ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

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.

People frequently struggle to juggle their work, family, and social life in today’s fast-paced environment, which can leave them exhausted and worn out. The development of technologies for detecting fatigue while driving is an important field of research since driving when fatigued poses concerns to road safety. In order to throw light on the most recent advancements in this field of research, this paper provides an extensive review of fatigue driving detection approaches based on electroencephalography (EEG) data. The process of fatigue driving detection based on EEG signals encompasses signal acquisition, preprocessing, feature extraction, and classification. Each step plays a crucial role in accurately identifying driver fatigue. In this review, we delve into the signal acquisition techniques, including the use of portable EEG devices worn on the scalp that capture brain signals in real-time. Preprocessing techniques, such as artifact removal, filtering, and segmentation, are explored to ensure that the extracted EEG signals are of high quality and suitable for subsequent analysis. A crucial stage in the fatigue driving detection process is feature extraction, which entails taking pertinent data out of the EEG signals and using it to distinguish between tired and non-fatigued states. We give a thorough rundown of several feature extraction techniques, such as topology features, frequency-domain analysis, and time-domain analysis. Techniques for frequency-domain analysis, such wavelet transform and power spectral density, allow the identification of particular frequency bands linked to weariness. Temporal patterns in the EEG signals are captured by time-domain features such autoregressive modeling and statistical moments. Furthermore, topological characteristics like brain area connection and synchronization provide light on how the brain’s functional network alters with weariness. Furthermore, the review includes an analysis of different classifiers used in fatigue driving detection, such as support vector machine (SVM), artificial neural network (ANN), and Bayesian classifier. We discuss the advantages and limitations of each classifier, along with their applications in EEG-based fatigue driving detection. Evaluation metrics and performance assessment are crucial aspects of any detection system. We discuss the commonly used evaluation criteria, including accuracy, sensitivity, specificity, and receiver operating characteristic (ROC) curves. Comparative analyses of existing models are conducted, highlighting their strengths and weaknesses. Additionally, we emphasize the need for a standardized data marking protocol and an increased number of test subjects to enhance the robustness and generalizability of fatigue driving detection models. The review also discusses the challenges and potential solutions in EEG-based fatigue driving detection. These challenges include variability in EEG signals across individuals, environmental factors, and the influence of different driving scenarios. To address these challenges, we propose solutions such as personalized models, multi-modal data fusion, and real-time implementation strategies. In conclusion, this comprehensive review provides an extensive overview of the current state of fatigue driving detection based on EEG signals. It covers various aspects, including signal acquisition, preprocessing, feature extraction, classification, performance evaluation, and challenges. The review aims to serve as a valuable resource for researchers, engineers, and practitioners in the field of driving safety, facilitating further advancements in fatigue detection technologies and ultimately enhancing road safety.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective: To understand the current status of diagnosis and treatment of chronic lymphocytic leukemia (CLL) /small lymphocytic lymphoma (SLL) among hematologists, oncologists, and lymphoma physicians from hospitals of different levels in China. Methods: This multicenter questionnaire survey was conducted from March 2021 to July 2021 and included 1,000 eligible physicians. A combination of face-to-face interviews and online questionnaire surveys was used. A standardized questionnaire regarding the composition of patients treated for CLL/SLL, disease diagnosis and prognosis evaluation, concomitant diseases, organ function evaluation, treatment selection, and Bruton tyrosine kinase (BTK) inhibitor was used. Results: ①The interviewed physicians stated that the proportion of male patients treated for CLL/SLL is higher than that of females, and the age is mainly concentrated in 61-70 years old. ②Most of the interviewed physicians conducted tests, such as bone marrow biopsies and immunohistochemistry, for patient diagnosis, in addition to the blood test. ③Only 13.7% of the interviewed physicians fully grasped the initial treatment indications recommended by the existing guidelines. ④In terms of cognition of high-risk prognostic factors, physicians' knowledge of unmutated immunoglobulin heavy-chain variable and 11q- is far inferior to that of TP53 mutation and complex karyotype, which are two high-risk prognostic factors, and only 17.1% of the interviewed physicians fully mastered CLL International Prognostic Index scoring system. ⑤Among the first-line treatment strategy, BTK inhibitors are used for different types of patients, and physicians have formed a certain understanding that BTK inhibitors should be preferentially used in patients with high-risk factors and elderly patients, but the actual use of BTK inhibitors in different types of patients is not high (31.6%-46.0%). ⑥BTK inhibitors at a reduced dose in actual clinical treatment were used by 69.0% of the physicians, and 66.8% of the physicians had interrupted the BTK inhibitor for >12 days in actual clinical treatment. The use of BTK inhibitors is reduced or interrupted mainly because of adverse reactions, such as atrial fibrillation, severe bone marrow suppression, hemorrhage, and pulmonary infection, as well as patients' payment capacity and effective disease progression control. ⑦Some differences were found in the perceptions and behaviors of hematologists and oncologists regarding the prognostic assessment of CLL/SLL, the choice of treatment options, the clinical use of BTK inhibitors, etc. Conclusion: At present, a gap remains between the diagnosis and treatment of CLL/SLL among Chinese physicians compared with the recommendations in the guidelines regarding the diagnostic criteria, treatment indications, prognosis assessment, accompanying disease assessment, treatment strategy selection, and rational BTK inhibitor use, especially the proportion of dose reduction or BTK inhibitor discontinuation due to high adverse events.
Female ; Humans ; Male ; Aged ; Middle Aged ; Leukemia, Lymphocytic, Chronic, B-Cell/drug therapy* ; Prognosis ; Lymphoma, B-Cell ; Immunohistochemistry ; Immunoglobulin Heavy Chains/therapeutic use*

