against hepatic steatosis but also greatly ameliorated fibrosis and ferroptosis. ONL@MSN also displayed enhanced therapeutic actions on the maintenance of intrahepatic macrophages/monocytes homeostasis, inhibition of immune response/lipid peroxidation, and correction of microbiota dysbiosis. These findings present a promising synergistic nanotherapeutic strategy for the treatment of NASH by simultaneously targeting FXR, ferroptosis, and fibrosis.

Discovery of common molecular signatures and drug repurposing for COVID-19/Asthma comorbidity: ACE2 and multi-partite networks.

Angiotensin-converting enzyme 2 (ACE2) is identified as the functional receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the ongoing global coronavirus disease-2019 (COVID-19) pandemic. This study aimed to elucidate potential therapeutic avenues by scrutinizing approved drugs through the identification of the genetic signature associated with SARS-CoV-2 infection in individuals with asthma. This exploration was conducted through an integrated analysis, encompassing interaction networks between the ACE2 receptor and common host (co-host) factors implicated in COVID-19/asthma comorbidity. The comprehensive analysis involved the identification of common differentially expressed genes (cDEGs) and hub-cDEGs, functional annotations, interaction networks, gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), and module construction. Interaction networks were used to identify overlapping disease modules and potential drug targets. Computational biology and molecular docking analyzes were utilized to discern functional drug modules. Subsequently, the impact of the identified drugs on the expression of hub-cDEGs was experimentally validated using a mouse model. A total of 153 cDEGs or co-host factors associated with ACE2 were identified in the COVID-19 and asthma comorbidity. Among these, seven significant cDEGs and proteins - namely, HRAS, IFNG, JUN, CDH1, TLR4, ICAM1, and SCD-were recognized as pivotal host factors linked to ACE2. Regulatory network analysis of hub-cDEGs revealed eight top-ranked transcription factors (TFs) proteins and nine microRNAs as key regulatory factors operating at the transcriptional and post-transcriptional levels, respectively. Molecular docking simulations led to the proposal of 10 top-ranked repurposable drug molecules (Rapamycin, Ivermectin, Everolimus, Quercetin, Estradiol, Entrectinib, Nilotinib, Conivaptan, Radotinib, and Venetoclax) as potential treatment options for COVID-19 in individuals with comorbid asthma. Validation analysis demonstrated that Rapamycin effectively inhibited ICAM1 expression in the HDM-stimulated mice group (p < 0.01). This study unveils the common pathogenesis and genetic signature underlying asthma and SARS-CoV-2 infection, delineated by the interaction networks of ACE2-related host factors. These findings provide valuable insights for the design and discovery of drugs aimed at more effective therapeutics within the context of lung disease comorbidities.

Urban professionals' restorative tourism: exploring the role of perceived environmental restorativeness, push and pull motivations and destination attributes on tourism expectations.

Introduction: Urban professionals often seek respite from their daily routines through restorative tourism, driven by a complex interplay of motivations that include both internal "push" factors and external "pull" factors. This study investigates the intricate relationship between the perceived environmental restorativeness of tourist destinations and the expectations of urban professionals engaging in restorative tourism. Furthermore, it examines how push and pull motivations mediate this relationship while also considering the moderating effect of destination attributes. Methods: The multiple regression analyses on the survey data collected from 221 urban professionals with restorative tourism experiences provided quantitative evidence regarding the hypothesized relationships among perceived environmental restorativeness, push and pull motivations, destination attributes, and tourism expectations. Results: The results showed that perceived environmental restorativeness has a positive effect on urban professionals' tourism expectations; urban professionals' pull motivation and push motivation each play a mediating role between perceived environmental restorativeness and tourist expectations; and restorative tourism destination attributes have a moderating effect between perceived environmental restorativeness and push motivation, as well as the relationship between perceived environmental restorativeness and pull motivation. Discussion: This study provides essential theoretical contributions to restorative tourism and practical implications when designing restorative tourism destinations that target urban professionals.

Design of composite puncture blood collection system and research on puncture force.

