OBJECTIVE To analyze the differences in chemical components of Gardenia jasminoides before and after processing with ginger， and to evaluate the quality differences among different producing areas. METHODS Ultra-high performance liquid chromatography-tandem time-of-flight mass spectrometry was used to analyze the compositional differences of G. jasminoides before and after processing with ginger. The water content， total ash， and ethanol-soluble extract content of ginger- processed G. jasminoides were determined according to the 2020 edition of Chinese Pharmacopoeia. High performance liquid chromatography was adopted to determine the contents of genipin gentiobioside， geniposide， crocin Ⅰ and crocin Ⅱ in ginger- processed G. jasminoides. RESULTS A total of 49 chemical components were identified from raw G. jasminoides and ginger- processed G. jasminoides， including 14 flavonoids， 15 iridoids， 10 organic acids， 2 alkaloids and 8 other compounds. Among them， 42 components were detected in raw G. jasminoides， 28 in ginger-processed G. jasminoides， and 21 components were common to both. After processing with ginger， raw G. jasminoides lost 21 components （including iridoids， flavonoids， alkaloids， and others）， while 7 chemical components were added （including coumarins， organic acids， organic acid esters， and flavonoids）. For the 15 batches of ginger-processed G. jasminoides， the water content ranged from 5.64% to 7.11%， total ash from 2.92% to 4.87%， and ethanol-soluble extract from 40.61% to 58.02%. The average contents of genipin gentiobioside， geniposide， crocin Ⅰ and crocin Ⅱ were 0.108 7， 0.542 2， 0.565 0， and 0.012 5 mg/g， respectively. CONCLUSIONS After processing with ginger， G. jasminoides loses 21 components， while 7 new components are added. Differences are observed in the water content， total ash， ethanol-soluble extract， and the contents of genipin gentiobioside， geniposide， crocin Ⅰ， and crocin Ⅱ of ginger-processed G. jasminoides from different producing areas. Notably， samples from Fujian exhibit high contents of genipin gentiobioside and ethanol-soluble extract， while samples from Jiangxi have a high content of crocin Ⅰ.

Oral squamous cell carcinoma (OSCC) is a common head and neck malignancy. Approximately 50% to 60% of patients with OSCC are diagnosed at a locally advanced stage (clinical staging III-IVa). Even with comprehensive and sequential treatment primarily based on surgery, the 5-year overall survival rate remains below 50%, and patients often suffer from postoperative functional impairments such as difficulties with speaking and swallowing. Programmed death receptor-1 (PD-1) inhibitors are increasingly used in the neoadjuvant treatment of locally advanced OSCC and have shown encouraging efficacy. However, clinical practice still faces key challenges, including the definition of indications, optimization of combination regimens, and standards for efficacy evaluation. Based on the latest research advances worldwide and the clinical experience of the expert group, this expert consensus systematically evaluates the application of PD-1 inhibitors in the neoadjuvant treatment of locally advanced OSCC, covering combination strategies, treatment cycles and surgical timing, efficacy assessment, use of biomarkers, management of special populations and immune related adverse events, principles for immunotherapy rechallenge, and function preservation strategies. After multiple rounds of panel discussion and through anonymous voting using the Delphi method, the following consensus statements have been formulated: 1) Neoadjuvant therapy with PD-1 inhibitors can be used preoperatively in patients with locally advanced OSCC. The preferred regimen is a PD-1 inhibitor combined with platinum based chemotherapy, administered for 2-3 cycles. 2) During the efficacy evaluation of neoadjuvant therapy, radiographic assessment should follow the dual criteria of Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 and immune RECIST (iRECIST). After surgery, systematic pathological evaluation of both the primary lesion and regional lymph nodes is required. For combination chemotherapy regimens, PD-L1 expression and combined positive score need not be used as mandatory inclusion or exclusion criteria. 3) For special populations such as the elderly (≥ 70 years), individuals with stable HIV viral load, and carriers of chronic HBV/HCV, PD-1 inhibitors may be used cautiously under the guidance of a multidisciplinary team (MDT), with close monitoring for adverse events. 4) For patients with a poor response to neoadjuvant therapy, continuation of the original treatment regimen is not recommended; the subsequent treatment plan should be adjusted promptly after MDT assessment. Organ transplant recipients and patients with active autoimmune diseases are not recommended to receive neoadjuvant PD-1 inhibitor therapy due to the high risk of immune related activation. Rechallenge is generally not advised for patients who have experienced high risk immune related adverse events such as immune mediated myocarditis, neurotoxicity, or pneumonitis. 5) For patients with a good pathological response, individualized de escalation surgery and function preservation strategies can be explored. This consensus aims to promote the standardized, safe, and precise application of neoadjuvant PD-1 inhibitor strategies in the management of locally advanced OSCC patients.

