ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

α7 nicotinic acetylcholine receptor(α7nAChR)is widely expressed in the central nervous system and immune system,and plays a neuro-immunoregulatory role.On the one hand,α7nAChR is involved in the transmission of neurotransmitters,the conduction of excitatory signals and the maintenance of synaptic plasticity,which is of great significance for maintaining the normal and stable neurocognitive function.On the other hand,as an important part of the cholinergic anti-inflammatory pathway,α7nAChR is involved in the regulation of physiological and pathological processes such as inflammatory response,oxidative stress,apoptosis and autophagy in the central system,and plays an immunomodulatory and neuroprotective role,thus being potential target for improving perioperative neurocognitive function.This article reviews the biological characteristics of α7nAChR and its effect on perioperative neurocognitive function,in order to provide ideas and methods for clinical improvement of perioperative neurocognitive function in surgical patients.

The occurrence and development of tumors are closely related to the body's immune function.It has been confirmed that immunotherapy plays a role in the treatment of various cancers.Some traditional Chinese medicines can control the growth and metastasis of tumors by enhancing anti-tumor immunity.Even in the immunosuppressive tumor microenvironment,traditional Chinese medicine can exert anti-tumor effects by upregulating immune responses.Further research on the regulation of the immune mechanisms by traditional Chinese medicine will provide new insights into how traditional Chinese medicine controls tumor growth and metastasis and help improve its effectiveness in the clinical treatment of various cancers.This article aims to provide a theoretical reference for the role of immunoregulation in tumors,summarize its mechanisms in tumors,and traditional Chinese medicine intervention research in tumors for the prevention and treatment of tumors with traditional Chinese medicine.

Objective Little is known about the association between whole-blood nicotinamide adenine dinucleotide(NAD+)levels and nabothian cysts.This study aimed to assess the association between NAD+levels and nabothian cysts in healthy Chinese women. Methods Multivariate logistic regression analysis was performed to analyze the association between NAD+levels and nabothian cysts. Results The mean age was 43.0±11.5 years,and the mean level of NAD+was 31.3±5.3 μmol/L.Nabothian cysts occurred in 184(27.7%)participants,with single and multiple cysts in 100(15.0%)and 84(12.6%)participants,respectively.The total nabothian cyst prevalence gradually decreased from 37.4%to 21.6%from Q1 to Q4 of NAD+and the prevalence of single and multiple nabothian cysts also decreased across the NAD+quartiles.As compared with the highest NAD+quartile(≥34.4 μmol/L),the adjusted odds ratios with 95%confidence interval of the NAD+Q1 was 1.89(1.14-3.14)for total nabothian cysts.The risk of total and single nabothian cysts linearly decreased with increasing NAD+levels,while the risk of multiple nabothian cysts decreased more rapidly at NAD+levels of 28.0 to 35.0 μmol/L. Conclusion:Low NAD+levels were associated with an increased risk of total and multiple nabothian cysts.

AIM To evaluate the quality of Beidougen Formula Granules.METHODS Fifteen batches of standard decoctions and three batches of formula granules were prepared,after which paste rate and contents,transfer rates of magnoflorine,daurisoline,dauricine were determined.HPLC specific chromatograms were established,and cluster analysis was adopted in chemical pattern recognition.RESULTS For three batches of formula granules,the paste rates were 15.1%-16.6%,the contents of magnoflorine,daurisoline,dauricine were 18.93-19.39,9.42-9.60,6.79-6.85 mg/g with the transfer rates of 34.42%-35.25%,43.81%-44.65%,27.27%-27.51%from decoction pieces to formula granules,respectively,and there were seven characteristic peaks in the specific chromatograms with the similarities of more than 0.95,which demonstrated good consistence with those of standard decoctions and accorded with related limit requirements.Fifteen batches of standard decoctions were clustered into two types,and the medicinal materials produced from Jilin,Hebei,Shangdong could be used for the preparation of formula granules.CONCLUSION This reasonable and reliable method can provide references for the quality control and clinical application of Beidougen Formula Granules.

