Objective By combining biological detection and imaging evaluation, a clinical prediction model is constructed based on a large cohort to improve the accuracy of distinguishing between benign and malignant pulmonary nodules. Methods A retrospective analysis was conducted on the clinical data of the 32 627 patients with pulmonary nodules who underwent chest CT and testing for 7 types of lung cancer-related serum autoantibodies (7-AABs) at our hospital from January 2020 to April 2024. The univariate and multivariate logistic regression models were performed to screen independent risk factors for benign and malignant pulmonary nodules, based on which a nomogram model was established. The performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results A total of 1 017 patients with pulmonary nodules were included in the study. The training set consisted of 712 patients, including 291 males and 421 females, with a mean age of (58±12) years. The validation set included 305 patients, comprising 129 males and 176 females, with a mean age of (58±13) years. Univariate ROC curve analysis indicated that the combination of CT and 7-AABs testing achieved the highest area under the curve (AUC) value (0.794), surpassing the diagnostic efficacy of CT alone (AUC=0.667) or 7-AABs alone (AUC=0.514). Multivariate logistic regression analysis showed that radiological nodule diameter, nodule nature, and CT combined with 7-AABs detection were independent predictors, which were used to construct a nomogram prediction model. The AUC values for this model were 0.826 and 0.862 in the training and validation sets, respectively, demonstrating excellent performance in DCA. Conclusion The combination of 7-AABs with CT significantly enhances the accuracy of distinguishing between benign and malignant pulmonary nodules. The developed predictive model provides strong support for clinical decision-making and contributes to achieving precise diagnosis and treatment of pulmonary nodules.

Electromagnetic fields can regulate the fundamental biological processes involved in bone remodeling. As a non-invasive physical therapy, electromagnetic fields with specific parameters have demonstrated therapeutic effects on bone remodeling diseases, such as fractures and osteoporosis. Electromagnetic fields can be generated by the movement of charged particles or induced by varying currents. Based on whether the strength and direction of the electric field change over time, electromagnetic fields can be classified into static and time-varying fields. The treatment of bone remodeling diseases with static magnetic fields primarily focuses on fractures, often using magnetic splints to immobilize the fracture site while studying the effects of static magnetic fields on bone healing. However, there has been relatively little research on the prevention and treatment of osteoporosis using static magnetic fields. Pulsed electromagnetic fields, a type of time-varying field, have been widely used in clinical studies for treating fractures, osteoporosis, and non-union. However, current clinical applications are limited to low-frequency, and research on the relationship between frequency and biological effects remains insufficient. We believe that different types of electromagnetic fields acting on bone can induce various “secondary physical quantities”, such as magnetism, force, electricity, acoustics, and thermal energy, which can stimulate bone cells either individually or simultaneously. Bone cells possess specific electromagnetic properties, and in a static magnetic field, the presence of a magnetic field gradient can exert a certain magnetism on the bone tissue, leading to observable effects. In a time-varying magnetic field, the charged particles within the bone experience varying Lorentz forces, causing vibrations and generating acoustic effects. Additionally, as the frequency of the time-varying field increases, induced currents or potentials can be generated within the bone, leading to electrical effects. When the frequency and power exceed a certain threshold, electromagnetic energy can be converted into thermal energy, producing thermal effects. In summary, external electromagnetic fields with different characteristics can generate multiple physical quantities within biological tissues, such as magnetic, electric, mechanical, acoustic, and thermal effects. These physical quantities may also interact and couple with each other, stimulating the biological tissues in a combined or composite manner, thereby producing biological effects. This understanding is key to elucidating the electromagnetic mechanisms of how electromagnetic fields influence biological tissues. In the study of electromagnetic fields for bone remodeling diseases, attention should be paid to the biological effects of bone remodeling under different electromagnetic wave characteristics. This includes exploring innovative electromagnetic source technologies applicable to bone remodeling, identifying safe and effective electromagnetic field parameters, and combining basic research with technological invention to develop scientifically grounded, advanced key technologies for innovative electromagnetic treatment devices targeting bone remodeling diseases. In conclusion, electromagnetic fields and multiple physical factors have the potential to prevent and treat bone remodeling diseases, and have significant application prospects.

OBJECTIVE To analyze the potential adverse drug interactions （pADIs） of clarithromycin， and establish refined prescription pre-review rules. METHODS Outpatient prescriptions of clarithromycin in combination with other drugs were collected from January 1， 2024 to June 30， 2024 through hospital information system of the Third People’s Hospital of Bengbu. pADIs were identified and their risk severities were graded according to Lexicomp and Micromedex databases. Then， refined prescription pre- review rules for clarithromycin pADIs-related drugs were established according to the identification and risk level results. RESULTS Among 3 046 clarithromycin combined drug prescriptions， 946 cases of pADIs occurred in 812 prescriptions. There were 6， 415 and 525 cases classified as “contraindicated”，“ major” and “moderate”， respectively. The combination drugs with “contraindicated” levels were tamsulosin， rupatadine， domperidone and ticagrelor， while those with “major” levels were mainly theophylline， dexamethasone and amlodipine. Accordingly， 26 refined rules were established， including 4 items of “warning information→prescription interception”， 11 items of “warning information→prescription double signature” and 11 items of “attention information→prescription approval”. CONCLUSIONS There are “contraindicated” and “major” risks associated with clarithromycin and its combination drugs in the hospital， and refined prescription pre-review rules for clarithromycin combined drug prescription have been established successfully.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

