There is significant inter-individual variation of pharmacokinetics and pharmacody-namics in patients receiving tacrolimus(TAC)for an-ti-rejection therapy,which cause the rejection or toxic action.Based on results of therapeutic drug monitoring and pathophysiological index of trans-plant patients,the individualized dosing regimen can be designed and adjusted by using model in-formed precision dosing(MIPD).The patients'clini-cal outcome can be improved.In the consensus,the different methods of MIPD used for patients re-ceived TAC for anti-rejection therapy were intro-duced,which can be used for the designing and ad-justing doing regimen,predicting adverse drug reac-tion,improving medication adherence and econom-ics during therapy.

Objective To propose a classification model based on a pseudo-bag strategy and feature adjustment for whole slide imaging in pathology.Methods A pseudo-bag generator was constructed to divide a parent bag into 3 pseudo-bags for increasing the number of training bags.Then,a pseudo-bag learning method based on Nystr?m-based algorithm for approximating self-attention and a selective feature fusion method were employed to process the pseudo-bags.Specifically,the pseudo-bag learning method based on Nystr?m-based algorithm for approximating self-attention reduced computational complexity through an improved multi-head self-attention mechanism while deeply extracting instance features to obtain pseudo-bag classification predictions,thereby enhancing pseudo-bag classification accuracy;and the selective feature fusion method refined pseudo-bag features by filtering and extracting relevant instances.Finally,the model adjusted bag features by extracting confounding factors to avoid interference from irrelevant information and further improve classification accuracy.Results The proposed model was evaluated on two datasets(CAMELYON-16 and TCGA-NSCLC)and compared with 10 other methods,and the results demonstrated that the proposed model achieved the best performance.The proposed method reached an accuracy of 0.943 on the CAMELYON-16 dataset and 0.906 on the TCGA-NSCLC dataset.Conclusion The proposed model can significantly improve the accuracy of whole-slide pathological image classification by effectively mitigating the overfitting and avoiding interference from irrelevant information.

A VLi-net based cell nucleus segmentation method integrating convolutional neural networks(CNN)and Vision Transformer(ViT)is proposed to address the limitation that the U-Net with CNN as its backbone is only proficient in capturing local features and has a restricted receptive field.Firstly,to mitigate challenges such as high cost of data annotation and insufficient annotated data,text annotations are introduced to enhance the network's understanding of image information.Secondly,to improve the segmentation performance of VLi-net,ViT and CNN are combined to fully extract global and local features,with multi-receptive field convolution features incorporating into the ViT structure for effectively mitigating the issues of limited local information interaction and single feature representation in ViT.Finally,an interactive fusion module(ViFusion)is used to efficiently fuse the multi-level features from the CNN and ViT branches.Experimental results show that VLi-net achieves a Dice coefficient of 80.85%and a mean intersection over union(MIoU)of 66.83%on the MoNuSeg dataset,obtains a Dice coefficient of 80.53%and a MIoU of 67.54%on the DSB-2018 dataset,and has a Dice coefficient of 86.87%and a MIoU of 77.44%on the TNBC dataset.These findings confirm that VLi-net outperforms other methods across multiple experimental metrics.

A VLi-net based cell nucleus segmentation method integrating convolutional neural networks(CNN)and Vision Transformer(ViT)is proposed to address the limitation that the U-Net with CNN as its backbone is only proficient in capturing local features and has a restricted receptive field.Firstly,to mitigate challenges such as high cost of data annotation and insufficient annotated data,text annotations are introduced to enhance the network's understanding of image information.Secondly,to improve the segmentation performance of VLi-net,ViT and CNN are combined to fully extract global and local features,with multi-receptive field convolution features incorporating into the ViT structure for effectively mitigating the issues of limited local information interaction and single feature representation in ViT.Finally,an interactive fusion module(ViFusion)is used to efficiently fuse the multi-level features from the CNN and ViT branches.Experimental results show that VLi-net achieves a Dice coefficient of 80.85%and a mean intersection over union(MIoU)of 66.83%on the MoNuSeg dataset,obtains a Dice coefficient of 80.53%and a MIoU of 67.54%on the DSB-2018 dataset,and has a Dice coefficient of 86.87%and a MIoU of 77.44%on the TNBC dataset.These findings confirm that VLi-net outperforms other methods across multiple experimental metrics.

There is significant inter-individual variation of pharmacokinetics and pharmacody-namics in patients receiving tacrolimus(TAC)for an-ti-rejection therapy,which cause the rejection or toxic action.Based on results of therapeutic drug monitoring and pathophysiological index of trans-plant patients,the individualized dosing regimen can be designed and adjusted by using model in-formed precision dosing(MIPD).The patients'clini-cal outcome can be improved.In the consensus,the different methods of MIPD used for patients re-ceived TAC for anti-rejection therapy were intro-duced,which can be used for the designing and ad-justing doing regimen,predicting adverse drug reac-tion,improving medication adherence and econom-ics during therapy.

Objective To propose a classification model based on a pseudo-bag strategy and feature adjustment for whole slide imaging in pathology.Methods A pseudo-bag generator was constructed to divide a parent bag into 3 pseudo-bags for increasing the number of training bags.Then,a pseudo-bag learning method based on Nystr?m-based algorithm for approximating self-attention and a selective feature fusion method were employed to process the pseudo-bags.Specifically,the pseudo-bag learning method based on Nystr?m-based algorithm for approximating self-attention reduced computational complexity through an improved multi-head self-attention mechanism while deeply extracting instance features to obtain pseudo-bag classification predictions,thereby enhancing pseudo-bag classification accuracy;and the selective feature fusion method refined pseudo-bag features by filtering and extracting relevant instances.Finally,the model adjusted bag features by extracting confounding factors to avoid interference from irrelevant information and further improve classification accuracy.Results The proposed model was evaluated on two datasets(CAMELYON-16 and TCGA-NSCLC)and compared with 10 other methods,and the results demonstrated that the proposed model achieved the best performance.The proposed method reached an accuracy of 0.943 on the CAMELYON-16 dataset and 0.906 on the TCGA-NSCLC dataset.Conclusion The proposed model can significantly improve the accuracy of whole-slide pathological image classification by effectively mitigating the overfitting and avoiding interference from irrelevant information.

