Objective:This study aims to investigate the differences in hemostatic efficacy and patient comfort between an innovative domestically produced biodegradable nasal packing sponge and a traditional absorbent sponge following endoscopic nasal surgery. Methods:A prospective, randomized controlled trial design was utilized, including 30 patients who were divided into two groups according to random allocation, each receiving one of the two types of nasal packing. The study assessed the hemostatic efficacy, comfort, and safety of the materials by comparing the rates of no bleeding within 24 hours after packing, re-bleeding rates after 48 hours, pain ratings in the head and nasal areas, scores on a visual analog scale for nasal ocular symptoms, and safety indicators between the two groups. Results:The rates of no bleeding within 24 hours post-packing were 73.33% for both the experimental and control groups, with a no-bleeding rate of 100% after 48 hours in both groups. The pain rating in the head and nasal areas at various times post-packing was Grade Ⅰ（100%） in both groups, with no statistically significant difference（P=1.000）. The experimental groups sneezing score on the day of packing was（0.73±1.03）, lower than the control groups（2.27±1.67）, （P=0.007）; after 48 hours, the experimental groups sneezing score was（0.67±0.98）, also lower than the control groups（1.67±1.18）, （P=0.019）. There was no significant difference between the two groups in the Lund-Kennedy scoring during endoscopic examinations at the screening period, 7 days, 1 month, and 3 months post-packing（P>0.05）. Laboratory tests for other examination indicators were normal in both groups. Conclusion:The innovative domestically produced biodegradable nasal packing sponge not only provides hemostatic efficacy comparable to imported materials but also significantly improves patient comfort after surgery. It represents an economical and effective choice for nasal packing materials.
Humans ; Prospective Studies ; Surgical Sponges ; Endoscopy/methods* ; Male ; Female ; Epistaxis/prevention & control* ; Middle Aged ; Nasal Surgical Procedures/methods* ; Adult

OBJECTIVES: The risk factors and role of mother‒child gut microbiota in pediatric inflammatory bowel disease (PIBD) remain unclear. We aimed to explore the clinical risk factors associated with PIBD, analyze the characteristics of gut microbiota of children and their mothers, and examine the correlation of the microbial composition in mother‒child pairs. METHODS: We conducted a case-control study including children with PIBD and their mothers as the case group, as well as healthy children and their mothers as the control group. Questionnaires were used to collect information such as family illness history and maternal and early-life events. Fecal samples were collected from the children and mothers for microbiota 16S ribosomal RNA (rRNA) sequencing to analyze the composition and its potential association with PIBD. RESULTS: A total of 54 pairs of cases and 122 pairs of controls were recruited. A family history of autoimmune disease and antibiotic use during pregnancy were associated with an increased risk of PIBD, and a higher education level of the father was associated with a decreased risk of PIBD. Children with PIBD and mothers exhibited different gut microbiota compared to healthy children and mothers. Similarities were observed in the gut microbiota of mothers and children in the same groups. Some bacterial biomarkers of mothers discovered in this study had the power to predict PIBD in their offspring. CONCLUSIONS PIBD is influenced by maternal risk factors and has unique gut microbiota characteristics. The mother‒child gut microbiota is closely related, suggesting the transmission and influence of the gut microbiota between mothers and children. This study highlights the potential pathogenesis of PIBD and provides a basis for developing targeted interventions.
Humans ; Gastrointestinal Microbiome ; Female ; Risk Factors ; Case-Control Studies ; Male ; Child ; Inflammatory Bowel Diseases/etiology* ; Adult ; RNA, Ribosomal, 16S/genetics* ; Feces/microbiology* ; Mothers ; Pregnancy ; Child, Preschool

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.

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.

