Jie Liu

Background: Pulmonary sarcomatoid carcinoma (PSC) is a rare, hidden-onset, rapidly progressive, poorly differentiated non-small cell lung cancer. Its accurate diagnosis is troublesome. Herein, we reported a case of pulmonary sarcomatoid carcinoma diagnosed by contrast-enhanced ultrasound angiography-guided lung biopsy and described the imaging features in this case. Case presentations: A 75-year-old female patient developed ...

Objective To develop a multimodal ultrasound radiomics model integrating power Doppler (PD) and superb microvascular imaging (SMI) data, combined with clinical baseline characteristics, and to evaluate its predictive performance for active inflammation in rheumatoid arthritis (RA). Methods A total of 2,503 PD and 2,503 SMI ultrasound images of metacarpophalangeal and proximal interphalangeal joints were collected from RA patients with active inflammation and non-active controls between December 2022 and March 2024. Single-modality (PD/SMI), multimodal (SMI_PD), and clinical-integrated models were developed. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis. Results The area under the curve (AUC) values for PD, SMI, multimodal SMI_PD, and clinical-integrated models were 0.76, 0.75, 0.82, and 0.83, respectively. Conclusion The multimodal radiomics model demonstrated superior diagnostic performance for RA active inflammation. SMI shows potential as a tool for subclinical inflammation monitoring, while the integration of multimodal ultrasound radiomics with clinical data further enhances clinical utility.

Pulmonary sarcomatoid carcinoma(PSC) is a rare, hidden-onset, rapidly progressive, poorly differentiated non-small cell lung cancer. Its accurate diagnosis is troublesome. Herein, we reported a case of pulmonary sarcomatoid carcinoma diagnosed by contrast-enhanced ultrasound angiography-guided lung biopsy. We described the CEUS imaging features in this case. These features differing from enhanced computed tomography have not been reported in previous literature.

Objective A prostate ultrasound (US) imaging omics model was established to assess its effectiveness in diagnosing prostate cancer (PCa), predicting Gleason score (GS), and determining the likelihood of distant metastasis. Methods US images of patients with prostate pathology confirmed by biopsy or surgery at our hospital were retrospectively analyzed. Regions of interest (ROI) segmentation, feature extraction, feature screening, and the construction and training of the radiomics model were performed. Results Area under the curve (AUC) for the magnetic resonance imaging Prostate Imaging Reporting and Data System (MRI PI-RADS) classification, radiomics alone, and radiomics combined with prostate-specific antigen (PSA) in diagnosing PCa were 70.74%, 71.13%, and 90.47%, respectively. AUCs for the MRI PI-RADS classification, radiomics alone, and radiomics combined with PSA in predicting the GS of PCa were 75.6%, 74.7%, and 88.9%, respectively. Furthermore, AUCs for MRI PI-RADS classification and radiomics alone in predicting distant metastasis of PCa were 66.7% and 90.8%, respectively. Conclusion The combination of ultrasonic imaging omics and serum PSA significantly improves the efficiency of PCa diagnosis, GS prediction, and distant metastasis prediction. This method is an important tool for PCa screening and follow-up.

Background: Early childhood enteric infection with Shigella/EIEC, enteroaggregative E. coli (EAEC), Campylobacter, and Giardia has been associated with reduced child growth, yet a recent randomized trial of antimicrobial therapy to reduce these infections did not improve growth outcomes. To interrogate this discrepancy, we measured the enteric infections from this study. Methods: We leveraged the Early Life Interventions for Childhood Growth and Development in Tanzania (ELICIT) trial, a randomized double-blind placebo-controlled trial of antimicrobial therapy with azithromycin and nitazoxanide provided quarterly to infants from 6 to 15 months of age. We tested 5,479 stool samples at time points across the study for 34 enteropathogens using quantitative PCR. Results: There was substantial carriage of enteropathogens in stool. Azithromycin administration led to reductions in Campylobacter jejuni/coli, enteroaggregative E. coli, and Shigella/EIEC (absolute risk difference ranged from -0.06 to 0.24) 2 weeks after treatment however there was no effect after 3 months. There was no difference in Giardia after nitazoxanide administration (ARR 0.03 at the 12 month administration). When examining the effect of azithromycin versus placebo on the subset of children infected with specific pathogens at the time of treatment, a small increase in weight-for-age Z score was seen only in those infected with Campylobacter jejuni/coli (0.10 Z score, 95% CI -0.01–0.20; length-for-age Z score 0.07, 95% CI -0.06–0.20). Conclusion: The antimicrobial intervention of quarterly azithromycin plus or minus nitazoxanide led to only transient decreases in enteric infections with Shigella/EIEC, enteroaggregative E. coli (EAEC), Campylobacter, and Giardia. There was a trend towards improved growth in children infected with Campylobacter that received quarterly azithromycin.

Tumor necrosis factor-α (TNF-α) is closely related to the occurrence of human cancers. Cervical cancer seriously affects female health. Therefore, our study aimed to investigate the correlation between the polymorphism of TNF‑α‑308 gene and susceptibility to cervical cancer. Whole blood was collected from 142 patients with cervical cancer and 150 healthy controls. PCR‑RFLP was used to detect the polymorphism of TNF‑α‑308 and the correlation between polymorphism of TNF‑α‑308 and the susceptibility to cervical cancer was analyzed. The three genotypes of TNF‑α‑308 were GG, GA and AA, and the distributions of genotypes of TNF‑α‑308 were consistent with Hardy‑Weinberg equilibrium in both cervical cancer group and control group. There were no significant differences in genotype and allele frequency between cervical cancer group and healthy control group (P>0.05). A/A genotype increased the risk of cervical cancer by 1.46 times with 95% confidence interval of 0.32-6.67. Different genotypes were not associated with tumor type (P>0.05). Different genotypes are correlated with cervical cancer TNM stages, tumor differentiation and lymph node metastasis. Proportion of GA+AA genotype in TNM stage III+IV group, low differentiation group and lymph node metastasis group were 28.1, 29.0 and 29.8%, respectively, which were significantly higher than those in stage I+II group, moderate/high differentiation group and non‑lymph node metastasis group (P<0.05). The results suggested that TNF‑α‑308 gene polymorphism is associated with the degree of malignancy of cervical cancer. Female patients with A allele have higher malignant degree of cervical cancer.