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.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

OBJECTIVE: To explore prevalence, incidence and possible factors of immediate herniated discs after posterior cervical expansive open-door laminoplasty (EODL). METHODS: Totally 29 patients with cervical spinal stenosis and intervertebral disc herniation who underwent EODL from October 2020 to December 2021 were collected, including 24 males and 5 females, aged from 43 to 81 years old with an average of (61.3±9.0) years old;the courses of disease ranged from 1 to 120 months with an average of (36.4±37.0) months. Three or more intervertebral discs on C₃-C₇ were observed. The clinical efficacy was evaluated according to Japanese Orthopaedic Association (JOA) score before operation, 3 days and 1, 3, 6 and 12 months after operation, respectively. The changes of herniated disc before and after operation were measured by multipoint area method and two-dimensional distance method, and incidence and percentage of herniated disc regression were further calculated. Cervical imaging parameters such as Cobb angle (C₃-C₇), intervertebral angle, T₁ slope (T₁S), spinal canal sagittal diameter, K-line angle, dural sac sagittal diameter were measured and compared before and after operation. Pearson correlation was used to analyze correlation between cervical sagittal imaging parameters and disc herniation changes before and after operation. RESULTS: All patients obtained grade A wound healing, and 14 of them were followed up for 3(1.00, 5.25) months. There were no immediate or long-term postoperative complications. Totally 101 herniated intervertebral discs were measured, of which 79 regression numbers were obtained by area measurement. The number of intervertebral disc regressions by distance measurement was 77. There was no statistically significant difference in Cobb angle, intervertebral angle, T₁S and K-line angle of C₃-C₇ (P>0.05), however, there were statistically significant differences in sagittal diameter of spinal canal, sagittal diameter of dural sac, and JOA score before and after operation(P<0.05). The regression ratio of disc herniation ranged from 5% to 50%, and regression ratio of disc herniation was greater than 25% in 45.57%(36/79). Disc herniation in C_4,5 was positively correlated with sagittal plane diameter in C₅(r=0.423, P=0.028). There was a negative correlation between changes of C_3,4 and C_3,4 intervertebral angle (r=-0.450, P=0.041). The improvement rate of cervical JOA score immediately after operation was (59.54±15.07) %, and postoperative follow-up improved to (76.57±14.66) %. CONCLUSION Herniated disc regression immediately after EODL is a common occurrence, and EODL should be selected as far as possible under the premise of satisfying surgical indications. The regression of disc herniation is positively correlated with spinal canal sagittal diameter, and spinal canal should be enlarged as far as possible in the appropriate scope during EODL, so as to create more opportunities and conditions for disc regression and achieve better clinical results.
Humans ; Female ; Male ; Intervertebral Disc Displacement/diagnostic imaging* ; Spinal Stenosis/diagnostic imaging* ; Laminoplasty/methods* ; Middle Aged ; Aged ; Cervical Vertebrae/diagnostic imaging* ; Adult ; Aged, 80 and over ; Intervertebral Disc/surgery*

OBJECTIVE: To investigate the prognostic value of peripheral blood absolute monocyte count(AMC) in non-severe aplastic anaemia(NSAA) patients. METHODS: 178 patients with NSAA who attended the Affiliated Hospital of Xuzhou Medical University from April 2008 to September 2020 were retrospectively analyzed, and the optimal cut-off value of peripheral blood AMC was determined by the receiver operating characteristic curve of the subjects, and they were divided into low AMC group (48 patients) and normal AMC group (130 patients), and the differences in clinical characteristics between the two groups were compared. Overall survival(OS) and progression-free survival(PFS) were analyzed by Kaplan-Meier. Univariate and multivariate Cox regression analysis were used to determine the independent prognostic value of AMC. RESULTS: Among 178 NSAA patients, 105(59.0%) were male and 73(41.0%) were female, with a median age of 31(18-87) years old, a median follow-up time of 58 months (range: 6 months-175 months), and a median AMC of 0.15×10⁹/L ［range: (0.01-0.59)×10⁹/L)］. The proportion of granulocytes (27.5% vs 36.0%, P < 0.05), and the proportion of mature monocytes (1% vs 2%, P < 0.05) in the low AMC group were lower than that in the normal AMC group; the proportion of mature lymphocytes in the low AMC group was higher than that in the normal AMC group (54% vs 50%, P < 0.05). However, there was no significantly different in the proportion of erythropoietic cells and stages of the erythropoietic cells between the two groups ( P >0.05). CR (27.7% vs 10.4%) and ORR (75.4% vs 56.3%) in the normal AMC group were higher than that in the low AMC group. Compared with patients in the low AMC group, AA patients in the normal AMC had better 5-year OS (98.5% vs 86.9%, P < 0.01), and the 5-year PFS (86.0% vs 58.9%, P < 0.01). Also, the 10-year survival rate of patients in the normal AMC group was higher than that in the low AMC group (98.5% vs 60.5%,P < 0.01). Univariate analysis showed that age, reticulocyte count, AMC<0.1×10⁹/L and the proportion of bone marrow mature monocytes were related with patients survival. Multivariate Cox regression analysis showed that monocyte count reduction was not an independent poor prognostic factor in NSAA patients （HR =4.474，95%CI ：0.508-44.390； P =0.172）. CONCLUSION Low AMC level at initial diagnosis is not an independent prognostic factor for NSAA patients, but still suggest potential prognostic value of AMC.
Humans ; Anemia, Aplastic/diagnosis* ; Female ; Male ; Prognosis ; Monocytes ; Adult ; Middle Aged ; Retrospective Studies ; Adolescent ; Aged ; Young Adult ; Aged, 80 and over ; Leukocyte Count

Mycophenolic acid (MPA), the active moiety of both mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), serves as a primary immunosuppressant for maintaining solid organ transplants. Therapeutic drug monitoring (TDM) enhances treatment outcomes through tailored approaches. This study aimed to develop an evidence-based guideline for MPA TDM, facilitating its rational application in clinical settings. The guideline plan was drawn from the Institute of Medicine and World Health Organization (WHO) guidelines. Using the Delphi method, clinical questions and outcome indicators were generated. Systematic reviews, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) evidence quality evaluations, expert opinions, and patient values guided evidence-based suggestions for the guideline. External reviews further refined the recommendations. The guideline for the TDM of MPA (IPGRP-2020CN099) consists of four sections and 16 recommendations encompassing target populations, monitoring strategies, dosage regimens, and influencing factors. High-risk populations, timing of TDM, area under the curve (AUC) versus trough concentration (C₀), target concentration ranges, monitoring frequency, and analytical methods are addressed. Formulation-specific recommendations, initial dosage regimens, populations with unique considerations, pharmacokinetic-informed dosing, body weight factors, pharmacogenetics, and drug‍-‍drug interactions are covered. The evidence-based guideline offers a comprehensive recommendation for solid organ transplant recipients undergoing MPA therapy, promoting standardization of MPA TDM, and enhancing treatment efficacy and safety.
Mycophenolic Acid/administration & dosage* ; Drug Monitoring/methods* ; Humans ; Organ Transplantation ; Immunosuppressive Agents/administration & dosage* ; Delphi Technique