Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

This article systematically reviews and verifies the historical evolution of Stemonae Radix from the aspects of name， origin， harvesting and processing， quality and others by consulting ancient and modern literature， in order to provide reference for the development and utilization of famous classical formulas containing this medicinal herb. Stemonae Radix has a long history of application， and it derives its name from its distinctive growth pattern， featuring clusters of ten to several dozen underground tuberous roots. This morphology resembles that of certain plants in the genus Asparagus， leading to historical instances where tuberous roots from genus Asparagus were mistakenly used as Stemonae Radix. After the research， it can be concluded that Stemonae Radix was first recorded in Mingyi Bielu， and throughout history， Baidu has been recognized as its official name， though it also bears alternative names such as Baibing， Pofucao and Ye Tianmendong. The mainstream sources used throughout history have been the dried tuberous roots of Stemona sessilifolia， S. japonica or S. tuberosa from the family Stemonaceae. This aligns with the 2025 edition of Pharmacopoeia of the People's Republic of China（hereinafter referred to as Chinese Pharmacopoeia）. Additionally， Asparagus filicinus and A. officinalis from the genus Asparagus are common sources of confusion with Stemonae Radix. The three primitive plants are mainly distributed in the Yangtze River basin and southern China， exhibiting a wide distribution. Historically， wild harvesting was predominant， but cultivation is now established. In ancient times， the harvesting time was mostly in the second， third， and eighth lunar months， when roots were harvested and dried. Nowadays， it is more common to pick and excavate in the spring and autumn seasons. After excavation， the roots are washed， fibrous roots removed， briefly blanched in boiling water or steamed until no white core remains， and then sun-dried or oven-dried. In ancient times， the processing of Stemonae Radix primarily involved roasting（stir-frying）， wine roasting， or raw materials. Modern mainstream processing specifications include two types of raw and honey-roasted products. In terms of quality evaluation of the medicinal materials， ancient criteria of "preferring plump and moist roots" align with modern requirement favoring "thick， robust stems with firm texture". Evaluating quality with authenticity， since the Song dynasty， it has been highly praised to produce in Chuzhou and Hengyang as the best. It was an ancient method of fixing the production area to stabilize the medicinal origin， reflecting the ancient recognition of the therapeutic efficacy of plants belonging to the genus Stemona. The main functions of Stemonae Radix remain consistent throughout history， including relieving coughs， eliminating phlegm and parasites. Based on the research results， it is recommended that when developing famous classical formulas containing the medicinal material Stemonae Radix， the botanical source specified in the 2025 edition of Chinese Pharmacopoeia should be selected. The specific species can be determined according to the distribution of resources and the main production areas， and the origin and corresponding botanical source should be fixed. Processing methods should be chosen based on the prescription requirements. It is recommended to use raw products without specified requirements.