OBJECTIVE To analyze the potential adverse drug interactions based on pharmacokinetics （PK-pADIs） of gefitinib， and establish its corresponding prescription review rules. METHODS Outpatient prescriptions of gefitinib combination therapy in our hospital from January 1， 2022 to November 30， 2024 were collected through rational drug software system. PK- pADIs present in the prescriptions were identified based on the Drugs.com® drug interactions database. The specific combination drugs and cases of PK-pADIs were statistically analyzed， and prescription review rules were established according to the severity classification of PK-pADIs. RESULTS & CONCLUSIONS A total of 217 prescriptions of gefitinib combination therapy were enrolled. Among them， 28 prescriptions （12.90%）， involving a total of 28 patients， had 29 cases of PK-pADIs， with respiratory medicine prescriptions （22 prescriptions） being the main type. The combination drugs included proton pump inhibitors （13 cases）， strong cytochrome P450 3A4 （CYP3A4） inhibitors （7 cases）， H2 receptor antagonists （4 cases）， CYP3A4 inducers （3 cases）， and CYP2D6 substrates （2 cases）. The severity classifications for these interactions were severe， moderate， severe， moderate and moderate， respectively. Based on the above severity classification of PK-pADIs， four prescription review rules had been established as follows： when gefitinib was combined with acid-suppressing drugs， it should be subject to “manual review”； when gefitinib was combined with dexamethasone， metoprolol， or strong CYP3A4 inhibitors， an “alert” should be triggered， and the physician should be informed via an alert box to strengthen the monitoring of relevant indicators. Clinical pharmacists need to conduct in-depth training on knowledge related to gefitinib drug interactions in key clinical departments such as respiratory medicine. They should strengthen the monitoring and guidance of rational drug use for patients who are on long-term gefitinib therapy， and promptly identify and intervene in PK-pADIs， thereby enhancing the rationality， safety， and effectiveness of clinical drug use.

Background The widespread use of herbicides has led to environmental contamination and has implications for human health. The liver is an important organ for the detoxification of environmental pollutants; however, studies on the association between herbicide exposure and liver function are limited. Objectives To investigate the association between baseline serum herbicide levels and changes in liver enzyme levels and liver enzyme abnormalities over a 5-year period in middle-aged and older adults. Methods This study was based on a nested case-control population of type 2 diabetes established in the Dongfeng-Tongji cohort, with a total of 1388 subjects included in this study and followed up for 5 years. Epidemiological data were collected through questionnaires, and baseline serum concentrations of three herbicides (metolachlor, propham, and acetochlor) were measured by gas chromatography-triple quadrupole mass spectrometry. Serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels were detected at baseline and follow-up visits. The associations between baseline serum herbicide levels and changes in AST and ALT over 5 years were assessed using linear regression models with herbicide levels categorized into quartiles, adjusting for age, sex, education level, smoking status, drinking status, physical activity, body mass index, and new-onset type 2 diabetes occurred during follow-up. The relationship between baseline serum herbicide levels and the risk of liver enzyme abnormalities during follow-up was further analyzed using logistic regression models. Results The positive rates of metolachlor, propham, and acetochlor were all higher than 80%, and their spiked rates of recovery ranged from 73.46% to 106.77%. The mean ± standard deviation of the age of subjects at baseline was (62.7±7.6) years, with 34.1% being male. The median serum levels of metolachlor, propham, and acetochlor at baseline were 0.05, 0.16, and 0.03 ng·mL⁻¹, respectively. There was no significant difference in baseline serum herbicide levels between the normal and abnormal liver enzyme groups at follow-up (P >0.05). The baseline liver enzyme levels and the changes in AST and ALT over 5 years in those who developed abnormal liver enzymes were significantly higher than those in the normal liver enzyme group (P <0.05). The linear regression analysis showed that the changes in AST increased progressively over 5 years in the second, third, and fourth quartiles of propham compared to the lowest quartile group (the second quartile: b=1.49, 95%CI: 0.10, 2.87; the third quartile: b=1.52, 95%CI: 0.14, 2.90; the fourth quartile: b=1.69, 95%CI: 0.31, 3.08; P <0.05). The associations of serum metolachlor and acetochlor with changes in AST were not significant. Additionally, no significant relationships were found between the three serum herbicides and the changes in ALT over 5 years or the risk of liver enzyme abnormalities. Conclusion Serum propham levels in middle-aged and older adults are positively associated with changes in liver enzyme AST, which may have an effect on liver function. More studies are needed to provide scientific evidence for the association between herbicide exposure and liver function.