ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

Objective To investigate the distribution characteristics of Oncomelania hupensis snails in Yunnan Province fol-lowing interruption of schistosomiasis transmission, so as to provide the evidence for assessing the risk of schistosomiasis transmission and scientifically formulating the schistosomiasis surveillance program. Methods According to the requirements of the National Schistosomiasis Surveillance Scheme (2020 Edition), O. hupensis snail surveillance data were collected from 18 schistosomiasis-endemic counties (cities, districts) in Yunnan Province from 2020 to 2024, including area of snail survey, area of snail habitats, area of re-emerging snail habitats, number of frames surveyed, number of frames with O. hupensis snails, number of O. hupensis snails captured, and number of living snails, and the occurrence of frames with snails and mean density of living snails were calculated. Changes in snail status over the 5-year period from 2020 to 2024 and the differences in snail distributions specified by epidemic intensity, environmental type, and vegetation type were analyzed. Results The areas of snail survey increased from 1 727.96 hm² in 2020 to 3 894.45 hm² in 2024 (peak) across 18 schistosomiasis-endemic counties (cities, districts) in Yunnan Province during the period from 2020 through 2024. The areas of snail habitats increased from 70.36 hm² in 2020 to a peak in 2023 (172.04 hm²), followed by a reduction to 132.36 hm² in 2024, and the areas of re-emerging snail habitats increased from 42.71 hm² in 2020 to a peak in 2022 (78.43 hm²), followed by a reduction to 40.21 hm² in 2024. The occurrence of frames with snails and mean density of living snails increased from 1.24% (3 025/244 404) and (0.033 2 ± 0.038 7) snails/0.1 m² in 2020 to peaks at 2.03% (6 231/307 563) and (0.066 9 ± 0.068 4) snails/0.1 m² in 2023, followed by reductions to 1.04% (5 829/559 941) and (0.032 6 ± 0.057 7) snails/0.1 m² in 2024, respectively. There was a significant difference in the occurrence of frames with snails over the 5-year study period (χ² = 1 962.95, P < 0.05), and the occurrence of frames with snails reduced by 48.71% in 2024 relative to in 2023 (χ² = 1 411.05, P < 0.005); however, there was no significant difference in the mean density of living snails over the 5 years (H = 5.310, P > 0.05). There were significant differences in the occurrence of frames with snails (χ² = 481.27, P < 0.05) and mean density of living snails (H = 6.872, P < 0.05) in schistosomiasis-endemic areas with different epidemic intensities. The occurrence of frames with snails (χ² = 25.32 and 38.70, both P values < 0.017) and mean density of living snails (Z = 28.55 and 49.96, both P values < 0.017) were higher in schistosomiasis transmission-interrupted and eliminated areas with snails than in schistosomiasis-eliminated areas without snails, and the occurrence of frames with snails (χ² = 453.54, P < 0.017) and mean density of living snails (Z = −56.97, P < 0.017) were higher in schistosomiasis-eliminated areas with snails than in schistosomiasis transmission-interrupted areas with snails. O. hupensis snails were mainly distributed in paddy fields, dry farmlands and ditches; however, the occurrence of frames with snails (13.40%, 424/3 164) and mean density of living snails [(0.252 8 ± 0.158 7) snails/0.1 m²] were higher in ponds/weirs than in other types of environments (both P values < 0.05). Rice, dry farmland crops and weeds were main vegetations in which O. hupensis snails were distributed, and the occurrence of frames with snails (2.29%, 7 111/310 140) and mean density of living snails [(0.072 3 ± 0.018 9) snails/0.1 m²] were higher in weeds than in other types of environments (both P values < 0.05). Conclusions O. hupensis snails have been effectively controlled in Yunnan Province following implementation of integrated schistosomiasis control measures; however, there are still risk factors for schistosomiasis transmission, including reduced attention to schistosomiasis control and snail re-emergence. Improved control efforts and surveillance system construction and timely identification of risk factors of snail status and timely management are recommended to ensure the achievement of the target of schistosomiasis elimination as scheduled.