Immune evasion has made ovarian cancer notorious for its refractory features, making the development of immunotherapy highly appealing to ovarian cancer treatment. The immune-stimulating cytokine IL-12 exhibits excellent antitumor activities. However, IL-12 can induce IFN-γ release and subsequently upregulate PDL-1 expression on tumor cells. Therefore, the tumor-targeting folate-modified delivery system F-DPC is constructed for concurrent delivery of IL-12 encoding gene and small molecular PDL-1 inhibitor (iPDL-1) to reduce immune escape and boost anti-tumor immunity. The physicochemical characteristics, gene transfection efficiency of the F-DPC nanoparticles in ovarian cancer cells are analyzed. The immune-modulation effects of combination therapy on different immune cells are also studied. Results show that compared with non-folate-modified vector, folate-modified F-DPC can improve the targeting of ovarian cancer and enhance the transfection efficiency of pIL-12. The underlying anti-tumor mechanisms include the regulation of T cells proliferation and activation, NK activation, macrophage polarization and DC maturation. The F-DPC/pIL-12/iPDL-1 complexes have shown outstanding antitumor effects and low toxicity in peritoneal model of ovarian cancer in mice. Taken together, our work provides new insights into ovarian cancer immunotherapy. Novel F-DPC/pIL-12/iPDL-1 complexes are revealed to exert prominent anti-tumor effect by modulating tumor immune microenvironment and preventing immune escape and might be a promising treatment option for ovarian cancer treatment.

Objective:To describe the characteristics, etiology and patterns of outpatients and inpatients patients with moderate or severe valvular heart disease (VHD).Methods:This is a cross-sectional study. Outpatients and inpatients with moderate or severe VHD who underwent transthoracic echocardiography for first examination from 1 st January 2001 to 1 st January 2020 in Southwest Hospital, Army Medical University were enrolled. Data were collected from medical records and big data platform of Southwest Hospital. Characteristics of age and gender, etiology and types of VHD were descriptively analysed. Results:A total of 68 354 patients with moderate or severe VHD were enrolled. The age was 63 (50, 72) years. And 35 706 (52.24%) patients were female. (1) Age characteristics: There was similar age trend between male and female patients with moderate or severe VHD. The number of patients increased firstly and then decreased and reached its peak in the age group of 65-69 years old. The peak age of mitral stenosis patients was 45-49 years, which was earlier than that of whole patients with moderate or severe VHD. The median age of patients with bicuspid aortic valve was 42 years. (2) Gender characteristics: The proportion of tricuspid regurgitation, pulmonary regurgitation, mitral regurgitation, mitral stenosis and valve surgery in female patients with moderate or severe VHD were higher than those in male patients. The proportion of aortic regurgitation, aortic stenosis and bicuspid aortic valve in male patients with moderate or severe VHD were significantly higher than those in female patients (all P<0.05). (3) Etiology: The proportion of rheumatic VHD was 13.07% (8 934/68 354), which was higher than that of degenerative VHD (0.67% (458/68 354)). (4) Types of VHD: Tricuspid regurgitation made contribution to the largest proportion with 60.72% (41 503/68 354), followed by mitral regurgitation, aortic regurgitation, mitral stenosis, pulmonary regurgitation and aortic stenosis. Conclusions:There are certain regional characteristics in the prevalence of moderate or severe VHD in southwest China, suggesting different attention should be paid on the whole process of refined management of moderate or severe VHD.

Allergic rhinitis is a common allergic disease in children.Its pathogenesis is complex and it is difficult to achieve radi-cal cure or effective and stable long-term treatment goals.Chinese medicine has obvious advantages in preventing and treating allergic rhinitis in children due to its wide range of targets,long-lasting effects and few adverse reactions.This paper proposes that the onset of allergic rhinitis is mostly caused by the dysfunction of the lung,spleen and kidney,the external wind triggering the latent wind,and the combination of the two winds.A staged prevention and treatment strategy of Chinese medicine should be adopted,which includes dispersing external wind,suppressing latent wind,and promoting lung-qi and clearing nasal orifice during the attack period to treat its symptoms,and preventing external wind,calming down latent wind,and regulating and tonifying the lung,spleen,and kidney during the remission period to treat its root cause;meanwhile,attention should be paid to avoiding the adverse effects of congenital endowment factors and the induction of acquired environmental factors,strengthening the body's health to protect against the evil wind,preventing the transformation of existing diseases and the recurrence of allergic rhinitis in children at all stages.

Antibody-drug conjugates (ADCs) are conjugated by a linker between an antibody drug targeting a specific antigen and a payload, such as a small cytotoxic drug. ADCs combine the potent killing effect of traditional small cytotoxic drugs with the tumor targeting property of antibody drugs. As of February 2022, the U.S. Food and Drug Administration (FDA) had approved 12 ADC antitumor agents. Based on the analysis of clinical pharmacology review reports of approved ADC drugs combined with relevant guidelines, it is found that in the development of ADC, in addition to the general research in clinical pharmacology, there are special considerations in dose selection and dose modification for special population due to the special anti-tumor mechanism of ADC. It is hoped that this paper will be enlightening to domestic researchers when developing ADC.