This article systematically reviews and verifies the historical evolution of Stemonae Radix from the aspects of name， origin， harvesting and processing， quality and others by consulting ancient and modern literature， in order to provide reference for the development and utilization of famous classical formulas containing this medicinal herb. Stemonae Radix has a long history of application， and it derives its name from its distinctive growth pattern， featuring clusters of ten to several dozen underground tuberous roots. This morphology resembles that of certain plants in the genus Asparagus， leading to historical instances where tuberous roots from genus Asparagus were mistakenly used as Stemonae Radix. After the research， it can be concluded that Stemonae Radix was first recorded in Mingyi Bielu， and throughout history， Baidu has been recognized as its official name， though it also bears alternative names such as Baibing， Pofucao and Ye Tianmendong. The mainstream sources used throughout history have been the dried tuberous roots of Stemona sessilifolia， S. japonica or S. tuberosa from the family Stemonaceae. This aligns with the 2025 edition of Pharmacopoeia of the People's Republic of China（hereinafter referred to as Chinese Pharmacopoeia）. Additionally， Asparagus filicinus and A. officinalis from the genus Asparagus are common sources of confusion with Stemonae Radix. The three primitive plants are mainly distributed in the Yangtze River basin and southern China， exhibiting a wide distribution. Historically， wild harvesting was predominant， but cultivation is now established. In ancient times， the harvesting time was mostly in the second， third， and eighth lunar months， when roots were harvested and dried. Nowadays， it is more common to pick and excavate in the spring and autumn seasons. After excavation， the roots are washed， fibrous roots removed， briefly blanched in boiling water or steamed until no white core remains， and then sun-dried or oven-dried. In ancient times， the processing of Stemonae Radix primarily involved roasting（stir-frying）， wine roasting， or raw materials. Modern mainstream processing specifications include two types of raw and honey-roasted products. In terms of quality evaluation of the medicinal materials， ancient criteria of "preferring plump and moist roots" align with modern requirement favoring "thick， robust stems with firm texture". Evaluating quality with authenticity， since the Song dynasty， it has been highly praised to produce in Chuzhou and Hengyang as the best. It was an ancient method of fixing the production area to stabilize the medicinal origin， reflecting the ancient recognition of the therapeutic efficacy of plants belonging to the genus Stemona. The main functions of Stemonae Radix remain consistent throughout history， including relieving coughs， eliminating phlegm and parasites. Based on the research results， it is recommended that when developing famous classical formulas containing the medicinal material Stemonae Radix， the botanical source specified in the 2025 edition of Chinese Pharmacopoeia should be selected. The specific species can be determined according to the distribution of resources and the main production areas， and the origin and corresponding botanical source should be fixed. Processing methods should be chosen based on the prescription requirements. It is recommended to use raw products without specified requirements.

Objective To analyze the hotspots and trends in the research field of inflammation in polycystic ovary syndrome(PCOS).Methods This study retrieved data from the Web of Science Core Collection database,with the retrieval period spanning from January 2000 to December 2023.The litera-ture types included were papers and review papers in English.The search was conducted using"Poly-cystic Ovarian Syndrome"and its synonyms,along with"inflammation"as subject terms.Visualization analysis was performed using software such as CiteSpace,VOSviewer,and SCImago Graphica.Results A total of 1,803 articles were included in this study.The number of publications in this field had rapidly increased after 2018.China had the highest number of publications,and Tehran University of Medical Sciences was the institution with the most publications.Key scholars included Asemi Z,Gonzalez AM,Escobar-Morreale HF,etc.,and a core group of authors had been formed.The main research hotspots centered around insulin resistance,obesity,oxidative stress,etc.,and five clusters were formed.Highly cited and burst-cited literature were mainly review papers.Conclusion The re-search field of inflammation in PCOS is currently in a stage of rapid development,with research content covering PCOS inflammation markers,the impact of inflammation on PCOS pathophysiology,inflamma-tion-based PCOS treatment and prognosis,etc.The debate on whether the chronic low-grade inflammatory state in PC OS patients is related to obesity or not remains a focal point of contention.

