OBJECTIVE To develop a method for the determination of tacrolimus （TAC） concentration in human whole blood and to apply it in clinical therapeutic drug monitoring. METHODS Whole blood samples were processed by protein precipitation with methanol. The determination was performed using liquid chromatography-tandem mass spectrometry （LC-MS/MS）， with ascomycin serving as the internal standard. Chromatographic separation was carried out on a Kinetex F5 100Å column with a mobile phase consisting of 0.1 mmol/L ammonium acetate containing 0.2 mmol/L formic acid and methanol. Gradient elution was performed at a flow rate of 0.4 mL/min. The injection volume was 5 μL. Detection was conducted using multiple reaction monitoring （ m / z 821.6→768.6 for TAC； m / z 809.4→756.1 for ascomycin） with an electrospray ionization source in positive ion mode. The study focused on 86 whole blood samples collected from 83 pedi atric patients who received TAC therapy at Children’s Hospital of Nanjing Medical University from September 1 to 30， 2025. The aforementioned method was employed to measure the TAC concentration in the whole blood samples. The correlation and agreement between the aforementioned method and the traditional enzyme multiplied immunoassay technique （EMIT） were evaluated through Spearman correlation analysis， Bland-Altman analysis， and Passing-Bablok regression analysis. RESULTS The linear range of TAC was 0.5-100 ng/mL； the evaluation results for accuracy， precision， extraction recovery， matrix effect， and stability tests all met the relevant requirements. Clinical application results showed that the median concentration of TAC in pediatric whole blood measured by LC-MS/MS and EMIT methods were 4.4 and 4.0 ng/mL， respectively. Moreover， the two methods exhibited a strong correlation （correlation coefficient of 0.848 1） and good agreement （average relative deviation of 6.5%）. CONCLUSIONS A reliable LC-MS/MS method for the determination of TAC concentration in human whole blood is successfully established. This method demonstrates strong correlation and good agreement with the EMIT method， making it suitable for clinical therapeutic drug monitoring.

Objective:The actor-partner interdependence model was used to explore the subject-object effect of family care on disease acceptance in maintenance hemodialysis (MHD) patients and their primary caregivers, and to provide empirical research support for formulating intervention strategies to improve the quality of life of MHD patients and their primary caregivers at the dyadic coping perspective.Methods:This study was a cross-sectional study. A convenience sampling method was used to select 223 pairs of MHD patients and their primary caregivers who received treatment at three hospitals from December 2023 to May 2024, namely the Second Affiliated Hospital of Guizhou Medical University, Qiandongnan People′s Hospital and Qiandongnan Traditional Chinese Medicine Hospital. The General Information Questionnaire, Family APGAR Index (APGAR) and the Acceptance of Illness Scale (AIS) were used to conduct the survey. An actor-partner interdependence model of the impact of family care levels on disease acceptance was constructed.Results:There were 223 patients with MHD, 134 males and 89 females, aged (48.41 ± 14.41) years. Among the 223 primary caregivers of MHD patients, 83 were males and 140 were females, aged (49.44 ± 12.40) years. The scores of APGAR and AIS for MHD patients were (7.92 ± 1.94), (20.45 ± 4.66) points, and (8.16 ± 1.67), (21.86 ± 3.54) points for their primary caregivers. There were statistically significant differences in scores ( t = - 2.28, - 7.69, both P<0.05). The results of correlation analysis showed that there was a significant positive correlation between the degree of family care of MHD patients and the disease acceptance of MHD patients, the family care of primary caregivers, and the disease acceptance of primary caregivers ( r = 0.454, 0.625, 0.515, all P<0.05). There was a significant positive correlation between the disease acceptance of MHD patients and the family care of their primary caregivers, the disease acceptance of primary caregivers, and the family care of primary caregivers and the disease acceptance of primary caregivers ( r = 0.442, 0.813, 0.495, all P<0.05). In terms of the actor effect, the level of family care positively influenced the disease acceptance for both MHD patients and their primary caregivers ( β = 0.715, 0.603, both P<0.001), the actor effect was significant. In terms of partner effect, there was a positive correlation between the family care levels of MHD patients and their primary caregivers and the disease acceptance of the other party ( β = 0.628, 0.725, both P<0.001), the partner effect was significant. Conclusions:There is an interactive effect between the disease acceptance of maintenance hemodialysis patients and their primary caregivers and their levels of family care.

