The incidence of papillary thyroid microcarcinoma (PTMC) is steadily rising. Although conventional thyroid surgery techniques are well-established, they present challenges such as functional impairment and overtreatment. Cellular-level fluorescence-guided imaging technology (EndoSCell^®) enables precise intraoperative tumor localization and real-time identification of neurovascular structures via high-resolution imaging and targeted labeling. This technology significantly improves surgical precision, reduces the incidence of postoperative complications including recurrent laryngeal nerve injury and hypoparathyroidism, and strengthens standards for functional preservation. This article aimed to systematically explore recent advances in the application of EndoSCell^® for PTMC management, analyze its influence on the innovation of surgical approaches and the enhancement of functional preservation criteria, and discuss future directions, thereby providing a theoretical basis for clinical practice.

[摘 要] 目的：评估汉曲优（HLX02，Zercepac®）与帕妥珠单抗联合化疗在人表皮生长因子受体2（HER-2）阳性、非特殊型浸润性乳腺癌患者中的新辅助治疗效果，并与传统曲妥珠单抗原研药赫赛汀联合帕妥珠单抗方案的疗效和安全性进行对比。方法：本研究为一项多中心回顾性队列研究。纳入2020年5月至2024年9月于莆田学院附属医院及漳州正兴医院接受汉曲优或赫赛汀（均联合帕妥珠单抗及化疗）新辅助治疗的132例HER-2阳性乳腺癌患者。主要终点为病理完全缓解（pCR）率（依据Miller-Payne系统G5级定义）。次要终点包括客观缓解率（ORR，基于RECIST 1.1标准）、不良事件（采用CTCAE 5.0和PRO-CTCAE标准评估）发生率、生活质量（EORTC QLQ-C30量表）及治疗费用。采用SPSS 27.0软件进行统计分析，为控制混杂偏倚，应用倾向性评分匹配（PSM）以1∶1比例匹配组间基线特征。结果：经筛选后共117例患者纳入分析（汉曲优组65例，赫赛汀组52例）。经PSM匹配后，两组各42例患者，基线特征均衡。汉曲优组与赫赛汀组的pCR率无显著差异（66.67% vs 69.05%，P = 0.815）。两组的ORR（83.33% vs 85.71%，P = 0.763）、各级别不良事件发生率及生活质量评分均无统计学差异（均P > 0.05）。然而，汉曲优组患者自付费用显著低于赫赛汀组[（40 358.82 ± 15 042.69）元 vs （51 170.20 ± 15 664.63）元，P = 0.002]。结论：本真实世界研究表明，在新辅助治疗中，汉曲优联合帕妥珠单抗相较于赫赛汀联合帕妥珠单抗，在HER-2阳性IBC-NST患者中表现出相当的疗效和相似的安全性，且能显著减轻患者的经济负担，为国产生物类似药的临床应用提供了循证依据。

Objective To investigate the heterogeneity and key molecular features of epithelial cells in triple-negative breast cancer (TNBC), identify prognostic biomarkers, and develop a robust survival prediction model. Methods Using TNBC single-cell transcriptomic data, epithelial cells were extracted, normalized, and subclustered to characterize their molecular signatures and functional differences. High-dimensional weighted gene co-expression network analysis (hdWGCNA) was applied to establish co-expression modules in epithelial cells. Multiple machine learning algorithms were integrated to select key prognostic genes and develop a risk-score model, whose performance was evaluated using receiver operating characteristic (ROC) curves and Kaplan-Meier (K-M) survival analysis. In addition, the immune microenvironment features and potential drug-response differences between the high- and low-risk groups were systematically assessed. Finally, PCR was performed to validate the expression differences of the key genes between tumor and normal tissues. Results We characterized the composition and molecular features of TNBC epithelial subpopulations and identified a TNBC-associated epithelial subset. By integrating hdWGCNA with machine learning approaches, 10 key genes were selected to construct a prognostic model, which effectively stratified patients into distinct survival-risk groups and demonstrated favorable predictive performance in ROC and K-M analyses. Immune profiling revealed the differences in the infiltration levels of seven immune cell types and immune function-related features between the high- and low-risk groups. Drug-sensitivity analysis suggested potential differential responses to eight agents across the risk groups. PCR validation further confirmed the differential expression of the ten signature genes between tumor and normal tissues. Conclusion This study reveals epithelial heterogeneity in TNBC at single-cell resolution and establishes a 10-gene prognostic model, which may facilitate the stratification of TNBC risk and the evaluation of immune characteristics and potential therapeutic strategies.