Objective:To investigate the risk factors for detecting clinically significant prostate cancer (CSPCa) in patients with Prostate Imaging Reporting and Data System (PI-RADS) score≤3 on multi-parameter magnetic resonance imaging (mpMRI).Methods:Retrospective analysis was performed on the case data of 335 patients with suspected prostate cancer and PI-RADS score ≤3 who were admitted to Beijing Friendship Hospital, Capital Medical University from January 2013 to October 2022. All patients underwent 24-needle prostate biopsy. Clinical data such as age, body mass index, past medical history, serological laboratory indicators, and mpMRI imaging data were collected. The patients were grouped according to whether the puncture pathology was CSPCa or not, and the differences in clinical data between the two groups were analyzed by t-test, rank sum test and Chi-test. Multivariate Logistic regression analysis was further used to determine independent risk factors for MRI invisible prostate cancer, and receiver operating characteristics (ROC) curves were drawn. At the same time, further subgroup analysis was conducted based on whether prostate-specific antigen (PSA) was positive before puncture and PI-RADS score, respectively, and the same statistical method was used to further determine the influence of different serological indicators and PI-RADS score on the analysis results of risk factors. Results:Among all patients, 81 were CSPCa patients and 254 were non-CSPCa patients. Multivariate Logistic regression analysis showed that prostate-specific antigen density (PSAD) and PI-RADS score of 3 were independent risk factors for MRI invisible prostate cancer. At the same time, compared with suspected lesions located only in the transitional zone, the incidence of CSPCa in patients with suspected lesions located in the peripheral zone would increase, and the incidence of CSPCa would further increase when suspected lesions were found in both the transitional zone and the peripheral zone. In PSA-negative patients, only suspected lesion location was an independent risk factor for MRI invisible prostate cancer, while in PSA-positive patients, prostate volume, PSAD, and PI-RADS scores were independent risk factors. In subgroup analysis with different PI-RADS scores, suspicious lesions in both the transitional zone and peripheral zone indicate a higher likelihood of CSPCa. For patients with PI-RADS scores of 1 to 2, suspicious lesions in the peripheral zone alone may also indicated CSPCa, while for patients with PI-RADS scores of 3, the lower free prostate-specific antigen/total prostate-specific anti-principle was more accurate in predicting CSPCa.Conclusions:For patients who are clinically suspected of prostate cancer but whose PI-RADS score is less than or equal to 3 points indicated by mpMRI, it is necessary to further focus on the results of different serological indicators according to whether their PSA is positive and PI-RADS score respectively to judge whether patients should receive systemic prostate puncture, instead of using PSA level as a single indication for puncture. At the same time, clinicians should also pay full attention to the location of suspected lesions, when they are located in the peripheral zone, or there are suspected lesions in both the peripheral zone and the transitional zone, the possibility of CSPCa should be fully considered.

This article systematically reviews and verifies the medicinal materials of Dioscoreae Hypoglaucae Rhizoma（DHR）， Dioscoreae Spongiosae Rhizoma（DSR）， Smilacis Chinae Rhizoma（SCR） and Smilacis Glabrae Rhizoma（SGR） from the aspects of name， origin， producing area， quality， harvesting， processing and efficacy by consulting historical literature， in order to provide reference for the development and utilization of famous classical formulas containing the four medicinal materials. DHR， DSR， SCR and SGR have a long history of application as medicinal materials. However， due to their similar growth environment and medicinal properties， as well as their functions of promoting dampness， dispelling wind and removing numbness， there have been instances of homonymous foreign objects and homonymous synonyms throughout history， resulting in confusion of the origin. Therefore， it is necessary to conduct comparative analysis and systematic research for clarifying the historical development and changes of the four， in order to provide a basis for safe and effective medication. According to research， Bixie was first recorded in Shennong Bencaojing and has been historically known as Baizhi， Chijie， Zhumu， and other aliases. From ancient times to the mid-20th century， there has always been a situation where the rhizomes of Dioscorea plants and Smilax