Objective: To construct a prediction model for sleep disorders in shift workers of a chemical fiber enterprise, so as to provide the basis for early identification and prevention of sleep disorders in shift workers. Methods: Shift workers were sampled from a chemical fiber enterprise in Tongxiang City, Zhejiang Province using a cluster sampling method from August 2022 to July 2024. Demographic information, length of service and average weekly working hours were collected through questionnaire surveys. Depressive symptoms, anxiety symptoms and sleep disorders were evaluated using the Pittsburgh Sleep Quality Index, Patient Health Questionnaire and Generalized Anxiety Disorder Questionnaire, respectively. The shift workers were randomly divided into a training set and a validation set at a ratio of 7∶3. Predictive factors were selected using a multivariable logistic regression model based on the training set, and a nomograph model for prediction of sleep disorders in shift workers was established. The predictive values of the model were evaluated using the receiver operating characteristic (ROC) curve and calibration curve based on the training set and validation set. Results: Totally 673 shift workers were included, with a median age of 32 (interquartile range, 12) years. There were 493 males, accounting for 73.25%. There were 471 (69.99%) workers in the training set and 202 (30.01%) workers in the validation set. There were 274 workers with sleep disorders, accounting for 40.71%. The equation for the prediction model was ln[p/(1-p)]=-8.391+1.906×average weekly working hours+1.822×depressive symptoms+1.667×anxiety symptoms. The area under the ROC curve was 0.769 (95%CI: 0.661-0.835) for the training set and 0.655 (95%CI: 0.593-0.737) for the validation set, and Hosmer-Lemeshow test showed a good fitting effect (both P>0.05). Conclusion The nomograph model constructed by average weekly working hours, depressive symptoms and anxiety symptoms can be used to predict the risk of sleep disorders in shift workers of a chemical fiber enterprise.

Objective:The actor-partner interdependence model was used to explore the subject-object effect of family care on disease acceptance in maintenance hemodialysis (MHD) patients and their primary caregivers, and to provide empirical research support for formulating intervention strategies to improve the quality of life of MHD patients and their primary caregivers at the dyadic coping perspective.Methods:This study was a cross-sectional study. A convenience sampling method was used to select 223 pairs of MHD patients and their primary caregivers who received treatment at three hospitals from December 2023 to May 2024, namely the Second Affiliated Hospital of Guizhou Medical University, Qiandongnan People′s Hospital and Qiandongnan Traditional Chinese Medicine Hospital. The General Information Questionnaire, Family APGAR Index (APGAR) and the Acceptance of Illness Scale (AIS) were used to conduct the survey. An actor-partner interdependence model of the impact of family care levels on disease acceptance was constructed.Results:There were 223 patients with MHD, 134 males and 89 females, aged (48.41 ± 14.41) years. Among the 223 primary caregivers of MHD patients, 83 were males and 140 were females, aged (49.44 ± 12.40) years. The scores of APGAR and AIS for MHD patients were (7.92 ± 1.94), (20.45 ± 4.66) points, and (8.16 ± 1.67), (21.86 ± 3.54) points for their primary caregivers. There were statistically significant differences in scores ( t = - 2.28, - 7.69, both P<0.05). The results of correlation analysis showed that there was a significant positive correlation between the degree of family care of MHD patients and the disease acceptance of MHD patients, the family care of primary caregivers, and the disease acceptance of primary caregivers ( r = 0.454, 0.625, 0.515, all P<0.05). There was a significant positive correlation between the disease acceptance of MHD patients and the family care of their primary caregivers, the disease acceptance of primary caregivers, and the family care of primary caregivers and the disease acceptance of primary caregivers ( r = 0.442, 0.813, 0.495, all P<0.05). In terms of the actor effect, the level of family care positively influenced the disease acceptance for both MHD patients and their primary caregivers ( β = 0.715, 0.603, both P<0.001), the actor effect was significant. In terms of partner effect, there was a positive correlation between the family care levels of MHD patients and their primary caregivers and the disease acceptance of the other party ( β = 0.628, 0.725, both P<0.001), the partner effect was significant. Conclusions:There is an interactive effect between the disease acceptance of maintenance hemodialysis patients and their primary caregivers and their levels of family care.

Pancreatic cancer is a common malignant tumor of the digestive system,with a low early diagnosis rate,a high surgical mortality rate,a low cure rate,and a poor overall prognosis.In recent years,with the continuous development of artificial intelligence in the medical field,artificial intelligence techniques,such as machine learning and deep learning,have been widely used in medical research.This article reviews the application of artificial intelligence techniques in the screening,diagnosis,treatment,complications,and prognosis prediction of pancreatic cancer,so as to provide a basis and new ideas for the application of artificial intelligence in the diagnosis and treatment of pancreatic cancer.

