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Allogeneic chimeric antigen receptor (CAR)-T cells hold great promise for expanding the accessibility of CAR-T therapy, whereas the risks of allograft rejection have hampered its application. Here, we genetically engineered healthy-donor-derived, CD19-targeting CAR-T cells using CRISPR-Cas9 to address the issue of immune rejection and treated one patient with refractory immune-mediated necrotizing myopathy and two patients with diffuse cutaneous systemic sclerosis with these cells. This study was registered at ClinicalTrials.gov (NCT05859997). The infused cells persisted for over 3 months, achieving complete B cell depletion within 2 weeks of treatment. During the 6-month follow-up, we observed deep remission without cytokine release syndrome or other serious adverse events in all three patients, primarily shown by the significant improvement in the clinical response index scores for the two diseases, respectively, and supported by the observations of reversal of inflammation and fibrosis. Our results demonstrate the high safety and promising immune modulatory effect of the off-the-shelf CAR-T cells in treating severe refractory autoimmune diseases.
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Optical scatterometry, also referred to as optical critical dimension (OCD) metrology, is a widely used technique for characterizing nanostructures in semiconductor industry. As a model-based optical metrology, the measurement in optical scatterometry is not straightforward but involves solving a complicated inverse problem. So far, the methods for solving the inverse scattering problem, whether traditional or deep-learning-based, necessitate a predefined geometric model, but they are also constrained by this model with poor applicability. Here, we demonstrate a sketch-guided neural network (SGNN) for nanostructure reconstruction in optical scatterometry. By learning from training data based on the designed generic profile model, the neural network acquires not only scattering knowledge but also sketching techniques, that allows it to draw the profiles corresponding to the input optical signature, regardless of whether the sample structure is the same as the generic profile model or not. The accuracy and strong generalizability of proposed approach is validated by using a series of one-dimensional gratings. Experiments have also demonstrated that it is comparable to nonlinear regression methods and outperforms traditional deep learning methods. To our best knowledge, this is the first time that the concept of sketching has been introduced into deep learning for solving the inverse scattering problem. We believe that our method will provide a novel solution for semiconductor metrology, enabling fast and accurate reconstruction of nanostructures.
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Mask optimization, a compensation method for the thick mask effect and the optical proximity effect in projection lithography, is essential for advanced EUV-enabled production nodes. However, owing to high computation costs and the absence of gradient calculations, it is challenging to optimize EUV masks under rigorous consideration of the thick mask effect. In this work, a linearized EUV mask optimization method based on the adjoint method is proposed to provide fast and effective optimizations. The adjoint method is introduced to calculate the gradient of the EUV mask model. Additionally, a linearized gradient is proposed to quickly compensate for wafer pattern distortion caused by the prominent thick mask effect. Two examples of the EUV mask optimization implemented with a two-step strategy were provided, from which it was observed that the linearized gradient can improve the efficiency by about 40% in the coarse optimization step. The proposed method is promising for accurate full-chip EUV mask optimization.
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Channeled spectropolarimetry (CSP) has emerged as a notable technique due to its unique capacity to instantaneously measure either the polarization state of light or the Mueller matrix of a sample over a broad spectral range. Leveraging the quasi-linear relation between phase retardances of thick birefringent retarders and wavenumber, the target signal undergoes wavelength encoding. For the first time, we present a theoretical framework for the general CSP from a perspective of information theory. This framework comprehensively addresses the frequency properties of CSP, encompassing signal bandwidth, modulation frequency, sampling relationships, and filter window width during the demodulation process. Drawing from the frequency properties of CSP, we establish a theoretical foundation that informs the design of versatile CSPs and evaluates their measurement capabilities. Simulations for both Stokes CSP and Mueller CSP validate the efficacy of the proposed approach.
