Objective This study aims to assess the impact of four-dimensional cone-beam computed tomography (4D-CBCT) image guidance on setup error correction and target dose distribution optimization in patients receiving stereotactic body radiotherapy for lung cancer. Methods A total of 82 lung cancer patients treated with SBRT in our hospital between February 2023 and February 2025 were randomly selected as study subjects. Using a random number table, they were divided into two groups. The conventional group underwent positioning verification using traditional three-dimensional cone-beam CT, while the study group underwent verification using 4D-CBCT. Setup errors, target dose-volume parameters, organ at risk dose-volume parameters, and adverse reactions were compared between the two groups. Results The setup errors in the X, Y, and Z axes in the study group were 0.21, 0.19, and 0.23 mm, respectively, which were significantly lower than 0.58, 0.62, and 0.59 mm in the conventional group (P<0.05). The three-dimensional vector error was 0.34 (0.21, 0.48) mm in the study group, which was significantly lower than 0.98 (0.65, 1.32) mm in the conventional group (P<0.05). The rotational errors in left-right, anteroposterior, and superior-inferior directions in the study group were (0.25±0.12)°, (0.21±0.10)°, and (0.23±0.11)°, respectively; these values were significantly lower than (0.48±0.18)°, (0.42±0.15)°, and (0.45±0.16)° in the conventional group (P<0.05). The minimum dose received by 95% of the target volume [(59.45±0.85) Gy] and the percentage of the target volume receiving at least 100% of the prescription dose [(95.82±2.65)%] in the study group were higher than those in the conventional group [(58.90±1.20) Gy and (93.65±3.85)%]. The homogeneity index and conformity index in the study group were 1.07±0.03 and 1.15±0.05, respectively, which were lower than 1.12±0.05 and 1.23±0.08 in the conventional group (P<0.05). No significant differences were observed between the two groups in the volume of the lung receiving 5 Gy [(28.11±5.52)% vs. (28.85±6.24)%], the volume of the lung receiving 20 Gy [(12.84±3.56)% vs. (13.45±3.90)%], mean lung dose [(8.65±2.11) Gy vs. (8.95±2.34) Gy], maximum spinal cord dose [(18.54±3.62) Gy vs. (19.13±4.25) Gy], or mean heart dose[(14.85±4.22) Gy vs. (16.27±4.83) Gy](P>0.05). The incidence rates of radiation pneumonitis, radiation esophagitis, and skin reactions in the study group were 12.20%, 7.32%, and 4.88%, respectively, which were not significantly different from 17.07%, 9.76%, and 7.32% in the conventional group (P>0.05). Conclusion The 4D-CBCT can reduce setup errors, improve target dose accuracy and conformity in lung cancer patients undergoing SBRT, and minimize radiation exposure to normal tissues, making it worthy of clinical promotion.

Objective This study aims to assess the impact of four-dimensional cone-beam computed tomography (4D-CBCT) image guidance on setup error correction and target dose distribution optimization in patients receiving stereotactic body radiotherapy for lung cancer. Methods A total of 82 lung cancer patients treated with SBRT in our hospital between February 2023 and February 2025 were randomly selected as study subjects. Using a random number table, they were divided into two groups. The conventional group underwent positioning verification using traditional three-dimensional cone-beam CT, while the study group underwent verification using 4D-CBCT. Setup errors, target dose-volume parameters, organ at risk dose-volume parameters, and adverse reactions were compared between the two groups. Results The setup errors in the X, Y, and Z axes in the study group were 0.21, 0.19, and 0.23 mm, respectively, which were significantly lower than 0.58, 0.62, and 0.59 mm in the conventional group (P<0.05). The three-dimensional vector error was 0.34 (0.21, 0.48) mm in the study group, which was significantly lower than 0.98 (0.65, 1.32) mm in the conventional group (P<0.05). The rotational errors in left-right, anteroposterior, and superior-inferior directions in the study group were (0.25±0.12)°, (0.21±0.10)°, and (0.23±0.11)°, respectively; these values were significantly lower than (0.48±0.18)°, (0.42±0.15)°, and (0.45±0.16)° in the conventional group (P<0.05). The minimum dose received by 95% of the target volume [(59.45±0.85) Gy] and the percentage of the target volume receiving at least 100% of the prescription dose [(95.82±2.65)%] in the study group were higher than those in the conventional group [(58.90±1.20) Gy and (93.65±3.85)%]. The homogeneity index and conformity index in the study group were 1.07±0.03 and 1.15±0.05, respectively, which were lower than 1.12±0.05 and 1.23±0.08 in the conventional group (P<0.05). No significant differences were observed between the two groups in the volume of the lung receiving 5 Gy [(28.11±5.52)% vs. (28.85±6.24)%], the volume of the lung receiving 20 Gy [(12.84±3.56)% vs. (13.45±3.90)%], mean lung dose [(8.65±2.11) Gy vs. (8.95±2.34) Gy], maximum spinal cord dose [(18.54±3.62) Gy vs. (19.13±4.25) Gy], or mean heart dose[(14.85±4.22) Gy vs. (16.27±4.83) Gy](P>0.05). The incidence rates of radiation pneumonitis, radiation esophagitis, and skin reactions in the study group were 12.20%, 7.32%, and 4.88%, respectively, which were not significantly different from 17.07%, 9.76%, and 7.32% in the conventional group (P>0.05). Conclusion The 4D-CBCT can reduce setup errors, improve target dose accuracy and conformity in lung cancer patients undergoing SBRT, and minimize radiation exposure to normal tissues, making it worthy of clinical promotion.