Objective To determine the prognostic biomarkers and new therapeutic targets of the lung adenocarcinoma (LUAD), based on which to establish a prediction model for the survival of LUAD patients. Methods An integrative analysis was conducted on gene expression and clinicopathologic data of LUAD, which were obtained from the UCSC database. Subsequently, various methods, including screening of differentially expressed genes (DEGs), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Set Enrichment Analysis (GSEA), were employed to analyze the data. Cox regression and least absolute shrinkage and selection operator (LASSO) regression were used to establish an assessment model. Based on this model, we constructed a nomogram to predict the probable survival of LUAD patients at different time points (1-year, 2-year, 3-year, 5-year, and 10-year). Finally, we evaluated the predictive ability of our model using Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and time-dependent ROC curves. The validation group further verified the prognostic value of the model. Results The different-grade pathological subtypes' DEGs were mainly enriched in biological processes such as metabolism of xenobiotics by cytochrome P450, natural killer cell-mediated cytotoxicity, antigen processing and presentation, and regulation of enzyme activity, which were closely related to tumor development. Through Cox regression and LASSO regression, we constructed a reliable prediction model consisting of a five-gene panel (MELTF, MAGEA1, FGF19, DKK4, C14ORF105). The model demonstrated excellent specificity and sensitivity in ROC curves, with an area under the curve (AUC) of 0.675. The time-dependent ROC analysis revealed AUC values of 0.893, 0.713, and 0.632 for 1-year, 3-year, and 5-year survival, respectively. The advantage of the model was also verified in the validation group. Additionally, we developed a nomogram that accurately predicted survival, as demonstrated by calibration curves and C-index. Conclusion We have developed a prognostic prediction model for LUAD consisting of five genes. This novel approach offers clinical practitioners a personalized tool for making informed decisions regarding the prognosis of their patients.

Objective: This study aimed to elucidate the hand function recovery capacity of degenerative cervical myelopathy (DCM) patients with different severities of hand dexterity impairment. Methods: Hand functional outcome measures such as the 10-second grip and release (10s-G&R) test, modified Japanese Orthopaedic Association (mJOA) upper extremity score and Japanese Orthopaedic Association Cervical Myelopathy Evaluation Questionnaire (JOACMEQ) upper extremity function were collected before surgery and at the 1-year follow-up. A total of 102 DCM patients were categorized into mild, moderate and severe group based on the preoperative 10s-G&R test result. Hand functional parameters were compared across the 3 groups. Multivariate linear regression was conducted to explore predictive factors. Receiver operating characteristic curve analysis was performed to assess the predictive efficacy of the preoperative 10s-G&R test and establish the cutoff value for incomplete recovery of hand dexterity. Results: At the 1-year follow-up, significant improvements were observed in all hand functional parameters across all 3 groups. However, the incomplete recovery rates of the mild, moderate, severe groups were 26.67%, 46.88%, and 57.50%, respectively (p < 0.05). Multivariate regression revealed that preoperative 10s-G&R test result, age, Hoffmann sign, duration of symptom, and mJOA Upper score serve as significant predictors for postoperative 10s-G&R test outcomes. Patients with a preoperative 10s-G&R test < 15 cycles have a 1.9 times higher risk of incomplete recovery of hand function (p = 0.005). Conclusion Most patients, regardless of their preoperative hand function, exhibit potential for improvement in hand dexterity. However, worse initial hand dexterity correlates with poorer outcomes. Surgical treatment is recommended before the 10s-G&R test drops below 15 cycles.

Background: Active surveillance (AS) has emerged as a viable management strategy for low-risk papillary thyroid microcarcinoma (PTMC), following pioneering trials at Kuma Hospital and the Cancer Institute Hospital in Japan. Numerous prospective cohort studies have since validated AS as a management option for low-risk PTMC, leading to its inclusion in thyroid cancer guidelines across various countries. From 2016 to 2020, the Multicenter Prospective Cohort Study of Active Surveillance on Papillary Thyroid Microcarcinoma (MAeSTro) enrolled 1,177 patients, providing comprehensive data on PTMC progression, sonographic predictors of progression, quality of life, surgical outcomes, and cost-effectiveness when comparing AS to immediate surgery. The second phase of MAeSTro (MAeSTro-EXP) expands AS to low-risk papillary thyroid carcinoma (PTC) tumors larger than 1 cm, driven by the hypothesis that overall risk assessment outweighs absolute tumor size in surgical decision-making. Methods: This protocol aims to address whether limiting AS to tumors smaller than 1 cm may result in unnecessary surgeries for low-risk PTCs detected during their rapid initial growth phase. By expanding the AS criteria to include tumors up to 1.5 cm, while simultaneously refining and standardizing the criteria for risk assessment and disease progression, we aim to minimize overtreatment and maintain rigorous monitoring to improve patient outcomes. Conclusion This study will contribute to optimizing AS guidelines and enhance our understanding of the natural course and appropriate management of low-risk PTCs. Additionally, MAeSTro-EXP involves a multinational collaboration between South Korea and Australia. This cross-country study aims to identify cultural and racial differences in the management of low-risk PTC, thereby enriching the global understanding of AS practices and their applicability across diverse populations.

