AIM:This study aims to investigate the mechanism by which Zhilianwan(ZLW)decoction affects dextran sodium sulfate(DSS)-induced ulcerative colitis(UC)in mice,focusing on the Toll-like receptor 4(TLR4)/myeloid differentiation factor 88(MyD88)/nuclear factor-κB(NF-κB)signaling pathway.METHODS:Fifty male C57BL/6J mice were allowed ad libitum access to food for 1 week before the experiment.They were randomly divided into 5 groups:control group,model group,mesalazine(ME)group,high-dose ZLW(ZLW-H)group,and low-dose ZLW(ZLW-L)group,with ten mice in each group.All mice,except those in control group that received distilled water,were given a 3%DSS solution for seven consecutive days,starting the intervention on the first day of modeling.Each group re-ceived their respective treatments via gavage at volume of 20 μL/g for ten consecutive days.The mice in control and model groups received an equivalent volume of distilled water,while those in ME,ZLW-H,and ZLW-L groups were adminis-tered 0.2 g·kg-1·d-1 of ME,10.92 g·kg-1·d-1 of ZLW,and 2.73 g·kg-1·d-1 of ZLW,respectively.Body weight and dis-ease activity index(DAI)scores were recorded daily.At the end of the intervention,colon length was measured,and he-matoxylin-eosin staining was performed to assess pathological changes in colon tissues.ELISA and qPCR were employed to measure serum levels of interleukin-1β(IL-1β),IL-6,tumor necrosis factor-α(TNF-α)and IL-10,as well as the mRNA expression levels in colon tissues.Western blot analysis was conducted to evaluate the protein levels of TLR4,MyD88,cytosolic NF-κB and nuclear NF-κB in colon tissues.RESULTS:Compared with model group,the mice treated with ZLW exhibited an increase in body weight and colon length(P＜0.05),along with a decrease in DAI and colon histo-pathological scores(P＜0.05).Serum levels of IL-1β,IL-6,and TNF-α were significantly lower(P＜0.05),while IL-10 levels increased(P＜0.05).The mRNA expression levels of these inflammatory factors in colonic tissues reflected similar trends.Additionally,levels of TLR4,MyD88,and nuclear NF-κB proteins were reduced(P＜0.05),whereas cytosolic NF-κB protein expression was elevated(P＜0.05)in the colon tissues of treated mice.CONCLUSION:ZLW exerts at-tenuating effects on DSS-induced intestinal injury in UC mice,though modulation of the TLR4/MyD88/NF-κB signaling pathway.

Objective To propose a novel method based on three-dimensional depthwise separable convolution network(3D DSN)for the separation of PET images with dual tracers of 18F-FDG and 18F-FAPI.Methods A total of 120 pairs of 18F-FDG and 18F-FAPI PET images of the same patient scanned separately at different time points were collected,and the dual-tracer PET image was generated through simulation.After the image registration of PET images of two tracers for ensuring spatial position matching,the registered PET images were forward-projected to generate sinogram data,and the sinogram data of two tracers were accumulated to obtain mixed sinogram data.Subsequently,the dual-tracer PET image was reconstructed using maximum likelihood expectation maximization and input into a 3D DSN based network for image separation,thereby obtaining PET images of two single tracers.Results Compared with 3D CNN method,the proposed method increased the structure similarity index measure(SSIM)of the separated 18F-FDG images to the real 18F-FDG images by 0.87%,increased the peak signal-to-noise ratio(PSNR)by 11.8%,and reduced the normalized root mean square error(NRMSE)by 52%.The SSIM of the separated 18F-FAPI images to the real 18F-FAPI images increased by 1.1%,PSNR increased by 17.0%,and NRMSE decreased by 51%.Conclusion The proposed method can be effectively applied to simultaneous PET imaging with dual PET tracers,reducing the number of scans and costs in time and money,and providing clinical doctors more accurate and abundant diagnostic information.

