Quantum dot-based single-virus tracking has become a practical method to explore the molecular mechanism of virus entry into cells,because it can realize virion imaging in living cells.Mink enteritis virus(MEV)is a single-stranded DNA virus with strong environmental resistance,which has caused huge economic losses for the global mink farming industry.Although epidemio-logic and clinical aspects of MEVs have been studied,the mechanisms by which it infect target cells remain unclear.In this study,we implemented quantum dot labeling of mink enteritis virus u-sing the biotin-streptomycin affinity system and monitored the viral infection process in host cells.We found that MEV first attaches to the cell membrane and enters the cell by endocytosis.Live cell images showed quantum dot(QD)-MEV movement along microtubules,and viral infection was also inhibited by treatment with the microtubule inhibitor nocodazole,whereas the addition of the microfilament inhibitor CytoD had no effect on infection,suggesting that MEV transport is de-pendent on microtubules rather than microfilaments.Another imaging results showed that MEV co-localized with Rab5 and Rab7 in host cells,suggesting that the endosomal system is required for MEV internalization.Biochemical analyses showed that viral infection was significantly inhibited after pretreatment of host cells with the endosomal acidification inhibitors NH4 Cl and chloro-quine,suggesting that MEV invasion requires an acidic environment in the endosomes.Our results indicated that MEV enters early and late endosomes after entering the cell membrane,and that in-tracellular translocation is microtubule-dependent,which may in turn uncover a novel target for antiviral treatment.

Bispecific antibodies have shown significant efficacy in tumor therapy due to their dual targeting ability, but the complexity of their structure leads to the production of various process-related impurities such as host cell proteins, host cell DNA, and Protein A, and product-related impurities such as semi antibodies, 3/4 antibodies, homodimers, bispecific antibodies lacking one Fab arm, and aggregates during the manufacturing process. This paper systematically summarizes downstream purification strategies for dual antibodies, including affinity chromatography, deep filtration, hydroxyapatite chromatography, hydrophobic interaction chromatography, ion exchange chromatography, and multimodal chromatography, to efficiently remove various impurities and provide theoretical support for the purification of dual antibodies.

Implementation evaluation frameworks are essential tools in implementation science for assessing the quality and effectiveness of evidence-based interventions. This paper systematically reviews eight internationally representative evaluation frameworks, outlining their development backgrounds and structural features. It then compares their usability, applicability, and testability. Two case studies are presented to illustrate how evaluation frameworks can be integrated with process models and determinant frameworks to enhance the understanding and guidance of complex interventions. This paper aims to offer practical guidancefor selecting and applying evaluation frameworks, thereby supporting the advancement of implementation science in both local and global health contexts.

Objective To examine the effects of SMAD4 on the proliferation and apoptosis of ovarian granulosa cells in rats with poly-cystic ovary syndrome(PCOS).Methods A PCOS rat model was established using DHEA,and ovarian granulosa cells were extracted and cultured in vitro.The expression of SMAD4 in ovarian granulosa cells was detected by quantitative real-time PCR and Western blot-ting.SMAD4-siRNA was transfected into ovarian granulosa cells from PCOS rats.The expression of SMAD4 mRNA after transfection was determined by quantitative real-time PCR.Western blotting was performed to detect the expression levels of PCNA,BAX,and BCL-2 proteins after transfection.A CCK-8 assay was performed to evaluate cell growth after siRNA interference.Results The HE staining results revealed that the number of ovarian follicular vacuoles increased and that the number of granulosa cell layers and corpus luteum decreased,thus indicating the establishment of a PCOS model.The FSHR positivity rate exceeded 95％.SMAD4 expression in ovarian granulosa cells was higher in the PCOS group than in the control group(P＜0.05).Furthermore,siRNA effectively reduced SMAD4 expression in ovarian granulosa cells of PCOS rats(P＜0.01),promoted proliferation,and inhibited the apoptosis of granulosa cells.Con-clusion The hindered growth of ovarian granulosa cells in PCOS rats may be linked to the overexpression of SMAD4 mRNA,which sug-gests that targeting SMAD4 could be a promising approach for treating ovulatory abnormalities in patients with PCOS.