Purpose: This study was conducted to evaluate the clinical efficacy of autologous parathyroid transplantation into the forearm brachioradialis muscle during thyroid surgery and analyze the timing of graft function recovery. Methods: A total of 52 patients undergoing thyroid surgery with autologous parathyroid transplantation were selected.Serum parathyroid hormone (PTH) levels were measured at various postoperative intervals, and instances of hypoparathyroidism were recorded. Results: Postoperative PTH levels on the transplant side were significantly higher than on the non-transplant side from week 1 to 1 year. Effective graft rates were 1.9% on day 1, 40.4% at week 1, 84.6% at 1 month, and stabilized at around 73% after 1 year. Transient hypoparathyroidism was observed in 17.3% of patients, with no permanent cases. Conclusion Autologous parathyroid transplantation into the forearm brachioradialis muscle effectively preserves parathyroid function, with grafts regaining optimal function within 2–3 months and the graft still having good secretory function 1 year after surgery.

Thyroid cancer is one of the most prevalent cancers in the world, accounting for the increased sensitivity of diagnostic assessments, the environment, and extensive imaging. While open thyroidectomy still forms the base surgical treatment of differentiated thyroid carcinoma (DTC), its visible scarring and postoperative morbidity have mandatorily propelled a longitudinal shift to minimally invasive techniques. Robotic thyroidectomy using the bilateral axillo-breast approach (BABA) is an emerging transformative technique that combines robotic precision and visualization with oncologic efficacy and superior cosmetic outcomes to enhance recovery. Molecular diagnostics such as next-generation sequencing (NGS) and microRNA classifiers have transformed preoperative planning. These tools aid in accurate risk stratification, enabling clinicians to determine the course of surgery and avoid overtreatment. Artificial intelligence (AI) enhances precision medicine by improving nodule classification, predicting surgical risks, providing intraoperative navigation guidance, and supporting postoperative histopathological evaluations. Despite these innovations, cost, accessibility, and ethical governance issues highlight persistent challenges. This review consolidates the current state of robotic-assisted surgery for thyroid cancer with molecular profiling and AI. It proposes future aims and strides toward precision surgery that is accessible worldwide.

Effective symptom management can alleviate the physical and psychological distress experienced by patients with cancer, improve quality of life, and contribute to treatment adherence and improve clinical outcomes. However, most existing guidelines are developed for healthcare professionals, and patients and the public have limited access to standardized and comprehensible guidance on symptom management. To address this gap and to facilitate effective communication and shared decision-making, this study proposes the development of a patient version of the cancer symptom management guideline. The development process will adhere to the methodological framework recommended by the Guidelines International Network and the World Health Organization. The GRADE approach will be employed to assess the certainty of evidence and to formulate recommendations. In addition, the process will be informed by the Appraisal of Guidelines for Research and Evaluation Ⅱ (AGREE Ⅱ) instrument and the Reporting Items for Practice Guidelines in Healthcare-Public or Patient Versions of Guidelines (RIGHT-PVG). This protocol outlines the establishment of the guideline working group, the identification and prioritization of key questions, evidence retrieval and appraisal, and the formulation of recommendations, with the aim of ensuring methodological rigor and transparency in the development of the patient guideline and providing methodological reference for similar guideline initiatives.

Objective To evaluate the effectiveness of thermal tomography in breast cancer (BC) screening. Methods We conducted a general population-based BC screening in three regions of Hubei Province (Xiantao, Hongan, and Yangxin Districts). Participants underwent a questionnaire-based interview for baseline data collection. They then received a physical examination, thermal tomography, and ultrasound from doctors and technicians. We compared the efficacies, including sensitivity, specificity, and false-positive rates, of ultrasound and thermal tomography in BC screening. Results A total of 59 712 eligible women were included in this screening program. The BI-RADS 1, 2, 3, 4, and 5 accordance rates between the two screening methods were 0.9549, 0.8047, 0.9037, 0.3352, and 0, respectively. The overall accordance rate was 0.933 1. The kappa consistency results showed that the Cicchetti-Allison and Fleiss-Cohen kappa values were 0.7970 and 0.8583, respectively. Although the two methods had equal sensitivities, specificity was higher in thermal tomography than in ultrasound. The false-positive rate was lower in thermal tomography than in ultrasound. The area under the receiver operating characteristic (ROC) curve of thermal tomography was significantly larger than that of ultrasound. Conclusion The general consistency between thermal tomography and ultrasound in BC screening was high. Thermal tomography outperformed ultrasound in terms of specificity and diagnostic efficiency. Therefore, thermal tomography has a high application value for general population-based BC screening.