Venous blood collection testing is one of the most commonly used medical diagnostic methods. Compared with conventional venous blood collection, robotic collection can reduce needle-stick injuries, medical staff workload, and infection risk; allow doctor-patient isolation; and improve collection reliability. Existing venous blood collection robots use rigid puncture needles, which can easily puncture the lower wall of blood vessels, causing vessel damage and collection failure. This paper proposes a bionic blood collection strategy based on a composite puncture needle that mimics the structure and function of mosquito mouthparts. A bionic composite puncture needle insertion system with puncture-force sensing was designed, and venipuncture forces were simulated and mathematically modelled. A prototype insertion system was built and used in an experiment, which demonstrated effective composite puncture blood collection and explored the factors influencing puncture force. Puncture force decreases with increased puncture speed and angle and with a decreased needle diameter. This provides a basis for optimising the parameters of blood collection robots.

Mapping structural covariance networks of emotional withdrawal symptoms in males with methamphetamine use disorder during abstinence.

Individuals with methamphetamine use disorder (MUD) often experience anxiety and depressive symptoms during abstinence, which can worsen the likelihood of relapse. Thus, it is essential to understand the neuro-mechanism behind methamphetamine use and its associated emotional withdrawal symptoms in order to develop effective clinical strategies. This study aimed to evaluate associations between emotional withdrawal symptoms and structural covariance networks (SCNs) based on cortical thickness (CTh) across the brain. The CTh measures were obtained from Tl-weighted MRI data from a sample of 48 males with MUD during abstinence and 48 male healthy controls. The severity of anxiety and depressive symptoms was assessed by the Hamilton Anxiety Scale (HAMA) and depression (HAMD) scales. Two important nodes belonging to the brain reward system, the right rostral anterior cingulate cortex (rACC) and medial prefrontal cortex (medPFC), were selected as seeds to conduct SCNs and modulation analysis by emotional symptoms. MUDs showed higher structural covariance between the right rACC and regions in the dorsal attention, right frontoparietal, auditory, visual and limbic networks. They also displayed higher structural covariance between the right medPFC and regions in the limbic network. Moreover, the modulation analysis showed that higher scores on HAMA were associated with increased covariance between the right rACC and the left parahippocampal and isthmus cingulate cortex in the default mode network. These outcomes shed light on the complex neurobiological mechanisms underlying methamphetamine use and its associated emotional withdrawal symptoms and may provide new insights into the development of effective treatments for MUD.

Using machine learning to develop a five-item short form of the children's depression inventory.

BACKGROUND: Many adolescents experience depression that often goes undetected and untreated. Identifying children and adolescents at a high risk of depression in a timely manner is an urgent concern. While the Children's Depression Inventory (CDI) is widely utilized in China, it lacks a localized revision or simplified version. With its 27 items requiring professional administration, the original CDI proves to be a time-consuming method for predicting children and adolescents with high depression risk. Hence, this study aimed to develop a shortened version of the CDI to predict high depression risk, thereby enhancing the efficiency of prediction and intervention. METHODS: Initially, backward elimination is conducted to identify various version of the short-form scales (e.g., three-item and five-item versions). Subsequently, the performance of five machine learning (ML) algorithms on these versions is evaluated using the area under the ROC curve (AUC) to determine the best algorithm. The chosen algorithm is then utilized to model the short-form scales, facilitating the identification of the optimal short-form scale based on predefined evaluation metrics. Following this, evaluation metrics are computed for all potential decision thresholds of the optimal short-form scale, and the threshold value is determined. Finally, the reliability and validity of the optimal short-form scale are assessed using a new sample. RESULTS: The study identified a five-item short-form CDI with a decision threshold of 4 as the most appropriate scale considering all assessment indicators. The scale had 81.48% fewer items than the original version, indicating good predictive performance (AUC = 0.81, Accuracy = 0.83, Recall = 0.76, Precision = 0.71). Based on the test of 315 middle school students, the results showed that the five-item CDI had good measurement indexes (Cronbach's alpha = 0.72, criterion-related validity = 0.77). CONCLUSIONS: This five-item short-form CDI is the first shortened and revised version of the CDI in China based on large local data samples.

Manipulation of Electronic Effect and Assembly Architecture to Invoke Oxidation of Ethylbenzene by Hierarchical Co3O4 Wreaths.