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In computational imaging and lithography, it has been a challenge for a numerical model to faithfully preserve symmetries in the physical imaging system. In this Letter, we present a project-to-symmetry-subspace (PTSS) method to prevent symmetry loss during the iterative generation of optical kernels. Essentially, PTSS is to project iterative vectors onto a predefined symmetric subspace when decomposing the transmission cross coefficient (TCC). Simulation results demonstrate the PTSS-generation of a truncated set of optical kernels that are substantially free of symmetry error, regardless of the order of truncation.
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BACKGROUND: Lung compliance, a biomarker of pulmonary fibrosis, is generally measured globally. Hyperpolarized 129Xe gas MRI offers the potential to evaluate lung compliance regionally, allowing for visualization of changes in lung compliance associated with fibrosis. PURPOSE: To assess global and regional lung compliance in a rat model of pulmonary fibrosis using hyperpolarized 129Xe gas MRI. STUDY TYPE: Prospective. ANIMAL MODEL: Twenty Sprague-Dawley male rats with bleomycin-induced fibrosis model (N = 10) and saline-treated controls (N = 10). FIELD STRENGTH/SEQUENCE: 7-T, fast low-angle shot (FLASH) sequence. ASSESSMENT: Lung compliance was determined by fitting lung volumes derived from segmented 129Xe MRI with an iterative selection method, to corresponding airway pressures. Similarly, lung compliance was obtained with computed tomography for cross-validation. Direction-dependencies of lung compliance were characterized by regional lung compliance ratios (R) in different directions. Pulmonary function tests (PFTs) and histological analysis were used to validate the pulmonary fibrosis model and assess its correlation with 129Xe lung compliance. STATISTICAL TESTS: Shapiro-Wilk tests, unpaired and paired t-tests, Mann-Whitney U and Wilcoxon signed-rank tests, and Pearson correlation coefficients. P < 0.05 was considered statistically significant. RESULTS: For the entire lung, the global and regional lung compliance measured with 129Xe gas MRI showed significant differences between the groups, and correlated with the global lung compliance measured using PFTs (global: r = 0.891; regional: r = 0.873). Additionally, for the control group, significant difference was found in mean regional compliance between areas, eg, 0.37 (0.32, 0.39) × 10-4 mL/cm H2O and 0.47 (0.41, 0.56) × 10-4 mL/cm H2O for apical and basal lung, respectively. The apical-basal direction R was 1.12 ± 0.09 and 1.35 ± 0.13 for fibrosis and control groups, respectively, indicating a significant difference. DATA CONCLUSION: Our findings demonstrate the feasibility of using hyperpolarized gas MRI to assess regional lung compliance. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.
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In this study, we proposed a method for fabricating Janus sheets using biological "microflowers" as a sacrificial template. The microflower-templated Janus sheets (MF-JNSs) were employed as a foam stabilizer in foam separation of the whey soybean protein (WSP). The MF-JNSs took inorganic hybrid microflowers (BSA@Cu3 (PO4)2-MF) as template, followed by the sequential attachment of protamine and silica to the surface of the BSA@Cu3(PO4)2-MF. Subsequently, the template was removed using ethylenediaminetetraacetic acid after the silicon dioxide was modified by 3-(methacryloyloxy) propyl trimethoxysilane. Upon template dissolution, the modified silica layer, lacking support from the core, fractured to form the MF-JNSs. This method omitted the step of treating the hollow ball by external force and obtained Janus sheets in one step, indicating that it was simple and feasible. The morphology, structure, and composition of the MF-JNSs were analyzed by SEM, TEM, AFM, XRD, and FT-IR. The MF-JNSs were found to delay the breakage time of the Pickering emulsion, demonstrating their emulsion stabilizing capability. Importantly, they significantly enhanced the foam half-life and foam height of soybean whey wastewater (SWW). Moreover, the recovery percentage and enrichment ratio of WSP, separated from SWW by foam separation, were improved to 81 ± 0.28 and 1.20 ± 0.05%, respectively.
