Xin Zhao

Background: Accurate preoperative characterization of breast lesions is important for individualized management. The conventional monoexponential (Mono) model has limited ability to capture the complex microstructure of lesions. Non‐Gaussian diffusion models, including continuous‐time random walk (CTRW) and fractional‐order calculus (FROC), may overcome this limitation, but their value in predicting biomarkers and molecular subtypes remains unclear. Purpose: To comprehensively evaluate the diagnostic utility of the Mono, CTRW, and FROC models and their derived parameters for preoperative breast lesion characterization. Study Type: Prospective. Population: 189 women (mean age, 47.4 ± 11.2 years) with 238 histopathologically confirmed breast lesions (138 benign, 100 malignant). Field Strength/Sequence: 3.0‐T MRI; single‐shot spin‐echo echo‐planar imaging for multi‐ b ‐value diffusion‐weighted imaging (10 b ‐values ranging from 0 to 3000 s/mm ² ). Assessment: Diffusion parameters were extracted from whole‐lesion volumes generated from slice‐wise segmentations by two independent, blinded breast radiologists. Multiparameter joint models were constructed using logistic regression. Statistical Tests: Model performance was evaluated using repeated 5‐fold cross‐validation and patient‐level cluster bootstrap for AUC comparisons. A two‐sided p < 0.05 was considered statistically significant, and Bonferroni‐adjusted thresholds were applied for multiple comparisons. Results: For benign–malignant differentiation, the CTRW and FROC models yielded higher cross‐validated AUCs than the Mono model (0.928, 0.918, and 0.865, respectively). For prognostic biomarkers, the FROC model achieved optimal predictive performance for HER2 status (AUC = 0.836). For molecular subtyping, the CTRW model significantly outperformed the Mono model in distinguishing HER2‐positive lesions (AUC = 0.848 vs. 0.674); however, all models showed limited performance for triple‐negative lesions, with all AUCs ≤ 0.502. Data Conclusion: Non‐Gaussian diffusion models, particularly the CTRW model, provide additional value beyond the Mono model for preoperative breast lesion characterization. Evidence Level: 2. Technical Efficacy: Stage 2.

Background: The key biomarkers, therapeutic targets, and pathological mechanisms of endometriosis are urgently needed to be elucidated. The role of CTSZ in EM needs to be clarified, and the potential regulatory mechanisms and corresponding therapeutic drugs of CTSZ need to be explored to demonstrate the feasibility of CTSZ as a biomarker and therapeutic target. Methods: Based on transcriptome sequencing of local clinical tissue samples and public data, the key pathogenic gene ( CTSZ ) was screened out using machine learning algorithms (LASSO and SVM-RFE), and the expression of CTSZ was evaluated at multiple levels. The effects of knocking down CTSZ on the proliferation and migration of endometriosis cell lines (12Z) were assessed. The effects of knocking down CTSZ on apoptosis, autophagy and AMPK/mTOR signaling pathways were predicted and investigated. Results: CTSZ was found to be abnormally overexpressed in sequencing data, endometriosis clinical tissue samples, and corresponding cell lines (12Z), suggesting it is a potential pathogenic gene. Knockdown of CTSZ significantly inhibited the proliferation and migration of 12Z. CTSZ may be related to key processes and proteins of apoptosis, autophagy and AMPK/mTOR signaling pathways. Knockdown of CTSZ significantly promoted apoptosis and autophagy by activating AMPK and subsequently inhibiting mTOR signaling. Conclusion: CTSZ is a potential pathogenic gene and therapeutic target. Its knockdown could activate AMPK and subsequently inhibit mTOR signaling, thereby inducing autophagy and synergistically promoting apoptosis, inhibiting proliferation and migration, and ultimately inhibiting endometriosis.

Cervical cancer, a human papillomavirus (HPV) -driven malignancy with inherent viral antigenicity, serves as a key model in immuno-oncology. Yet, the variable efficacy of immune checkpoint inhibitors highlights a critical gap: the lack of preclinical models that accurately mirror the patient-specific tumor microenvironment (TME). Patient-derived organoids (PDOs) offer a transformative solution, preserving autologous tumor and immune components for personalized therapeutic testing. This study provides the first bibliometric analysis of this evolving field, mapping its knowledge structure from model development to immuno-oncological application. By analyzing 130 publications (1992-2025) from Web of Science, PubMed, and Scopus using VOSviewer and CiteSpace, we delineate a clear, three-stage evolution: from foundational HPV virology and culture techniques, through pivotal organoid methodology establishment (e.g., Burk RD, 2017), to the current translational phase. This progression is marked by citation bursts in TME modeling (e.g., Lohmussaar K, 2021) and the emergence of keywords like “drug screening” and “immunotherapy”. Research is dominated by the U.S., China, and European nations, published within an interdisciplinary core of oncology, immunology, and virology journals. Our analysis highlights the role of organoids as a crucial bridge linking basic virology to clinical immuno-oncology. However, standardization hurdles and suboptimal establishment rates for certain subtypes impede clinical translation. To realize the full potential of PDOs, future work must prioritize standardized immune-competent co-culture systems, integrate AI for high-content data analysis, and promote equitable global collaborations. Our analysis suggests the role of organoids as a crucial bridge linking basic virology to clinical immuno-oncology, highlighting that current advancements in tumor microenvironment modeling are establishing the necessary foundation for future immunotherapeutic applications.

