ObjectiveTo analyze the adverse reactions associated with the clinical use of Banxia （Rhizoma Pinelliae）- Wutou （Aconitum） in the same formula， with the aim of providing a reference for the safety of their clinical application. MethodsLiterature on the clinical application of antagonistic herbs "Banxia-Wutou" used in the same formula， published from January 1st， 2014， to June 30th， 2023， was retrieved from databases including CNKI， VIP， Wanfang， SinoMed， PubMed， Cochrane Library， and Embase. A database was established， and information related to adverse reactions was extracted， including descriptions， classifications， specific manifestations， management and outcomes， patients' primary diseases （western medicine diseases and traditional Chinese medicine diagnoses and syndromes）， and medication information （dosage， ratio， administration routes， and dosage forms）. ResultsA total of 79 researches simultaneously used antagonistic herbs Banxia-Wutou in the same formula and reported associated advers reactions. Gastrointestinal adverse reactions were the most common， with 8 studies reporting management of adverse reactions and 3 studies reporting improvement with no intervention. Among the 11 researches， the adverse reaction relieved to extant， while other 69 researches didn't report the managment of adverse reaction and its prognosis. For the primary disease in western medicine system， chronic bronchitis and chronic obstructive pulmonary disease （COPD） were most common， while gastric pain was the most common symptom in traditional Chinese medicine with spleen and kidney deficiency and spleen stomach cold deficiency being the most frequent syndromes. The most common Banxia dosage was 10 g， while for the Wutou， Fuzi （Radix Aconiti Lateralis Praeparata） was predominant with the highest dose at 15 g. The most frequent herbal combination was Banxia-fuzi， with a 1∶1 ratio. The main administration route was oral， and the primary dosage form was decoction. ConclusionGastrointestinal adverse reactions are the most common in the clinical use of Banxia-Wutou antagonistic herb combinations. Research on the safety of "Banxia-Wutou" combinations should focus on respiratory system diseases and spleen-stomach related conditions.

Objective: This study aimed to systematically evaluate potential causal relationships between nine cathepsins and female infertility using Mendelian randomization (MR) methods. Methods: A bidirectional MR analysis was conducted utilizing single nucleotide polymorphisms as instrumental variables to investigate the potential causal effects between nine cathepsins and female infertility. Genetic data on female infertility were sourced from the FinnGen study, and cathepsin-related data were obtained from genome-wide association studies datasets of European ancestry. Results: Elevated levels of cathepsin E were significantly and inversely associated with the risk of female infertility, suggesting a potential protective role. This finding was further supported by multivariable MR analysis. However, no significant associations were observed between the other eight cathepsins and female infertility. Conclusion This study represents the first systematic MR analysis to identify a potential protective effect of cathepsin E on female infertility.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Background/Aims: Anti-reflux mucosal ablation (ARMA) is a promising endoscopic intervention for proton pump inhibitor (PPI)-dependent gastroesophageal reflux disease (GERD). However, the effect of ARMA on esophageal motility remains unclear. Methods: Twenty patients with PPI-dependent GERD receiving ARMA were prospectively enrolled. Comprehensive self-report symptom questionnaires, endoscopy, 24-hour impedance-pH monitoring, and high-resolution impedance manometry were performed and analyzed before and 3 months after ARMA. Results: All ARMA procedures were performed successfully. Symptom scores, including GerdQ (11.16 ± 2.67 to 9.11 ± 2.64, P = 0.026) and reflux symptom index (11.63 ± 5.62 to 6.11 ± 3.86, P = 0.001), improved significantly, while 13 patients (65%) reported discontinuation of PPI. Total acid exposure time (5.84 ± 4.63% to 2.83 ± 3.41%, P = 0.024) and number of reflux episodes (73.05 ± 19.34 to 37.55 ± 22.71, P < 0.001) decreased significantly after ARMA. Improved esophagogastric junction (EGJ) barrier function, including increased lower esophageal sphincter resting pressure (13.89 ± 10.78 mmHg to 21.68 ± 11.5 mmHg, P = 0.034), 4-second integrated relaxation pressure (5.75 ± 6.42 mmHg to 9.99 ± 5.89 mmHg, P = 0.020), and EGJ-contractile integral(16.42 ± 16.93 mmHg · cm to 31.95 ± 21.25 mmHg · cm, P = 0.016), were observed. Esophageal body contractility also increased significantly (distal contractile integral, 966.85 ± 845.84 mmHg · s · cm to 1198.8 ± 811.74 mmHg · s · cm, P = 0.023). Patients with symptom improvement had better pre-AMRA esophageal body contractility. Conclusions ARMA effectively improves symptoms and reflux burden, EGJ barrier function, and esophageal body contractility in patients with PPIdependent GERD during short-term evaluation. Longer follow-up to clarify the sustainability of ARMA is needed.