Background/Aims: Inaccurate prediction of lymph node metastasis (LNM) may lead to unnecessary surgery following endoscopic resection of T1 colorectal cancer (CRC). We aimed to validate the usefulness of artificial intelligence (AI) models for predicting LNM in patients with T1 CRC. Methods: We analyzed the clinical data, laboratory results, pathological reports, and endoscopic findings of patients who underwent radical surgery for T1 CRC. We developed AI models to predict LNM using four algorithms: regularized logistic regression classifier (RLRC), random forest classifier (RFC), CatBoost classifier (CBC), and the voting classifier (VC). Four histological factors and four endoscopic findings were included to develop AI models. Areas under the receiver operating characteristics curves (AUROCs) were measured to distinguish AI model performance in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines. Results: Among 1,386 patients with T1 CRC, 173 patients (12.5%) had LNM. The AUROC values of the RLRC, RFC, CBC, and VC models for LNM prediction were significantly higher (0.673, 0.640, 0.679, and 0.677, respectively) than the 0.525 suggested in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines (vs RLRC, p<0.001; vs RFC, p=0.001; vs CBC, p<0.001; vs VC, p<0.001). The AUROC value was similar between T1 colon versus T1 rectal cancers (0.718 vs 0.615, p=0.700). The AUROC value was also similar between the initial endoscopic resection and initial surgery groups (0.581 vs 0.746, p=0.845). Conclusions AI models trained on the basis of endoscopic findings and pathological features performed well in predicting LNM in patients with T1 CRC regardless of tumor location and initial treatment method.

AIM:To measure preoperative corneal curvature in elderly cataract patients using five different systems, including Keratograph 5M, Pentacam, KR.800 autorefractor, IOL Master, and KR-1W wavefront aberrometer, analyze its discrepancy and consistency, and provide a reference for accurate intraocular lens(IOL)power calculation in elderly patients before cataract surgery.METHODS:This prospective study included 53 elderly cataract in-patients(90 eyes)who were admitted to our ophthalmology department between October 2022 and November 2024. The corneal curvature values(K1, K2)of postoperative eyes were measured using Keratograph 5M, Pentacam, KR.800, IOL Master, and KR-1W, and the mean keratometry(Km)was calculated.RESULTS:Statistically significant differences were observed in K1, K2, and Km values between Keratograph 5M and Pentacam, as well as between Keratograph 5M and IOL Master(all P<0.05), whereas no significant differences were found in K1, K2 and Km between Keratograph 5M and KR.800 or KR-1W(all P>0.05). Pearson correlation analysis showed a certain correlation of K1, K2 and Km obtained from Keratograph 5M with those from KR.800, Pentacam, IOL Master, and KR-1W(r=0.913-0.987, all P<0.001). Bland-Altman scatter plots demonstrated good consistency between Keratograph 5M and KR.800 or KR-1W, while its consistency with Pentacam and IOL Master was relatively poor.CONCLUSION:As an ocular surface analyzer, Keratograph 5M offers advantages such as simplicity, rapid measurement, strong repeatability, and low patient cooperation requirements. In elderly patients, corneal curvature measurements obtained by Keratograph 5M demonstrated good consistency with those from KR.800 and KR-1W, making them interchangeable based on individual conditions and cooperation levels of patients. However, its consistency with Pentacam and IOL Master was relatively poor; therefore, clinical practical situation should be considered when selecting such measurement devices.

