ObjectiveTo investigate the association between single and combined exposure to arsenic （As）， mercury （Hg）， and cadmium （Cd） in urine and hearing loss in adults. MethodsA total of 400 adult patients were recruited for the study， comprising 200 participants in the normal hearing group and 200 in the hearing loss group. General demographic information of the study subjects was collected by a self-administered questionnaire， morning urine samples were tested for As， Hg， and Cd concentrations， and hearing status was assessed by Pure Tone Audiometry. A binary Logistic regression model was used to explore the association between the concentrations of the three metals in urine and hearing loss， and a Bayesian kernel-machine regression （BKMR） model was used to further explore the association between the concentrations of the three metal mixtures and hearing loss. ResultsAfter correction for urinary creatinine， As， Hg， and Cd concentrations were higher in the hearing loss group than those in the normal hearing group （P<0.05）. Binary Logistic regression indicated that concentrations of As， Hg， and Cd were positively associated with hearing loss， and the risk of hearing loss was significantly higher in the second quartile of Cd concentration compared to the first quartile （OR=2.000， 95%CI： 1.009-3.964）. BKMR modeling analysis showed that the combined exposure levels of As， Hg， and Cd significantly increased the risk of hearing loss， with Cd being the most important contributor （posterior inclusion probability=0.412）， and that there were potential interactions between As and Cd， and Cd and Hg. ConclusionCombined exposure to As， Hg， and Cd in urine is significantly associated with adult hearing loss， with Cd being the primary contributor in the exposure combination. The interactions between As and Cd， as well as Cd and Hg， may have adverse effects on hearing loss.

A deep learning-based method for recognizing the minutiae in fingerprint,as well as a Python programming-based evaluation system for quantifying the evidence value of fingerprint was proposed.Firstly,latent fingerprints,which were developed using a series of fluorescent nanomaterials synthesized by chemical methods,were used as unknown fingerprint(UKFP),while ink impressed fingerprints were used as known fingerprint(KFP).Then,the bifurcations and terminations in minutiae were recognized using the improved YOLOv8 deep learning model.After that,the similarity index(Sim.)of UKFP vs KFP were calculated by analyzing the angle similarity factor(α)and the curve similarity factor(β)between UKFP and KFP,meanwhile,the sensitivity index(Sen.)were calculated by analyzing the fineness factor(γ)between UKFP and KFP.The evidence value(EV)of fingerprint was thus obtained by the combination of Sim.and Sen..The calculation formulas for above evaluation factors(i.e.α,β and γ),evaluation indexes(i.e.Sim.and Sen.),and EV were also put forward.Finally,the evaluation system for quantifying the evidence value of fingerprint was established,the feasibility and reliability of this system were verified,and the external factors that impacted on Sim.,Sen.,and EV were investigated in detail.The Python-based evaluation system for quantifying the evidence value of fingerprint could achieve the goals objectively,comprehensively,accurately and efficiently,exhibiting easy operability,high efficiency,responsiveness and reliability.This research was expected to provide beneficial references for quantitatively evaluating and thoroughly developing the evidence value.

