Design, synthesis, and evaluation of antitumor activity of Mobocertinib derivatives, a third-generation EGFR inhibitor.

Mobocertinib, as a structural analog of the third generation TKI Osimertinib, can selectively act on the EGFRex20 mutation. We have structurally modified Mobocertinib to obtain new EGFR inhibitors. In this paper, we chose Mobocertinib as a lead compound for structural modification to investigate the effect of Mobocertinib derivatives on EGFRT790M mutation. We designed and synthesized 63 Mobocertinib derivatives by structural modification using the structural similarity strategy and the bioelectronic isoarrangement principle. Then, we evaluated the in vitro antitumor activity of the 63 Mobocertinib derivatives and found that the IC50 of compound H-13 against EGFRL858R/T790M mutated H1975 cells was 3.91 µM, and in further kinase activity evaluation, the IC50 of H-13 against EGFRL858R/T790M kinase was 395.2 nM. In addition, the preferred compound H-13 was able to promote apoptosis of H1975 tumor cells and block the proliferation of H1975 cells in the G0/G1 phase; meanwhile, it was able to significantly inhibit the migratory ability of H1975 tumor cells and inhibit the growth of H1975 cells in a time-concentration-dependent manner. In the in vivo anti-tumor activity study, the preferred compound H-13 had no obvious toxicity to normal mice, and the tumor inhibition effect on H1975 cell-loaded nude mice was close to that of Mobocertinib. Finally, molecular dynamics simulations showed that the binding energy between compound H-13 and 3IKA protein was calculated to be -162.417 ± 14.559 kJ/mol. In summary, the preferred compound H-13 can be a potential third-generation EGFR inhibitor.

Robust Activity and Stability of P-Doped Fe-Carbon Composites Derived from MOF for Bromate Reduction.

Iron-based materials are effective for the reductive removal of the disinfection byproduct bromate in water, while the construction of highly stable and active Fe-based materials with wide pH adaptability remains greatly challenging. In this study, highly dispersed iron phosphide-decorated porous carbon (Fe2P(x)@P(z)NC-y) was prepared via the thermal hydrolysis of Fe@ZIF-8, followed by phosphorus doping (P-doping) and pyrolysis. The reduction performances of Fe2P(x)@P(z)NC-y for bromate reduction were evaluated. Characterization results showed that the Fe, P, and N elements were homogeneously distributed in the carbonaceous matrix. P-doping regulated the coordination environment of Fe atoms and enhanced the conductivity, porosity, and wettability of the carbonaceous matrix. As a result, Fe2P(x)@P(1.0)NC-950 exhibited enhanced reactivity and stability with an intrinsic reduction kinetic constant (kint) 1.53-1.85 times higher than Fe(x)@NC-950 without P-doping. Furthermore, Fe2P(0.125)@P(1.0)NC-950 displayed superior reduction efficiency and prominent stability with very low Fe leaching (4.53-22.98 µg L-1) in a wide pH range of 4.0-10.0. The used Fe2P(0.125)@P(1.0)NC-950 could be regenerated by phosphating, and the regenerated Fe2P(0.125)@P(1.0)NC-950 maintained 85% of its primary reduction activity after five reuse cycles. The study clearly demonstrates that Fe2P-decorated porous carbon can be applied as a robust and stable Fe-based material in aqueous bromate reduction.

Development and validation of a Radiopathomics model based on CT scans and whole slide images for discriminating between Stage I-II and Stage III gastric cancer.