Objectives: . A substantial proportion of patients with head and neck cancer (HNC) require emergency room (ER) visits or unplanned hospitalizations during or after treatment with various modalities. We investigated HNC cases that necessitated ER visitation after cancer treatment, aiming to identify potential risk factors in the context of the Korean healthcare system. Methods: . This single-center cohort study examined patients with HNC who received cancer treatments at Samsung Medical Center in 2019 (n=566). Treatment modalities included surgery alone (n=184), surgery and adjuvant therapy (n=138), curative non-surgical treatment such as radiation or chemoradiation (n=209), and palliative treatments (n=35). We followed these cases for up to 3 years, focusing on those who visited the ER during or after cancer treatment, and analyzed the primary reasons and risk factors associated with these visits. Results: . The ER visitation rate was 8.0% (n=45) among patients with HNC, with a total of 70 ER visits (12.4%; mean, 1.56; range, 1–4). The rate of treatment-related ER visitation was 4.6%. Common reasons for ER visits included surgical site or wound complications (31.1% of patients visiting the ER, 22.9% of ER visits) and issues with oral intake or feeding (22.2% of patients, 31.4% of visits). Significant risk factors for ER visits included tumor subsite (with hypopharyngeal cancer associated with a 17.9% rate of treatment-related ER visits), tumor stage (T2–4, 8.6%–12.2%; N+ status, 6.7%), and treatment modality (surgery with adjuvant chemoradiation, 19.4%). Patient age and comorbidities did not represent significant factors. Conclusion . The most frequent reasons for ER visits among patients with HNC included complications with wounds and feeding. Additionally, tumor characteristics and treatment modality were independent risk factors for ER visits. Adequate planning and management to address these issues could potentially decrease the number of ER visits, lower costs, and improve patient care.

Background: Active surveillance (AS) has emerged as a viable management strategy for low-risk papillary thyroid microcarcinoma (PTMC), following pioneering trials at Kuma Hospital and the Cancer Institute Hospital in Japan. Numerous prospective cohort studies have since validated AS as a management option for low-risk PTMC, leading to its inclusion in thyroid cancer guidelines across various countries. From 2016 to 2020, the Multicenter Prospective Cohort Study of Active Surveillance on Papillary Thyroid Microcarcinoma (MAeSTro) enrolled 1,177 patients, providing comprehensive data on PTMC progression, sonographic predictors of progression, quality of life, surgical outcomes, and cost-effectiveness when comparing AS to immediate surgery. The second phase of MAeSTro (MAeSTro-EXP) expands AS to low-risk papillary thyroid carcinoma (PTC) tumors larger than 1 cm, driven by the hypothesis that overall risk assessment outweighs absolute tumor size in surgical decision-making. Methods: This protocol aims to address whether limiting AS to tumors smaller than 1 cm may result in unnecessary surgeries for low-risk PTCs detected during their rapid initial growth phase. By expanding the AS criteria to include tumors up to 1.5 cm, while simultaneously refining and standardizing the criteria for risk assessment and disease progression, we aim to minimize overtreatment and maintain rigorous monitoring to improve patient outcomes. Conclusion This study will contribute to optimizing AS guidelines and enhance our understanding of the natural course and appropriate management of low-risk PTCs. Additionally, MAeSTro-EXP involves a multinational collaboration between South Korea and Australia. This cross-country study aims to identify cultural and racial differences in the management of low-risk PTC, thereby enriching the global understanding of AS practices and their applicability across diverse populations.

Background/Aims: Inaccurate prediction of lymph node metastasis (LNM) may lead to unnecessary surgery following endoscopic resection of T1 colorectal cancer (CRC). We aimed to validate the usefulness of artificial intelligence (AI) models for predicting LNM in patients with T1 CRC. Methods: We analyzed the clinical data, laboratory results, pathological reports, and endoscopic findings of patients who underwent radical surgery for T1 CRC. We developed AI models to predict LNM using four algorithms: regularized logistic regression classifier (RLRC), random forest classifier (RFC), CatBoost classifier (CBC), and the voting classifier (VC). Four histological factors and four endoscopic findings were included to develop AI models. Areas under the receiver operating characteristics curves (AUROCs) were measured to distinguish AI model performance in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines. Results: Among 1,386 patients with T1 CRC, 173 patients (12.5%) had LNM. The AUROC values of the RLRC, RFC, CBC, and VC models for LNM prediction were significantly higher (0.673, 0.640, 0.679, and 0.677, respectively) than the 0.525 suggested in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines (vs RLRC, p<0.001; vs RFC, p=0.001; vs CBC, p<0.001; vs VC, p<0.001). The AUROC value was similar between T1 colon versus T1 rectal cancers (0.718 vs 0.615, p=0.700). The AUROC value was also similar between the initial endoscopic resection and initial surgery groups (0.581 vs 0.746, p=0.845). Conclusions AI models trained on the basis of endoscopic findings and pathological features performed well in predicting LNM in patients with T1 CRC regardless of tumor location and initial treatment method.