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The current study presents a scalable approach for the preparation of temperature-responsive PEG/SiO2/PNIPAM-PEA Janus particles and, for the first time, investigates their potential applications in stabilizing foam and defoaming by adjusting the temperature. The method utilizes a (W1 + O)/W2 emulsion system, which incorporates appropriate surfactants to stabilize the emulsion and prevent rapid dissolution of the hydrophilic triblock polymer PEG-b-PTEPM-b-PNIPAM in water. The PEG/SiO2/PNIPAM-PEA Janus particles with temperature-responsive characteristics were synthesized in a single step that combined the sol-gel reaction and photoinduced free radical polymerization. The contact angle of the hydrophilic PEG/SiO2/PNIPAM surface was measured to be 54.7 ± 0.1°, while the contact angle of the hydrophobic PEA surface was found to be 122.4 ± 0.1°. By incorporating PEG/SiO2/PNIPAM-PEA Janus particles at a temperature of 25 °C, the foam's half-life is significantly prolonged from 42 s to nearly 30 min. However, with an increase in temperature to 50 °C, the foam's half-life rapidly diminished to only 44 s. This innovative application effectively enhances foam stabilization at low temperatures and facilitates the rapid dissipation of foam at high temperatures.
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Esophageal cancer (EC) is a familiar digestive tract tumor with highly lethal. The hypoxic environment has been demonstrated to be a significant factor in modulating malignant tumor progression and is strongly associated with the abnormal energy metabolism of tumor cells. Serine hydroxymethyl transferase 2 (SHMT2) is one of the most frequently expressed metabolic enzymes in human malignancies. The study was designed to investigate the biological functions and regulation mechanisms of SHMT2 in EC under hypoxia. We conducted RT-qPCR to assess SHMT2 levels in EC tissues and cells (TE-1 and EC109). EC cells were incubated under normoxia and hypoxia, respectively, and altered SHMT2 expression was evaluated through RT-qPCR, western blot, and immunofluorescence. The biological functions of SHMT2 on EC cells were monitored by performing CCK-8, EdU, transwell, sphere formation, glucose uptake, and lactate production assays. The SHMT2 protein lactylation was measured by immunoprecipitation and western blot. In addition, SHMT2-interacting proteins were analyzed by bioinformatics and validated by rescue experiments. SHMT2 was notably upregulated in EC tissues and cells. Hypoxia elevated SHMT2 protein expression, augmenting EC cell proliferation, migration, invasion, stemness, and glycolysis. In addition, hypoxia triggered lactylation of the SHMT2 protein and enhanced its stability. SHMT2 knockdown impeded the malignant phenotype of EC cells. Further mechanistic studies disclosed that SHMT2 is involved in EC progression by interacting with MTHFD1L. Hypoxia-induced SHMT2 protein lactylation and upregulated its protein level, which in turn enhanced MTHFD1L expression and accelerated the malignant progression of EC cells.
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OBJECTIVE: To comprehensively assess the impact of aging, cigarette smoking, and chronic obstructive pulmonary disease (COPD) on pulmonary physiology using 129Xe MR. METHODS: A total of 90 subjects were categorized into four groups, including healthy young (HY, n = 20), age-matched control (AMC, n = 20), asymptomatic smokers (AS, n = 28), and COPD patients (n = 22). 129Xe MR was utilized to obtain pulmonary physiological parameters, including ventilation defect percent (VDP), alveolar sleeve depth (h), apparent diffusion coefficient (ADC), total septal wall thickness (d), and ratio of xenon signal from red blood cells and interstitial tissue/plasma (RBC/TP). RESULTS: Significant differences were found in the measured VDP (p = 0.035), h (p = 0.003), and RBC/TP (p = 0.003) between the HY and AMC groups. Compared with the AMC group, higher VDP (p = 0.020) and d (p = 0.048) were found in the AS group; higher VDP (p < 0.001), d (p < 0.001) and ADC (p < 0.001), and lower h (p < 0.001) and RBC/TP (p < 0.001) were found in the COPD group. Moreover, significant differences were also found in the measured VDP (p < 0.001), h (p < 0.001), ADC (p < 0.001), d (p = 0.008), and RBC/TP (p = 0.032) between the AS and COPD groups. CONCLUSION: Our findings indicate that pulmonary structure and functional changes caused by aging, cigarette smoking, and COPD are various, and show a progressive deterioration with the accumulation of these risk factors, including cigarette smoking and COPD. CLINICAL RELEVANCE STATEMENT: Pathophysiological changes can be difficult to comprehensively understand due to limitations in common techniques and multifactorial etiologies. 129Xe MRI can demonstrate structural and functional changes caused by several common factors and can be used to better understand patients' underlying pathology. KEY POINTS: Standard techniques for assessing pathophysiological lung function changes, spirometry, and chest CT come with limitations. 129Xe MR demonstrated progressive deterioration with accumulation of the investigated risk factors, without these limitations. 129Xe MR can assess lung changes related to these risk factors to stage and evaluate the etiology of the disease.
