AIM: To compare the clinical outcomes of extended depth-of-focus intraocular lenses(EDOF IOLs)using either micromonovision implantation or mixed implantation of EDOF and diffractive bifocal IOLs.METHODS: This retrospective clinical trial included 130 patients(260 eyes), who were divided into two groups. Group RR comprised 70 patients(140 eyes)bilaterally implanted with ZXR00 IOLs(Tecnis ZXR00, where one target was -0.5 D to -0.75 D and the other was 0 to -0.25 D). Group RM comprised 60 patients(120 eyes)unilaterally implanted with both ZXR00 and ZMB00 IOLs(Tecnis ZMB00, 0 to -0.25 D). Postoperative outcomes were compared after 3 mo, including visual acuity, defocus curves, stereoacuity, modulation transfer functions(MTFs), higher-order aberrations, and Visual Function-14(VF-14)questionnaire responses.RESULTS: Group RR had superior bilateral intermediate vision, while the group RM had superior bilateral near vision(both P<0.05). Group RM also exhibited superior MTFs and reduced higher-order aberrations(both P<0.05). Stereoacuity and VF-14 questionnaire results showed no statistically significant difference between groups(P>0.05).CONCLUSION: The implantation of micromonovision has significantly improved near vision. IOLs and their collocation can be customized according to individual patient needs to achieve precise treatment and provide cataract patients with high-quality vision.

AIM: To compare the clinical outcomes of extended depth-of-focus intraocular lenses(EDOF IOLs)using either micromonovision implantation or mixed implantation of EDOF and diffractive bifocal IOLs.METHODS: This retrospective clinical trial included 130 patients(260 eyes), who were divided into two groups. Group RR comprised 70 patients(140 eyes)bilaterally implanted with ZXR00 IOLs(Tecnis ZXR00, where one target was -0.5 D to -0.75 D and the other was 0 to -0.25 D). Group RM comprised 60 patients(120 eyes)unilaterally implanted with both ZXR00 and ZMB00 IOLs(Tecnis ZMB00, 0 to -0.25 D). Postoperative outcomes were compared after 3 mo, including visual acuity, defocus curves, stereoacuity, modulation transfer functions(MTFs), higher-order aberrations, and Visual Function-14(VF-14)questionnaire responses.RESULTS: Group RR had superior bilateral intermediate vision, while the group RM had superior bilateral near vision(both P<0.05). Group RM also exhibited superior MTFs and reduced higher-order aberrations(both P<0.05). Stereoacuity and VF-14 questionnaire results showed no statistically significant difference between groups(P>0.05).CONCLUSION: The implantation of micromonovision has significantly improved near vision. IOLs and their collocation can be customized according to individual patient needs to achieve precise treatment and provide cataract patients with high-quality vision.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.