Purpose Based on a variety of combinations of cranial MR Dixon images,the deep learning method is used to generate CT images,and the reconstruction efficiency is evaluated by comparing with the corresponding CT images.Materials and Methods A total of 77 cranial CT and MR images were collected retrospectively in Ruijin Hospital,Shanghai Jiaotong University School of Medicine from June to December 2021.The U-Net neural network was used for network training,with 62 cases in the training set and 15 cases in the test set.CT image reconstruction was performed using four kinds of Dixon images and a total of seven models among the various combinations.Mean absolute error,mean squared error,Pearson correlation coefficient and skull area Dice similarity coefficient were used to evaluate the image reconstruction efficiency.Results The generated CT images of the various Dixon image combination models showed strong correlation with the corresponding CT images(R>0.75,P<0.05),and the CT images reconstructed by the four-channel model had the closest value to the actual CT images[mean absolute error=147.516±30.802,mean squared error=(8.648±3.403)×104],the highest correlation coefficient(R=0.796±0.055),and the highest similarity coefficient in the cranial region(Dice similarity coefficient=0.800±0.036).Conclusion Deep learning training through Dixon images can be used to generate CT images,and the combination of four kinds of Dixon contrast images can improve the CT image reconstruction efficiency.

Quantum dot-based single-virus tracking has become a practical method to explore the molecular mechanism of virus entry into cells,because it can realize virion imaging in living cells.Mink enteritis virus(MEV)is a single-stranded DNA virus with strong environmental resistance,which has caused huge economic losses for the global mink farming industry.Although epidemio-logic and clinical aspects of MEVs have been studied,the mechanisms by which it infect target cells remain unclear.In this study,we implemented quantum dot labeling of mink enteritis virus u-sing the biotin-streptomycin affinity system and monitored the viral infection process in host cells.We found that MEV first attaches to the cell membrane and enters the cell by endocytosis.Live cell images showed quantum dot(QD)-MEV movement along microtubules,and viral infection was also inhibited by treatment with the microtubule inhibitor nocodazole,whereas the addition of the microfilament inhibitor CytoD had no effect on infection,suggesting that MEV transport is de-pendent on microtubules rather than microfilaments.Another imaging results showed that MEV co-localized with Rab5 and Rab7 in host cells,suggesting that the endosomal system is required for MEV internalization.Biochemical analyses showed that viral infection was significantly inhibited after pretreatment of host cells with the endosomal acidification inhibitors NH4 Cl and chloro-quine,suggesting that MEV invasion requires an acidic environment in the endosomes.Our results indicated that MEV enters early and late endosomes after entering the cell membrane,and that in-tracellular translocation is microtubule-dependent,which may in turn uncover a novel target for antiviral treatment.

Objective To examine the effects of SMAD4 on the proliferation and apoptosis of ovarian granulosa cells in rats with poly-cystic ovary syndrome(PCOS).Methods A PCOS rat model was established using DHEA,and ovarian granulosa cells were extracted and cultured in vitro.The expression of SMAD4 in ovarian granulosa cells was detected by quantitative real-time PCR and Western blot-ting.SMAD4-siRNA was transfected into ovarian granulosa cells from PCOS rats.The expression of SMAD4 mRNA after transfection was determined by quantitative real-time PCR.Western blotting was performed to detect the expression levels of PCNA,BAX,and BCL-2 proteins after transfection.A CCK-8 assay was performed to evaluate cell growth after siRNA interference.Results The HE staining results revealed that the number of ovarian follicular vacuoles increased and that the number of granulosa cell layers and corpus luteum decreased,thus indicating the establishment of a PCOS model.The FSHR positivity rate exceeded 95％.SMAD4 expression in ovarian granulosa cells was higher in the PCOS group than in the control group(P＜0.05).Furthermore,siRNA effectively reduced SMAD4 expression in ovarian granulosa cells of PCOS rats(P＜0.01),promoted proliferation,and inhibited the apoptosis of granulosa cells.Con-clusion The hindered growth of ovarian granulosa cells in PCOS rats may be linked to the overexpression of SMAD4 mRNA,which sug-gests that targeting SMAD4 could be a promising approach for treating ovulatory abnormalities in patients with PCOS.