ObjectiveTo conduct sarcopenia-related screening and assessment among community-dwelling elderly patients with type 2 diabetes mellitus (T2DM) in Changning District of Shanghai, to analyze the current status and influencing factors of suspected sarcopenia in this population, and to provide references for the early prevention and treatment of sarcopenia. MethodsUsing a stratified random sampling method, elderly T2DM patients under management in the Chronic Disease Health Management System of Changning District in Shanghai were selected as the study subjects. Patients were screened for sarcopenia and underwent related health examinations according to the Chinese Expert Consensus on Diagnosis and Treatment of Sarcopenia in the Elderly (2021). Self-designed questionnaires were used to collect basic information, lifestyle habits and health status, and the Montreal Cognitive Assessment (MoCA) was employed to evaluate cognitive function. ResultsAmong 758 elderly patients with T2DM [average age: (72.19±6.19) years old], 214 patients were identified as having suspected sarcopenia,accounting for 28.23%. The proportion of suspected sarcopenia was higher in females (30.94%) than in males (24.08%) (χ²=4.20, P=0.040), and higher in older patients (χ²=22.26, P<0.001). Higher proportions of suspected sarcopenia were also observed among patients who followed a vegetarian diet (39.77%) (χ²=73.28, P=0.011), had diabetic foot (59.09%) (χ²=10.65, P=0.001), reported feeling fatigued most of the time (37.11%) (χ²=4.33, P=0.037), or had mild cognitive impairment (χ²=3.95, P=0.047). The duration of T2DM in the suspected sarcopenia group [(12.86±10.07) years old] was longer than that in the non-sarcopenia group [(9.73±8.63) years old] (t=3.79, P<0.001), and the average body mass index (BMI) in the suspected sarcopenia group [(22.17±2.45) kg⋅m^-²)] was lower than that in the non-sarcopenia group [(25.11±3.26) kg⋅m^-²)] (t=-11.41, P<0.001). Multivariate logistic regression analyses showed that older age (OR=1.08, 95%CI:1.047‒1.110) and longer duration of T2DM (OR=1.02, 95%CI:1.005‒1.043) were associated with a higher risk of suspected sarcopenia in elderly T2DM patients. Female elderly T2DM patients had a higher risk of suspected sarcopenia (OR=1.89, 95%CI:1.310‒2.733) than males, and those with diabetic foot (OR=3.66, 95%CI:1.341‒9.990) had a higher risk than those without diabetic foot. ConclusionThe proportion of elderly T2DM patients with suspected sarcopenia was relatively high. In community-based integrated health management, healthcare providers should pay more attention to elderly T2DM patients who are older, have longer disease duration, are female, or have diabetic foot, so as to identify risks early and implement targeted comprehensive interventions and health management.

Forensic medicine has been designated as a first-level discipline,presenting new opportunities and challenges for the development of forensic medicine.Since the 1980s,the establishment of foren-sic medicine discipline and the cultivation of high-level forensic talents have become hot topics in the development of forensic medicine in China.Since the 13th Five-Year Plan,the forensic team of Shanxi Medical University has been aiming at the forefront,proposing the development goals of"Five First-class"and the discipline development path"Six Major Achievements".It has selected benchmark disci-plines,identified gaps in disciplinary development,unified thoughts,formulated completion timelines,concentrated superior resources,assigned tasks to individuals,and created an"Organized Fill-in-the-Blank Format"forensic medicine discipline construction model with the characteristics of the new era.The construction model of forensic medicine has achieved good results in the goals,discipline frame-work,scientific research,talent cultivation,discipline team and platform construction,forming a rela-tively complete discipline construction and management system,and accumulating valuable experience for the construction of first-level discipline and high-level talent cultivation of forensic medicine.