Objective This study aims to assess the impact of four-dimensional cone-beam computed tomography (4D-CBCT) image guidance on setup error correction and target dose distribution optimization in patients receiving stereotactic body radiotherapy for lung cancer. Methods A total of 82 lung cancer patients treated with SBRT in our hospital between February 2023 and February 2025 were randomly selected as study subjects. Using a random number table, they were divided into two groups. The conventional group underwent positioning verification using traditional three-dimensional cone-beam CT, while the study group underwent verification using 4D-CBCT. Setup errors, target dose-volume parameters, organ at risk dose-volume parameters, and adverse reactions were compared between the two groups. Results The setup errors in the X, Y, and Z axes in the study group were 0.21, 0.19, and 0.23 mm, respectively, which were significantly lower than 0.58, 0.62, and 0.59 mm in the conventional group (P<0.05). The three-dimensional vector error was 0.34 (0.21, 0.48) mm in the study group, which was significantly lower than 0.98 (0.65, 1.32) mm in the conventional group (P<0.05). The rotational errors in left-right, anteroposterior, and superior-inferior directions in the study group were (0.25±0.12)°, (0.21±0.10)°, and (0.23±0.11)°, respectively; these values were significantly lower than (0.48±0.18)°, (0.42±0.15)°, and (0.45±0.16)° in the conventional group (P<0.05). The minimum dose received by 95% of the target volume [(59.45±0.85) Gy] and the percentage of the target volume receiving at least 100% of the prescription dose [(95.82±2.65)%] in the study group were higher than those in the conventional group [(58.90±1.20) Gy and (93.65±3.85)%]. The homogeneity index and conformity index in the study group were 1.07±0.03 and 1.15±0.05, respectively, which were lower than 1.12±0.05 and 1.23±0.08 in the conventional group (P<0.05). No significant differences were observed between the two groups in the volume of the lung receiving 5 Gy [(28.11±5.52)% vs. (28.85±6.24)%], the volume of the lung receiving 20 Gy [(12.84±3.56)% vs. (13.45±3.90)%], mean lung dose [(8.65±2.11) Gy vs. (8.95±2.34) Gy], maximum spinal cord dose [(18.54±3.62) Gy vs. (19.13±4.25) Gy], or mean heart dose[(14.85±4.22) Gy vs. (16.27±4.83) Gy](P>0.05). The incidence rates of radiation pneumonitis, radiation esophagitis, and skin reactions in the study group were 12.20%, 7.32%, and 4.88%, respectively, which were not significantly different from 17.07%, 9.76%, and 7.32% in the conventional group (P>0.05). Conclusion The 4D-CBCT can reduce setup errors, improve target dose accuracy and conformity in lung cancer patients undergoing SBRT, and minimize radiation exposure to normal tissues, making it worthy of clinical promotion.