Purpose Based on a variety of combinations of cranial MR Dixon images,the deep learning method is used to generate CT images,and the reconstruction efficiency is evaluated by comparing with the corresponding CT images.Materials and Methods A total of 77 cranial CT and MR images were collected retrospectively in Ruijin Hospital,Shanghai Jiaotong University School of Medicine from June to December 2021.The U-Net neural network was used for network training,with 62 cases in the training set and 15 cases in the test set.CT image reconstruction was performed using four kinds of Dixon images and a total of seven models among the various combinations.Mean absolute error,mean squared error,Pearson correlation coefficient and skull area Dice similarity coefficient were used to evaluate the image reconstruction efficiency.Results The generated CT images of the various Dixon image combination models showed strong correlation with the corresponding CT images(R>0.75,P<0.05),and the CT images reconstructed by the four-channel model had the closest value to the actual CT images[mean absolute error=147.516±30.802,mean squared error=(8.648±3.403)×104],the highest correlation coefficient(R=0.796±0.055),and the highest similarity coefficient in the cranial region(Dice similarity coefficient=0.800±0.036).Conclusion Deep learning training through Dixon images can be used to generate CT images,and the combination of four kinds of Dixon contrast images can improve the CT image reconstruction efficiency.

Hepatocellular carcinoma is the most common malignancy of the liver and poses serious health burdens on China and the whole world. However， most patients with hepatocellular carcinoma are already in the advanced stage at the time of diagnosis， with fewer opportunities for surgery and limited treatment options. In recent years， the advances in molecular targeted therapies have brought new hope for patients with advanced hepatocellular carcinoma. Among these therapies， lenvatinib is the second first-line drug after sorafenib approved by the US Food and Drug Administration for the treatment of advanced hepatocellular carcinoma， and it has attracted widespread attention for its powerful anti-tumor properties. However， the efficacy of lenvatinib is severely limited by its drug resistance. This article reviews the research advances in the molecular mechanisms of lenvatinib resistance in hepatocellular carcinoma and discusses possible ways to improve the efficacy of lenvatinib， so as to improve its efficacy.

Objective To analyze the hotspots and development trends in orientation and mobility research within the international field of visual impairment. Methods Literature related to orientation and mobility in the field of visual impairment was retrieved from the Web of Science Core Collection database from January,2004 to March,2024,and was analyzed with CiteSpace 6.3 R1. Results A total of 197 literatures were included.The quantity of literature in the field of orientation and mobility for visu-al impairment showed a growth trend.The top scholars in this field by publication volume were Robert Wall Em-erson,Kim Dae Shik,Nora Griffin-Shirley,and Giulio E Lancioni.The United States demonstrated high research output and influence in the study of orientation and mobility for individuals with visual impairments.Core key-words included navigation,assistive technology,cognitive maps,older adults,design,experience,children,per-ception and acuity.Hot topics primarily focused on five aspects:transportation and rehabilitation for low-vision individuals,development of orientation and mobility assistive technologies,orientation and mobility research for individuals with multiple disabilities due to visual impairment,construction of spatial cognition for visually im-paired individuals,and navigation research based on multisensory cues.Scholars evolved their focus from the ba-sic living needs and simple applications of assistive technologies for visually impaired individuals to an emphasis on personal experiences and actual needs,and finally to exploring how to utilize assistive technologies to en-hance quality of life and orientation and mobility capabilities. Conclusion Researches in orientation and mobility are on the rise,with hot topics including transportation and rehabilita-tion,assistive technologies,spatial cognition,and individuals with multiple disabilities related to visual impair-ment.It is needed to promote interdisciplinary research and collaboration,while focus on the development and in-novation of orientation and mobility assistive technologies.