A high-performance transition-metal oxide catalyst can be designed by appropriately integrating the concepts of morphology regulation and electronic structure modulation. In this work, hierarchical Co3O4 wreaths (CCW) enriched with oxygen vacancies (Ov) were facilely constructed for the selective oxidation of ethylbenzene (EB) to acetophenone (AP). Under the screened optimal reaction conditions, the CCW catalyst can offer a 79.1% conversion of EB (ri = 0.244 mol gcat-1 h-1) accompanied by a selectivity of 92.3% to AP. The good reaction performance can be attributed to the cooperation of defect engineering and architecture design, which can synergistically facilitate the EB oxidation performance by augmenting the intrinsic reactivity and accessibility of active sites. This work presents a reliable route to construct a high-performance transitional metal oxide catalyst via manipulation of electronic effect and assembly architecture for the selective oxidation of EB and beyond.

Biomimetic NIR-II fluorescent proteins created from chemogenic protein-seeking dyes for multicolor deep-tissue bioimaging.

Near-infrared-I/II fluorescent proteins (NIR-I/II FPs) are crucial for in vivo imaging, yet the current NIR-I/II FPs face challenges including scarcity, the requirement for chromophore maturation, and limited emission wavelengths (typically < 800 nm). Here, we utilize synthetic protein-seeking NIR-II dyes as chromophores, which covalently bind to tag proteins (e.g., human serum albumin, HSA) through a site-specific nucleophilic substitution reaction, thereby creating proof-of-concept biomimetic NIR-II FPs. This chemogenic protein-seeking strategy can be accomplished under gentle physiological conditions without catalysis. Proteomics analysis identifies specific binding site (Cys 477 on DIII). NIR-II FPs significantly enhance chromophore brightness and photostability, while improving biocompatibility, allowing for high-performance NIR-II lymphography and angiography. This strategy is universal and applicable in creating a wide range of spectrally separated NIR-I/II FPs for real-time visualization of multiple biological events. Overall, this straightforward biomimetic approach holds the potential to transform fluorescent protein-based bioimaging and enables in-situ albumin targeting to create NIR-I/II FPs for deep-tissue imaging in live organisms.

Site-specific albumin tagging with NIR-II fluorogenic dye for high-performance and super-stable bioimaging.

Synthetic near-infrared-II (NIR-II) dyes are promising for deep tissue imaging, yet they are generally difficult to target a given biomolecule with high specificity. Furthermore, the interaction mechanism between albumin and cyanine molecules, which is usually regarded as uncertain "complexes" such as crosslinked nanoparticles, remains poorly understood. Methods: Here, we propose a new class of NIR-II fluorogenic dyes capable of site-specific albumin tagging for in situ albumin seeking/targeting or constructing high-performance cyanine@albumin probes. We further investigate the interaction mechanism between NIR-II fluorogenic dyes and albumin. Results: We identify CO-1080 as an optimal dye structure that produces a stable/bright NIR-II cyanine@albumin probe. CO-1080 exhibits maximum supramolecular binding affinity to albumin while catalyzing their covalent attachment. The probe shows exact binding sites located on Cys476 and Cys101, as identified by proteomic analysis and docking modeling. Conclusion: Our cyanine@albumin probe substantially improves the pharmacokinetics of its free dye counterpart, enabling high-performance NIR-II angiography and lymphography. Importantly, the site-specific labeling tags between NIR-II fluorogenic dyes and albumin occur under mild conditions, offering a specific and straightforward synthesis strategy for NIR-II fluorophores in the fields of targeting bioimaging and imaging-guided surgery.

Progress in the Elimination of Organic Contaminants in Wastewater by Activation Persulfate over Iron-Based Metal-Organic Frameworks.

The release of organic contaminants has grown to be a major environmental concern and a threat to the ecology of water bodies. Persulfate-based Advanced Oxidation Technology (PAOT) is effective at eliminating hazardous pollutants and has an extensive spectrum of applications. Iron-based metal-organic frameworks (Fe-MOFs) and their derivatives have exhibited great advantages in activating persulfate for wastewater treatment. In this article, we provide a comprehensive review of recent research progress on the significant potential of Fe-MOFs for removing antibiotics, organic dyes, phenols, and other contaminants from aqueous environments. Firstly, multiple approaches for preparing Fe-MOFs, including the MIL and ZIF series were introduced. Subsequently, removal performance of pollutants such as antibiotics of sulfonamides and tetracyclines (TC), organic dyes of rhodamine B (RhB) and acid orange 7 (AO7), phenols of phenol and bisphenol A (BPA) by various Fe-MOFs was compared. Finally, different degradation mechanisms, encompassing free radical degradation pathways and non-free radical degradation pathways were elucidated. This review explores the synthesis methods of Fe-MOFs and their application in removing organic pollutants from water bodies, providing insights for further refining the preparation of Fe-MOFs.