OBJECTIVE: This study aimed to develop and validate an artificial intelligence radiopathological model using preoperative CT scans and postoperative hematoxylin and eosin (HE) stained slides to predict the pathological staging of gastric cancer (stage I-II and stage III). METHODS: This study included a total of 202 gastric cancer patients with confirmed pathological staging (training cohort: n = 141; validation cohort: n = 61). Pathological histological features were extracted from HE slides, and pathological models were constructed using logistic regression (LR), support vector machine (SVM), and NaiveBayes. The optimal pathological model was selected through receiver operating characteristic (ROC) curve analysis. Machine learnin algorithms were employed to construct radiomic models and radiopathological models using the optimal pathological model. Model performance was evaluated using ROC curve analysis, and clinical utility was estimated using decision curve analysis (DCA). RESULTS: A total of 311 pathological histological features were extracted from the HE images, including 101 Term Frequency-Inverse Document Frequency (TF-IDF) features and 210 deep learning features. A pathological model was constructed using 19 selected pathological features through dimension reduction, with the SVM model demonstrating superior predictive performance (AUC, training cohort: 0.949; validation cohort: 0.777). Radiomic features were constructed using 6 selected features from 1834 radiomic features extracted from CT scans via SVM machine algorithm. Simultaneously, a radiopathomics model was built using 17 non-zero coefficient features obtained through dimension reduction from a total of 2145 features (combining both radiomics and pathomics features). The best discriminative ability was observed in the SVM_radiopathomics model (AUC, training cohort: 0.953; validation cohort: 0.851), and clinical decision curve analysis (DCA) demonstrated excellent clinical utility. CONCLUSION: The radiopathomics model, combining pathological and radiomic features, exhibited superior performance in distinguishing between stage I-II and stage III gastric cancer. This study is based on the prediction of pathological staging using pathological tissue slides from surgical specimens after gastric cancer curative surgery and preoperative CT images, highlighting the feasibility of conducting research on pathological staging using pathological slides and CT images.

Mechanically stimulated osteocytes maintain tumor dormancy in bone metastasis of non-small cell lung cancer by releasing small extracellular vesicles.

Although preclinical and clinical studies have shown that exercise can inhibit bone metastasis progression, the mechanism remains poorly understood. Here, we found that non-small cell lung cancer (NSCLC) cells adjacent to bone tissue had a much lower proliferative capacity than the surrounding tumor cells in patients and mice. Subsequently, it was demonstrated that osteocytes, sensing mechanical stimulation generated by exercise, inhibit NSCLC cell proliferation and sustain the dormancy thereof by releasing small extracellular vesicles with tumor suppressor micro-RNAs, such as miR-99b-3p. Furthermore, we evaluated the effects of mechanical loading and treadmill exercise on the bone metastasis progression of NSCLC in mice. As expected, mechanical loading of the tibia inhibited the bone metastasis progression of NSCLC. Notably, bone metastasis progression of NSCLC was inhibited by moderate exercise, and combinations with zoledronic acid had additive effects. Moreover, exercise preconditioning effectively suppressed bone metastasis progression. This study significantly advances the understanding of the mechanism underlying exercise-afforded protection against bone metastasis progression.

Cytological characteristics of blueberry fruit development.

Using the blueberry cultivar "Powderblue" after pollination, fruits at different developmental stages were collected for study. The transverse and longitudinal diameters, individual fruit weight, and fruit water content were measured during their development. Employing tissue sectioning and microscopy techniques, we systematically studied the morphological features and anatomical structures of the fruits and seeds at various developmental stages, aiming to elucidate the cytological patterns during blueberry fruit development. The results of our study revealed that the "Powderblue" blueberry fruit growth and development followed a double "S" curve. Mature "Powderblue" blueberries were blue-black in color, elliptical in shape, with five locules, an inferior ovary, and an average fruit weight of 1.73 ± 0.17 g, and a moisture content of 78.865 ± 0.9%. Blueberry fruit flesh cells were densely arranged with no apparent intercellular spaces, and mesocarp cells accounted for 52.06 ± 7.4% of fruit cells. In the early fruit development stages, the fruit flesh cells were rapidly dividing, significantly increasing in number but without greatly affecting the fruit's morphological characteristics. During the later stages of fruit development, the expansion of the fruit flesh cells became prominent, resulting in a noticeable increase in the fruit's dimensions. Except for the epidermal cells, cells in all fruit tissues showed varying degrees of rupture as fruit development progressed, with the extent of cell rupture increasing, becoming increasingly apparent as the fruit gradually softened. Additionally, numerous brachysclereids (stone cells) appeared in the fruit flesh cells. Stone cells are mostly present individually in the fruit flesh tissue, while in the placental tissue, they often group together. The "Powderblue" blueberry seeds were light brown, 4.13 ± 0.42 mm long, 2.2 ± 0.14 mm wide, with each fruit containing 50-60 seeds. The "Powderblue" seeds mainly consisted of the seed coat, endosperm, and embryo. The embryo was located at the chalazal end in the center of the endosperm and was spatially separated. The endosperm, occupying the vast majority of the seed volume, comprised both the chalazal and outer endosperm, and the endosperm developed and matured before the embryo. As the seed developed, the seed coat was gradually lignified and consisted of palisade-like stone cells externally and epidermal layer cells internally.

