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 investigate the distribution of CGG repeat numbers in the FMR1 gene among reproductive-age women in China, providing data reference for carrier screening and genetic counseling of Fragile X syndrome. Methods:This cross-sectional study recruited 16 610 reproductive-age women from 12 medical institutions between July 2022 and October 2023. Peripheral venous blood samples (3 mL) were collected, and genomic DNA was extracted. The number of CGG repeats in the FMR1 gene was determined using the triplet-primed polymerase chain reaction (TP-PCR) combined with capillary electrophoresis technology. Statistical analyses were performed to assess the prevalence and distribution of CGG repeat expansions. Results:Among 16 610 women of childbearing age, 5 684 (34.220%) women had the same number of CGG repeats in the two alleles of FMR1 gene, and 10 926 (65.780%) women had different numbers of repeats in the two alleles. Among the 33 220 FMR1 alleles in 16 610 women of reproductive age, the most common CGG repeat numbers were 29 [48.645% (16 160/33 220)] and 30 [26.276% (8 729/33 220)], while the most frequent CGG genotype was CGG 29/29 [24.726% (4 107/16 610)]. The CGG repeat numbers of FMR1 gene were normal in 16 498 women (99.326%). Among the 112 women (0.674%) with CGG repeat abnormities, 96 (0.578%) women were classified as intermediate carriers, 15 (0.090%) as premutation carriers, and 1 (0.006%) as a full mutation carrier, whose CGG genotype was (36, >200). Conclusion:In the general reproductive-age female population in China, the normal CGG repeat numbers of the FMR1 gene account for 99.326%, while the intermediate carrier rate is 0.578%, and the combined carrier rate of the premutation and full mutation types is 0.096%.

Objective To investigate the electroencephalography(EEG)signal characteristics in patients with neuropathic pain(NP)associated with spinal cord injury(SCI).Methods A total of 90 patients with SCI from January,2018 to November,2023 were selected from the EEG database of the Department of Rehabilitation Medicine,Xijing Hospital,and divided into NP group(n=46)and non-NP group(n=44)according to their symptoms.The resting-state EEG power and reactivity to eye-opening were compared between two groups.Results Compared with non-NP group,EEG power increased in frontal lobe in α and β1 bands,central lobe in δ,θ,α1 and β1 bands,parietal lobe in α and β1 bands,temporal lobe in α and β1 bands,left occipital lobe in α2 band,and occipital lobe in α1 and β1 bands(|Z|>1.998,P<0.05)in NP group during eye-opening;during eye-closing,EEG power increased in prefrontal lobe in α1 and β1 bands,right frontal lobe in θ band,frontal lobe in α and β1 bands,left frontal lobe in β2 band,central lobe in δ,α1 and β1 bands,parietal lobe in α1 and β1 bands,left pari-etal lobe in α2 and β2 bands,right temporal lobe in θ band,temporal lobe in α and β bands,occipital lobe in α1 and β1 bands,and left occipital lobe in β2 band(|Z|>1.970,P<0.05);while the reactivity to eye-opening de-creased in right prefrontal lobe in β1 band,frontal lobe in θ,α and β bands,right central lobe in β1 band,parietal lobe in α1 and β1 bands,right parietal lobe in β2 band,right temporal lobe in δ and θ band,temporal lobe in α1 and β bands,left occipital lobe in α1 band,and occipital lobe in β1(|Z|>1.967,P<0.05).Conclusion Resting-state EEG power characteristically elevates in NP patients after SCI,and the reactivity to eye-open-ing reduces.

Objective To construct a quality control model for cervical liquid-based thin cell smears using two different artificial intelligence(AI)techniques and to compare the total use of the two methods to improve the level of quality control of cervical liquid-based thin cell smears through the assistance of hybrid AI.Methods In this study,105 cervical liquid-based thin cell smear samples were used.Convolutional neural network(CNN)algorithm and Transformer network algorithm were used as specific AI algorithms in the AI model.The labeled features included the number of cells in the slice,excessive red blood cells,excessive inflammatory cells,and air bubbles.The smear samples were pre-processed and digitized by smear,followed by image segmentation and feature extraction.Using the labeled feature data,machine learning models were trained and optimized.Statistical AI and physician QC results were analyzed by calculating KAPPA index,sensitivity,specificity,area under the curve(AUC),and other indexes for AI QC results.Results CNN algorithm QC results in normal smear,inflammatory background and bloody background were significantly different from the expert review QC results(P＜0.001).Transformer algorithm QC results were similar to the expert review results,with no statistical difference(P＞0.05).General practitioner QC results were statistically different from the expert review QC results in normal smear detection rate and bloody background(P＜0.001).CNN algorithm Kappa value was 0.567,which had medium consistency with expert review results.Transformer algorithm Kappa value was 0.890,with the best consistency with expert review results.General practitioner Kappa value was 0.675,which had better consistency with expert review results.Using the expert review results as a reference standard,the predictive efficacy of the Transformer algorithm and the general practitioners' QC results was evaluated,and the predictive efficacy of the Transformer algorithm was higher than that of the general practitioners in detecting hemorrhagic backgrounds and normal smears(inflammatory backgrounds:AUC=1.000;normal smears:AUC=0.768)(hemorrhagic backgrounds:AUC=0.849;normal smears:AUC=0.849;normal smear:AUC=0.500).Conclusion In this study,we found that the Transformer algorithm was effective in improving the quality control of cervical liquid-based thin-layer cell smears by assisting doctors to perform smear quality control scoring and improving the efficiency and accuracy of smear sample quality control.It can be used as a new quality control method for cervical cancer cytological screening and has potential clinical applications.