Objective:The greater tuberosity angle(GTA)and critical shoulder angle(CSA)are commonly referred to as radiographic markers which were used to described morphology of the greater tu-berosity and acromion respectively.At present,most international studies focus on the correlation be-tween the above two parameters and rotator cuff tears(RCTs),and their diagnostic value and risk assess-ment.This study attempts to find out the trend of GTA and CSA changes and risk threshold of RCTs,as well as the protective factors and risk factors.Methods:In this study,130 individuals from May 2019 to December 2020 were recruited.According to Southern California Orthopedic Institute(SCOI)classifica-tion,the individuals were divided into four groups retrospectively:Group A,negative control group;Group B,partial tears(articular side);Group C,partial tears(bursal side);Group D,full-thickness tears.GTA and CSA were measured respectively on true anteroposterior position X-ray of shoulder with arm in neutral rotation and performed by the same trained technician team in single-blind.The correla-tions between RCTs and relevant factors were analyzed.Results:According to the area under the receiver operating characteristic curve(AUC),GTA and CSA of RCTs(Groups B,C and D)were 0.736 and 0.673 with 95％confidence interval(CI),the cut-off value of GTA and CSA of RCTs were 70.5° and 39.5° respectively.Comparing with the control group,RCTs groups had significant statistical differences in age and body mass index(BMI)(P＜0.05),especially the full-thickness RCTs(Group D),which was older than Groups A,B and C(P＜0.05,cut-off value:56.5 years old)and shorter than Groups A and B(P＜0.05,cut-off value:1.58 m).Analyzed from scatter plot and regression analysis,there was no linear correlation between GTA and CSA.There were no significant differences in gender,dominant shoulders and smoking between the RCTs groups and the control group(P＞0.05).Conclusion:Larger GTA(＞70.5°)and CSA(＞39.5°)would be highly predictive in diagnosing RCTs without linear cor-relation,and GTA has a higher diagnostic value in contrast.Subacromial impingement and shoulder de-generation occurred before RCTs.Patients with age＞56.5 years and height＜1.58 m were more likely to develop disease of full-thickness RCTs and no statistic differences in weight and BMI.Gender,domi-nant shoulder and smoking were neither risk factors nor protective factors.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)％.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0％vs 29.5％).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7％vs 7.8％,0.8％vs 0.1％,both P＜0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)％with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9％and 1.8％,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1％).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10％.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P＜0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.

OBJECTIVE: To explore the expression and clinical significance of programmed death receptor 1 (PD-1), Th1, Th2, and Th17 cytokines in multiple myeloma (MM). METHODS: A total of 76 MM patients treated in the Tengzhou Central People's Hospital from May 2021 to May 2023 were collected as MM group, and 48 healthy individuals who underwent physical examination during the same period were included as control group. The expression of PD-1 on the surface of CD4⁺ and CD8⁺ T cells and the levels of serum Th1 cytokines ［interleukin (IL) -2, interferon γ (IFN-γ), tumor necrosis factor α (TNF-α)］, Th2 cytokines (IL-4, IL-6, IL-10) and Th17 cytokines (IL-17) were detected in the two groups. Spearman correlation was used to examine the relationship between PD-1, Th1, Th2 and Th17 cytokines and clinical stage and immune typing of MM patients. Multivariate logistic regression analysis was used to analyze the related factors affecting the efficacy of chemotherapy in MM patients, and the factors were tested for multicollinearity. Receiver operating characteristic (ROC) curve was drawn to analyze the predictive value of PD-1, Th1, Th2 and Th17 cytokines in chemotherapy efficacy of MM patients. RESULTS: The levels of CD4⁺T PD-1, CD8⁺T PD-1, IL-4, IL-6, IL-10, and IL-17 in the MM group were higher than those in the control group, while the levels of IL-2, IFN-γ, and TNF-α were lower (all P <0.001). The levels of CD4⁺T PD-1, CD8⁺T PD-1, IL-4, IL-6, IL-10, and IL-17 in R-ISS stage III patients were higher than those in stage II and I patients, and the levels in stage II patients were higher than those in stage I patients (all P <0.05). The IL-2 level in R-ISS stage III patients was lower than that in stage II and I patients, and IL-2 level in R-ISS stage II patients was lower than that in stage I patients (all P <0.05). The levels of CD4⁺T PD-1, CD8⁺T PD-1, IL-4, IL-6, IL-10, and IL-17 in IgG patients were higher than those in IgA, light chain, and non secretory patients, while the level of IL-2 was lower (all P <0.05). Correlation analysis showed that CD4⁺T PD-1, CD8⁺T PD-1, IL-4, IL-6, IL-10, and IL-17 were positively correlated with R-ISS staging in MM patients (r =0.623, 0.635, 0.728, 0.330, 0.742, 0.412), and negatively correlated with immune classification (r =-0.664, -0.756, -0.642, -0.479, -0.613, -0.323). IL-2 was negatively correlated with R-ISS staging in MM patients (r =-0.280), and positively correlated with immune classification (r =0.483). The levels of CD4⁺T PD-1, CD8⁺T PD-1, IL-4, IL-6, IL-10, and IL-17 in the non-remission group were higher than those in the remission group, while the level of IL-2 was lower (all P <0.001). Multivariate logistic regression analysis showed that the increased CD4⁺T PD-1, CD8⁺T PD-1, IL-4, IL-6, IL-10 and IL-17 were risk factors for the efficacy of chemotherapy in MM patients (OR >1, P <0.05), while the increased IL-2 was a protective factor (OR < 1, P <0.05). The results of multicollinearity test showed that the tolerance of the seven factors included was between 0.714-0.885, and the variance inflation factor was between 1.130-1.400. There was no multicollinearity. The ROC curve analysis results showed that the area under the curve for the combined prediction of chemotherapy efficacy in MM patients by the above 7 factors was 0.942, with specificity of 0.741 and sensitivity of 0.909. CONCLUSION The expression levels of PD-1 on the surface of CD4⁺ and CD8⁺ T cells and serum Th2 and Th17 cytokines in MM patients are high, while Th1 cytokines are low. PD-1, Th1, Th2, and Th17 cytokines are related to clinical stage and immune classification of MM patients. The combined detection of these indicators can help predict the chemotherapy efficacy of MM patients.