Objective:To study the current status of transitional readiness from adolescence to adulthood of patients with inflammatory bowel disease（IBD）in China,analyze the factors affecting transitional readiness,and provide a basis for developing scientific and targeted transitional preparedness programmes.Methods:The IBD patients aged 12-24 years who were admitted to the Department of Gastroenterology,Beijing Children's Hospital Affiliated to Capital Medical University from January 1,2016 to January 15,2025 were enrolled.From November 1,2024 to January 15,2025,the survey was conducted through online distribution of the transition readiness assessment questionnaire (TRAQ)6.0 Chinese version scale to IBD patients by using the convenient sampling method.The scores of each dimension of TRAQ scale were calculated,and multiple linear regression analysis was used to analyze the factors influencing the scores of TRAQ during the transitional period.Results:A total of 184 patients were included and 184 questionnaires were collected.Male patients were slightly more than female(109:75),with an average age of (14.94±2.35) years.70.11% of patients had a disease duration of 1 to 5 years,with Crohn's disease accounting for the highest proportion(54.89%),and the severity of the disease was mostly mild to moderate.Family support was generally higher(84.24%).Parents were highly involved in patient disease management(94.02%).There were 52.72% of the patients received social support.The mean score of the TRAQ was 4.14 ± 0.89,and the mean scores of the four dimensions from high to low were following health problems(4.28±0.97),insisting on making an appointment and seeing a doctor on time(4.20±1.10),talking with medical staff(4.17±1.05) and drug management(4.14±0.99).Multiple linear regression analysis showed that family status,the encourage,supports and help from the family members,and the supports from the society were the independent influencing factors of IBD patients' readiness score for transition from adolescence to adulthood( P<0.05).Among them,family status had a positive effect on transition readiness score,and the degree of readiness score increased with the increase of harmony( P<0.05).Social support also had a positive effect on transition readiness score( P<0.05).Compared with no encouragement,support and help from family members,the situation of little encouragement had a certain improvement on the readiness score( P<0.05). Conclusion:Children with IBD have better overall performance during the transition from adolescence to adulthood.Family status,the encourage,supports and help from the family members,and the supports from the society are the important factors influencing transitional preparedness.

Objective:By using cognitive interviews,the interviewees' cognition and understanding of the inflammatory bowel disease(IBD) self-efficacy scale for adolescents and young adults (IBDSES-A) were evaluated,and the semantic content of IBDSES-A,which was initially translated into Chinese,was tested and revised.Methods:Using purposive sampling,15 IBD patients aged 12-18 were selected from Beijing Children's Hospital,Capital Medical University,between January and February 2025,stratified by age group and disease type.Two rounds of cognitive interviews were conducted.Feedback and suggestions from interviewees were analyzed using a question appraisal system for coding and integration.Based on expert panel discussions,ambiguous items were revised to finalize the Chinese version of the IBDSES-A.Results:In the first round,10 interviewees were interviewed,followed by 5 interviewees in the second round.There were no statistically significant differences ( P>0.05) between the interviewees of two rounds in terms of age,gender,and education level.During the first round of interview,interviewees expressed comprehension difficulties with 76.9% (10/13) of the items.Coding analysis revealed that the primary issue was "clarification",as unclear wording made it difficult for interviewees to fully grasp the intended meaning of certain items.Based on these findings,the expert panel revised 10 of the 13 items in the IBDSES-A.The second round of cognitive interview showed that the interviewees generally understood the revised items，achieving linguistic and semantic consistency with the original scale. Conclusion:The application of cognitive interviews in the translation process of the IBDSES-A helps reduce comprehension biases caused by inappropriate wording，ensuring that the localized version of the scale is more accessible and understandable to the target population.

This study investigated the drug resistance and genetic relationships among strains co-existing in animals,the environ-ment,and the living quarters of employees at large-scale pig farms in certain regions of Shandong Province,to provide a scientific ba-sis for elucidating the transmission mechanisms of drug-resistant bacteria through bacterial traceability analysis.Samples were col-lected from two pig farms,and bacteria were isolated and purified.The species of the isolated strains were identified via 16S rRNA gene sequencing.Antimicrobial susceptibility testing was conducted with a VITEK-2 Compact system and the disk diffusion method for strains present in pigs,the environment,and living areas.Furthermore,whole-genome sequencing was performed on the Illumina Miniseq platform to annotate drug resistance genes,and multilocus sequence typing(MLST)and core genome single nucleotide poly-morphism(cgSNP)analyses were used to trace the resistant strains.Three species—Staphylococcus aureus,Pseudomonas aeruginosa,and Bacillus cereus—were isolated and cultured from animals,the environment,and employee living areas,and their distributions were analyzed.These strains exhibited diverse drug resistance spectra and genetic diversity.Additionally,the strains displayed highly consistent resistance profiles,resistance genes,ST types,and SNP loci in pig urine,soil both inside and outside the facility,human drinking water,and the cafeteria and dormitories.Our findings indicated a potential risk of transmission of opportunistic pathogens be-tween the pig farming area and the living quarters.Particular attention should be paid to the environmental transmission of methicillin-resistant Staphylococcus aureus.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.