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OBJECTIVES: To evaluate the value of CT-based whole lung radiomics nomogram for identifying the risk of cardiovascular disease (CVD) in patients with chronic obstructive pulmonary disease (COPD). MATERIALS AND METHODS: A total of 974 patients with COPD were divided into a training cohort (n = 402), an internal validation cohort (n = 172), and an external validation cohort (n = 400) from three hospitals. Clinical data and CT findings were analyzed. Radiomics features of whole lung were extracted from the non-contrast chest CT images. A radiomics signature was constructed with algorithms. Combined with the radiomics score and independent clinical factors, multivariate logistic regression analysis was used to establish a radiomics nomogram. ROC curve was used to analyze the prediction performance of the model. RESULTS: Age, weight, and GOLD were the independent clinical factors. A total of 1218 features were extracted and reduced to 15 features to build the radiomics signature. In the training cohort, the combined model (area under the curve [AUC], 0.731) showed better discrimination capability (p < 0.001) than the clinical factors model (AUC, 0.605). In the internal validation cohort, the combined model (AUC, 0.727) performed better (p = 0.032) than the clinical factors model (AUC, 0.629). In the external validation cohort, the combined model (AUC, 0.725) performed better (p < 0.001) than the clinical factors model (AUC, 0.690). Decision curve analysis demonstrated the radiomics nomogram outperformed the clinical factors model. CONCLUSION: The CT-based whole lung radiomics nomogram has the potential to identify the risk of CVD in patients with COPD. CLINICAL RELEVANCE STATEMENT: This study helps to identify cardiovascular disease risk in patients with chronic obstructive pulmonary disease on chest CT scans. KEY POINTS: ⢠To investigate the value of CT-based whole lung radiomics features in identifying the risk of cardiovascular disease in chronic obstructive pulmonary disease patients. ⢠The radiomics nomogram showed better performance than the clinical factors model to identify the risk of cardiovascular disease in patients with chronic obstructive pulmonary disease. ⢠The radiomics nomogram demonstrated excellent performance in the training, internal validation, and external validation cohort (AUC, 0.731; AUC, 0.727; AUC, 0.725).
