Objective:To evaluate the efficacy of bevacizumab in reducing dyspnea, avoiding tracheostomy, and assessing the overall safety and effectiveness of the treatment in patients with juvenile-onset recurrent respiratory papillomatosis (JORRP).Methods:This study included 19 patients with JORRP treated with Bevacizumab at the Department of Otolaryngology-Head and Neck Surgery, BenQ Medical Center, from March 2022 to June 2024. The age of patients ranged from 1.0 to 27.0 years (10.47±8.45 years), with age at onset ranging from 0.5 to 15.0 years (3.66±3.70 years). The cohort included 11 males and 8 females. Bevacizumab was administered intravenously at a dose of 10 mg/kg every three weeks for three sessions. Efficacy was evaluated by comparing the standardized lesion volume pre-and post-treatment, with statistical analysis performed using R software (4.3.1).Results:Among the 19 patients, 11 presented with dyspnea before treatment. All patients experienced varying degrees of dyspnea relief within 72 hours following the initial treatment, and only one patient had mild dyspnea by the second treatment session three weeks later. The average reduction rates at 24 and 48 hours post-initia treatment were 25.75% and 47.16%, respectively. Following three treatment cycles, the average cumulative reduction rate was 67.47%, significantly higher than after the first treatment ( Z=3.38, P=0.002). Throughout the treatment period, no adverse events that of grade 2 or higher were noted. Conclusions:Bevacizumab can rapidly alleviate dyspnea symptoms and significantly reduce lesion volume in JORRP patients, exhibiting satisfactory overall safety and effectiveness. However additional large-scale prospective studies are warranted to validate its long-term safety and efficacy.

Objective:To identify and validate secreted effector proteins of Chlamydia psittaci ( C. psittaci) through bioinformatic prediction and experimental verification, and to characterize their subcellular localization in host cells. Methods:Potential effector proteins were predicted using bioinformatics tools. Candidate effectors were fused to β-lactamase through the constructed expression vectors, and these vectors were transformed into C. psittaci. The secretion of these candidate effectors was evaluated by β-lactamase translocation assays. Eukaryotic expression vectors of confirmed effectors were transfected into host cells to determine their intracellular localization patterns. Results:Bioinformatic analysis identified 29 candidate effector proteins. Experimental validation confirmed the secretion of five effectors, with four exhibiting cytoplasmic localization and one displaying nuclear localization in host cells.Conclusion:This study characterizes five novel C. psittaci secreted effector proteins, providing critical insights for investigating the molecular pathogenesis of psittacosis.

Objective:To explore the pathogenic mechanism of a child with Waardenburg syndrome type 4C due to a c. 661_664dup (p.P222Lfs*60) variant of SOX10 gene through in vitro experiments. Methods:A child diagnosed at the Handan First Hospital was selected as the study subject. Clinical data of the child was collected. Peripheral blood samples were collected from the child and his parents. Following extraction of genomic DNA, trio-whole exome sequencing was carried out. Pathogenicity of candidate variant was determined by bioinformatic analysis and reference to the guidelines from the American College of Medical Genetics and Genomics (ACMG). Candidate variant was verified by Sanger sequencing. Expression plasmids of wild-type SOX10 and the c. 661_664dup (p.P222Lfs*60) variant were constructed and transiently transfected into 293T cells to determine the expression at the RNA and protein levels. The 293T cells transiently transfected with the wild-type/mutant SOX10 were treated with 10 μg/mL cycloheximide (CHX) for 0, 4, 8, 24 h, respectively, and the degradation rate of target protein was detected by Western blotting assay. This study has been approved by the Ethics Committe of Handan First Hospital(Ethics No.HDYY-LW-25053). Results:The child was found to harbor a heterozygous c. 661_664dup (p.P222Lfs*60) variant of the SOX10 gene, which was unreported previously. The variant did not significantly alter the expression of SOX10 at the mRNA level but the protein level. After the CHX treatment, the degradation of mutant SOX10 protein had slowed down. Conclusion:The mutant SOX10 may affect the expression of downstream genes by affecting the degradation rate of its protein product.