Engraving Polyamide Layers by In Situ Self-Etchable CaCO3 Nanoparticles Enhances Separation Properties and Antifouling Performance of Reverse Osmosis Membranes.

Nanovoids within a polyamide layer play an important role in the separation performance of thin-film composite (TFC) reverse osmosis (RO) membranes. To form more extensive nanovoids for enhanced performance, one commonly used method is to incorporate sacrificial nanofillers in the polyamide layer during the exothermic interfacial polymerization (IP) reaction, followed by some post-etching processes. However, these post-treatments could harm the membrane integrity, thereby leading to reduced selectivity. In this study, we applied in situ self-etchable sacrificial nanofillers by taking advantage of the strong acid and heat generated in IP. CaCO3 nanoparticles (nCaCO3) were used as the model nanofillers, which can be in situ etched by reacting with H+ to leave void nanostructures behind. This reaction can further degas CO2 nanobubbles assisted by heat in IP to form more nanovoids in the polyamide layer. These nanovoids can facilitate water transport by enlarging the effective surface filtration area of the polyamide and reducing hydraulic resistance to significantly enhance water permeance. The correlations between the nanovoid properties and membrane performance were systematically analyzed. We further demonstrate that the nCaCO3-tailored membrane can improve membrane antifouling propensity and rejections to boron and As(III) compared with the control. This study investigated a novel strategy of applying self-etchable gas precursors to engrave the polyamide layer for enhanced membrane performance, which provides new insights into the design and synthesis of TFC membranes.

LncRNA PRBC induces autophagy to promote breast cancer progression through modulating PABPC1-mediated mRNA stabilization.

Breast cancer is one of the major malignant tumors among women worldwide. Long noncoding RNAs (lncRNAs) have been documented as significant modulators in the development and progression of various cancers; however, the contribution of lncRNAs to breast cancer remains largely unknown. In this study, we found a novel lncRNA (NONHSAT137675) whose expression was significantly increased in the breast cancer tissues. We named the novel lncRNA as lncRNA PRBC (PABPC1-related lncRNA in breast cancer) and identified it as a key lncRNA associated with breast cancer progression and prognosis. Functional analysis displayed that lncRNA PRBC could promote autophagy and progression of breast cancer. Mechanistically, we verified that lncRNA PRBC physically interacted with PABPC1 through RIP assay, and PABPC1 overexpression could reverse the inhibiting effect of lncRNA PRBC knockdown on the malignant behaviors in breast cancer cells. Knockdown of lncRNA PRBC interfered the translocation of PABPC1 from nucleus to cytoplasm as indicated by western blot and IF assays. Significantly, the cytoplasmic location of PABPC1 was required for the interaction between PABPC1 and AGO2, which could be enhanced by lncRNA PRBC overexpression, leading to strengthened recruitment of mRNA to RNA-induced silencing complex (RISC) and thus reinforcing the inhibition efficiency of miRNAs. In general, lncRNA PRBC played a critical role in malignant progression of breast cancer by inducing the cytoplasmic translocation of PABPC1 to further regulate the function of downstream miRNAs. This study provides novel insight on the molecular mechanism of breast cancer progression, and lncRNA PRBC might be a promising therapeutic target and prognostic predictor for breast cancer.

