ObjectiveThe present study aimed to investigate alterations in white matter microstructure and spontaneous neural activity in male college smokers, and to further explore their associations with nicotine dependence. Given that adolescence and early adulthood represent critical periods for brain maturation, particularly for white matter development, understanding the neural correlates of smoking behavior during this stage is of substantial importance for both neuroscience and public health. MethodsA total of 115 male undergraduate students were initially recruited for this study. After quality control and exclusion procedures, 52 male college smokers and 42 demographically matched healthy non-smokers were included in the final analysis. All participants underwent multimodal magnetic resonance imaging (MRI), including diffusion tensor imaging (DTI) and resting-state functional MRI (rs-fMRI). White matter fiber tracts were reconstructed using the automated fiber quantification (AFQ) method, which enables precise identification and quantification of major fiber bundles. Eighteen major white matter tracts were segmented for each participant. Along the core trajectory of each tract, 100 equidistant nodes were sampled. Fractional anisotropy (FA) was calculated at each node to assess white matter microstructural integrity, while amplitude of low-frequency fluctuation (ALFF) was computed to evaluate spontaneous neural activity within white matter tracts. Between-group differences in FA and ALFF were assessed using two-sample t-tests, with appropriate corrections applied for multiple comparisons. Furthermore, Pearson correlation analyses were conducted to examine the relationships between imaging-derived metrics (FA and ALFF values in regions showing significant group differences) and nicotine dependence severity, as measured by the Fagerström test for nicotine dependence (FTND). ResultsCompared with healthy non-smokers, male college smokers exhibited significantly increased FA values in several white matter tracts, including the left thalamic radiation, right corticospinal tract, forceps major of the corpus callosum, left uncinate fasciculus, and right arcuate fasciculus. These findings suggest altered microstructural organization or increased directional coherence within these pathways. In addition, smokers demonstrated significantly elevated ALFF values in the forceps major, right uncinate fasciculus, and left arcuate fasciculus, indicating enhanced spontaneous neural activity in these white matter regions. Correlation analyses revealed that FA values in the left thalamic radiation and right corticospinal tract were negatively correlated with FTND scores, suggesting that higher levels of nicotine dependence were associated with reduced microstructural integrity or altered fiber organization in these regions. In contrast, ALFF values in the forceps major and right uncinate fasciculus were positively correlated with FTND scores, indicating that greater nicotine dependence was associated with increased spontaneous neural activity in specific white matter pathways. ConclusionThe present study provides evidence that male college smokers exhibit distinct alterations in both white matter microstructure and functional activity. These abnormalities are not uniformly distributed but rather localized to specific fiber tracts implicated in sensorimotor processing, interhemispheric communication, and higher-order cognitive and emotional regulation. Importantly, the observed associations between imaging metrics and nicotine dependence severity suggest that these structural and functional alterations may reflect neurobiological mechanisms underlying addiction. The combination of AFQ-based tract profiling and multimodal MRI offers a sensitive approach for detecting subtle changes along white matter pathways, highlighting its potential utility in identifying neuroimaging biomarkers of nicotine dependence. Overall, these findings indicate that smoking during early adulthood may disrupt ongoing white matter maturation, potentially leading to long-term consequences for brain function. This study provides novel insights into the neural basis of nicotine dependence and underscores the importance of early intervention and prevention strategies targeting young smokers.

Objective:To explore the evaluation value of blood routine derived indicators[derived neutrophil to lymphocyte ratio(dNLR),red blood cell distribution width to platelet ratio(RPR)]combine with serum C-reactive protein(CRP)and procalcitonin(PCT)detection for the clinical outcomes of children with Mycoplasma pneumoniae pneumonia(MPP).Methods:149 children with MPP who were admitted to our hospital from April 2022 to August 2024 were included,they were divided into good prognosis and poor prognosis groups based on their clinical outcomes 28 d after admission.The blood routine derived indicators,serum CRP,and PCT levels between the good prognosis group and the poor prognosis group were compared.The influencing factors of clinical outcomes in children with MPP were analyzed by Multiple logistic regression analysis,the value of blood routine derived indicators,serum CRP,and PCT testing alone and in combination to evaluate the clinical outcomes of children with MPP were analyzed by receiver operating characteristic(ROC)curves.Results:Among 149 children with MPP,113 had good prognosis and 36 had poor prognosis 28 d after admission,with a poor prognosis incidence rate of 24.16％(36/149).dNLR,RPR,CRP,and PCT levels in the poor prognosis group were higher than those in the good prognosis group(P＜0.05).Univariate analysis showed that,the clinical outcome of children with MPP was related to pleural thickening,pleural effusion,severity disease and peak body temperature(P＜0.05).Multivariate Logistic regression analysis showed:Pleural thickening,pleural effusion,severity disease was severe,elevated dNLR,elevated RPR,elevated CRP and elevated PCT were risk factors for poor prognosis in children with MPP(P＜0.05).The area under the Curve(AUC)of dNLR,RPR,CRP and PCT combined to predict the prognosis of children with MPP was higher than that evaluated by the four indicators alone.Conclusion:Pleural thickening,pleural effusion,severe disease severity,elevated dNLR,elevated RPR,elevated CRP and elevated PCT are risk factors for poor prognosis in children with MPP.Moreover,the combined evaluate value of dNLR,RPR,CRP,and PCT is relatively high.