Objectives:To compare the diagnostic efficacy of non-ST-segment elevation myocardial infarction (NSTEMI) and the predictive value for major adverse cardiovascular events (MACE) of the 0/3-hour algorithm for high-sensitivity cardiac troponin (hs-cTn) recommended by the 2015 European Society of Cardiology (ESC) guidelines for the management of non-ST-segment elevation acute coronary syndrome (NSTE-ACS) and the 2021 "Chinese Expert Consensus on Laboratory Testing and Clinical Application of Cardiac Troponin" in suspected acute coronary syndrome (ACS) patients in the Chinese population. Methods:This is a multicenter prospective observational study,including 1527 patients with suspected ACS from three clinical centers from January 2017 to September 2020.Plasma hs-cTnI levels were measured using the ARCHITECT assay at the time of presentation and 3 hours later in patients with suspected ACS (test determination).Clinical judgment (independent clinical judgment by cardiac experts,independent of the test results) was used as the gold standard to compare the sensitivity,specificity,and consistency of the two diagnostic algorithms,and to analyze their predictive value for MACE at 30 days and 180 days.MACE in this study was defined as a composite event of cardiovascular death,myocardial infarction,and unplanned coronary revascularization. Results:According to clinical judgment,there were 400 patients with NSTEMI and 1127 patients without NSTEMI.The 0/3-hour algorithm recommended by the 2021 Chinese Expert Consensus showed higher sensitivity in diagnosing NSTEMI than the 2015 ESC guidelines (91.50％[95％ CI:88.32％-94.04％]vs.87.75％[95％ CI:84.13％-90.80％]),but slightly lower specificity (93.88％[95％ CI:92.32％-95.21％]vs.95.56％[95％ CI:94.19％-96.69％]),with both differences being statistically significant (both P<0.001).In the follow-up at 30 days and 180 days,the incidence of MACE in patients diagnosed with NSTEMI by both algorithms was higher than in those without NSTEMI (P<0.001).The incidence of MACE at 30 days and 180 days for the group excluded from the diagnosis of NSTEMI by 2015 ESC guidelines was 0.19％ and 1.120％,respectively,and for the NSTEMI group was 2.89％ and 3.68％,respectively;for the group excluded from NSTEMI by the 2021 Chinese Expert Consensus,the incidence was 0.096％ and 0.770％,respectively,and for the NSTEMI group was 2.91％ and 4.36％,respectively.Cox analysis showed that the HR ratio for MACE at 180 days in the NSTEMI group diagnosed by both algorithms was 3.418 and 5.892,respectively,significantly higher than the group excluded from NSTEMI. Conclusions:The 0/3-hour algorithm recommended by the 2021 Chinese Expert Consensus has superior diagnostic sensitivity compared to the 2015 ESC NSTE-ACS guidelines,at the cost of slightly lower specificity.Both algorithms can effectively predict MACE within 180 days,but based on the data from this study,the algorithm recommended by the 2021 Chinese Expert Consensus is more sensitive in predicting the risk of MACE,and patients excluded from the diagnosis of NSTEMI by this method have a lower incidence of MACE,suggesting that its application in clinical practice may be more helpful in terms of long-term safe management of patients.

Objective To simulate the microflow field environment between the anastomotic nail surface and intestinal wall tissue after implantation and to study the effect of hydrophobic surfaces on the flow rate of extracellular fluid and the fluid shear force on the wall to regulate bacterial adhesion through changes in the flow field.Methods The microstructure of shark skin was observed,and a simplified two-dimensional(2D)movement model of bacteria in a microflow field was established.Using computational fluid dynamics(CFD)numerical simulation,the movement of bacteria on a smooth surface and micro-textured surface in a static and dynamic flow field were simulated.The flow field characteristics around bacteria and the magnitude of fluid shear force under the two surface environments were compared,and the internal mechanism of the fluid shear force affecting bacterial adhesion was analyzed.Results The addition of the biomimetic microtexture enhanced the flow rate of the extracellular fluid in the microflow field,and the fluid had little viscous effect on the bacteria in the static flow field.The fluid in the dynamic flow field had a stronger pushing effect on the bacteria.The fluid shear force on the microtextured wall increased when the pit width was within a specific range.Conclusions The bionic micro-textured surface of the anastomotic nail can accelerate the flow rate of extracellular fluid,increase the fluid shear force of micro-textured walls and bacteria,and influence bacterial adhesion.These result provide a theoretical basis for studying bacteriostatic surfaces of anastomotic nails.