Research on Inertial Navigation and Environmental Correction Indoor Ultra-Wideband Ranging and Positioning Methods.

In contrast to outdoor environments, indoor positioning encounters signal propagation disruptions due to the presence of buildings, resulting in reduced accuracy and, at times, the inability to determine a location accurately. This research, leveraging the robust penetrative capabilities of Ultra-Wideband (UWB) signals in non-line-of-sight (NLOS) scenarios, introduces a methodology for refining ranging outcomes through a combination of inertial navigation and environmental adjustments to achieve high-precision spatial positioning. This approach systematically enhances the correction of signal propagation errors through walls. Initially, it digitalizes the spatial setting, preserving the error correction parameters. Subsequently, it employs inertial navigation to estimate spatial coordinates and delineate signal propagation pathways to achieve precise ranging results. It iteratively hones the positioning outcomes for enhanced precision. Empirical findings demonstrate that within NLOS conditions, compared to standalone UWB positioning and IMU/UWB fusion positioning using the ESKF algorithm, this positioning technique significantly enhances planar positioning accuracy while achieving a marginal elevation accuracy improvement, albeit with some residual deviations from actual values. Furthermore, this positioning methodology effectively rectifies results in NOLS settings, paving the way for a novel approach to optimize indoor positioning through UWB technology.

Epigenetic-based combination therapy and liposomal codelivery overcomes osimertinib-resistant NSCLC via repolarizing tumor-associated macrophages.

Osimertinib (Osi) is widely used as a first-line treatment for non-small cell lung cancer (NSCLC) with EGFR mutations. However, the majority of patients treated with Osi eventually relapse within a year. The mechanisms of Osi resistance remain largely unexplored, and efficient strategies to reverse the resistance are urgently needed. Here, we developed a lactoferrin-modified liposomal codelivery system for the combination therapy of Osi and panobinostat (Pan), an epigenetic regulator of histone acetylation. We demonstrated that the codelivery liposomes could efficiently repolarize tumor-associated macrophages (TAM) from the M2 to M1 phenotype and reverse the epithelial-mesenchymal transition (EMT)-associated drug resistance in the tumor cells, as well as suppress glycolysis, lactic acid production, and angiogenesis. Our results suggested that the combination therapy of Osi and Pan mediated by liposomal codelivery is a promising strategy for overcoming Osi resistance in NSCLC.

A comprehensive radiopathological nomogram for the prediction of pathological staging in gastric cancer using CT-derived and WSI-based features.

OBJECTIVE: This study aims to develop and validate an innovative radiopathomics model that combines radiomics and pathomics features to effectively differentiate between stages I-II and stage III gastric cancer (pathological staging). METHODS: Our study included 200 patients with well-defined stages of gastric cancer divided into a training cohort (n = 140) and a test cohort (n = 60). Radiomics features were extracted from contrast-enhanced CT images using PyRadiomics, while pathomics features were obtained from whole slide images of pathological specimens through a fine-tuned deep learning model (ResNet-18). After rigorous feature dimensionality reduction and selection, we constructed radiomics models (SVM_rad, LR_rad, and MLP_rad) and pathomics models (SVM_path, LR_path, and MLP_path) utilizing support vector machine (SVM), logistic regression (LR), and multilayer perceptron (MLP) algorithms. The optimal radiomics and pathomics models were chosen based on comprehensive evaluation criteria such as ROC curves, Hosmer‒Lemeshow tests, and calibration curve tests. Feature patterns extracted from the best-performing radiomics model (MLP_rad) and pathomics model (SVM_rad) were integrated to create a powerful radiopathomics nomogram. RESULTS: From a pool of 1834 radiomics features extracted from CT images, 14 were selected to construct radiomics models. Among these, the MLP_rad model exhibited the most robust predictive performance (AUC, training cohort: 0.843; test cohort: 0.797). Likewise, 10 pathomics features were chosen from 512 extracted from whole slide images to build pathomics models, with the SVM_path model demonstrating the highest predictive efficiency (AUC, training cohort: 0.937; test cohort: 0.792). The combined radiopathomics nomogram model exhibited optimal discriminative ability (AUC, training cohort: 0.951; test cohort: 0.837), as confirmed by decision curve analysis (DCA), which indicated superior clinical effectiveness. CONCLUSION: This study presents a cutting-edge radiopathomics nomogram model designed to predict pathological staging in gastric cancer, distinguishing between stages I-II and stage III. Our research leverages preoperative CT images and histopathological slides to forecast gastric cancer staging accurately, potentially facilitating the estimation of staging before radical gastric cancer surgery in the future.