Coupled Interface and Oxygen-Defect Engineering in Co3O4/CoMoO4 Heterostructures toward Active Oxidation of Ethylbenzene.

The catalytic oxidation of ethylbenzene (EB) is a promising route to produce acetophenone (AcPO). Unfortunately, it remains a great challenge to achieve the highly efficient oxidation of EB under solvent-free conditions using molecular oxygen as the sole oxidant. In this contribution, we present a facile strategy to construct hierarchical oxygen vacancy-rich Co3O4/CoMoO4 heterostructures (Vö-CCMO), which delivers a high yield value of 74.5% at 83.2% conversion of EB and selectivity of 89.6% to AcPO. Both experimental studies and theoretical calculations substantiate the important role of oxygen-defect engineering triggered by the modified chemistry environment at the interfaces between the biphasic phases, which contributes to the good catalytic performance. This work illustrates a promising paradigm for the exploit of advanced catalysts toward boosting EB oxidation reaction in a more practical way.

Alterations in the brain functional network of abstinent male individuals with methamphetamine use disorder.

Methamphetamine is a highly addictive psychostimulant drug that is abused globally and is a serious threat to health worldwide. Unfortunately, the specific mechanism underlying addiction remains unclear. Thus, this study aimed to investigate the characteristics of functional connectivity in the brain network and the factors influencing methamphetamine use disorder in patients using magnetic resonance imaging. We included 96 abstinent male participants with methamphetamine use disorder and 46 age- and sex-matched healthy controls for magnetic resonance imaging. Compared with healthy controls, participants with methamphetamine use disorder had greater impulsivity, fewer small-world attributes of the resting-state network, more nodal topological attributes in the cerebellum, greater functional connectivity strength within the cerebellum and between the cerebellum and brain, and decreased frontoparietal functional connectivity strength. In addition, after controlling for covariates, the partial correlation analysis showed that small-world properties were significantly associated with methamphetamine use frequency, psychological craving, and impulsivity. Furthermore, we revealed that the small-word attribute significantly mediated the effect of methamphetamine use frequency on motor impulsivity in the methamphetamine use disorder group. These findings may further improve our understanding of the neural mechanism of impulse control dysfunction underlying methamphetamine addiction and assist in exploring the neuropathological mechanism underlying methamphetamine use disorder-related dysfunction and rehabilitation.

Pro-ferroptotic signaling promotes arterial aging via vascular smooth muscle cell senescence.

Senescence of vascular smooth muscle cells (VSMCs) contributes to aging-related cardiovascular diseases by promoting arterial remodelling and stiffness. Ferroptosis is a novel type of regulated cell death associated with lipid oxidation. Here, we show that pro-ferroptosis signaling drives VSMCs senescence to accelerate vascular NAD+ loss, remodelling and aging. Pro-ferroptotic signaling is triggered in senescent VSMCs and arteries of aged mice. Furthermore, the activation of pro-ferroptotic signaling in VSMCs not only induces NAD+ loss and senescence but also promotes the release of a pro-senescent secretome. Pharmacological or genetic inhibition of pro-ferroptosis signaling, ameliorates VSMCs senescence, reduces vascular stiffness and retards the progression of abdominal aortic aneurysm in mice. Mechanistically, we revealed that inhibition of pro-ferroptotic signaling facilitates the nuclear-cytoplasmic shuttling of proliferator-activated receptor-γ and, thereby impeding nuclear receptor coactivator 4-ferrtin complex-centric ferritinophagy. Finally, the activated pro-ferroptotic signaling correlates with arterial stiffness in a human proof-of-concept study. These findings have significant implications for future therapeutic strategies aiming to eliminate vascular ferroptosis in senescence- or aging-associated cardiovascular diseases.

Trends and driving forces of agricultural carbon emissions: A case study of Anhui, China.