plants， and even the rhizomes of Heterosmilax plants， were mixed together to be used as medicinal herbs for Bixie. However， since the Tang dynasty， it has been clearly advocated that the rhizomes of Dioscorea plants have excellent quality and have been the mainstream throughout history. The 2020 edition of Chinese Pharmacopoeia categorized it into two types of medicinal herbs（DHR and DSR）. Among them， the origin of DHR is the dry rhizomes of Dioscorea hypoglauca， and the origins of DSR are the dry rhizomes of D. spongiosa and D. futschauensis. In ancient times， due to different types， the corresponding production areas of DHR and DSR were also different. Nowadays， They are mainly produced in the southern region of the Yangtze River. Since the Tang dynasty， the quality of Bixie has been characterized by its white color and soft nature. In modern times， it has been summarized that those with white color， large and thin pieces， powdery texture， tough and elastic texture， and neat and unbreakable are the best. The harvesting times of DHR and DSR are in spring or autumn， with the best quality harvested in autumn. The mainstream processing methods of them are slicing and then using the raw products or wine-processed products. SCR was first recorded in Mingyi Bielu and has been known as Jinganggen， Tielingjiao， Tieshuazi， and other aliases in history. The mainstream source is the dry rhizomes of Smilax china in the past dynasties， with the best quality being those that are tough and rich in powder. The harvesting time is from the late autumn to the following spring， and the main processing method throughout history has been slicing for raw use. SGR was first recorded under the item of Yuyuliang in Variorum of Shennong's Classic of Materia Medica. It was listed as an independent medicinal material from Bencao Gangmu. In history， there were such aliases as Cao Yuyuliang， Lengfantuan， Xianyiliang， Tubixie， etc. The main source of the past dynasties was dry rhizomes of S. glabra. In history， there have also been instances of multiple plants belonging to the same genus， and even cases of mixing the rhizomes of plants in the genus Heterosmilax. It is mainly produced in Guangdong， Hunan， Hubei， Zhejiang， Sichuan， Anhui and other regions， its quality has been summarized as large in size， powdery in texture， with few veins， and light brown in cross-section since modern times. The harvesting time is in spring or autumn， and the main processing method throughout history has been slicing for raw use. DHR， DSR， SCR and SGR all have the effects of promoting dampness， dispelling wind， relieving rheumatism and detoxifying. However， their detoxification abilities are ranked as follows：SGR>SCR>Bixie（DHR and DSR）. Especially for the treatment of limb spasms， arthralgia and myalgia， scrofula， and scabies caused by syphilis and mercury poisoning， SGR has a unique effect. Based on the research results， DHR is recommended to develop the famous classical formulas containing Bixie as the first choice for medicinal herbs. It should be harvested in autumn， sliced thinly while fresh， and processed according to the requirements of the famous classical formulas， without any requirements for raw use. Selecting the rhizomes of S. china， harvested in late autumn， and thinly sliced while fresh. If there are no special processing requirements in the formulas， use it raw. Selecting the rhizomes of S. glabra， it is harvested in autumn and thinly sliced while fresh. If there are no special processing requirements in the formulas， raw products can be used.

Objective:To explore the independent risk factors for chemoresistance during gemcitabine plus cisplatin (GC) adjuvant chemotherapy in patients with locally advanced bladder cancer after radical cystectomy and to construct a related predictive model.Methods:The clinical data of 228 patients with locally advanced bladder cancer who received GC chemotherapy after radical cystectomy at Beijing Friendship Hospital, Capital Medical University, from January 2013 to June 2024 were retrospectively analyzed. Among them, 184 were males, and 44 were females, with an average age of (68.8±10.6)years and an average body mass index (BMI) of (24.2±3.6)kg/m 2. According to tumor progression during chemotherapy, patients were divided into a chemotherapy-resistant(CR) group ( n=59) and a non-chemotherapy-resistant(NCR) group ( n=169). Independent sample t-test, chi-square test, and non-parametric test were used to compare general clinical characteristics and relevant examination results during chemotherapy between the two groups. Multivariate linear regression analysis was used to identify independent risk factors for GC chemoresistance. Propensity score matching (PSM) was used to match the TNM stage data between the two groups, and Kaplan-Meier and log-rank tests were used to compare overall survival(OS)after matching. Results:The median number of chemotherapy cycles was 3 in the CR group and 4 in the NCR group. Compared with the NCR group, CR patients were younger [(66.3±9.4) years vs.