Comprehensive evaluation of fruit quality for premium Wangmo Castanea mollissima plants.

In this study, the fruit phenotype and quality of 32 superior Wangmo Castanea mollissima plants (designated GM1 to GM32) were examined to identify the trait characteristics of different cluster groups and germplasms with excellent comprehensive performance. The goal was to provide a theoretical basis and research foundation for collecting high-quality germplasm resources and breeding superior cultivars of Wangmo C. mollissima. Ten fruit phenotypic traits and 13 quality traits were measured and analyzed in these 32 superior Wangmo C. mollissima plants. Cluster analysis and principal component analysis (PCA) were used to perform a comprehensive evaluation. Extremely significant positive correlations (P<0.01) were observed for 15 pairs of fruit phenotypic and quality traits, and significant positive correlations (P<0.05) were observed for 16 pairs of traits. Highly significant negative correlations (P<0.01) were observed for 4 pairs of fruit phenotypic and quality traits, and significant negative correlations (P<0.05) were observed for 15 pairs. The plants were divided into three groups by cluster analysis: the first group had large fruits and good fruit quality, the second group had small fruits and poor fruit quality, and the third group had medium-sized fruits with a high starch content. Four principal components were extracted from the 23 traits by PCA, contributing 76.23% of the variance. The ten plants with the highest comprehensive quality were GM32, GM31, GM29, GM1, GM8, GM17, GM10, GM30, GM3 and GM28. The results of this study provide a reference for the development and utilization of Wangmo C. mollissima germplasm resources.

Predicting disease progression in cirrhotic patients after transjugular intrahepatic portosystemic shunt implantation: A sex-stratified analysis.

BACKGROUND: Transjugular intrahepatic portosystemic shunt (TIPS) has been extensively used to treat portal hypertension-associated complications, including cirrhosis. The prediction of post-TIPS prognosis is important for cirrhotic patients, as more aggressive liver transplantation is needed when the post-TIPS prognosis is poor. AIM: To construct a nutrition-based model that could predict the disease progression of cirrhotic patients after TIPS implantation in a sex-dependent manner. METHODS: This study retrospectively recruited cirrhotic patients undergoing TIPS implantation for analysis. Muscle quality was assessed by measuring the skeletal muscle index (SMI) by computed tomography. Multivariate Cox proportional hazard models were utilized to determine the association between SMI and disease progression in cirrhotic patients after TIPS implantation. RESULTS: This study eventually included 186 cirrhotic patients receiving TIPS who were followed up for 30.5 ± 18.8 mo. For male patients, the 30-mo survival rate was significantly lower and the probability of progressive events was higher (3.257-fold) in the low-level SMI group than in the high-level SMI group. According to the multivariate Cox analysis of male patients, SMI < 32.8 was an independent risk factor for long-term adverse outcomes after TIPS implantation. A model was constructed, which involved creatinine, plasma ammonia, SMI, and acute-on-chronic liver failure and hepatic encephalopathy occurring within half a year after surgery. This model had an area under the receiver operating characteristic curve of 0.852, sensitivity of 0.926, and specificity of 0.652. According to the results of the DeLong test, this model outperformed other models (Child-Turcotte-Pugh, Model for End-Stage Liver Disease, and Freiburg index of post-TIPS survival) (P < 0.05). CONCLUSION: SMI is strongly associated with poor long-term outcomes in male patients with cirrhosis who underwent TIPS implantation.