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Enfermedades Cardiovasculares , Nomogramas , Enfermedad Pulmonar Obstructiva Crónica , Tomografía Computarizada por Rayos X , Humanos , Enfermedad Pulmonar Obstructiva Crónica/diagnóstico por imagen , Enfermedad Pulmonar Obstructiva Crónica/complicaciones , Masculino , Femenino , Tomografía Computarizada por Rayos X/métodos , Enfermedades Cardiovasculares/diagnóstico por imagen , Persona de Mediana Edad , Anciano , Medición de Riesgo/métodos , Pulmón/diagnóstico por imagen , Factores de Riesgo , Estudios Retrospectivos , RadiómicaRESUMEN
To improve the biodistribution of the drug in the tumor, a supramolecular prodrug of SN38 was fabricated in situ between endogenous albumin and SN38 prodrug modified with semaglutide side chain. Firstly, SN38 was conjugated with semaglutide side chain and octadecanedioic acid via glycine linkers to obtain SI-Gly-SN38 and OA-Gly-SN38 prodrugs, respectively. Both SI-Gly-SN38 and OA-Gly-SN38 exhibited excellent stability in PBS for over 24 h. Due to the strong binding affinity of the semaglutide side chain with albumin, the plasma half-life of SI-Gly-SN38 was 2.7 times higher than that of OA-Gly-SN38. Furthermore, with addition of HSA, the fluorescence intensity of SI-Gly-SN38 was 4 times higher than that of OA-Gly-SN38, confirming its strong binding capability with HSA. MTT assay showed that the cytotoxicity of SI-Gly-SN38 and OA-Gly-SN38 was higher than that of Irinotecan. Even incubated with HSA, the SI-Gly-SN38 and OA-Gly-SN38 still maintained high cytotoxicity, indicating minimal influence of HSA on their cytotoxicity. In vivo pharmacokinetic studies demonstrated that the circulation half-life of SI-Gly-SN38 was twice that of OA-Gly-SN38. SI-Gly-SN38 exhibited significantly reduced accumulation in the lungs, being only 0.23 times that of OA-Gly-SN38. The release of free SN38 in the lungs from SI-Gly-SN38 was only 0.4 times that from OA-Gly-SN38 and Irinotecan. The SI-Gly-SN38 showed the highest accumulation in tumors. The tumor inhibition rate of SI-Gly-SN38 was 6.42% higher than that of OA-Gly-SN38, and 8.67% higher than that of Irinotecan, respectively. These results indicate that the supramolecular prodrug delivery system can be constructed between SI-Gly-SN38 and endogenous albumin, which improves drug biodistribution in vivo, enhances tumor accumulation, and plays a crucial role in tumor growth inhibition.
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Irinotecán , Profármacos , Irinotecán/química , Irinotecán/farmacología , Profármacos/química , Profármacos/farmacología , Profármacos/síntesis química , Animales , Humanos , Ratones , Distribución Tisular , Antineoplásicos/química , Antineoplásicos/farmacología , Antineoplásicos/síntesis química , Antineoplásicos/farmacocinética , Estructura Molecular , Ensayos de Selección de Medicamentos Antitumorales , Proliferación Celular/efectos de los fármacos , Línea Celular Tumoral , Ratones Endogámicos BALB C , Ratones Desnudos , Albúminas/química , Masculino , Relación Estructura-Actividad , Albúmina Sérica Humana/química , Péptidos Similares al GlucagónRESUMEN
BACKGROUND: The present study aims to evaluate the postprocessing image quality of a deep-learning (DL)-based automatic bone removal algorithm in the real clinical practice for cervical computed tomography angiography (CTA). MATERIALS AND METHODS: A total of 100 patients (31 females, 61.4 ± 12.4 years old) who had performed cervical CTA from January 2022 to July 2022 were included retrospectively. Three different types of scanners were used. Ipsilateral cervical artery was divided into 10 segments. The performance of the DL algorithm and conventional algorithm in terms of bone removal and vascular integrity was independently evaluated by two radiologists for each segment. The difference in the performance between the two algorithms was compared. Inter- and intrarater consistency were assessed, and the correlation between the degree of carotid artery stenosis and the rank of bone removal and vascular integrity was analyzed. RESULTS: Significant differences were observed in the rankings of bone removal and vascular integrity between the two algorithms on most segments on both sides. Compared to DL algorithm, the conventional algorithm showed a higher correlation between the degree of carotid artery stenosis and vascular integrity (r = -0.264 vs r = -0.180). The inter- and intrarater consistency of DL algorithm were found to be higher than or equal to those of conventional algorithm. CONCLUSIONS: The DL algorithm for bone removal in cervical CTA demonstrated significantly better performance than conventional postprocessing method, particularly in the segments with complex anatomical structures and adjacent to bone.
