Patients with inflammatory bowel disease (IBD) require long-term pharmacotherapy. Due to the wide variety of clinically available drugs, medication safety has become increasingly concerning. As an indispensable component of pharmaceutical formulations, drug excipients may induce various adverse reactions, including rash, allergic responses, and gastrointestinal discomfort, and may even lead to severe organic injury. However, they are often overlooked in clinical practice. Therefore, identifying and managing excipient-related adverse reactions is crucial for ensuring medication safety. To address this issue, this article systematically reviews common excipients in IBD therapeutics, the underlying mechanisms of excipient-induced adverse reactions, and corresponding management strategies, aiming to enhance clinicians' awareness of excipient-related issues, improve their ability to recognize and manage such reactions, and ultimately ensure patient safety.

Objective To distinguish Cremastra appendiculata(D.Don)Makino,Pleione yunnanensis Rolfe and Pleione bulbocodioides,and its easily confusing products Oreorchis patens and Iphigenia indica Kunth using the ITS sequence in DNA barcodes;To explore the genetic diversity of Cremastra appendiculata germplasm resources.Methods Three different original Cremastra appendiculata,Pleione yunnanensis Rolfe and Pleione bulbocodioides,and their easily confusing products Cremastrae Pseudobulbus of Oreorchis patens and Iphigenia indica Kunth were selected as the research objects,and the genomic DNA of the above samples were extracted by the modified CTAB method,and then the ITS sequences were amplified,sequenced and spliced by PCR technology.The Kimura 2-Parameter(K2P)model was used to calculate the genetic distance,and the phylogenetic tree was constructed with the help of neighbour joining method(NJ)for genetic relationship analysis.Results Except for the Iphigenia indica Kunth species that were not found during the BLAST search,the BLAST comparison results of the other samples were higher than 95%.At the same time,the results of phylogenetic tree showed that Cremastra appendiculata,Pleione yunnanensis Rolfe and Pleione bulbocodioides were clustered into one branch,respectively,and the easily confusing products were also respectively clustered into one branch.Conclusion The ITS sequence in DNA barcodes can be used to accurately distinguish Cremastra appendiculata,Pleione yunnanensis Rolfe and Pleione bulbocodioides,and its easily confusing products Oreorchis patens and Iphigenia indica Kunth.

BACKGROUND: Disease-modifying therapies have been approved for the treatment of relapsing multiple sclerosis (RMS). The present study aims to examine the safety of teriflunomide in Chinese patients with RMS. METHODS: This non-randomized, multi-center, 24-week, prospective study enrolled RMS patients with variant (c.421C>A) or wild type ABCG2 who received once-daily oral teriflunomide 14 mg. The primary endpoint was the relationship between ABCG2 polymorphisms and teriflunomide exposure over 24 weeks. Safety was assessed over the 24-week treatment with teriflunomide. RESULTS: Eighty-two patients were assigned to variant ( n  = 42) and wild type groups ( n  = 40), respectively. Geometric mean and geometric standard deviation (SD) of pre-dose concentration (variant, 54.9 [38.0] μg/mL; wild type, 49.1 [32.0] μg/mL) and area under plasma concentration-time curve over a dosing interval (AUC tau ) (variant, 1731.3 [769.0] μg∙h/mL; wild type, 1564.5 [1053.0] μg∙h/mL) values at steady state were approximately similar between the two groups. Safety profile was similar and well tolerated across variant and wild type groups in terms of rates of treatment emergent adverse events (TEAE), treatment-related TEAE, grade ≥3 TEAE, and serious adverse events (AEs). No new specific safety concerns or deaths were reported in the study. CONCLUSION: ABCG2 polymorphisms did not affect the steady-state exposure of teriflunomide, suggesting a similar efficacy and safety profile between variant and wild type RMS patients. REGISTRATION NCT04410965, https://clinicaltrials.gov .
Humans ; Crotonates/adverse effects* ; Toluidines/adverse effects* ; Nitriles ; Hydroxybutyrates ; Female ; Male ; Adult ; ATP Binding Cassette Transporter, Subfamily G, Member 2/genetics* ; Middle Aged ; Multiple Sclerosis, Relapsing-Remitting/genetics* ; Prospective Studies ; Young Adult ; Neoplasm Proteins/genetics* ; East Asian People

Objective:To create a reliable and efficient evaluation tool for postpartum rehabilitation assessment and treat-ment by developing the Postpartum Rehabilitation Assessment Scale.Method:The initial version of the scale was developed through a comprehensive literature review,theoretical analysis,and semi-structured interviews.The Delphi expert consensusmethod was used in two rounds to deter-mine item importance.Reliability was evaluated using correlation coefficients,dispersion,Cronbach's alpha,combinatory reliability,split-half reliability,and factor analysis.Validity was evaluated based on content,struc-ture,and predictive aspects.Result:Twenty-four items were selected and rated by Delphi expert correspondence.The item level content va-lidity index(I-CVI)was 1,and the total table level content validity index(S-CVI)was 1.After selection,the scale was refined to include 12 items.It demonstrated good internal consistency with a coefficient of 0.738 and high half reliability of 0.817.The cumulative variance contribution of 8 factors was 64.380％.The prediction accuracy of the scale was 0.956.Conclusion:The evaluation scale of postpartum female dysfunction is scientific,reasonable,reliable and val-id.It serves as a robust evaluation tool for postpartum female patients.