Mitochondrial fission drives neuronal metabolic burden to promote stress susceptibility in male mice.

Neurons are particularly susceptible to energy fluctuations in response to stress. Mitochondrial fission is highly regulated to generate ATP via oxidative phosphorylation; however, the role of a regulator of mitochondrial fission in neuronal energy metabolism and synaptic efficacy under chronic stress remains elusive. Here, we show that chronic stress promotes mitochondrial fission in the medial prefrontal cortex via activating dynamin-related protein 1 (Drp1), resulting in mitochondrial dysfunction in male mice. Both pharmacological inhibition and genetic reduction of Drp1 ameliorates the deficit of excitatory synaptic transmission and stress-related depressive-like behavior. In addition, enhancing Drp1 fission promotes stress susceptibility, which is alleviated by coenzyme Q10, which potentiates mitochondrial ATP production. Together, our findings unmask the role of Drp1-dependent mitochondrial fission in the deficits of neuronal metabolic burden and depressive-like behavior and provides medication basis for metabolism-related emotional disorders.

A radiomics model based on magnetic resonance imaging to predict cytokeratin 7/19 expression and liver fluke infection of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. HCC with liver fluke infection could harbor unique biological behaviors. This study was aimed at investigating radiomics features of HCC with liver fluke infection and establishing a model to predict the expression of cytokeratin 7 (CK7) and cytokeratin 19 (CK19) as well as prognosis at the same time. A total of 134 HCC patients were included. Gadoxetic acid-enhanced magnetic resonance imaging (MRI) images of all patients were acquired. Radiomics features of the tumor were extracted and then data dimensionality was reduced. The radiomics model was established to predict liver fluke infection and the radiomics score (Radscore) was calculated. There were 11 features in the four-phase combined model. The efficiency of the combined model increased significantly compared to each single-phase MRI model. Radscore was an independent predictor of liver fluke infection. It was also significantly different between different expression of CK7/ CK19. Meanwhile, liver fluke infection was associated with CK7/CK19 expression. A cut-off value was set up and all patients were divided into high risk and low risk groups of CK7/CK19 positive expression. Radscore was also an independent predictor of these two biomarkers. Overall survival (OS) and recurrence free survival (RFS) of negative liver fluke infection group were significantly better than the positive group. OS and RFS of negative CK7 and CK19 expression were also better, though not significantly. Positive liver fluke infection and CK19 expression prediction groups harbored significantly worse OS and RFS, survival of positive CK7 expression prediction was unsatisfying as well. A radiomics model was established to predict liver fluke infection among HCC patients. This model could also predict CK7 and CK19 expression. OS and RFS could be foreseen by this model at the same time.

Liposomal Resveratrol Alleviates Platelet Storage Lesion via Antioxidation and the Physical Buffering Effect.

Platelet transfusion is essential in the treatment of platelet-related diseases and the prevention of bleeding in patients with surgical procedures. Platelet transfusion efficacy and shelf life are limited mainly by the development of platelet storage lesion (PSL). Mitigating PSL is the key to prolonging the platelet shelf life and reducing wastage. Excess intracellular reactive oxygen species (ROS) are one of the main factors causing PSL. In this study, we explored a nanomedicine strategy to improve the quality and functions of platelets in storage. Resveratrol (Res), a natural plant product, is known for its antioxidative effect. However, medical applications of Res are limited due to its low water solubility and stability. Therefore, we used a resveratrol-loaded liposomal system (Res-Lipo) to better utilize the antioxidant effect of the drug. This study aimed to evaluate the effect of Res-Lipo on platelet oxidative stress and alleviation of PSL during the storage time. Res-Lipo scavenged intracellular ROS and inhibited platelet apoptosis and activation during storage. Res-Lipo not only maintained mitochondrial function but also improved platelet aggregation in response to adenosine 5'-diphosphate. These results revealed that Res-Lipo ameliorated PSL and prolonged the platelet survival time in vivo. The strategy provides a potential method for extending the platelet storage time and might be considered a potential and safe additive to alleviate PSL.