Objective:To investigate the effects and possible mechanisms of targeted inhibition of Polo-like kinase 1 (PLK1) on the proliferation, mitosis and apoptosis of cervical cancer cells.Methods:Logarithmically growing human cervical cancer cell lines HeLa and C-33A were selected, and cells treated with 10 and 20 nmol/L PLK1 inhibitor GSK461364 were used as different concentrations of GSK461364 groups, while cells not treated with GSK461364 were used as the control group. CCK-8 method was used to detect cell proliferation ability (represented by absorbance values at wavelength 450 nm), flow cytometry was used to detect chromosome ploidy (propidium iodide staining), mitochondrial membrane potential detected by flow cytometry was used to evaluate cell apoptosis status (JC-1 fluorescent probe, the cells where the JC-1 monomers emitting green fluorescence were located were apoptotic cells), and Western blotting was used to detect the expression levels of cell cycle and apoptosis-related proteins.Results:The results of CCK-8 method showed that the proliferation ability of HeLa cells was lower than that of the control group after 24 hours of treatment with 10 and 20 nmol/L GSK461364 and continued culture for 24, 48 and 72 hours without GSK461364. The proliferation ability of C-33A cells was lower than that of the control group after 24 hours of treatment with 10 and 20 nmol/L GSK461364 and continued culture for 48 and 72 hours without GSK461364, and the differences were statistically significant (all P < 0.05). The results of flow cytometry analysis showed that after 24 hours of treatment with GSK461364 and continued culture for 72 hours without GSK461364, the proportions of polyploid cell subpopulations in HeLa cells of the 10 and 20 nmol/L GSK461364 groups and the control group were (13.89±3.73)%, (12.30±5.49)% and (9.86±1.15)%, respectively, with no statistically significant difference ( F = 0.82, P > 0.05); the proportions of polyploid cell subpopulations in C-33A cells of the 10 and 20 nmol/L GSK461364 groups and the control group were (8.45±2.20)%, (11.06±2.53)% and (5.42±1.36)%, respectively, with statistically significant difference ( F = 5.46, P = 0.045). Among them, the proportion of polyploid cell subpopulations in the 20 nmol/L GSK461364 group was higher than that in the control group, with statistically significant differences ( t = 3.40, P = 0.027). The results of flow cytometry detection of mitochondrial membrane potential showed that after 24 hours of treatment with GSK461364 and continued culture for 72 hours without GSK461364, the proportions of apoptotic cells in HeLa cells of the control group, 10 nmol/L GSK461364 group and 20 nmol/L GSK461364 group were (3.96±2.28)%, (24.38±4.89)%, and (46.24±4.38)%, respectively, and the difference was statistically significant ( F = 83.18, P < 0.000 1), the proportion of apoptotic cells in the 10 and 20 nmol/L GSK461364 groups was higher than that in the control group, and the difference was statistically significant (both P < 0.01), and the proportion of apoptotic cells in the 20 nmol/L group was higher than that in the 10 nmol/L group ( t = 5.76, P = 0.005); the proportions of apoptotic cells in C-33A cells of the control group, 10 nmol/L GSK461364 group and 20 nmol/L GSK461364 group were (1.81±1.59)%, (5.22±1.57)% and (15.87±5.81)%, respectively, with statistically significant differences ( F = 12.49, P = 0.007), and the proportion of apoptotic cells in the 20 nmol/L group was higher than that in the 10 nmol/L group and the control group (both P < 0.05). The results of Western blotting analysis showed that after 24 hours of treatment with GSK461364 and continued culture for 72 hours without GSK461364, the relative expression levels of cleaved Caspase-9 and cleaved polyadenosine diphosphate-ribose polymerase in HeLa and C-33A cells treated with 10 and 20 nmol/L GSK461364 were higher than those in the control group, and the relative expression levels of cdc25c and phosphorylated cdc25c (Ser216) were lower than those in the control group, and the differences were statistically significant (all P < 0.05). Conclusions:Targeted inhibition of PLK1 can inhibit the proliferation activity of cervical cancer cells in vitro, induce cell mitotic cycle arrest, and promote cell apoptosis; these may be achieved by regulating cell cycle and apoptosis-related proteins.

Objective:To explore the efficacy of deep learning-based automatic segmentation technology in the segmentation of hepatocellular carcinoma (HCC) lesions using gadoxetate disodium-enhanced MRI (EOB-MRI), and to investigate the prognostic value of radiomics analysis in predicting patient outcomes.Methods:This was a cross-sectional, retrospective study that collected data from 352 patients with solitary HCC who underwent imaging at the Harbin Medical University Cancer Hospital between June 2015 and May 2023. The patients were randomly divided into a training set ( n=213) and a validation set ( n=139) in a 3∶2 ratio using weighted random sampling. Two radiologists manually annotated the lesions. Hepatobiliary-phase EOB-MRI images were standardized, and six deep learning models,nnU-Net, nnFormer, UnetR, Swin-UnetR, UnetR++ and MedNeXt,were trained for automatic segmentation on the training set. The segmentation performance was evaluated on the validation set, and the segmentation efficacy was assessed using the Dice coefficient and 95% Hausdorff distance (HD 95), identifying of the optimal model. Radiomics features were extracted from both manual and automatic segmentation regions, and the radiomics score (Radscore) was calculated to stratify patients into high-risk and low-risk groups. Kaplan-Meier curves and log-rank tests were used to analyze the differences in relapse-free survival (RFS) and overall survival (OS) between the different stratified groups. Results:Among the automatic segmentation models, the MedNeXt model performed best in the validation set, with a Dice coefficient of 76.0%, HD 95 of 7.2, and a segmentation success rate of 90.6% (126/139). The nnFormer model was the second-best, with a Dice coefficient of 75.3%, HD 95 of 10.1, and a segmentation success rate of 89.9% (125/139). Other models showed Dice coefficients ranging from 66.3% to 74.1%. A MedNext-nnF model was established by combining the MedNeXt and nnFormer models, achieving a Dice coefficient of 78.2%, HD 95 of 5.9, and a segmentation success rate of 92.1% (128/139) in the validation group. After constructing the automatic segmentation radiomics prognostic model, patients were stratified by Radscore. Both manual and automatic segmentation models showed statistically significant differences in RFS and OS between different risk groups ( P<0.001). Conclusions:The Mednext-nnF fusion model enables efficient and automated segmentation of HCC lesions in EOB-MRI. The radiomics model constructed based on the automated segmentation demonstrates strong performance in predicting and stratifying prognostic risk.