Objective To observe the value of three-dimensional ultrasound combined with microvascular flow imaging for prenatal diagnosis of fetal intracranial anomalies.Methods Totally 118 fetuses with intracranial anomalies diagnosed through cranial MRI/induced labor specimen dissection who underwent prenatal ultrasound examination were retrospectively enrolled.Two-dimensional,three-dimensional ultrasound and microvascular flow imaging manifestations of fetal intracranial anomalies were observed,and the accuracy of three-dimensional ultrasound combined with microvascular flow imaging for prenatal diagnosis of fetal intracranial anomalies was analyzed.Results The accuracy of three-dimensional ultrasound combined with microvascular flow imaging for prenatal diagnosis of fetal intracranial anomalies was 93.22％(110/118),of isolated and non-isolated intracranial anomalies was 97.47％(77/79)and 84.62％(33/39),respectively.Six fetuses were missed diagnosis of malformations of cortical development(1 fetus of tuberous sclerosis,4 of abnormal morphology of the sulci gyrus and 1 of schizencephaly)and 1 fetus of intracranial softening lesion,while posterior fossa arachnoid cyst in 1 fetus was misdiagnosed as mega cisterna magna.Conclusion The accuracy of three-dimensional ultrasound combined with microvascular flow imaging for prenatal diagnosis of fetal intracranial anomalies was relatively high.

Objective:To explore the evaluation value of blood routine derived indicators[derived neutrophil to lymphocyte ratio(dNLR),red blood cell distribution width to platelet ratio(RPR)]combine with serum C-reactive protein(CRP)and procalcitonin(PCT)detection for the clinical outcomes of children with Mycoplasma pneumoniae pneumonia(MPP).Methods:149 children with MPP who were admitted to our hospital from April 2022 to August 2024 were included,they were divided into good prognosis and poor prognosis groups based on their clinical outcomes 28 d after admission.The blood routine derived indicators,serum CRP,and PCT levels between the good prognosis group and the poor prognosis group were compared.The influencing factors of clinical outcomes in children with MPP were analyzed by Multiple logistic regression analysis,the value of blood routine derived indicators,serum CRP,and PCT testing alone and in combination to evaluate the clinical outcomes of children with MPP were analyzed by receiver operating characteristic(ROC)curves.Results:Among 149 children with MPP,113 had good prognosis and 36 had poor prognosis 28 d after admission,with a poor prognosis incidence rate of 24.16％(36/149).dNLR,RPR,CRP,and PCT levels in the poor prognosis group were higher than those in the good prognosis group(P＜0.05).Univariate analysis showed that,the clinical outcome of children with MPP was related to pleural thickening,pleural effusion,severity disease and peak body temperature(P＜0.05).Multivariate Logistic regression analysis showed:Pleural thickening,pleural effusion,severity disease was severe,elevated dNLR,elevated RPR,elevated CRP and elevated PCT were risk factors for poor prognosis in children with MPP(P＜0.05).The area under the Curve(AUC)of dNLR,RPR,CRP and PCT combined to predict the prognosis of children with MPP was higher than that evaluated by the four indicators alone.Conclusion:Pleural thickening,pleural effusion,severe disease severity,elevated dNLR,elevated RPR,elevated CRP and elevated PCT are risk factors for poor prognosis in children with MPP.Moreover,the combined evaluate value of dNLR,RPR,CRP,and PCT is relatively high.

A 20-year-old male patient with T-lymphoblastic lymphoma/leukemia received 9/10 human leukocyte antigen-compatible unrelated peripheral blood stem cell transplantation. He was transplanted with 5.91×10 8 mononuclear cells/kg and 2.88×10 6 CD34 + cells/kg, and neutrophil engraftment was obtained at +11 days and platelet engraftment at +9 days. After transplantation, he presented with repeatedly increased serum creatinine levels, BK virus (BKV) -associated hemorrhagic cystitis, and BKV viremia. BK virus nephropathy was diagnosed based on renal biopsy and metagenomic next-generation sequencing. After adjusting the immunosuppressant, intravenous immunoglobulin, and donor lymphocyte infusion treatment, the patient’s renal function deteriorated progressively, and he eventually died of multiple organ failure at +289 days.