Background: Early-onset severe preeclampsia (EOSPE) is a serious pregnancy complication associated with adverse maternal and neonatal outcomes. This study aimed to identify potential diagnostic biomarkers for EOSPE and to investigate their clinical significance. Methods: MicroRNAs (miRNAs) expression datasets from the Gene Expression Omnibus (GEO) database, specifically from placental tissue ( GSE103542 ) and plasma ( GSE234611 ), were screened to identify miRNAs consistently dysregulated in early-onset preeclampsia (EOPE) and to discover robust biomarker candidates. Weighted gene co-expression network analysis (WGCNA) was employed to identify key modules associated with preeclampsia (PE). The differentially expressed miRNAs (DEmiRNAs) were intersected with miRNAs from WGCNA-identified modules to prioritize candidates. Functional enrichment analysis predicted target genes and involved pathways. Clinical samples (serum and placental tissues from EOSPE patients and normal pregnant women) and a lipopolysaccharide (LPS)-induced preeclampsia rat model were utilized to validate the expression of DEmiRNAs via reverse transcription quantitative polymerase chain reaction (RT-qPCR). The diagnostic value of these miRNAs was evaluated using receiver operating characteristic (ROC) curve analysis, and their correlations with clinical parameters were assessed. Results: Bioinformatics analysis identified miR-431-5p as a key molecule, with its expression was significantly upregulated in both serum and placental tissues of patients with EOSPE. Circulating miR-431-5p demonstrated promising diagnostic potential for EOSPE (AUC = 0.803). Its expression level positively correlated with systolic blood pressure (r = 0.395, P = 0.017) and diastolic blood pressure (r = 0.41, P = 0.013), uric acid (r = 0.389, P = 0.02), lactate dehydrogenase (r = 0.399, P = 0.018), and the umbilical artery S/D ratio (r = 0.457, P = 0.01). Conversely, it negatively correlated with gestational age at delivery (r = −0.562, P < 0.001) and neonatal birth weight (r = −0.503, P = 0.02). Multivariable regression analysis showed that after adjusting for confounding factors, miR-431-5p remained significantly positively associated with the occurrence of EOSPE. Animal experiments confirmed similar upregulation of miR-431-5p in the LPS-induced preeclampsia rat model. Conclusions: In this study, miR-431-5p was significantly upregulated in EOSPE and demonstrated preliminary diagnostic potential. Its expression level was potentially associated with disease severity and adverse perinatal outcomes. These findings suggest that miR-431-5p may serve as a promising candidate biomarker for EOSPE.

Germinal matrix hemorrhage (GMH), a major complication of prematurity, involves severe neuroinflammation leading to neurological deficits. While G protein-coupled receptor 17 (GPR17) is known to modulate neuroinflammation, its therapeutic potential in GMH remains unexplored. This study investigated the anti-inflammatory effects and mechanisms of GPR17 activation in a neonatal rat GMH model induced by collagenase injection. Pre-treatment with the GPR17 agonist MDL-29951 was found to upregulate GPR17, downregulate cleaved Caspase-3, IL-1β, and TNF-α, and reduce apoptosis and glial infiltration at 1 day post-GMH. The treatment also improved neurological function, inhibited IκBα degradation and p65 nuclear translocation, and preserved white matter (WM) integrity. In vitro, GPR17 functioned as a negative regulator of the NF-κB pathway in primary microglia. These results suggest that GPR17 activation alleviates neuroinflammation and improves neurological outcomes after GMH, at least in part through attenuation of the NF‑κB pathway.

Objectives: To evaluate the agreement and diagnostic performance of the Node Reporting and Data System 1.0 (Node-RADS) for preoperative lymph node staging in cervical cancer across readers with different experience levels. Methods: This retrospective study enrolled 439 consecutive cervical cancer patients who underwent preoperative MRI and lymph node dissection. Target nodes were pre-specified by a most experienced consultant radiologist to unify the assessment objects. Four readers (two senior with 9–11 years of experience, two junior with 3–5 years of experience) independently assigned Node-RADS scores, blinded to histopathology. Inter-reader agreement and between-group agreement were assessed using weighted and Cohen’s kappa. Diagnostic performance was evaluated against histopathology as reference standard. Results: Senior readers achieved near-perfect agreement for Node-RADS scores (k = 0.988), nodal status (k = 0.959) and all individual morphological parameters (k = 0.847–0.967). Junior readers showed moderate to substantial agreement (k = 0.554–0.754). Although junior readers requiring consensus more frequently (7.1% vs. 1.4%, p < 0.01), the between-group agreement for nodal status was substantial (k = 0.783). For nodal metastasis detection, senior readers demonstrated higher diagnostic performance (AUC 0.868; sensitivity 76.4%; specificity 97.3%) compared to junior readers (AUC 0.758; sensitivity 54.6%; specificity 97.0%), and both groups presented favorable diagnostic efficacy overall. Conclusions: Inter-reader agreement for nodal status was almost perfect among senior readers and substantial among junior readers. Diagnostic performance was slightly better in the senior group, suggesting an influence of reader experience.