Humans ; COVID-19 ; Prone Position ; SARS-CoV-2 ; Patient Positioning

OBJECTIVETo prepare ligustrazine (TMPZ) ocular sustained-release implant, and investigate its in vitro drug release, pharmacokinetics in rabbit vitreum and in vitro correlation.

METHODLigustrazine ocular sustained-release implants were prepared by micro-twin conical screw mixers with hot-melting extrusion method, with polyactic-co-glycolic acid (PLGA) as the matrix. HPLC was adopted to determine the concentration in vitreum after ligustrazine was implanted in rabbit eyes, in order to examine its in vivo sustained-release behavior, and study the correlation between in vitro and in vivo.

RESULTLigustrazine implants were prepared with a drug-loading rate between 10% and 30%, which was in conformity to the pharmacopoeia in terms of the content uniformity. Its in vitro release was in conformity to the zero-order release model. With PLGA 5050, 2. 5A as a vector, ligustrazine implants with a drug-loading rate of 30% could slowly release drug for more than 3 weeks, indicating a good correlation between in vitro and in vivo release.

CONCLUSIONLigustrazine ocular implants prepared with hot-melting extrusion method is practicable. Ligustrazine ocular implants release drug smoothly in rabbit vitreous vitreums, suggesting good sustained-release effect.

Animals ; Biological Availability ; Drug Implants ; Eye ; Female ; Male ; Polyglycolic Acid ; chemistry ; Pyrazines ; administration & dosage ; chemistry ; pharmacokinetics ; Rabbits ; Vitreous Body

BACKGROUNDNeuroblastoma (NB) is one of the most common malignant solid tumors of childhood. It is still not clear whether the apoptosis of tumor cells or the non-tumor cells contributes to the increase of concentration of cytochrome c (Cyt c) in the serum of the cancer patients. The aim of this research was to identify the source of the Cyt c in the serum when the tumor grows up by subcutaneous inoculation of human NB cells into nude mice.

METHODSWe subcutaneously inoculated human NB cells (KP-N-NS) into nude mice and collected the sera of tumor-bearing mice (n = 14) and control mice (n = 25) 4 weeks later in order to screen for and identify differentially expressed proteins in the serum. Differentially expressed proteins in the serum were screened by surface-enhanced laser desorption/ionization-time-of-flight (SELDI-TOF) mass spectrometry.

RESULTSThe relative intensity of a protein having a mass-to-charge ratio (m/z) of 11 609 was 3338.37 ± 3410.85 in the tumor group and 59.84 ± 40.74 in the control group, indicating that the expression level of this protein in the tumor group was 55.8 times higher than that in the control group. Serum proteins were separated and purified by high-performance liquid chromatography (HPLC). Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) was performed to produce peptide mass fingerprints (PMFs). Spectrum analysis and a database search revealed that the highly expressed protein (m/z = 11 605.4) from the serum of tumor-bearing mice was the mouse Cyt c.

CONCLUSIONSIncreased concentration of Cyt c in the serum of tumor-bearing nude mice might be partially attributed to the secretion of this protein by non-tumor cells.