Objective To explore the prognostic value of hs-cTnⅠ in patients with suspected acute coronary syndrome(ACS)in emergency department.Methods A large-scale,prospective observa-tional study was conducted on totally 966 patients with suspected ACS admitted in Fuwai Hospi-tal from January 2017 to October 2020.Their baseline serum/plasma hs-cTnⅠ level was detected at admission,conventional treatment was performed,and relevant data were collected.Logistic regression analysis was used to predict the risk of primary and secondary endpoint events within 30 d by hs-TnⅠ concentration,and subgroup analysis was performed.Results Among the 966 patients,the time from chest pain to visit was 5.0(2.5,13.0)h,and 284 patients had primary end-point events within 30 d,including 283 cases of myocardial infarction(99.6％)at the first visit,1 case of recurrent myocardial infarction(0.4％),5 cases of cardiovascular death(1.8％),and 1 case of unplanned revascularization(0.4％).When hs-cTnⅠ was at the minimum detection limit of 2 ng/L,the incidence of adverse events was 5.8％,when the limit of 70 ng/L,the incidence was 49.2％,and when of 316 ng/L,the incidence reached 100％.The model could correctly classify 92.3％of the patients.Conclusion The hs-cTn sequence has a good predictive effect for the risk of short-term cardiovascular adverse events in Chinese population.

Objective:To investigate the effects and mechanisms of copper transporter 1 (CTR1) in radiation induced intestinal injury in vitro. Methods:Human small intestinal epithelial cells (HIEC) were irradiated with 2, 4, 6, 8 Gy of X-rays and rat intestinal epithelial cells (IEC-6) were irradiated with 5, 10, 15, 20 Gy of X-rays. At 2, 4, 8, 24, and 48 h after irradiation, the expression of CTR1 was detected by Western blot assay. In some experiments, HIEC and IEC-6 cells were transfected with CTR1 shRNA and then exposed to X-rays. Copper levels were detected by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The radiosensitivity of cells was verified by colonogenic assay, the cellular reactive oxygen species (ROS) level and DNA damage were detected to further explore the related mechanism. In addition, Western blot was applied to detect the expressions of antioxidants and cuproptosis associated proteins in enterocytes after silencing CTR1 or irradiation.Results:The expression of CTR1 was increased by X-ray irradiation in a dose-dependent manner ( t=3.53, 3.45, 6.37, 11.11, 11.13, P<0.05). CTR1 expression was successfully diminished by CTR1 shRNA adenovirus vectors. According to the survival curves, the enhancement ratios of the radiosensitivity of HIEC and IEC-6 cells with CTR1 knocking-down were 1.146 and 1.201, respectively. Radiation-induced copper accumulation was alleviated after CTR1 silencing in IEC-6 cells ( t=3.10, P<0.05). At 0.5 h after irradiation, the ROS production in the CTR1 knockdown group was significantly lower than that in the control group ( t=5.23, 2.96, P<0.05). At 1 h after irradiation, the protein expression of γ-H2AX in the CTR1 knockdown group was obviously lower than that in the control group ( t=7.50, 4.29, P<0.05). The expressions of Nrf2 and HO-1 were increased after irradiation, which could be further increased after CTR1 silencing. In addition, cuproptosis associated protein DLAT, LIAS and FDX1 were reduced post-irradiation, which were recovered after CTR1 silencing. Conclusions:The radioresistance of HIEC and IEC-6 cells was enhanced after CTR1 silencing, possibly through the intracellular ROS and cuproptosis pathway.

Objective:To investigate clinical and imaging parameters to predict blood loss and cranial nerve injury (CNI) following carotid body paraganglioma (CBP) resection.Methods:A retrospective examination of clinical and imaging data was conducted on 63 patients who underwent CBP resection at Xiangya Hospital of Central South University from January 2016 to December 2022, including 23 males and 40 females, aged 26-87 years old. Three imaging parameters including tumor volume, the angle of contact with the internal carotid artery (ICA), and the distance to the base of skull (DTBOS) were gauged using the IMEDPACS software on CTA and MR imaging. The predictive efficacies of age, gender, Shamblin classification, and three imaging parameters for blood loss and CNI following surgery were analysed. Logistic composite parameter models were constructed and their predictive validity was assessed.Results:Multivariate logistic regression analysis underscored that only tumor volume ( OR=1.381,95% CI:1.167-1.507, P=0.001) showed significant statistical correlations with blood loss following surgery. Area under curve (AUC) values of 0.910 for receiver operating characteristic (ROC) curves showed a sensitivity of 1.000 and a specificity of 0.694. Tumor volume ( OR=1.126,95% CI:1.030-1.231, P=0.002) and DTBOS ( OR=0.225,95% CI:0.081-0.630, P=0.005) were significantly associated with postoperative CNI. The analysis of logistic composite model showed AUC values for tumor volume, DTBOS and combination of the two parameters were 0.858, 0.788, and 0.872, respectively. The model for combination of tumor volume and DTBOS also proved superior in predicting postoperative CNI ( Z=3.106, P<0.001), with a sensitivity of 0.833 and a specificity of 0.769. Conclusions:Tumor volume and DTBOS emerged as effective predictors for blood loss and/or CNI in patients with CBP resection. Moreover, the logistic composite parameter model outclassed single-parameter models in terms of their predictive clinical value.