(69.7±10.9)years], had a higher proportion of kidney transplantation history[6.8%(4/59) vs. 0.6%(1/169)], hypertension [50.8%(30/59) vs. 36.1%(61/169)], coronary heart disease[23.7%(14/59) vs.9.5% (16/169)], and hydronephrosis [13.6%(8/59) vs. 4.1%(7/169)](all P<0.05). CR patients had a higher proportion of T 4 stage [20.3% (12/59) vs. 5.9% (10/169)], N 2 stage [42.4% (25/59) vs. 8.3% (14/169)], multifocal tumors at initial diagnosis [59.3% (35/59) vs. 26.6% (45/169)], and larger maximum tumor diameter [2.5 (1.5, 3.4) cm vs. 1.6 (1.2, 2.5) cm] (all P < 0.05). The CR group showed higher proportions of long-term urinary tract infection (UTI) [90.1% (53/59) vs. 7.7% (15/169)], higher systemic immune-inflammation index (SII) [991.6 (451.0, 1577.9) vs. 462.8 (309.0, 766.7)], absolute neutrophil count [6.5(4.1, 7.8)× 10 9/L vs. 3.9 (2.9, 5.1)× 10 9/L], and platelet count [(220.0 ± 96.2)× 10 9/L vs. (191.0 ± 64.8)× 10 9/L], but lower albumin levels [(34.3 ± 4.2) g/L vs. (39.9 ± 3.8) g/L] and albumin-to-globulin ratio (A/G) [(1.2 ± 0.3) vs. (1.3 ± 0.2)] (all P < 0.05). Multivariate linear regression analysis identified only T stage and long-term UTI as independent risk factors for GC chemoresistance( P<0.05).The probability of GC chemoresistance in bladder cancer patients was calculated as: P(Chemoresistance)=[0.155×T stage+ 0.624×(long-term UTI)]×100%(long-term UTI = 1 if present during chemotherapy, otherwise=0). After PSM, survival analysis showed that the median OS was significantly higher in the NCR group (55 months) than that in the CR group (30 months) ( P=0.020). Conclusions:This study demonstrates that advanced T stage and persistent UTI are independent risk factors for GC chemotherapy resistance in locally advanced bladder cancer patients. Based on these findings, a predictive model for chemotherapy resistance probability was constructed using multivariate linear regression analysis.

Objective:To assess the physical activity levels(PA)and patterns among older adults in rural areas, as well as to evaluate the association between PA levels and the conditions of sarcopenia and frailty.Methods:A cross-sectional survey was conducted involving 690 rural individuals aged 60 and above.Data on socio-demographic characteristics were collected, while Appendicular Skeletal Muscle Mass Index(ASMI)and grip strength were measured.The Physical Activity Scale for the Elderly(PASE)was employed to evaluate PA levels.Based on their PASE scores, participants were categorized into three groups: low PA level, medium PA level, and high PA level.Sarcopenia was defined according to the 2019 criteria established by the Asian Working Group for Sarcopenia(AWGS), and frailty status was assessed using the Frail Scale.Results:Among the study sample, 38.0% exhibited a low level of physical activity, 46.2% had a medium level, and 15.8% engaged in high levels of activity.As age increased, the level of physical activity among older adults significantly declined.Most of the physical activity reported by participants was attributed to household chores and farming-related activities.Participation in structured exercise among older adults was notably low, with only 1.3% engaging in muscle-strengthening exercises on a weekly basis.The majority(53.9%)reported walking as their preferred form of weekly exercise.After adjusting for confounding factors, the prevalence of sarcopenia was found to be 0.40(95% CI: 0.26-0.62)times lower in the medium physical activity group, and 0.56(95% CI: 0.31-1.01)times lower in the high physical activity group, compared to those with a low physical activity level.Similarly, regarding frailty as a negative outcome, the prevalence was 0.66(95% CI: 0.51-0.84)times lower in the medium physical activity group and 0.46(95% CI: 0.30-0.73)times lower in the high physical activity group, relative to the low physical activity group.When using PASE scores as a continuous variable, the results remained consistent. Conclusions:The physical activity levels of rural older adults are inadequate, and participation in multicomponent exercise programs is notably low.A lower level of physical activity is significantly associated with a higher prevalence of sarcopenia and frailty.Our findings indicate that it is essential to implement physical activity education and interventions to enhance exercise health literacy and to prevent sarcopenia and frailty among rural older adults.