The writing of pharmacist-managed clinics documents （hereinafter referred to as “outpatient medication record”） is a necessary part of pharmacist-managed clinics service. Outpatient medication record is an important carrier to reflect the quality of pharmacist-managed clinics service. The Chinese Hospital Association Pharmaceutical Specialized Committee was entrusted by the Pharmaceutical Administration Department of the National Health Commission to lead the formulation of the Guidelines for the Pharmacist-managed Clinics Service and Document Writing and Usage （Reference） （hereinafter referred to as Guidelines） according to the compilation method of group standards and the technical route of “documentation combing→framework establishment→draft writing→opinion collection→Guidelines formation”. The Guidelines standardizes the basic requirements of pharmacist-managed clinics record management and the basic content of record， and provides a general template and two specialized templates including pregnant and lactating pharmacist-managed clinics record template and cough and asthma pharmacist-managed clinics record template， which provides a reference for medical institutions to write pharmacist-managed clinics record. This paper introduces the formulation process of Guidelines and analyzes the key contents of Guidelines， which is helpful for the application practice of Guidelines and further improves the quality of pharmacist-managed clinics work.

Patients suffering from nerve injury often experience exacerbated pain responses and complain of memory deficits. The dorsal hippocampus (dHPC), a well-defined region responsible for learning and memory, displays maladaptive plasticity upon injury, which is assumed to underlie pain hypersensitivity and cognitive deficits. However, much attention has thus far been paid to intracellular mechanisms of plasticity rather than extracellular alterations that might trigger and facilitate intracellular changes. Emerging evidence has shown that nerve injury alters the microarchitecture of the extracellular matrix (ECM) and decreases ECM rigidity in the dHPC. Despite this, it remains elusive which element of the ECM in the dHPC is affected and how it contributes to neuropathic pain and comorbid cognitive deficits. Laminin, a key element of the ECM, consists of α-, β-, and γ-chains and has been implicated in several pathophysiological processes. Here, we showed that peripheral nerve injury downregulates laminin β1 (LAMB1) in the dHPC. Silencing of hippocampal LAMB1 exacerbates pain sensitivity and induces cognitive dysfunction. Further mechanistic analysis revealed that loss of hippocampal LAMB1 causes dysregulated Src/NR2A signaling cascades via interaction with integrin β1, leading to decreased Ca²⁺ levels in pyramidal neurons, which in turn orchestrates structural and functional plasticity and eventually results in exaggerated pain responses and cognitive deficits. In this study, we shed new light on the functional capability of hippocampal ECM LAMB1 in the modulation of neuropathic pain and comorbid cognitive deficits, and reveal a mechanism that conveys extracellular alterations to intracellular plasticity. Moreover, we identified hippocampal LAMB1/integrin β1 signaling as a potential therapeutic target for the treatment of neuropathic pain and related memory loss.
Animals ; Laminin/genetics* ; Hippocampus/metabolism* ; Neuralgia/metabolism* ; Cognitive Dysfunction/etiology* ; Male ; Peripheral Nerve Injuries/metabolism* ; Extracellular Matrix/metabolism* ; Integrin beta1/metabolism* ; Pyramidal Cells/metabolism* ; Signal Transduction

Objective:To analyze the clinical characteristics and treatment outcomes of central nervous system（CNS）mucormycosis following allogeneic hematopoietic stem cell transplantation（allo-HSCT）.Methods:Clinical data of 6 patients diagnosed with CNS mucormycosis after allo-HSCT at Henan Cancer Hospital between January 2020 and December 2024 were retrospectively collected. The patients' clinical manifestations，laboratory findings，imaging features，treatment regimens，and outcomes were analyzed.Results:The incidence of CNS mucormycosis post-allo-HSCT was 0.7%（6/851）. The main clinical manifestations included impaired consciousness（5 cases），convulsions（3 cases），headache（2 cases），hemiplegia（1 case），ptosis（1 case），and mydriasis with sluggish light reflex and incomplete eye closure（1 case）. The median time from transplantation to the onset of neurological symptoms was 138 days（94-572 days）. Metagenomic next-generation sequencing（mNGS）of cerebrospinal fluid identified Rhizopus spp.（2 cases）， Rhizomucor spp.（2 cases），and Absidia spp.（2 cases）. Cranial MRI performed in five patients revealed multiple mass or patchy lesions in various regions；one patient underwent cranial CT，which showed patchy hypodense lesions in multiple areas. All patients received antifungal therapy，with 2 cases receiving combined intrathecal injection of amphotericin B liposomes；five patients died，and one survived. Conclusions:CNS mucormycosis is a rare but severe complication after allo-HSCT. Its clinical and radiological features are non-specific，posing diagnostic challenges. Intravenous administration of liposomal amphotericin B at full dosage，combined with intrathecal injection，may improve treatment efficacy.

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.