Objective:To investigate the distribution of CGG repeat numbers in the FMR1 gene among reproductive-age women in China, providing data reference for carrier screening and genetic counseling of Fragile X syndrome. Methods:This cross-sectional study recruited 16 610 reproductive-age women from 12 medical institutions between July 2022 and October 2023. Peripheral venous blood samples (3 mL) were collected, and genomic DNA was extracted. The number of CGG repeats in the FMR1 gene was determined using the triplet-primed polymerase chain reaction (TP-PCR) combined with capillary electrophoresis technology. Statistical analyses were performed to assess the prevalence and distribution of CGG repeat expansions. Results:Among 16 610 women of childbearing age, 5 684 (34.220%) women had the same number of CGG repeats in the two alleles of FMR1 gene, and 10 926 (65.780%) women had different numbers of repeats in the two alleles. Among the 33 220 FMR1 alleles in 16 610 women of reproductive age, the most common CGG repeat numbers were 29 [48.645% (16 160/33 220)] and 30 [26.276% (8 729/33 220)], while the most frequent CGG genotype was CGG 29/29 [24.726% (4 107/16 610)]. The CGG repeat numbers of FMR1 gene were normal in 16 498 women (99.326%). Among the 112 women (0.674%) with CGG repeat abnormities, 96 (0.578%) women were classified as intermediate carriers, 15 (0.090%) as premutation carriers, and 1 (0.006%) as a full mutation carrier, whose CGG genotype was (36, >200). Conclusion:In the general reproductive-age female population in China, the normal CGG repeat numbers of the FMR1 gene account for 99.326%, while the intermediate carrier rate is 0.578%, and the combined carrier rate of the premutation and full mutation types is 0.096%.

Objective:To explore the clinical efficacy of Wenshen Chushi Decoction combined with low intensity pulsed ultra-sound(LIPUS)on erectile dysfunction(ED)caused by renal deficiency and phlegm-dampness syndrome.Methods:One hundred and twenty ED patients were included from the Department of Andrology in the First Hospital of Hunan University of Traditional Chinese Medicine.The patients in control group were treated with Wenshen Chushi Decoction.While the patients in observation group were trea-ted with Wenshen Chushi Decoction combined with LIPUS for 8 consecutive weeks.After the treatment,the efficacy was evaluated using the International Index of Erectile Function-5(IIEF-5)score,Penile Flow Index(PFI),Traditional Chinese Medicine Syndrome Score,Self-Rating Depression Scale(SDS)score,and Self-Rating Anxiety Scale(SAS)score.Safety was also observed.And the ef-ficacy was followed up 4 weeks after the end of treatment.Results:Fifty-seven cases were enrolled into control group finally with 55 cases in the treatment group.After the treatment,all the patients in both of groups showed an improvement in IIEF-5 scores(P＜0.01).Compared with the control group(19.09±2.22),the IIEF-5 score in observation group(20.42±2.39)increased signifi-cantly(P＜0.01).After the treatment,the scores of PFI,TCM syndrome and SDS in both groups decreased(P＜0.01,P＜0.05,P＜0.01).Compared with the control group([3.77±1.21],[9.91±1.71]and[39.88±2.63]points),the observation group([2.92±1.08],[4.78±1.45],and[34.51±2.09]points)showed a more significant decrease(P＜0.01).There was no significant difference in total effective rate between the two groups(P＞0.05).During follow-up,the IIEF-5 scores of both groups of patients were higher than those before(P＜0.05,P＜0.01),and the observation group score was higher than that in the control group([17.15±3.37]vs[13.63±1.96],P＜0.01).No adverse reaction and abnormality of indicators occurred in both of two groups.Conclusion:Wenshen Chushi Decoction has a significant therapeutic effect on ED caused by renal deficiency and phlegm-dampness syndrome.It can not only improve the quality of erection,but also improve the physical and mental symptoms associated with ED,which makes therapeutic effect lasting longer.