Enhancing the removal of organic micropollutants by nanofiltration membrane with Fe (III)-tannic acid interlayer: Mechanisms and environmental implications.

Nanofiltration technology has been applied in a variety of water treatment scenarios. However, conventional thin-film composite (TFC) membranes fail to remove emerging organic micropollutants (OMPs) efficiently. Here we applied thin-film nanocomposite membrane with an interlayer (TFNi) of Fe (III)-tannic acid to remove various types of OMPs, such as endocrine disrupting chemicals (EDCs), pharmaceutically active compounds (PhACs), and perfluoroalkyl substances (PFASs). Compared to the pristine TFC membrane, TFNi membrane exhibited crumpled morphology and its rejection layer was denser, better cross-linked and possessed smaller average pore size with narrower distribution. Significant enhancement in water-OMPs selectivity of PhACs and PFASs was observed. The mechanism lies in the effects of interlayer in improving the membrane permeance to water and meanwhile reducing the permeance to some OMPs by enhancing size exclusion effects. This work confirms the effectiveness of using TFNi membrane to simultaneously enhance the OMPs rejection and water permeance. The unraveled mechanism might inspire the future development of high-performance nanofiltration membranes targeting OMPs removal.

Deep learning-based lung image registration: A review.

Lung image registration can effectively describe the relative motion of lung tissues, thereby helping to solve series problems in clinical applications. Since the lungs are soft and fairly passive organs, they are influenced by respiration and heartbeat, resulting in discontinuity of lung motion and large deformation of anatomic features. This poses great challenges for accurate registration of lung image and its applications. The recent application of deep learning (DL) methods in the field of medical image registration has brought promising results. However, a versatile registration framework has not yet emerged due to diverse challenges of registration for different regions of interest (ROI). DL-based image registration methods used for other ROI cannot achieve satisfactory results in lungs. In addition, there are few review articles available on DL-based lung image registration. In this review, the development of conventional methods for lung image registration is briefly described and a more comprehensive survey of DL-based methods for lung image registration is illustrated. The DL-based methods are classified according to different supervision types, including fully-supervised, weakly-supervised and unsupervised. The contributions of researchers in addressing various challenges are described, as well as the limitations of these approaches. This review also presents a comprehensive statistical analysis of the cited papers in terms of evaluation metrics and loss functions. In addition, publicly available datasets for lung image registration are also summarized. Finally, the remaining challenges and potential trends in DL-based lung image registration are discussed.

3D printing of plasmonic nanofocusing tip enabling high resolution, high throughput and high contrast optical near-field imaging.

Scanning near-field optical microscopy (SNOM) offers a means to reach a fine spatial resolution down to ~ 10 nm, but unfortunately suffers from low transmission efficiency of optical signal. Here we present design and 3D printing of a fiber-bound polymer-core/gold-shell spiral-grating conical tip that allows for coupling the inner incident optical signal to the outer surface plasmon polariton with high efficiency, which then adiabatically transport, squeeze, and interfere constructively at the tip apex to form a plasmonic superfocusing spot with tiny size and high brightness. Numerical simulations and optical measurements show that this specially designed and fabricated tip has 10% transmission efficiency, ~ 5 nm spatial resolution, 20 dB signal-to-noise ratio, and 7000 pixels per second fast scanning speed. This high-resolution, high throughput, and high contrast SNOM would open up a new frontier of high spatial-temporal resolution detecting, imaging, and monitoring of single-molecule physical, chemical, and biological systems, and deepen our understanding of their basic science in the single-molecule level.