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There is considerable interest in creating a precise and sensitive strategy for in situ visualizing and profiling intracellular miRNA. Present here is a novel photocaged amplified FRET nanoflare (PAFN), which spatiotemporal controls of mRNA-powered nanomachine for precise and sensitive miRNA imaging in live cells. The PAFN could be activated remotely by light, be triggered by specific low-abundance miRNA and fueled by high-abundance mRNA. It offers high spatiotemporal control over the initial activity of nanomachine at desirable time and site, and a 'one-to-more' ratiometric signal amplification model. The PAFN, an unprecedented design, is quiescent during the delivery process. However, upon reaching the interest tumor site, it can be selectively activated by light, and then be triggered by specific miRNA, avoiding undesirable early activation and reducing nonspecific signals, allowing precise and sensitive detection of specific miRNA in live cells. This strategy may open new avenues for creating spatiotemporally controllable and endogenous molecule-powered nanomachine, facilitating application at biological and medical imaging.
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Técnicas Biosensibles , MicroARNs , Diagnóstico por Imagen , Transferencia Resonante de Energía de Fluorescencia , MicroARNs/genética , ARN Mensajero/genéticaRESUMEN
Seed vigor significantly affects peanut breeding and agricultural yield by influencing seed germination and seedling growth and development. Traditional vigor testing methods are inadequate for modern high-throughput assays. Although hyperspectral technology shows potential for monitoring various crop traits, its application in predicting peanut seed vigor is still limited. This study developed and validated a method that combines hyperspectral technology with genome-wide association studies (GWAS) to achieve high-throughput detection of seed vigor and identify related functional genes. Hyperspectral phenotyping data and physiological indices from different peanut seed populations were used as input data to construct models using machine learning regression algorithms to accurately monitor changes in vigor. Model-predicted phenotypic data from 191 peanut varieties were used in GWAS, gene-based association studies, and haplotype analyses to screen for functional genes. Real-time fluorescence quantitative PCR (qPCR) was used to analyze the expression of functional genes in three high-vigor and three low-vigor germplasms. The results indicated that the random forest and support vector machine models provided effective phenotypic data. We identified Arahy.VMLN7L and Arahy.7XWF6F, with Arahy.VMLN7L negatively regulating seed vigor and Arahy.7XWF6F positively regulating it, suggesting distinct regulatory mechanisms. This study confirms that GWAS based on hyperspectral phenotyping reveals genetic relationships in seed vigor levels, offering novel insights and directions for future peanut breeding, accelerating genetic improvements, and boosting agricultural yields. This approach can be extended to monitor and explore germplasms and other key variables in various crops.
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Arachis , Estudio de Asociación del Genoma Completo , Fenotipo , Semillas , Arachis/genética , Arachis/crecimiento & desarrollo , Estudio de Asociación del Genoma Completo/métodos , Semillas/genética , Semillas/crecimiento & desarrollo , Polimorfismo de Nucleótido Simple , Sitios de Carácter Cuantitativo/genética , Fitomejoramiento/métodos , Regulación de la Expresión Génica de las Plantas , Sitios Genéticos , Imágenes Hiperespectrales/métodos , HaplotiposRESUMEN
DNA cascaded circuits have great potential in detecting low abundance molecules in complex biological environment due to their powerful signal amplification capability and nonenzymatic feature. However, the problem of the cascaded circuits is that the design is relatively complex and the kinetics is slow. Herein, a new design paradigm called catalyst-accelerated circular cascaded circuits is proposed, where the catalyst inlet is implanted and the reaction speed can be adjusted by the catalyst concentration. This new design is very simple and only requires three hairpin probes. Meanwhile, the results of a series of studies demonstrate that the reaction speed can be accelerated and the sensitivity can be also improved. Moreover, endogenous mRNA can also be used as a catalyst to drive the circuits to amplify the detection of target miRNA in live cells and in mice. These catalyst-accelerated circular cascaded circuits can substantially expand the toolbox for intracellular low abundance molecular detection.