Objective To investigate the relationship between microRNA(miR)-425-5p/patched homolog 1(PTCH1)axis molecules and clinical pathological parameters and prognosis in cancer tissues of primary laryngeal cancer(PLC)patients.Methods 102 PLC patients admitted to Mianyang Central Hospital from March 2020 to March 2021 were selected.The relative expression level of miR-425-5p and PTCH1 positive expression rate in PLC cancer tissues and adjacent normal tissues were compared,and the relationship between miR-425-5p relative expression level,PTCH1 positive expression rate and PLC clinical pathological parameters was analyzed.Kaplan-Meier curve and Log-Rank were used χ2 tests were conducted to analyze the 3-year cumulative survival rate of miR-425-5p and PTCH1 positive/negative expression groups,and COX regression model was used to analyze the influencing factors of PLC prognosis.Results Compared with normal tissue adjacent to cancer,the relative expression level of miR-425-5p in PLC cancer tissue was significantly increased(2.12±0.52 vs 0.98±0.17),and the positive expression rate of PTCH1 was significantly reduced(27.45%vs 61.76%),with statistical significance(t/χ2=21.045,24.302,all P＜0.05).Compared with patients with T1-T2,N0,and high differentiation of tumors,patients with T3-T4,N1-N3,and low differentiation of tumors showed a significant increase in the relative expression of miR-425-5p(t=3.647,2.900,3.029),and a significant decrease in the positive expression rate of PTCH1(χ2=5.842,4.011,5.136),the differences were statistically significance(all P<0.05).The 3-year cumulative survival rate of the miR-425-5p high expression group was 64.52%(20/31),which was significantly lower than that of the low expression group at 84.06%(58/69).The 3-year cumulative survival rate of the PTCH1 high expression group was 80.00%(28/35),which was significantly higher than that of the low expression group at 64.62%(42/65),and the differences were statistically significant(Log-Rank χ2=4.287,4.548,all P<0.05).Elevated T taging,cervical lymph node recurrence,elevated N staging,pharyngeal recurrence,elevated miR-425-5p,and negative PTCH1 expression were risk factors for poor prognosis of PLC(all P<0.05).Conclusion High expression of miR-425-5p and low expression of PTCH1 in cancer tissues of primary laryngeal cancer patients are significantly correlated with elevated T stage,low tumor differentiation,elevated N stage,and low 3-year cumulative survival rate.

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.

Objective To investigate the relationship between microRNA(miR)-425-5p/patched homolog 1(PTCH1)axis molecules and clinical pathological parameters and prognosis in cancer tissues of primary laryngeal cancer(PLC)patients.Methods 102 PLC patients admitted to Mianyang Central Hospital from March 2020 to March 2021 were selected.The relative expression level of miR-425-5p and PTCH1 positive expression rate in PLC cancer tissues and adjacent normal tissues were compared,and the relationship between miR-425-5p relative expression level,PTCH1 positive expression rate and PLC clinical pathological parameters was analyzed.Kaplan-Meier curve and Log-Rank were used χ2 tests were conducted to analyze the 3-year cumulative survival rate of miR-425-5p and PTCH1 positive/negative expression groups,and COX regression model was used to analyze the influencing factors of PLC prognosis.Results Compared with normal tissue adjacent to cancer,the relative expression level of miR-425-5p in PLC cancer tissue was significantly increased(2.12±0.52 vs 0.98±0.17),and the positive expression rate of PTCH1 was significantly reduced(27.45%vs 61.76%),with statistical significance(t/χ2=21.045,24.302,all P＜0.05).Compared with patients with T1-T2,N0,and high differentiation of tumors,patients with T3-T4,N1-N3,and low differentiation of tumors showed a significant increase in the relative expression of miR-425-5p(t=3.647,2.900,3.029),and a significant decrease in the positive expression rate of PTCH1(χ2=5.842,4.011,5.136),the differences were statistically significance(all P<0.05).The 3-year cumulative survival rate of the miR-425-5p high expression group was 64.52%(20/31),which was significantly lower than that of the low expression group at 84.06%(58/69).The 3-year cumulative survival rate of the PTCH1 high expression group was 80.00%(28/35),which was significantly higher than that of the low expression group at 64.62%(42/65),and the differences were statistically significant(Log-Rank χ2=4.287,4.548,all P<0.05).Elevated T taging,cervical lymph node recurrence,elevated N staging,pharyngeal recurrence,elevated miR-425-5p,and negative PTCH1 expression were risk factors for poor prognosis of PLC(all P<0.05).Conclusion High expression of miR-425-5p and low expression of PTCH1 in cancer tissues of primary laryngeal cancer patients are significantly correlated with elevated T stage,low tumor differentiation,elevated N stage,and low 3-year cumulative survival rate.

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.