Objective:To explore the risk factors for bronchiolitis obliterans (BO) after Mycoplasma pneumoniae bronchiolitis in children. Methods:A retrospective cohort study was conducted on 122 children diagnosed with Mycoplasma pneumoniae bronchiolitis in Department No.2 of Respiratory Medicine of Beijing Children′s Hospital, Capital Medical University, from March 2017 to December 2024. Clinical data, including general information, clinical manifestations, imaging findings, laboratory tests, and outcomes, were analyzed. Patients were divided into BO and non-BO groups based on the presence of BO. Differences between groups were assessed using Mann-Whitney U test, χ2 test, or Fisher exact test. Logistic regression and receiver operating characteristic (ROC) curve analysis were employed to identify risk factors and evaluate predictive performance. Results:Among 122 children (73 males, 49 females), the age at onset was 5.0 (2.4, 7.1) years. The BO group included 21 patients, and the non-BO group 101. The BO group exhibited significantly longer durations of persistent high fever and higher peak levels of C-reactive protein, lactate dehydrogenase, and D-dimer compared to the non-BO group (9 (7, 11) vs. 4 (2, 6) d, 19 (7, 35) vs. 10 (7, 18) mg/L, 438 (337, 498) vs. 315 (274, 351) U/L, 0.36 (0.27, 0.91) vs. 0.21 (0.15, 0.29) mg/L, U=295.00, 743.50, 463.50, 470.50, all P<0.05). The BO group also had higher proportions of resting oxygen saturation <0.95 on room air (100.0% (21/21) vs. 43.6% (44/101)), inspiratory retractions (57.1% (12/21) vs. 18.8% (19/101), χ2=11.53), and adenovirus co-infection (38.1% (8/21) vs. 5.0% (5/101)) (all P<0.05). Multivariate Logistic regression identified prolonged high fever ( OR=1.83, 95% CI 1.31-2.58, P<0.001), inspiratory retractions ( OR=10.48, 95% CI 1.72-63.85, P=0.011), and adenovirus co-infection ( OR=42.47, 95% CI 4.04-446.87, P=0.002) as independent risk factors for BO. ROC curve analysis revealed that a fever duration cutoff of 7.5 days predicted BO with 0.71 sensitivity and 0.92 specificity. Conclusions:Prolonged high fever (≥7.5 days), inspiratory retractions, and adenovirus co-infection are significant predictors of BO after Mycoplasma pneumoniae bronchiolitis in children, which are helpful for early clinical identification.

In order to investigate the related pathogens and reveal the etiological characteristics of gout in goslings,191 typical clinical cases from partial regions of China were examined by RT-PCR/PCR detection of viral nucleic acids in domestic poultry and pathological analysis.The autop-sy results show that the clinical cases could be classified into three types based on the severity of urate deposition:severe,moderate,and mild,namely systemic urate deposition,local urate deposi-tion mainly in the liver and kidneys,and only a small amount of fine-grained urate deposition in the liver,gallbladder,or glandular stomach.The results of RT-PCR/PCR detection showed that the to-tal positive rates were as follows:GAstV Group2 63.9％,GAstV Group1 50.3％,AAstV-2 38.7％,novel Muscovy duck parvovirus(NPV)17.8％,GPV 16.2％,GoCV 12.6％,MDPV 7.9％,MDRV 8.4％,DPV 0.5％,GPMV and NDV 0.5％,the AstV-1、ARV、TMUV、NDV、FAdV、GHPyV were zero.Among all the postive samples,the rates of single positive,double positive,and multiple posi-tive were 18.3％,27.2％,and 44.0％,respectively.The rate of single positive samples containing AAstV was only 12.0％,the double or multiple positive samples containing GAstV Group 1/2 was 60.7％,and the rate of samples without GAstV Group 1/2 was 10.5％.The results also showed that 20(10.5％)samples were negative for 16 types of viruses.The AAstV particles isolated from single positive samples appear spherical shape,non-enveloped and 20-80 nm minsize.Two types of virus particles which with spherical shape and diameters of 40-100 and 20-40 nm can be isolated from the negative samples.The virus inoculation results show that the goose embryos can be led to death by clinical GAstV isolates,which with classic histopathological characteristics.Although the GAstV isolates cannot led to death and obvious typical histopathological change in goslings,the vi-ral nucleic acids can be detected in heart,liver,spleen,kidney,intestine and cloacal anal swabs.The above results indicated that there were multiple pathogens co-infection dominated by AAstv in Gosling gout in China,including cross species infections of multiple AAstVs,parvovirus,ARV and suspec-ted novel viruses.Moreover,the GAstV maybe not the only pathogen causing gout in goslings.

