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.

Patients with lung cancer experience a heavy symptom burden during the perioperative period, which seriously affects their recovery and quality of life. Traditional symptom management models rely mainly on scheduled ward rounds during hospitalization and outpatient follow-up after discharge. However, they have limitations such as delayed symptom recognition, lack of post-discharge monitoring, and non-quantitative symptom assessment, which often lead to delayed interventions and low patient satisfaction. In recent years, the symptom management model based on electronic patient-reported outcomes (ePRO) has been increasingly valued in clinical practice. Existing high-level evidence from both domestic and international studies indicates that, through proactive monitoring, real-time alerts, and remote interventions, this model enables dynamic and continuous symptom management and helps improve patient recovery and healthcare experience. As a supplement to routine medical care, the ePRO-based symptom management model aims to enhance the quality of care rather than replace existing medical processes. To promote the standardized application of this model in perioperative lung cancer care, this consensus integrates domestic and international evidence. After multiple rounds of voting by more than 50 experts, it formulates 12 consensus statements covering the three core components, symptom monitoring, alerting, and intervention, to provide scientific and practical recommendations for clinical practice.

Objective To understand the implementation status of"Diagnosis of Ascariasis"(WS/T 565-2017)and provide a scientific basis for promoting,revising,and improving the Standard.Methods Using the convenient sampling method,the investigation targeted professional and technical personnel at the provincial,city,county,and township levels engaged in parasitic disease prevention,control,or diagnosis and treatment in Anhui and Sichuan provinces.No less than 150 individuals were included in each province.The implementation survey of Diagnosis of Ascariasis(WS/T 565-2017)was conducted by the subjects completing a questionnaire by themselves.Results The response rate to the questionnaire was 91.90%(386/420).The awareness and utilization rates of the Standard were 81.87%and 49.22%,respectively and both increased with age(χ2 trend=7.977 and 19.016,respectively,P＜0.01).Respondents with college degrees(90.72%)had a higher awareness rate(χ2=8.619,P＜0.05).In terms of utilization rate,males(58.38%),those with college degrees(67.01%),staff members of provincial-level units(77.78%),and personnel in medical institutions(71.43%)had higher utilization rates(χ2=13.486,17.166,8.426,and 5.956,respectively,all P＜0.05).The survey indicated that 57.77%of the work units of respondents have conducted promotional activities,and 53.89%of the work units of respondents have sent personnel to participate in training.Moreover,this proportion tended to increase as the unit level decreased(χ2 trend=9.403 and 14.729,P＜0.01).The level of participation in publicity and training by medical institutions(89.29%)was significantly higher than that of disease control institutions(55.31%and 51.12%,respectively,χ2=12.290 and 15.225,P＜0.01).Furthermore,training participation is a crucial factor in enhancing awareness rates.A total of 368 respondents(95.34%)reported that their work units have conducted testing for ascariasis.Additionally,378 individuals(97.92%)believe that the Standard is"applicable"or"basically applicable,"while 369(95.60%)felt that no revisions were needed.Conclusions The results indicated that"Diagnosis of Ascariasis"(WS/T 565-2017)remains applicable to the diagnostic needs of ascariasis and it is recommended to strengthen its promotion and implementation.

Objective: To investigate the potential therapeutic mechanisms of kaempferol , an active component in the traditional Chinese medicine gardenia , for lung cancer treatment using a network pharmacology approach . Methods: The main active ingredients and potential targets of Gardenia jasminoides were obtained through the Tra⁃ditional Chinese Medicine Pharmacology Database and Analysis Platform (TCMSP) , and combined with the lung cancer related target information collected from Gene Cards and OMIM databases , the intersection targets of Garde⁃nia jasminoides and lung cancer treatment were determined by drawing Venn diagrams . Further screening of core targets was conducted through PPI network analysis , and gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes ( KEGG) pathway enrichment analysis were performed using the Metascape platform . Auto dock software was used to evaluate the binding affinity between the active ingredients of Gardenia jasminoides and target proteins . In terms of experiments , cell proliferation ability was evaluated through CCK⁃8 assay , cell migration and invasion ability were detected through cell scratch healing assay and Transwell assay , and the expression levels of epithelial mesenchymal transition ( EMT) protein and inflammatory factors were detected by Western blot and RT⁃qPCR . Results: The active ingredient kaempferol in Gardenia jasminoides exhibited significant binding ability invasion of lung cancer cells . The results of Western blot and RT⁃qPCR further confirmed that kaempferol could promote an increase in E ⁃cadherin , a decrease in N ⁃cadherin and Vimentin , and reduce the expression of inflam⁃matory factors . Conclusion The active ingredient of Gardenia jasminoides , kaempferol , inhibits the proliferation ,migration and invasion of lung cancer cells by targeting BCL⁃2 , while reversing EMT progression and suppressing the expression levels of inflammatory cytokines in lung cancer cells , thus preventing lung cancer progression .