OBJECTIVES: Increasing detection of low-risk papillary thyroid carcinoma (PTC) is associated with overdiagnosis and overtreatment. N6-methyladenosine (m⁶A)-mediated microRNA (miRNA) dysregulation plays a critical role in tumor metastasis and progression. However, the functional role of m⁶A-miRNAs in PTC remains unclear. This study aims to elucidate the regulatory mechanism of m⁶A-miR-139-5p expression in PTC, determine its association with PTC metastasis, and evaluate its potential as a diagnostic biomarker for PTC metastasis, thereby providing experimental evidence for precision diagnosis and therapy. METHODS: Expression profiles of m⁶A-miRNAs were compared between the The Cancer Genome Atlas (TCGA) and GSE130512 cohorts to identify metastasis-associated candidates. Clinical specimens from 13 metastasis and 18 non-metastasis PTC patients were analyzed to assess m⁶A-miR-139-5p expression and its correlation with metastasis. Functional experiments were conducted to investigate the effect of fat mass and obesity-associated protein (FTO) on pri-miR-139 methylation and processing, clarifying its regulatory role in miR-139-5p expression. In TPC-1 cells, MTT assays were performed to evaluate whether miR-139-5p overexpression could counteract FTO-mediated cell proliferation. Transwell invasion assays were used to determine the impact of miR-139-5p on PTC cell invasion, exploring whether it functions through the ZEB1/E-cadherin axis. RESULTS: By comparing TCGA and GSE130512 cohorts, it was found that circulating m⁶A-miR-139-5p could serve as a biological indicator for detecting PTC metastasis. Detection of 13 metastatic and 18 non-metastatic clinical specimens showed that FTO inhibited the processing of pri-miR-139 by reducing its methylation level, leading to the dysregulation of miR-139-5p in PTC (P<0.05). In TPC-1 cells, MTT assay showed that overexpression of miR-139-5p could partially reverse FTO overexpression-mediated cell proliferation (P<0.05). In addition, miR-139-5p inhibited the invasive ability of PTC cells by targeting the ZEB1/E-cadherin axis, while FTO overexpression could partially weaken this inhibitory effect. CONCLUSIONS Circulating miR-139-5p can be a potential marker for evaluating PTC metastasis. FTO affects the expression and function of miR-139-5p by regulating m⁶A modification of pri-miR-139, but its clinical value needs further verification.
Humans ; MicroRNAs/metabolism* ; Thyroid Cancer, Papillary/metabolism* ; Alpha-Ketoglutarate-Dependent Dioxygenase FTO/metabolism* ; Thyroid Neoplasms/metabolism* ; Cell Line, Tumor ; Neoplasm Metastasis ; Adenosine/genetics* ; Gene Expression Regulation, Neoplastic ; Female ; Male ; Cadherins/metabolism* ; Cell Proliferation ; Zinc Finger E-box-Binding Homeobox 1/genetics*

Thyroid nodules are a common endocrine disorder, and their early detection and accurate diagnosis are crucial for the prevention of thyroid cancer. However, the highly heterogeneous morphology and boundaries of thyroid nodules pose significant challenges to their precise identification and classification. Traditional diagnostic approaches rely heavily on physicians' experience, which increases the risk of misdiagnosis and missed diagnoses. With the rapid advancement of computer-aided diagnosis (CAD) technologies, applying deep learning algorithms to the analysis of thyroid nodule ultrasound images has shown great potential. This paper reviews the latest research progress on deep learning-based CAD methods for thyroid nodules, with a focus on their applications in image preprocessing, segmentation and classification. The advantages and limitations of current techniques are analyzed, and potential future directions are discussed. This review aims to highlight the potential of deep learning in thyroid nodule diagnosis and to provide a foundation for selecting feasible pathways for future clinical applications.
Humans ; Thyroid Nodule/diagnostic imaging* ; Deep Learning ; Ultrasonography/methods* ; Diagnosis, Computer-Assisted/methods* ; Algorithms ; Thyroid Neoplasms/diagnostic imaging* ; Image Processing, Computer-Assisted/methods*

With the rising incidence of breast cancer among women, neoadjuvant chemotherapy (NAC) is becoming increasingly crucial as a preoperative treatment modality, enabling tumor downstaging and volume reduction. However, its efficacy varies significantly among patients, underscoring the importance of predicting pathological complete response (pCR) following NAC. Early research relied on statistical methods to integrate clinical data for predicting treatment outcomes. With the advent of artificial intelligence (AI), traditional machine learning approaches were subsequently employed for efficacy prediction. Deep learning emerged to dominate this field, and demonstrated the capability to automatically extract imaging features and integrate multimodal data for pCR prediction. This review comprehensively examined the applications and limitations of these three methodologies in predicting breast cancer pCR. Future efforts must prioritize the development of superior predictive models to achieve precise predictions, integrate them into clinical workflows, enhance patient care, and ultimately improve therapeutic outcomes and quality of life.
Humans ; Breast Neoplasms/pathology* ; Neoadjuvant Therapy ; Artificial Intelligence ; Female ; Machine Learning ; Deep Learning ; Chemotherapy, Adjuvant ; Treatment Outcome