Objective This study aimed to investigate the potential relationship between urinary metals copper (Cu), arsenic (As), strontium (Sr), barium (Ba), iron (Fe), lead (Pb) and manganese (Mn) and grip strength. Methods We used linear regression models, quantile g-computation and Bayesian kernel machine regression (BKMR) to assess the relationship between metals and grip strength.Results In the multimetal linear regression, Cu (β=-2.119), As (β=-1.318), Sr (β=-2.480), Ba (β=0.781), Fe (β= 1.130) and Mn (β=-0.404) were significantly correlated with grip strength (P < 0.05). The results of the quantile g-computation showed that the risk of occurrence of grip strength reduction was -1.007 (95％ confidence interval:-1.362, -0.652; P < 0.001) when each quartile of the mixture of the seven metals was increased. Bayesian kernel function regression model analysis showed that mixtures of the seven metals had a negative overall effect on grip strength, with Cu, As and Sr being negatively associated with grip strength levels. In the total population, potential interactions were observed between As and Mn and between Cu and Mn (Pinteractions of 0.003 and 0.018, respectively).Conclusion In summary, this study suggests that combined exposure to metal mixtures is negatively associated with grip strength. Cu, Sr and As were negatively correlated with grip strength levels, and there were potential interactions between As and Mn and between Cu and Mn.

The continuous advancement of molecular detection technology has greatly propelled the develop-ment of precision medicine for lung cancer.However,tumor heterogeneity is closely associated with tumor metastasis,recurrence,and drug resistance.Additionally,different lung cancer patients with the same genetic mutation may exhibit varying treatment responses to different therapeutic strategies.Therefore,the development of modern precision medicine urgently requires the precise formulation of personalized treatment strategies through personalized tumor models.Lung cancer organoid(LCO)can highly simulate the biological characteristics of tumor in vivo,facilitating the application of innovative drugs such as antibody-drug conjugate in precision medicine for lung cancer.With the development of co-culture model of LCO with tumor microenvironment and tissue engineering technology such as microfluidic chip,LCO can better preserve the biological characteristics and functions of tumor tissue,further improving high-throughput and automated drug sensitivity experiment.In this review,we combine the latest research progress to summarize the applica-tion progress and challenges of LCO in precision medicine for lung cancer.

Objective:To investigate the value of a novel technique called visual transient elastography (ViTE) and liver steatosis analysis (LiSA) in assessing liver function injury in hepatitis B virus-related hepatocellular carcinoma (HBV-related HCC) patients after ablation therapy.Methods:A total of 129 HBV-related HCC patients in Harbin Medical University Cancer Hospital from January 2022 to August 2023 were retrospectively analyzed.ViTE and LiSA examinations were applied to record the liver stiffness E value and LiSA value before ablation. An albumin-bilirubin (ALBI) score was constructed using laboratory indicators. Spearman correlation analysis was used to assess the correlation between E value, LiSA value and ALBI score, body mass index (BMI). According to the change of ALBI grade in perioperative period, the patients could be divided into two groups: liver function unchanged group and liver function injury group. Univariate and multivariate statistical methods were used to analyze related factors affecting changes in liver function after ablation, followed by establishing a predictive model.Results:Spearman analysis showed a strong positive correlation between E value and ALBI score ( rs=0.686, P<0.001), and LiSA value was weakly positively correlated with BMI ( rs=0.338, P<0.001). There were no significant correlations between E value and BMI, LiSA value and ALBI score (all P>0.05). Univariate analysis showed that differences of age, BMI, ablation parameters, E value, and LiSA value in the two groups were statistically significant (all P<0.05). Multivariate analysis showed that E value, LiSA value, and ablation time were independent predictors of hepatic dysfunction after ablation (all P<0.05). AUC was 0.892 indicating high accuracy in the predictive model based on above indicators. Conclusions:Under the real-time ultrasound guidance, a non-invasive liver function injury prediction model based on ViTE and LiSA technology can offer personalized predictions for ablative perioperative changes in liver function among HBV-related HCC patients.