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Técnicas Biosensibles , MicroARNs , Animales , Ratones , ADN Circular , ADN , MicroARNs/genética , ARN Mensajero , Cinética , Técnicas Biosensibles/métodos , Técnicas de Amplificación de Ácido Nucleico/métodosRESUMEN
Mask model is a critical part of computational lithography (CL). Owing to the significant 3D mask effects, it is challenging to accurately and efficiently calculate the near field of extreme ultraviolet (EUV) masks with complex patterns. Therefore, a method based on the modified Born series (MBS) was introduced for EUV mask modeling. With comparable accuracy, the MBS method was two orders of magnitude faster than the finite-difference time-domain method for the investigated examples. Furthermore, the time required for MBS was further reduced when the mask pattern was slightly changed. The proposed method shows great potential for constructing an accurate 3D mask model in EUV CL with high efficiency.
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Sidewall tilting is an important parameter to describe the grating morphology and would affect the diffraction efficiency of three-dimensional (3D) display devices based on pixelated nanogratings. However, there is currently a lack of a non-destructive measurement method that can accurately measure the sidewall tilting of the pixelated nanogratings. This is mainly because the kind of nanograting is manufactured in a micron-scale pixel region and the grating lines generally have various directions to ensure that the display device can display images smoothly. In this work, we propose to use a home-made imaging Mueller matrix ellipsometer (IMME) to monitor sidewall tilting of pixelated nanogratings. Simulation and experiments were carried out to characterize the sidewall tilting angle. Through the combination of Mueller matrix elements, we can quickly and qualitatively identify the tilting angle for the purpose of on-line quality monitoring of the device. Through the inverse calculation of the Mueller matrix, we can accurately and quantitatively obtain the value of the tilting, so as to meet the demands of the device design. It is expected the proposed method can provide guidance for the identification and detection of tilting in 3D display elements based on pixelated gratings.
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In advanced semiconductor technology nodes, the model accuracy of optical proximity correction (OPC) is the key for integrated circuit (IC) chip mask tape out, yield ramp up, and product time-to-market. An accurate model means a small prediction error for the full chip layout. As the full chip layout usually has large pattern variety, an optimal pattern set with good coverage is desired during the model calibration process. Currently, no existing solutions can provide the effective metrics to evaluate the coverage sufficiency of the selected pattern set before a real mask tape out, which may potentially cause higher re-tape out cost and product time-to-market delay due to the multiple rounds of model calibration. In this paper, we construct the metrics to evaluate the pattern coverage before any metrology data is obtained. The metrics are based on either the pattern's intrinsic, numerical feature representation, or its potential model simulation behavior. Experimental results show a positive correlation between these metrics and lithographic model accuracy. An incremental selection method is also proposed based on the pattern simulation error. It reduces up to 53% of the model's verification error range. These pattern coverage evaluation methods can improve the efficiency of OPC model building, and are, in turn, beneficial to the whole OPC recipe development process.
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Overlay serves as the pivotal performance indicator for lithography tools, and its prompt and precise measurement significantly underpins the process yield control. At present, diffraction-based overlay metrology employing optical wavelengths encounters constraints in terms of measurement sensitivity. When transitioning to x-ray wavelengths, the critical-dimension small-angle x-ray scattering (CDSAXS) method for nanostructure characterization necessitates reciprocal space mapping (RSM) and inverse problem solving, resulting in substantial throughput constraints. In this work, we propose an x-ray-based overlay metrology using reciprocal space slicing analysis (RSS), yielding high-precision overlay measurement at one single angle of incidence (AOI). Moreover, we examine the robustness of the proposed method against errors stemming from overlay target grating fabrication and measurement processes, substantiating its efficacy as a novel x-ray-based overlay metrology and unveiling the potential application of x-ray-based techniques within the realm of integrated circuit metrology.