Goose astrovirus(GAstV)has become one of the most important pathogens endangering the goose farming industry in China.To discover the genomic information of prevalent strains in China in 2022 and reveal their biological characteristics,the whole genomes of 9 strains of GAstV-1 and 12 strains of GAstV-2 isolated from parts of China in 2022 were sequenced by the Chromo-some Walking and analyzed by bioinformatics software and websites.The analysis results of gene structure showed that the sizes of the coding genes ranged from 6 977 to 7 215 bp.The open read-ing frame 1(ORF1)of all strains contained the characteristic motifs of serine protease,nuclear lo-calization signal(NLS)and RNA-dependent RNA polymerase(RdRp).The ribosomal frameshift signals(RFS)were all in the form of stem-loop structures.However,the numbers of stem and loop nucleotides in GAstV-1 were"14+11"configuration,while those in GAstV-2 were"12+14"configuration,and the loop of GAstV-2 was in the"8+6"double-loop configuration.The results of homological analysis for ORF1b showed that the homology of the GAstV-1 isolats compared with the representative strains of avian astrovirus types 1,2,and 3(AAstV-1,AAstV-2,AAstV-3)ranged from 7％to 64％,and the homology of the GAstV-2 isolates ranged from 8％to 68％.The average genetic distances of ORF2 were 0.9,1.2,and 0.9 respectively compared with the represent-ative strains of AAstV-1,AAstV-2 and AAstV-3.While for the GAstV-2 isolates,the highest ho-mologies were 68％and 56％,the lowest homologies were 8％and 36％respectively.And the aver-age genetic distances of ORF2 were 1.0,1.2,and 0.5 respectively.B-cell-conformational epitopes screening results of ORF2 showed that,there were four common epitopes in the GAstV Group 1 i-solates,namely PRE,LALQSQSVNTFA,AAG and YQQVTSDQSI except for N-145,N-287 and N-314 in the two strains G1FJ267 and G1JS277.And there were seven common conformational epitopes in the GAstV-2 isolates,namely NQE,RAN,GPE,PRQ,TRAQ,SNS,and AVPPNTPL except for N-83,N-136,N-331 and N-351 in the strain G2FJ283-3B.The above results indicated that GAstV maybe belong to a new type of AAstV because of the difference between the clinical i-solates and the known strains of AAstV.And there was pathogenic diversity among the isolates.All the isolates of GAstV-1 and GAstV-2 belong to two different serotypes,and the possible serologi-cal subtypes among the isolates of GAstV-1 or GAstV-2 are remained to be further identified by serological tests.

Objective:To explore the value of amide proton transfer weighted imaging (APTWI) combined with human epidermal growth factor receptor 2 (HER2) expression in predicting pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer.Methods:The study was a cross-sectional study. Clinicopathological [estrogen receptor (ER), progesterone receptor (PR), HER2, Ki-67 status, and molecular subtypes] and imaging data were retrospectively analyzed in 100 female patients who had invasive ductal carcinoma of the breast confirmed pathologically by preoperative puncture in the Henan Cancer Hospital from May 2023 to May 2024. All patients underwent MRI, including enhanced MRI, APTWI, and diffusion-weighted imaging (DWI) before NAC. The reference enhanced MRI images were segmented into lesions using the threshold extraction method, and the three-dimensional region of interest within the tumor was automatically outlined by the software and replicated in the amide proton transfer map generated by APTWI and the apparent diffuse coefficient (ADC) map generated by DWI. The magnetization transfer ratio asymmetry (MTRasym) value and the ADC value were measured, respectively. Tumor response to NAC was assessed using the Miller-Payne grading system, where Grade 5 indicated pCR and Grades 1-4 were classified as non-pCR. Independent sample t-tests and χ2 tests were used to compare clinical pathological and imaging parameters between pCR and non-pCR patients. Statistically significant variables were included in multivariate logistic regression to identify independent predictors of pCR. The diagnostic performance of individual and combined indicators for pCR was evaluated using receiver operating characteristic curves and the area under the curve (AUC). DeLong′s test was used to compare AUCs. Results:There were 39 pCR and 61 non-pCR patients. Significant differences were observed between the pCR and non-pCR patients in molecular subtypes, ER, PR, HER2, and Ki-67 statuses ( P<0.05). Pre-treatment MTRasym values were significantly higher in the pCR patients compared to the non-pCR patients ( P=0.005), whereas ADC values showed no statistical difference ( P=0.372). Multivariate logistic regression analysis showed HER2 positivity ( OR=5.87, 95% CI 1.99-17.30, P=0.001) and MTRasym values>2.61% (OR=4.39, 95% CI 1.37-14.08, P=0.013) was independent predictors of pCR after NAC. HER2 positivity combined with MTRasym value>2.61% predicted pCR after NAC in breast cancer with AUC of 0.819, which was superior to HER2 positivity and MTRasym value alone in predicting efficacy ( Z=3.91, P<0.001; Z=2.63, P=0.009). Conclusions:The MTRasym value of pre-treatment APTWI is valuable in predicting pCR after NAC in breast cancer. APTWI combined with HER2 expression status can further enhance the predictive efficacy.