Objective: This study aimed to systematically evaluate potential causal relationships between nine cathepsins and female infertility using Mendelian randomization (MR) methods. Methods: A bidirectional MR analysis was conducted utilizing single nucleotide polymorphisms as instrumental variables to investigate the potential causal effects between nine cathepsins and female infertility. Genetic data on female infertility were sourced from the FinnGen study, and cathepsin-related data were obtained from genome-wide association studies datasets of European ancestry. Results: Elevated levels of cathepsin E were significantly and inversely associated with the risk of female infertility, suggesting a potential protective role. This finding was further supported by multivariable MR analysis. However, no significant associations were observed between the other eight cathepsins and female infertility. Conclusion This study represents the first systematic MR analysis to identify a potential protective effect of cathepsin E on female infertility.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Objective: This study aimed to systematically evaluate potential causal relationships between nine cathepsins and female infertility using Mendelian randomization (MR) methods. Methods: A bidirectional MR analysis was conducted utilizing single nucleotide polymorphisms as instrumental variables to investigate the potential causal effects between nine cathepsins and female infertility. Genetic data on female infertility were sourced from the FinnGen study, and cathepsin-related data were obtained from genome-wide association studies datasets of European ancestry. Results: Elevated levels of cathepsin E were significantly and inversely associated with the risk of female infertility, suggesting a potential protective role. This finding was further supported by multivariable MR analysis. However, no significant associations were observed between the other eight cathepsins and female infertility. Conclusion This study represents the first systematic MR analysis to identify a potential protective effect of cathepsin E on female infertility.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

ObjectiveTo explore the ethical dilemmas of patients in a cancer specialty hospital in the context of the smart hospital and to propose relevant countermeasures. MethodsUsing the purposive sampling method， medical staff from a tertiary cancer specialty hospital in a certain city were selected as research subjects from December 2023 to January 2024. Qualitative interviews were conducted on the ethical dilemmas of the specialized cancer patients in the context of the smart hospital， and Nvivo 12.0 software was used for data transcription and analysis. ResultsThree themes were extracted. First， the ethical dilemmas faced by specialized cancer patients in the context of smart hospitals， including the ethical dilemma between privacy protection and information disclosure， the right to life and choice， fairness and priority， and scientific research and clinical practice. Second， smart hospitals relied on advanced information technology to improve the level of medical teaching and research， but this had led to various ethical dilemmas mentioned above. Medical staff should correctly view and scientifically respond to these ethical dilemmas. Third， the response strategies for ethical dilemmas in cancer specialty hospitals in the context of smart hospitals include improving relevant policies and regulations， optimizing medical resource allocation， strengthening ethics education of medical staff， enhancing doctor-patient communication， and strengthening feedback and regulatory mechanisms. ConclusionMedical institutions should strengthen ethical supervision while promoting innovation and application of medical information technology， to ensure compliance and sustainability in the development of smart hospitals.

Charcoal-processed traditional Chinese herbal medicine has various therapeutic effects， including astringing， hemostasis， anti-diarrhea， clearing heat， tonifying， and warming the interior. This paper summarizes the clinical application features， compatible experiences， dosages， and precautions for over 20 types of charcoal-processed herbal medicine in the treatment of gynecological bleeding disorders caused by dysfunctions such as dysfunctional uterine bleeding， endometriosis， uterine incision pseudocavity， and vaginal bleeding resulting from threatened miscarriage. The charcoal-processed herbal medicine include Huangqin （Scutellaria Baicalensis） Charcoal， Dahuang （Rheum Palmatum） Charcoal， Cebai （Platycladus Orientalis） Charcoal， Diyu （Sanguisorba Officinalis） Charcoal， Daji （Cirsium Setosum） Charcoal， Xiaoji （Cirsium Japonicum） Charcoal， Shengdi （Rehmannia Glutinosa） Charcoal， Aiye （Artemisia Argyi） Charcoal， Paojiang （Zingiber Officinale） Charcoal， Xuduan （Dipsacus Asper） Charcoal， Duzhong （Eucommia Ulmoides） Charcoal， Qiancao （Rubia Cordifolia） Charcoal， Puhuang （Typha Angustifolia） Charcoal， Shanzha （Crataegus Pinnatifida） Charcoal， Jingjie （Schizonepeta Tenuifolia） Charcoal， Xueyu （Carthamus Tinctorius） Charcoal， Zonglyu （Areca Catechu） Charcoal， Wumei （Prunus Mume） Charcoal， Shudahuang （Rheum Officinale） Charcoal， Lianfang （Nymphaea Alba） Charcoal， Mianmaguanzhong （Clematis Armandii） Charcoal， and Oujie （Nelumbo Nucifera） Charcoal.