Animals ; Apoptosis ; physiology ; Cell Line, Tumor ; Chromatography, High Pressure Liquid ; Cytochromes c ; blood ; Female ; Humans ; Mice ; Mice, Nude ; Neuroblastoma ; blood ; Tandem Mass Spectrometry ; Xenograft Model Antitumor Assays

This study was designed to compare the curative effect, prognosis and safety of different preconditioning regimens for patients who received autologous hematopoietic stem cell transplantation (AHSCT) for malignant lymphoma (ML). The clinical data of 100 ML patients (Sep 1992 to Aug 2010 in 307 Hospital) were retrospectively analyzed, and were divided into two groups by different preconditioning regimens: the high-dose chemotherapy preconditioning group and high-dose chemotherapy/radiotherapy preconditioning group. The overall survival (OS) rate, progress free survival (PFS) rate and adverse effect were analyzed. The results showed that until Feb 2011, the median follow-up was 33.5 months. All patients were engrafted and their hematopoiesis was reconstituted. The median time of WBC recovery up to > 1.0×1.0(9)/L in high-dose chemotherapy preconditioning group and high-dose chemotherapy/radiotherapy preconditioning group were (6.0 ± 0.4) d and (8.2 ± 0.4) d, platelet up to > 20.0×1.0(9)/L in two groups were (7.1 ± 0.8) d and (11.4 ± 2.5) d (P < 0.05). The 3-year OS rate of the two groups were 67.3% and 68.9%. 5-year OS rates of two groups were 62.8% and 60.6%, 10-year OS rates of two groups were 57.6% and 56.2% respectively; 3-year PFS of two group were 63.6% and 63.2%, 5-year of two group were 59.4% and 58.3%, 10-year of two group were 50.8% and 55.3% respectively (P > 0.05). Meanwhile, the incidence of fever, infection, bleeding, secondary cancer between two groups was not significant different (P > 0.05). It is concluded that the hematopoietic reconstitution of high-dose chemotherapy/radiotherapy preconditioning group is later than that of high-dose chemotherapy preconditioning group. However, there is no significant difference in curative effect and prognosis between the two groups.
Adolescent ; Adult ; Aged ; Child ; Combined Modality Therapy ; Female ; Hematopoietic Stem Cell Transplantation ; Humans ; Lymphoma ; surgery ; therapy ; Male ; Middle Aged ; Prognosis ; Retrospective Studies ; Transplantation Conditioning ; methods ; Transplantation, Autologous ; Young Adult

OBJECTIVETo examine the effect of RhoA/Rho kinase signal pathway on TGF-beta1-induced phenotypic differentiation of human dermal fibroblasts.

METHODSThe 4th generation of primary cultured human dermal fibroblasts were stimulated with TGF-beta1, (10 ng/ml). The expression of alpha-SMA was detected after treatment with TGF-beta1, for 0, 3, 6, and 24 h. The expression of alpha-SMA was also detected after treatment with different concentration of TGF-beta1 (0, 2, 10, 50 ng/ml). Then the human dermal fibroblasts (4th generation) were stimulated with TGF-beta1, (10 ng/ml) after being treated with the RhoA/Rho kinase signaling pathway inhibitor Y-27632 (10 umol/ml). The fibroblasts were treated with nothing as sham control, or with Y-27632 (10 umol/L) only as negative control group, or with TGF-beta1 (10 ng/ml) only as positive control group. The expression of alpha-SMA was detected in all the groups. Protein expression was analyzed with ANOVA statistical method.

RESULTSalpha-SMA expression in fibroblasts with 10 ng/ml TGF-beta1 stimulation for 0, 3, 6, 24 h was 1.0, 1.9 0.2, 2.1 +/- 0. 1, 3. 1 +/- 0.1, respectively. Alpha-SMA expression in 24 h group was significantly higher than that in other three groups (n = 4, P < 0.05). alpha-SMA expression in human dermal fibroblasts after stimulation with different concentration of TGF-beta1 (0, 2, 10, 50 ng/ml) was 1.0, 1.4 +/- 0.2, 3.2 + 0.1, 3.1 +/- 0.2, respectively. alpha-SMA expression in 10 ng/ ml group was significantly higher than that in 2 ng/ml group and control group (n = 4, P < 0.05). There was no statistical difference in alpha-SMA expression between 10 ng/ml group and 50 ng/ml group (n = 4, P > 0.05). With both Y-27632 (10 micromol/L) and TGF-beta1 stimulation, the cell phenotype differentiation was inhibited. Alpha-SMA expression in experimental group (1.2 +/- 0.2) was significantly reduced, when compared with that in positive control group (2.9 +/- 0.1) (n = 5, P < 0.05). There was no significant difference (n = 5, P > 0.05) in alpha-SMA expression between control group (1.0) and negative control group (1.1 +/- 0.1).

CONCLUSIONSRhoA/Rho kinase signaling pathway should be involved in TGF-beta1-induced phenotypic differentiation of human dermal fibroblasts.

Actins ; metabolism ; Adolescent ; Cell Differentiation ; Cells, Cultured ; Fibroblasts ; cytology ; Humans ; Male ; Signal Transduction ; Skin ; cytology ; Transforming Growth Factor beta1 ; pharmacology ; rho-Associated Kinases ; metabolism ; rhoA GTP-Binding Protein ; metabolism