Objective:To screen the Alzheimer's disease(AD)-related genes and construct its diagnostic model using bioinformatics technology and machine learning(ML)algorithms,to discuss the immunological characteristics of AD patients,and to provide novel biomarkers for AD diagnosis.Methods:The AD-related gene expression dataset GSE125583 was downloaded from the Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)were identified through differential analysis.Gene Ontology(GO)functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway enrichment analyses were performed to explore the biological functions and signaling pathways of DEGs.A protein-protein interaction(PPI)network was constructed,and hub genes were screened using Cytoscape software combined with three ML algorithms:Least Absolute Shrinkage and Selection Operator(LASSO),eXtreme Gradient Boosting(XGBoost),and Random Forest(RF).The screened hub genes were utilized to build an AD diagnostic model via RF,followed by feature importance ranking.The model's efficacy and key genes were evaluated using a test set.Single-sample gene set enrichment analysis(ssGSEA)was used for immune cell infiltration analysis between AD group and control group.Results:Differential analysis identified 1 287 DEGs.The GO functional enrichment analysis results revealed that DEGs were primarily involved in biological functions related to neural signaling,synapses,and vesicles.KEGG signaling pathway enrichment analysis indicated significant enrichment of DEGs in ion transport,neurotransmitter,and ligand-gated channel pathways.Nine overlapping hub genes were screened by the three ML algorithms.In the AD diagnostic model,the top four key genes with highest diagnostic performance were adenylate cyclase-activating polypeptide 1(ADCYAP1),brain-derived neurotrophic factor(BDNF),platelet-derived growth factor receptor β(PDGFRB),and C-X-C motif chemokine receptor 4(CXCR4),with corresponding area under the curve(AUC)values of 0.852,0.795,0.820,and 0.756,respectively.The model achieved an AUC of 0.828,accuracy of 81.25%,sensitivity of 84.40%,and specificity of 71.43%.The immune cell infiltration analysis results demonstrated higher infiltration of macrophages,monocytes,natural killer(NK)cells,and lymphocytes in AD tissue.Among these,NK/natural killer T(NKT)cells and plasmacytoid dendritic cells showed significant correlations with the four key genes(P<0.05).Conclusion:The feature genes screened based on bioinformatics and ML exhibit diagnostic potential for AD.Genes such as ADCYAP1 may serve as potential biomarkers for AD diagnosis,offering significant implications for early prevention and treatment.

Increasing evidence shows that the early lesions of Parkinson's disease (PD) originate from gut, and correction of microbiota dysbiosis is a promising therapy for PD. FLZ is a neuroprotective agent on PD, which has been validated capable of alleviating microbiota dysbiosis in PD mice. However, the detailed mechanisms still need elucidated. Through metabolomics and 16S rRNA analysis, we identified glycoursodeoxycholic acid (GUDCA) was the most affected differential microbial metabolite by FLZ treatment, which was specially and negatively regulated by Clostridium innocuum, a differential microbiota with the strongest correlation to GUDCA production, through inhibiting bile salt hydrolase (BSH) enzyme. The protection of GUDCA on colon and brain were also clarified in PD models, showing that it could activate Nrf2 pathway, further validating that FLZ protected dopaminergic neurons through promoting GUDCA production. Our study uncovered that FLZ improved PD through microbiota-gut-brain axis, and also gave insights into modulation of microbial metabolites may serve as an important strategy for treating PD.

Although enteric glial cell (EGC) abnormal activation is reported to be involved in the pathogenesis of Parkinson's disease (PD), and inhibition of EGC gliosis alleviated gut and dopaminergic neuronal dysfunction was verified in our previous study, the potential role of gut microbiota on EGC function in PD still need to be addressed. In the present study, fecal microbiota transplantation revealed that EGC function was regulated by gut microbiota. By employing 16S rRNA and metabolomic analysis, we identified that 3-indolepropionic acid (IPA) was the most affected differential microbial metabolite that regulated EGC gliosis. The protective effects of IPA on PD were validated in rotenone-stimulated EGCs and rotenone (30 mg/kg i.g. for 4 weeks)-induced PD mice, as indicated by decreased inflammation, improved intestinal and brain barrier as well as dopaminergic neuronal function. Mechanistic study showed that IPA targeted pregnane X receptor (PXR) in EGCs, and inhibition of IL-13Rα1 involved cytokine-cytokine receptor interaction pathway, leading to inactivation of downstream JAK1-STAT6 pathway. Our data not only provided evidence that EGC gliosis was critical in spreading intestinal damage to brain, but also highlighted the potential role of microbial metabolite IPA in alleviating PD pathological damages through gut-brain axis.