Objective:To create a reliable and efficient evaluation tool for postpartum rehabilitation assessment and treat-ment by developing the Postpartum Rehabilitation Assessment Scale.Method:The initial version of the scale was developed through a comprehensive literature review,theoretical analysis,and semi-structured interviews.The Delphi expert consensusmethod was used in two rounds to deter-mine item importance.Reliability was evaluated using correlation coefficients,dispersion,Cronbach's alpha,combinatory reliability,split-half reliability,and factor analysis.Validity was evaluated based on content,struc-ture,and predictive aspects.Result:Twenty-four items were selected and rated by Delphi expert correspondence.The item level content va-lidity index(I-CVI)was 1,and the total table level content validity index(S-CVI)was 1.After selection,the scale was refined to include 12 items.It demonstrated good internal consistency with a coefficient of 0.738 and high half reliability of 0.817.The cumulative variance contribution of 8 factors was 64.380％.The prediction accuracy of the scale was 0.956.Conclusion:The evaluation scale of postpartum female dysfunction is scientific,reasonable,reliable and val-id.It serves as a robust evaluation tool for postpartum female patients.

Objective:To assess the fall risk of hospitalized patients with cardiovascular diseases, analyze the related influencing factors, and construct a prediction model based on machine learning technology, so as to provide a basis for the fall management of hospitalized patients with cardiovascular diseases.Methods:This study was a retrospective cohort study. A total of 450 patients admitted to the Department of Cardiology, the First Affiliated Hospital of Nanjing Medical University from June 2017 to June 2024 were selected as the research objects by convenience sampling method. By reviewing electronic medical records, trained nurses extracted the patients' general information and Activities of Daily Living Scale (ADL) scores during hospitalization. Lasso regression was used to screen risk factors, and machine learning libraries were used to construct support vector machine (SVM), decision tree, XGBoost, and neural network models. Bootstrap resampling method and area under the curve (AUC) were used to verify the model performance.Results:Among the 450 patients, there were 261 males and 189 females, with a mean age of (66.0 ± 8.4) years. Among them, 90 patients fell during hospitalization and 360 patients did not fall. The results of Lasso regression showed that ADL score ≤60 points, use of hypnotics, hypokalemia, nighttime toilet visits≥2 times, use of antihypertensive drugs, no caregiver, and history of atrial fibrillation were all risk factors for falls in hospitalized patients with cardiovascular diseases (regression coefficients ranging from 0.61 to 1.20, all P<0.01). Among the machine learning models, XGBoost had the best comprehensive performance (AUC=0.98), which was better than decision tree (AUC=0.66), SVM (AUC=0.95), and neural network (AUC=0.87). Conclusions:The fall risk of hospitalized patients with cardiovascular diseases is jointly affected by physiological, medication and behavioral factors, and the XGBoost model can effectively identify high-risk groups. In actual clinical work, nursing strategies can be optimized in combination with risk factors, and the application of intelligent fall prediction and assessment tools can be promoted.

Objective:To assess the fall risk of hospitalized patients with cardiovascular diseases, analyze the related influencing factors, and construct a prediction model based on machine learning technology, so as to provide a basis for the fall management of hospitalized patients with cardiovascular diseases.Methods:This study was a retrospective cohort study. A total of 450 patients admitted to the Department of Cardiology, the First Affiliated Hospital of Nanjing Medical University from June 2017 to June 2024 were selected as the research objects by convenience sampling method. By reviewing electronic medical records, trained nurses extracted the patients' general information and Activities of Daily Living Scale (ADL) scores during hospitalization. Lasso regression was used to screen risk factors, and machine learning libraries were used to construct support vector machine (SVM), decision tree, XGBoost, and neural network models. Bootstrap resampling method and area under the curve (AUC) were used to verify the model performance.Results:Among the 450 patients, there were 261 males and 189 females, with a mean age of (66.0 ± 8.4) years. Among them, 90 patients fell during hospitalization and 360 patients did not fall. The results of Lasso regression showed that ADL score ≤60 points, use of hypnotics, hypokalemia, nighttime toilet visits≥2 times, use of antihypertensive drugs, no caregiver, and history of atrial fibrillation were all risk factors for falls in hospitalized patients with cardiovascular diseases (regression coefficients ranging from 0.61 to 1.20, all P<0.01). Among the machine learning models, XGBoost had the best comprehensive performance (AUC=0.98), which was better than decision tree (AUC=0.66), SVM (AUC=0.95), and neural network (AUC=0.87). Conclusions:The fall risk of hospitalized patients with cardiovascular diseases is jointly affected by physiological, medication and behavioral factors, and the XGBoost model can effectively identify high-risk groups. In actual clinical work, nursing strategies can be optimized in combination with risk factors, and the application of intelligent fall prediction and assessment tools can be promoted.