Diabetic kidney disease(DKD)with increasing global prevalence lacks effective therapeutic targets to halt or reverse its progression.Therapeutic targets supported by causal genetic evidence are more likely to succeed in randomized clinical trials.In this study,we integrated large-scale plasma proteomics,genetic-driven causal inference,and experimental validation to identify prioritized targets for DKD using the UK Biobank(UKB)and FinnGen cohorts.Among 2844 diabetic patients(528 with DKD),we identified 37 targets significantly associated with incident DKD,supported by both observational and causal evi-dence.Of these,22％(8/37)of the potential targets are currently under investigation for DKD or other diseases.Our prospective study confirmed that higher levels of three prioritized targets-insulin-like growth factor binding protein 4(IGFBP4),family with sequence similarity 3 member C(FAM3C),and prostaglandin D2 synthase(PTGDS)—were associated with a 4.35,3.51,and 3.57-fold increased likeli-hood of developing DKD,respectively.In addition,population-level protein-altering variants(PAVs)analysis and in vitro experiments cross-validated FAM3C and IGFBP4 as potential new target candidates for DKD,through the classic NLR family pyrin domain containing 3(NLRP3)-caspase-1-gasdermin D(GSDMD)apoptotic axis.Our results demonstrate that integrating omics data mining with causal inference may be a promising strategy for prioritizing therapeutic targets.

OBJECTIVE: To explore the pathogenic mechanism of a child with Waardenburg syndrome type 4C due to a c.661_664dup (p.P222Lfs*60) variant of SOX10 gene through in vitro experiments. METHODS: A child diagnosed at the Handan First Hospital was selected as the study subject. Clinical data of the child was collected. Peripheral blood samples were collected from the child and his parents. Following extraction of genomic DNA, trio-whole exome sequencing was carried out. Pathogenicity of candidate variant was determined by bioinformatic analysis and reference to the guidelines from the American College of Medical Genetics and Genomics (ACMG). Candidate variant was verified by Sanger sequencing. Expression plasmids of wild-type SOX10 and the c.661_664dup (p.P222Lfs*60) variant were constructed and transiently transfected into 293T cells to determine the expression at the RNA and protein levels. The 293T cells transiently transfected with the wild-type/mutant SOX10 were treated with 10 ug/mL cycloheximide (CHX) for 0, 4, 8, 24 h, respectively, and the degradation rate of target protein was detected by Western blotting assay. This study has been approved by the Ethics Committee of Handan First Hospital (Ethics No. HDYY-LW-25053). RESULTS: The child was found to harbor a heterozygous c.661_664dup (p.P222Lfs*60) variant of the SOX10 gene, which was unreported previously. The variant did not significantly alter the expression of SOX10 at the mRNA level but the protein level. After the CHX treatment, the degradation of mutant SOX10 protein had slowed down. CONCLUSION The mutant SOX10 may affect the expression of downstream genes by affecting the degradation rate of its protein product.
Humans ; HEK293 Cells ; Mutation ; SOXE Transcription Factors/metabolism* ; Waardenburg Syndrome/genetics* ; Child