Objective To propose a novel method based on three-dimensional depthwise separable convolution network(3D DSN)for the separation of PET images with dual tracers of 18F-FDG and 18F-FAPI.Methods A total of 120 pairs of 18F-FDG and 18F-FAPI PET images of the same patient scanned separately at different time points were collected,and the dual-tracer PET image was generated through simulation.After the image registration of PET images of two tracers for ensuring spatial position matching,the registered PET images were forward-projected to generate sinogram data,and the sinogram data of two tracers were accumulated to obtain mixed sinogram data.Subsequently,the dual-tracer PET image was reconstructed using maximum likelihood expectation maximization and input into a 3D DSN based network for image separation,thereby obtaining PET images of two single tracers.Results Compared with 3D CNN method,the proposed method increased the structure similarity index measure(SSIM)of the separated 18F-FDG images to the real 18F-FDG images by 0.87%,increased the peak signal-to-noise ratio(PSNR)by 11.8%,and reduced the normalized root mean square error(NRMSE)by 52%.The SSIM of the separated 18F-FAPI images to the real 18F-FAPI images increased by 1.1%,PSNR increased by 17.0%,and NRMSE decreased by 51%.Conclusion The proposed method can be effectively applied to simultaneous PET imaging with dual PET tracers,reducing the number of scans and costs in time and money,and providing clinical doctors more accurate and abundant diagnostic information.

AIM:This study aims to investigate the mechanism by which Zhilianwan(ZLW)decoction affects dextran sodium sulfate(DSS)-induced ulcerative colitis(UC)in mice,focusing on the Toll-like receptor 4(TLR4)/myeloid differentiation factor 88(MyD88)/nuclear factor-κB(NF-κB)signaling pathway.METHODS:Fifty male C57BL/6J mice were allowed ad libitum access to food for 1 week before the experiment.They were randomly divided into 5 groups:control group,model group,mesalazine(ME)group,high-dose ZLW(ZLW-H)group,and low-dose ZLW(ZLW-L)group,with ten mice in each group.All mice,except those in control group that received distilled water,were given a 3%DSS solution for seven consecutive days,starting the intervention on the first day of modeling.Each group re-ceived their respective treatments via gavage at volume of 20 μL/g for ten consecutive days.The mice in control and model groups received an equivalent volume of distilled water,while those in ME,ZLW-H,and ZLW-L groups were adminis-tered 0.2 g·kg-1·d-1 of ME,10.92 g·kg-1·d-1 of ZLW,and 2.73 g·kg-1·d-1 of ZLW,respectively.Body weight and dis-ease activity index(DAI)scores were recorded daily.At the end of the intervention,colon length was measured,and he-matoxylin-eosin staining was performed to assess pathological changes in colon tissues.ELISA and qPCR were employed to measure serum levels of interleukin-1β(IL-1β),IL-6,tumor necrosis factor-α(TNF-α)and IL-10,as well as the mRNA expression levels in colon tissues.Western blot analysis was conducted to evaluate the protein levels of TLR4,MyD88,cytosolic NF-κB and nuclear NF-κB in colon tissues.RESULTS:Compared with model group,the mice treated with ZLW exhibited an increase in body weight and colon length(P＜0.05),along with a decrease in DAI and colon histo-pathological scores(P＜0.05).Serum levels of IL-1β,IL-6,and TNF-α were significantly lower(P＜0.05),while IL-10 levels increased(P＜0.05).The mRNA expression levels of these inflammatory factors in colonic tissues reflected similar trends.Additionally,levels of TLR4,MyD88,and nuclear NF-κB proteins were reduced(P＜0.05),whereas cytosolic NF-κB protein expression was elevated(P＜0.05)in the colon tissues of treated mice.CONCLUSION:ZLW exerts at-tenuating effects on DSS-induced intestinal injury in UC mice,though modulation of the TLR4/MyD88/NF-κB signaling pathway.

Objective The prediction of RR intervals in hypertensive patients can help clinicians to analyze and warn patients'heart condition.Methods Using 8 patients'data as samples,the RR intervals of patients were predicted by long short-term memory network(LSTM)and gradient lift tree(XGBoost),and the prediction results of the two models were combined by the inverse variance method to overcome the disadvantage of single model prediction.Results Compared with the single model,the proposed combined model had a different degree of improvement in the prediction of RR intervals in 8 patients.Conclusion LSTM-XGBoost model provides a method for predicting RR intervals in hypertensive patients,which has potential clinical feasibility.