Objective To distinguish Cremastra appendiculata(D.Don)Makino,Pleione yunnanensis Rolfe and Pleione bulbocodioides,and its easily confusing products Oreorchis patens and Iphigenia indica Kunth using the ITS sequence in DNA barcodes;To explore the genetic diversity of Cremastra appendiculata germplasm resources.Methods Three different original Cremastra appendiculata,Pleione yunnanensis Rolfe and Pleione bulbocodioides,and their easily confusing products Cremastrae Pseudobulbus of Oreorchis patens and Iphigenia indica Kunth were selected as the research objects,and the genomic DNA of the above samples were extracted by the modified CTAB method,and then the ITS sequences were amplified,sequenced and spliced by PCR technology.The Kimura 2-Parameter(K2P)model was used to calculate the genetic distance,and the phylogenetic tree was constructed with the help of neighbour joining method(NJ)for genetic relationship analysis.Results Except for the Iphigenia indica Kunth species that were not found during the BLAST search,the BLAST comparison results of the other samples were higher than 95%.At the same time,the results of phylogenetic tree showed that Cremastra appendiculata,Pleione yunnanensis Rolfe and Pleione bulbocodioides were clustered into one branch,respectively,and the easily confusing products were also respectively clustered into one branch.Conclusion The ITS sequence in DNA barcodes can be used to accurately distinguish Cremastra appendiculata,Pleione yunnanensis Rolfe and Pleione bulbocodioides,and its easily confusing products Oreorchis patens and Iphigenia indica Kunth.

Objective: Progressive supranuclear palsy (PSP) involves a variety of visual symptoms that are thought to be partially caused by structural abnormalities of the retina. However, the relationship between retinal structural changes, disease severity, and intracranial alterations remains unknown. We investigated distinct retinal thinning patterns and their relationship with clinical severity and intracranial alterations in a PSP cohort. Methods: We enrolled 19 patients with PSP (38 eyes) and 20 age-matched healthy controls (40 eyes). All of the participants underwent peripapillary and macular optical coherence tomography. Brain 11C-2β-carbomethoxy-3β-(4-fluorophenyl) tropane (11C-CFT) and 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography imaging were also performed in patients with PSP. We investigated the association between retinal thickness changes and clinical features, striatal dopamine transporter availability, and cerebral glucose metabolism. Results: The peripapillary retinal nerve fiber layer (pRNFL) and macula were significantly thinner in patients with PSP than in controls. The thickness of the superior sector of the pRNFL demonstrated a significant negative relationship with the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale part III and Hoehn and Yahr staging scale scores. A significant negative correlation was found between outer inferior macular thickness and disease duration. Outer temporal macular thickness was positively correlated with Montreal Cognitive Assessment scores. In PSP, lower outer temporal macular thickness was also positively correlated with decreased dopamine transporter binding in the caudate. Conclusion The pRNFL and macular thinning may be candidate markers for monitoring disease severity. Additionally, macular thinning may be an in vivo indicator of nigrostriatal dopaminergic cell degeneration in PSP patients.

Objective To monitor the antifungal resistance of clinical isolates of Candida spp.in the East China region.Methods MALDI-TOF MS or molecular methods were used to re-identify the strains collected from January 2018 to December 2022.Antifungal susceptibility testing was performed using the broth microdilution method.The susceptibility test results were interpreted according to the breakpoints of 2022 Clinical and Laboratory Standards Institute(CLSI)documents M27 M44s-Ed3 and M57s-Ed4.Results A total of 3 026 strains of Candida were collected,65.33％of which were isolated from sterile body sites,mainly from blood(38.86％)and pleural effusion/ascites(10.21％).The predominant species of Candida were Candida albicans(44.51％),followed by Candida parapsilosis complex(19.46％),Candida tropicalis(13.98％),Candida glabrata(10.34％),and other Candida species(0.79％).Candida albicans showed overall high susceptibility rates to the 10 antifungal drugs tested(the lowest rate being 93.62％).Only 2.97％of the strains showed dose-dependent susceptibility(SDD)to fluconazole.Candida parapsilosis complex had a SDD rate of 2.61％and a resistance rate of 9.42％to fluconazole,and susceptibility rates above 90％to other drugs.Candida glabrata had a SDD rate of 92.01％and a resistance rate of 7.99％to fluconazole,resistance rates of 32.27％and 48.24％to posaconazole and voriconazole non-wild-type strains(NWT),respectively,and susceptibility rates above 90％to other drugs.Candida tropicalis had resistance rates of 29.55％and 26.24％to fluconazole and voriconazole,respectively,resistance rates of 76.60％and 21.99％to posaconazole and echinocandins non-wild-type strains(NWT),and a resistance rate of 2.36％to echinocandins.Conclusions The prevalence and species distribution of Candida spp.in the East China region are consistent with previous domestic and international reports.Candida glabrata exhibits certain degree of resistance to fluconazole,while Candida tropicalis demonstrates higher resistance to triazole drugs.Additionally,echinocandins resistance has emerged in Candida albicans,Candida glabrata,Candida tropicalis,and Candida parapsilosis.