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.

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.

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.

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.

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.

Objective:To investigate the effect of Stigma Maydis Palysaccharide(SMPS)on ATP synthesis in kidney mitochondria of D-galactose-induced aging mice, and to clarify its possible mechanism.Methods:The aging mouse model was established by subcutaneous injection of D-galactose solution in the back of the neck.The 48 SPF male mice were randomly divided into normal control group(control group), D-galactose model group(D-Gal group), SMPS low-dose group and SMPS high-dose group(n=12 for each). The control group was subcutaneously injected with 150 mg/kg normal saline on the back of the neck every day, while the other three groups were subcutaneously injected with 150 mg/kg of D-gal solution on the back of the neck every day.SMPS-L and-H dose groups were given 30 mg/kg and 60 mg/kg of SMPS solution by gavage at the same day of D-Gal injection.The control group and D-GAL group were given the same volume of normal saline daily by gavage for 42 days.Blood samples were collected from the eyeball under general anesthesia after 42 days of intervention for the detection of serum levels of superoxide dismutase(SOD), glutathione peroxidase(GSH-Px)and MDA.After harvesting the kidney tissue, various tests were used to detect ATP content, the mRNA expression levels and protein expression levels in kidney.Luciferase assay was used to detect ATP content in renal tissue.Real-time fluorescent quantitative PCR was used to detect the mRNA expression levels of succinate dehydrogenase(SDH)of complex Ⅱ, cytochrome C reductase(Cycs)of complex Ⅲ, complex Ⅳ(COXⅣ)and ATP5b in ATP synthase in mitochondrial oxidative respiratory chain.Western blot was used to detect the expression levels of mitochondrial fusion protein 2(MFN2), dynamin-related protein1(DRP1)and mitochondrial autophagy related protein P62 in renal tissues of each group.Results:Compared with control group, the activities of serum of SOD(116.53±10.01)U/mg and GSH-Px(127.58±8.74)μmol/L were significantly decreased in D-GAL group(both P< 0.01), and serum MDA content(15.42±0.91)μmol/L increased significantly in D-GAL group( P<0.01). Compared with D-GAL group, the activities of SOD(152.80±9.29)U/mg and GSH-Px(274.07±10.73)μmol/L were significantly increased in SMPS intervention group( P< 0.01), while the MDA content(8.10±0.66)μmol/L decreased significantly in SMPS intervention group( P< 0.01). Compared with control group, the content of ATP(178±4)10 -4 μmol in D-gal group was significantly decreased( P<0.01), the mRNA expression levels of SDH, Cycs and COXⅣ were not significantly changed in D-gal group, and the mRNA expression level of ATP5b(0.67±0.01)was down-regulated in D-gal group( P<0.01), the expression of MFN2 protein(0.29±0.02)was significantly decreased in D-gal group( P<0.01), and the expression of DRP1 and P62 protein(0.31±0.02 and 0.21±0.01)was significantly increased in D-gal group(both P<0.01). Compared with the D-gal group, the ATP content(193±1)10 -4 μmol in the kidney tissue of the mice was significantly increased in SMPS intervention group( P< 0.01), and the ATP5b mRNA expression and MFN2 protein expression(0.87±0.05 and 0.71±0.08)were significantly increased in SMPS intervention group(both P< 0.01), DRP1 and P62 protein expressions(0.20±0.01 and 0.10±0.01)were significantly down-regulated in in SMPS intervention group(both P< 0.01). Conclusions:SMPS can improve the mitochondrial dynamic homeostasis disorder in aging mice by increasing the activity of antioxidant enzymes, up-regulating the expression of ATP5b mRNA and MFN2 protein, down-regulating the expression of DRP1 and P62 protein, and promoting the generation of mitochondrial ATP in D-gal-induced aging mice kidney tissue.