Objective:To investigate the clinical characteristics of patients with multiple myeloma(MM)complicated by bone lesions and the risk factors associated with bone lesions.Methods:The clinical data of 294 newly diagnosed MM patients in Gansu Provincial Hospital from January 2017 to June 2021 were retrospectively analyzed.The patients were divided into the bone lesion group(154 cases)and the non-bone lesions group(140 cases)based on the presence of absence of bone lesions at diagnosis.The general data and laboratory parameters were compared between the two groups.The risk factors for bone lesions in MM patients were analyzed by logistic regression analysis,and the characteristic(ROC)curves were plotted to assess the predictive value of each risk factor for the occurrence of bone lesions in MM patients.Results:Compared to the non-bone lesion group,the bone lesion group had significantly higher serum calcium levels and significantly greater proportions of patients with Durie-Salmon(DS)stage Ⅲ,and bone pain(all P＜0.05).Logistic regression analysis showed that elevated serum calcium(OR=5.135,95％CI:1.931-13.653,P=0.001),DS stage Ⅲ(OR=1.841,95％CI:1.019-3.328,P=0.043),and bone pain(OR=8.208,95％CI:4.761-14.151,P＜0.001)were independent risk factors for bone lesions in MM patients.ROC curve analysis showed that serum calcium(AUC=0.619,95％CI:0.555-0.683,P＜0.001)and bone pain(AUC=0.743,95％CI:0.692-0.793,P＜0.001)had predictive value for bone lesions in MM patients.Conclusion:MM patients have a high incidence of bone lesions,and active monitoring and management of risk factors may improve treatment outcomes and prognosis.

Objective To investigate the electroencephalography(EEG)signal characteristics in patients with neuropathic pain(NP)associated with spinal cord injury(SCI).Methods A total of 90 patients with SCI from January,2018 to November,2023 were selected from the EEG database of the Department of Rehabilitation Medicine,Xijing Hospital,and divided into NP group(n=46)and non-NP group(n=44)according to their symptoms.The resting-state EEG power and reactivity to eye-opening were compared between two groups.Results Compared with non-NP group,EEG power increased in frontal lobe in α and β1 bands,central lobe in δ,θ,α1 and β1 bands,parietal lobe in α and β1 bands,temporal lobe in α and β1 bands,left occipital lobe in α2 band,and occipital lobe in α1 and β1 bands(|Z|>1.998,P<0.05)in NP group during eye-opening;during eye-closing,EEG power increased in prefrontal lobe in α1 and β1 bands,right frontal lobe in θ band,frontal lobe in α and β1 bands,left frontal lobe in β2 band,central lobe in δ,α1 and β1 bands,parietal lobe in α1 and β1 bands,left pari-etal lobe in α2 and β2 bands,right temporal lobe in θ band,temporal lobe in α and β bands,occipital lobe in α1 and β1 bands,and left occipital lobe in β2 band(|Z|>1.970,P<0.05);while the reactivity to eye-opening de-creased in right prefrontal lobe in β1 band,frontal lobe in θ,α and β bands,right central lobe in β1 band,parietal lobe in α1 and β1 bands,right parietal lobe in β2 band,right temporal lobe in δ and θ band,temporal lobe in α1 and β bands,left occipital lobe in α1 band,and occipital lobe in β1(|Z|>1.967,P<0.05).Conclusion Resting-state EEG power characteristically elevates in NP patients after SCI,and the reactivity to eye-open-ing reduces.

Objective To construct a quality control model for cervical liquid-based thin cell smears using two different artificial intelligence(AI)techniques and to compare the total use of the two methods to improve the level of quality control of cervical liquid-based thin cell smears through the assistance of hybrid AI.Methods In this study,105 cervical liquid-based thin cell smear samples were used.Convolutional neural network(CNN)algorithm and Transformer network algorithm were used as specific AI algorithms in the AI model.The labeled features included the number of cells in the slice,excessive red blood cells,excessive inflammatory cells,and air bubbles.The smear samples were pre-processed and digitized by smear,followed by image segmentation and feature extraction.Using the labeled feature data,machine learning models were trained and optimized.Statistical AI and physician QC results were analyzed by calculating KAPPA index,sensitivity,specificity,area under the curve(AUC),and other indexes for AI QC results.Results CNN algorithm QC results in normal smear,inflammatory background and bloody background were significantly different from the expert review QC results(P＜0.001).Transformer algorithm QC results were similar to the expert review results,with no statistical difference(P＞0.05).General practitioner QC results were statistically different from the expert review QC results in normal smear detection rate and bloody background(P＜0.001).CNN algorithm Kappa value was 0.567,which had medium consistency with expert review results.Transformer algorithm Kappa value was 0.890,with the best consistency with expert review results.General practitioner Kappa value was 0.675,which had better consistency with expert review results.Using the expert review results as a reference standard,the predictive efficacy of the Transformer algorithm and the general practitioners' QC results was evaluated,and the predictive efficacy of the Transformer algorithm was higher than that of the general practitioners in detecting hemorrhagic backgrounds and normal smears(inflammatory backgrounds:AUC=1.000;normal smears:AUC=0.768)(hemorrhagic backgrounds:AUC=0.849;normal smears:AUC=0.849;normal smear:AUC=0.500).Conclusion In this study,we found that the Transformer algorithm was effective in improving the quality control of cervical liquid-based thin-layer cell smears by assisting doctors to perform smear quality control scoring and improving the efficiency and accuracy of smear sample quality control.It can be used as a new quality control method for cervical cancer cytological screening and has potential clinical applications.