To facilitate accurate prediction and empirical research on regional agricultural carbon emissions, this paper uses the LLE-PSO-XGBoost carbon emission model, which combines the Local Linear Embedding (LLE), Particle Swarm Algorithm (PSO) and Extreme Gradient Boosting Algorithm (XGBoost), to forecast regional agricultural carbon emissions in Anhui Province under different scenarios. The results show that the regional agricultural carbon emissions in Anhui Province generally show an upward and then downward trend during 2000-2021, and the regional agricultural carbon emissions in Anhui Province in 2030 are expected to fluctuate between 11,342,100 tones and 14,445,700 tones under five different set scenarios. The projections of regional agricultural carbon emissions can play an important role in supporting the development of local regional agriculture, helping to guide the input and policy guidance of local rural low-carbon agriculture and promoting the development of rural areas towards a resource-saving and environment-friendly society.

GPNMB promotes peripheral nerve regeneration by activating the Erk1/2 and Akt pathways via binding Na+/K+-ATPase α1 in Schwann cells.

Glycoprotein non-metastatic melanoma protein B (GPNMB) is ubiquitously expressed and has protective effects on the central nervous system. In particular, it is also expressed in the peripheral nervous system (PNS) and upregulated after peripheral nerve injury. However, the role and underlying mechanism of GPNMB in the PNS, especially in peripheral nerve regeneration (PNR), are still unknown and need to be further investigated. In this study, recombinant human GPNMB (rhGPNMB) was injected into a sciatic nerve injury model. It was found that rhGPNMB facilitated the regeneration and functional recovery of the injured sciatic nerve in vivo. Moreover, it was also confirmed that GPNMB activated the Erk1/2 and Akt pathways via binding with Na+/K + -ATPase α1 (NKA α1) and promoted the proliferation and migration of Schwann cells (SCs) and their expression and secretion of neurotrophic factors and neural adhesion molecules in vitro. Our findings demonstrate that GPNMB facilitates PNR through activation of the Erk1/2 and Akt pathways in SCs by binding with NKA α1 and may be a novel strategy for PNR.

Sample size calculation for multi-arm parallel design with restricted mean survival time.

With the recent advances in oncology treatment, restricted mean survival time (RMST) is increasingly being used to replace the routine approach based on hazard ratios in randomized controlled trials for time-to-event outcomes. While RMST has been widely applied in single-arm and two-arm designs, challenges still exist in comparing RMST in multi-arm trials with three or more groups. In particular, it is unclear in the literature how to compare more than one intervention simultaneously or perform multiple testing based on RMST, and sample size determination is a major obstacle to its penetration to practice. In this paper, we propose a novel method of designing multi-arm clinical trials with right-censored survival endpoint based on RMST that can be applied in both phase II/III settings using a global χ2 test as well as a modeling-based multiple comparison procedure. The framework provides a closed-form sample size formula built upon a multi-arm global test and a sample size determination procedure based on multiple-comparison in the phase II dose-finding study. The proposed method enjoys strong robustness and flexibility as it requires less a priori set-up than conventional work, and obtains a smaller sample size while achieving the target power. In the assessment of sample size, we also incorporate practical considerations, including the presence of non-proportional hazards and staggered patient entry. We evaluate the validity of our method through simulation studies under various scenarios. Finally, we demonstrate the accuracy and stability of our method by implementing it in the design of two real clinical trial examples.

3D reconstruction of bone CT scan images based on deformable convex hull.

Three-dimensional (3D) reconstruction of computed tomography (CT) and magnetic resonance imaging (MRI) images is an important diagnostic method, which is helpful for doctors to clearly recognize the 3D shape of the lesion and make the surgical plan. In the study of medical image reconstruction, most researchers use surface rendering or volume rendering method to construct 3D models from image sequences. The watertightness of the algorithm-reconstructed surface will be affected by the segmentation precision or the thickness of the CT layer. The articular surfaces at femoral ends are often used in biomechanical simulation experiments. The model may not conform to its original shape due to the manual repair of non-watertight surfaces. To solve this problem, a 3D reconstruction method of leg bones based on deep learning is proposed in this paper. By deforming the convex hull of the target, comparing with state-of-the-art methods, our method can stably generate a watertight model with higher reconstruction accuracy. In the situation of target transition structures getting fuzzy and the layer spacing increasing, the proposed method can maintain better reconstruction performance and appear higher robustness. Also, the chamfer loss is optimized based on the rotational shape of the leg bones, and the weight of the loss function can be assigned according to the geometric characteristics of the target. Experiment results show that the optimization method improves the accuracy of the model. Furthermore, our research provides a reference for the application of deep learning in medical image reconstruction.