Humans ; Programmed Cell Death 1 Receptor/metabolism* ; Multiple Myeloma/blood* ; Cytokines/metabolism* ; Th17 Cells/metabolism* ; Th1 Cells/metabolism* ; Th2 Cells/metabolism* ; Female ; Male ; Interleukin-10 ; Interferon-gamma ; Middle Aged ; Interleukin-17 ; Interleukin-2 ; Interleukin-4 ; Tumor Necrosis Factor-alpha ; Interleukin-6 ; Aged

OBJECTIVE: To elucidate how spinal manipulative therapy (SMT) exerts its analgesic effects through regulating brain function in lumbar disc herniation (LDH) patients by utilizing resting-state functional magnetic resonance imaging (rs-fMRI). METHODS: From September 2021 to September 2023, we enrolled LDH patients (LDH group, n=31) and age- and sex-matched healthy controls (HCs, n=28). LDH group underwent rs-fMRI at 2 distinct time points (TPs): prior to the initiation of SMT (TP1) and subsequent to the completion of the SMT sessions (TP2). SMT was administered once every other day for 30 min per session, totally 14 treatment sessions over a span of 4 weeks. HCs did not receive SMT treatment and underwent only one fMRI scan. Additionally, participants in LDH group completed clinical questionnaires on pain using the Visual Analog Scale (VAS) and the Japanese Orthopedic Association (JOA) score, whereas HCs did not undergo clinical scale assessments. The effects on the brain were jointly characterized using the amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo). Correlation analyses were conducted between specific brain regions and clinical scales. RESULTS: Following SMT treatment, pain symptoms in LDH patients were notably alleviated and accompanied by evident activation of effects in the brain. In comparison to TP1, TP2 exhibited the most significant increase in ALFF values for Temporal_Sup_R and the most notable decrease in ALFF values for Paracentral_Lobule_L (voxelwise P<0.005; clusters >30; FDR correction). Additionally, the most substantial enhancement in ReHo values was observed for the Cuneus_R, while the most prominent reduction was noted for the Olfactory_R (voxelwise P<0.005; clusters >30; FDR correction). Moreover, a comparative analysis revealed that, in contrast to HCs, LDH patients at TP1 exhibited the most significant increase in ALFF values for Temporal_Pole_Sup_L and the most notable decrease in ALFF values for Frontal_Mid_L (voxelwise P<0.005; clusters >30; FDR correction). Furthermore, the most significant enhancement in ReHo values was observed for Postcentral_L, while the most prominent reduction was identified for ParaHippocampal_L (voxelwise P<0.005; clusters >30; FDR correction). Notably, correlation analysis with clinical scales revealed a robust positive correlation between the Cuneus_R score and the rate of change in the VAS score (r=0.9333, P<0.0001). CONCLUSIONS Long-term chronic lower back pain in patients with LDH manifests significant activation of the "AUN-DMN-S1-SAN" neural circuitry. The visual network, represented by the Cuneus_R, is highly likely to be a key brain network in which the analgesic efficacy of SMT becomes effective in treating LDH patients. (Trial registration No. NCT06277739).
Humans ; Magnetic Resonance Imaging ; Intervertebral Disc Displacement/diagnostic imaging* ; Male ; Female ; Brain/diagnostic imaging* ; Adult ; Manipulation, Spinal/methods* ; Middle Aged ; Lumbar Vertebrae/physiopathology* ; Pain Management ; Rest ; Case-Control Studies