Objective:To explore the clinical features and genetic etiology of a child with Char syndrome.Methods:A child who was presented at the Department of Child Health, Henan Children′s Hospital in February 2022 was selected as the study subject. Clinical data of the child was collected, and peripheral blood samples of the child and her parents were collected for the extraction of genomic DNA. Whole exome sequencing was carried out, and candidate variants were verified by Sanger sequencing and bioinformatic analysis.Results:The child had mainly manifested facial dysmorphism, patent ductus arteriosus, growth retardation, curving of fifth fingers and middle toes. Whole exome sequencing revealed that she has harbored a heterozygous c. 944A>C (p.Glu315Ala) variant of the TFAP2B gene, which was verified to be de novo by Sanger sequencing. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), the variant was rated to be likely pathogenic (PM1+ PM2_Supporting+ PM6+ PP3). Conclusion:The heterozygous c. 944A>C (p.Glu315Ala) variant of the TFAP2B gene probably underlay the Char syndrome in this child. Above finding has expanded the mutational and phenotypic spectra of the TFAP2B gene, which has facilitated early identification and diagnosis of Char syndrome.

Various types of software needed in radiomics studies come with the problems such as data incompatibility and hyperparameter tuning.Therefore,an artificial intelligence-based software is developed for radiomics studies,providing doctors and researchers a solution with image preprocessing,feature extraction,feature selection,modeling analysis and data visualization.The usability of the software is demonstrated using a public data set.Eight sets of feature selectors and classifiers are established for classification predication on test data set and key performance indicator output.Through hyperparameter tuning,the model is further optimized.Researchers will focus more on the research itself rather than unnecessary development efforts,and radiomics studies will become more convenient and efficient with the software addressed.

Various types of software needed in radiomics studies come with the problems such as data incompatibility and hyperparameter tuning.Therefore,an artificial intelligence-based software is developed for radiomics studies,providing doctors and researchers a solution with image preprocessing,feature extraction,feature selection,modeling analysis and data visualization.The usability of the software is demonstrated using a public data set.Eight sets of feature selectors and classifiers are established for classification predication on test data set and key performance indicator output.Through hyperparameter tuning,the model is further optimized.Researchers will focus more on the research itself rather than unnecessary development efforts,and radiomics studies will become more convenient and efficient with the software addressed.

Aim To explore the inhibition of Sinica Maxim′s extract( CSME) on resistant infections of burn wounds,such as the methicillin-resistant staphylococcus aureus ( MRSA ) , resistant pseudomonas aeruginosa (RPA) and resistant escherichia coli(RECO). Meth-ods The resistant strains were cultured by MH agar plates. After resistance genes of quality control strains were extracted and appraised, such as mecA, mexB, merA, qacE△1-sull, tnpU/A and mexB, etc, and then,some projects of CSME were detected,such as the antibacterial spectrum, the minimum inhibitory con-centration(MIC), different concentrations of sensitive rate and inhibition curves, etc. Finally, these results were compared with the inhibitory effects of some anti-biotics to determine the sensitivity rates of CSME. Re-sults The MIC of CSME was 62. 5 ,125 ,250 g · L-1 respectively on the MESA, RPA and RECO. The inhi-bition rates of CSME appeared concentration-dependent on these three kinds of resistant bacteria,and the inhi-bition rates of the multi-concentration CSME on RECO were significantly lower than on MRSA and RPA ( P<0. 05). While in MIC,the resistance rates of MRSA on carbenicillin, cefazolin, erythromycin were significant-ly higher than those of CSME(P<0. 05); The inhibi-tion zones of CSME were significantly smaller than those of ceftriaxone, cefepime, imipenem, but greater than those of other antibiotics( P<0. 05 ); The inhibi-tion zones of CSME on RPA were significantly smaller than those of carbenicillin, and greater than those of other antibiotics ( P <0. 05 ) . The inhibition zones of CSME on RECO were significantly smaller than those of ceftriaxone,cefepime,imipenem,ciprofloxacin,nitro-furazone,and greater than those of other antibiotics ( P<0. 05 ) . Conclusions CSME has a significant inhi-bition on burn wound infection with these three kinds of resistant bacteria,such as MRSA,RPA and RECO. It is prompted that CSME could become one of the effective drugs to control burn wound infections with multi-re-sistant strains.

OBJECTIVETo compare two methods for threshold selection in Huber regularization for low-dose computed tomography imaging.

METHODSHuber regularization-based iterative reconstruction (IR) approach was adopted for low-dose CT image reconstruction and the threshold of Huber regularization was selected based on global versus local edge-detecting operators.

RESULTSThe experimental results on the simulation data demonstrated that both of the two threshold selection methods in Huber regularization could yield remarkable gains in terms of noise suppression and artifact removal.

CONCLUSIONBoth of the two methods for threshold selection in Huber regularization can yield high-quality images in low-dose CT image iterative reconstruction.