Objective:To investigate the efficacy of microscopic decompression in degenerative lumbar spinal stenosis (DLSS) under single percutaneous tubular retractor system.Methods:A retrospective analysis was performed; 117 DLSS patients with imaging manifestations as non-segmental lumbar instability, admitted to Department of Neurosurgery, 900 th Hospital of PLA Joint Logistics Team from October 2018 to April 2023 were enrolled consecutively. These patients failed in strict conservative treatment and then changed to posterior lumbar spinal canal and nerve root decompression by microscopy and percutaneous tubular retractor system. These patients were followed up for 6-50 months. Pain visual analogue score (VAS) and lumbar Oswestry dysfunction index (ODI) were recorded and results of X-rays, CT and MRI of lumbar spines were analyzed 1 d before and 1 week after decompression and at the last follow-up. Modified MacNab criteria were used to evaluate the efficacy at the last follow-up. Results:Among the 117 patients, unilateral laminectomy for unilateral decompression was performed in 56 patients (47.9%) and unilateral laminotomy for bilateral decompression in 61 (52.1%). Single segment decompression was performed in 109 patients (93.2%) and double segment decompression in 8 (6.8%). Dural sac rupture occurred in 4 patients (3.5%), and immediate occlusion was given; no cerebrospinal fluid leakage was noted after decompression. All patients did not experience obvious nerve damage during decompression or intervertebral infection/lumbar instability after decompression. After 18 (13, 24) months of follow-up, VAS scores of the patients at the last follow-up decreased from (5.96±0.85) 1 d before decompression and (1.75±0.61) 1 week after decompression to (1.01±0.59), and lumbar ODI decreased from (63.22±8.33)% 1 d before decompression and (17.66±5.20)% 1 week after decompression to (10.64±3.44)%, with significant differences ( P<0.05). At the last follow-up, modified MacNab criteria indicated 46 patients (39.3%) as excellent, 66 (56.4%) as good, 3 (2.6%) as fair, and 2 (1.7%) as poor, with an excellent/good therapeutic rate of 95.7%. Conclusion:For surgical treatment of DLSS patients without evidenced preoperative spinal instability, personalized unilateral or bilateral spinal canal decompression under microscope by combiningsingle percutaneous tubular retractor system can effectively reduce surgical trauma and achieve satisfactory surgical results.

Objective:To compare the morphological differences of psoas major muscles between patients with lumbar disc herniation (LDH) of lower limb pain and lumbocrural pain based on CT imaging data.Methods:Sixty patients with LDH admitted to Department of Neurosurgery, 900 th Hospital of PLA Joint Logistic Team from January 2012 to February 2023 were included. According to clinical symptoms, they were divided into lower limb pain group and lumbocrural pain group ( n=30). 3D CT images of the psoas major muscles in the 2 groups were reconstructed; the longest transverse axis perpendicular to the longitudinal axis of the psoas major muscle was chosen as the cross-sectional area, and the maximum psoas major muscle cross-sectional area was calculated; maximum psoas major muscle cross-sectional area index (PI max) was defined as ratio of maximum psoas major muscle cross-sectional area and L 5 vertebral cross-sectional area. PI max difference between lower limb pain group and lumbocrural pain group was compared; PI max difference among patients with different pain degrees (visual analog scale [VAS] scores) or pain courses was further compared in both lower limb pain group and lumbocrural pain group. Pearson correlation was used to analyze the correlations of PI max with pain degree and pain course in the 2 groups. Results:PI max in lower limb pain group was significantly larger than that in lumbocrural pain group (0.62±0.05 vs. 0.54±0.04, t=7.320, P<0.001). PI max in patients with severe pain from both lower limb pain group and lumbocrural pain group was significantly smaller than that in patients with moderate pain (0.61±0.05 vs. 0.65±0.04, t=2.422, P=0.022; 0.53±0.03 vs. 0.58±0.04, t=3.502, P=0.002). PI max in patients with short pain course from both lower limb pain group and lumbocrural pain group was significantly larger than that in patients with long pain course (0.64±0.05 vs. 0.59±0.04, t=2.570, P=0.016; 0.57±0.04 vs. 0.53±0.03, t=2.941, P=0.007). Pearson correlation showed that PI max was negatively correlated with pain degree and pain course in LDH patients from both groups ( P<0.05). Conclusion:Atrophy of psoas major muscles in LDH patients is aggravated with increased pain degree and pain course.