Objective:To explore the efficacy of deep learning-based automatic segmentation technology in the segmentation of hepatocellular carcinoma (HCC) lesions using gadoxetate disodium-enhanced MRI (EOB-MRI), and to investigate the prognostic value of radiomics analysis in predicting patient outcomes.Methods:This was a cross-sectional, retrospective study that collected data from 352 patients with solitary HCC who underwent imaging at the Harbin Medical University Cancer Hospital between June 2015 and May 2023. The patients were randomly divided into a training set ( n=213) and a validation set ( n=139) in a 3∶2 ratio using weighted random sampling. Two radiologists manually annotated the lesions. Hepatobiliary-phase EOB-MRI images were standardized, and six deep learning models,nnU-Net, nnFormer, UnetR, Swin-UnetR, UnetR++ and MedNeXt,were trained for automatic segmentation on the training set. The segmentation performance was evaluated on the validation set, and the segmentation efficacy was assessed using the Dice coefficient and 95% Hausdorff distance (HD 95), identifying of the optimal model. Radiomics features were extracted from both manual and automatic segmentation regions, and the radiomics score (Radscore) was calculated to stratify patients into high-risk and low-risk groups. Kaplan-Meier curves and log-rank tests were used to analyze the differences in relapse-free survival (RFS) and overall survival (OS) between the different stratified groups. Results:Among the automatic segmentation models, the MedNeXt model performed best in the validation set, with a Dice coefficient of 76.0%, HD 95 of 7.2, and a segmentation success rate of 90.6% (126/139). The nnFormer model was the second-best, with a Dice coefficient of 75.3%, HD 95 of 10.1, and a segmentation success rate of 89.9% (125/139). Other models showed Dice coefficients ranging from 66.3% to 74.1%. A MedNext-nnF model was established by combining the MedNeXt and nnFormer models, achieving a Dice coefficient of 78.2%, HD 95 of 5.9, and a segmentation success rate of 92.1% (128/139) in the validation group. After constructing the automatic segmentation radiomics prognostic model, patients were stratified by Radscore. Both manual and automatic segmentation models showed statistically significant differences in RFS and OS between different risk groups ( P<0.001). Conclusions:The Mednext-nnF fusion model enables efficient and automated segmentation of HCC lesions in EOB-MRI. The radiomics model constructed based on the automated segmentation demonstrates strong performance in predicting and stratifying prognostic risk.

Objective:Based on HyperArc stereotactic radiotherapy(SRT)technique,six-dimensional free bed combined with double mask fixation was used to treat intracranial tumors,and the positioning errors of within batch and between batches were analyzed,so as to provide basis for the accuracy of clinical treatment of this technique.Methods:A total of 13 patients with intracranial tumors who admitted to Peking Union Medical College Hospital from March to July 2023 were retrospectively selected,and they were treated by using HyperArc SRT technique.The validation images of cone-beam computed tomography(CBCT)of within batch and between batches during treatment were analyzed.The positioning errors of three translational direction[left and right(x),head and foot(y)and abdominal and dorsal(z)]and rotational direction were analyzed.The each positioning error was set as group A,and the remaining error after the positioning error was corrected through six-dimensional free bed was set as group B,and the error post treatment was set as group C.The difference between group B and group C was defined as the change of within batch.According to the margin formula,the positioning error of within batch was used to calculate the required range of margin.Results:Under the mode of six-dimensional free bed correction combined with double mask fixation,a total of 59 times of HyperArc SRT on head were performed.In the comparison of the average errors on the six-dimensional direction among groups A,B and C,the errors of group A on x direction and y direction were respectively(0.119±0.039)and(-0.133±0.047)cm,and the differences of them between group A and group B[(0.004±0.002)and(0.018±0.005)cm]were significant(t=2.890,-3.224,P<0.05).There were no significant differences on other directions between the two groups(P>0.05).The error of RX direction of group B was(0.033±0.021)°,and the difference of that between group B and group C[(0.122±0.045)°]was significant(t=-2.306,P<0.05),while there were no significant differences on other directions(P>0.05).In the margin of the design of the plan of intracranial tumors,the x,y and z directions were respectively 0.6,0.9 and 0.4 mm.Conclusion:In the radiotherapy of using HyperArc SRT technique for intracranial tumors,the use of six-dimensional free bed combined with double mask treatment can significantly shorten the margin,and ensure accurate irradiation for gross tumor volume(GTV)and simultaneously reduce the irradiation volume and dose of surrounding normal tissue.

Objective:To identify and validate secreted effector proteins of Chlamydia psittaci ( C. psittaci) through bioinformatic prediction and experimental verification, and to characterize their subcellular localization in host cells. Methods:Potential effector proteins were predicted using bioinformatics tools. Candidate effectors were fused to β-lactamase through the constructed expression vectors, and these vectors were transformed into C. psittaci. The secretion of these candidate effectors was evaluated by β-lactamase translocation assays. Eukaryotic expression vectors of confirmed effectors were transfected into host cells to determine their intracellular localization patterns. Results:Bioinformatic analysis identified 29 candidate effector proteins. Experimental validation confirmed the secretion of five effectors, with four exhibiting cytoplasmic localization and one displaying nuclear localization in host cells.Conclusion:This study characterizes five novel C. psittaci secreted effector proteins, providing critical insights for investigating the molecular pathogenesis of psittacosis.