BACKGROUND: The beneficial effects of sodium-glucose co-transporter-2 inhibitors (SGLT2i) on adverse cardiac outcomes in diabetic patients are well-established. However, the effects of SGLT2i against cancer therapy-related cardiotoxicity remain understudied. We investigated the association between SGLT2i and cardiac outcomes in cancer patients. METHODS: PubMed, Embase, and the Cochrane Library were searched from their inception until September 30, 2024 for studies evaluating the effects of SGLT2i in patients with cancer. The primary outcomes included incident heart failure (HF), HF exacerbation, HF hospitalization, atrial fibrillation/atrial flutter (AF/AFL), myocardial infarction, and all-cause mortality. The secondary outcomes included acute kidney injury and sepsis. Odds ratio (OR) with 95% CI was pooled. RESULTS: Thirteen studies with 85,596 patients were included. Compared to non-SGLT2i use, SGLT2i treatment was associated with lower risks of incident HF (OR = 0.51, 95% CI: 0.32-0.79, P = 0.003), HF exacerbation (OR = 0.74, 95% CI: 0.63-0.87, P < 0.001), AF/AFL (OR = 0.67, 95% CI: 0.55-0.82, P < 0.001), myocardial infarction (OR = 0.61, 95% CI: 0.41-0.90, P = 0.01), and all-cause mortality (OR = 0.44, 95% CI: 0.28-0.69, P < 0.001), but not for HF hospitalization (OR = 0.58, 95% CI: 0.22-1.55, P = 0.28). As for safety outcomes, SGLT2i use was associated with lower risks of acute kidney injury (OR = 0.68, 95% CI: 0.57-0.81, P < 0.001) and sepsis (OR = 0.32, 95% CI: 0.23-0.44, P < 0.001). CONCLUSIONS SGLT2i were associated with lower risks of incident HF, HF exacerbation, AF/AFL, myocardial infarction, all-cause mortality, acute kidney injury, and sepsis in cancer patients.

Hypoxic-ischemic brain damage(HIBD)is a leading cause of neonatal mortality and neurological dysfunction in the infants,and it remains a focal point of research in neonatology.MicroRNA(miRNA)is involved in neural development,and its alterations is closely associated with the pathological progression of HIBD.However,there is a lack of effective integration of studies on the specific roles and mechanisms of miRNAs at different pathological stages of the disease.This review summarized the recent researches on miRNA in various stages of HIBD.During the hypoxic-ischemic phase,abnormal expression of certain hypoxia-related miRNA can serve as novel biological diagnostic markers.In the cerebral edema phase,miRNA may maintain the integrity of the blood-brain barrier,alleviating neuronal swelling and structural changes.In the cerebral infarction phase,miRNA can inhibit the expression of apoptotic proteins,enhance the neuronal survival rates,reduce the infarct size,and improve neurological behavior.Further research into the mechanisms of miRNA in HIBD will provide new insights for the development of diagnostic and therapeutic strategies for HIBD.

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: Varied acupoint selections represent a potential cause of the uncertainty surrounding the efficacy of acupuncture for knee osteoarthritis (OA). Skin temperature, a guiding factor for acupoint selection, may help to address this issue. This study explored thermal sensitization of acupoints used for the treatment of knee OA. METHODS: This cross-sectional case-control study enrolled cases aged 45-75 years with symptomatic knee OA and age- and gender-matched non-knee OA controls in a 1:1 ratio. All participants underwent infrared thermographic imaging. The primary outcome was the relative skin temperature of acupoint (STA), and the secondary outcome was the absolute STA of 11 acupoints. The Z test was used to compare the relative and absolute STAs between the groups. Principal component analysis was used to extract the common factors (CFs, acupoint cluster) in the STAs. A general linear model was used to identify factors affecting the STA in the knee OA cases. For the group comparisons of relative STA, P < 0.0045 (adjusted for 11 acupoints through Bonferroni correction) was considered to indicate statistical significance. For other analyses, P < 0.05 was used as the threshold for statistical significance. RESULTS: The analysis included 308 participants, consisting of 151 cases (mean age: [64.58 ± 6.67] years; male: 25.83%; mean body mass index: [25.70 ± 3.16] kg/m²) and 157 controls (mean age: [63.37 ± 5.96] years; male: 26.11%; mean body mass index: [24.47 ± 2.84] kg/m²). The relative STAs of ST34 (P = 0.0001), EX-LE2 (P < 0.0001), EX-LE5 (P = 0.0006), SP10 (P < 0.0001), BL40 (P = 0.0012) and GB39 (P = 0.0037) were higher in the knee OA group. No difference was found in the STAs of ST35, ST36, SP9, GB33 and GB34. Four CFs were identified for relative STA in both groups. The acupoints within each CF were consistent between the groups. The mean values of the relative STAs across each CF were higher in the knee OA group. In the knee OA cases, no factors were observed to affect the relative STA, while age and gender were found to affect the absolute STA. CONCLUSION Among patients with knee OA, thermal sensitization occurs in the acupoints of the lower extremity, exhibiting localized and regional thermal consistencies. The thermally sensitized acupoints that we identified in this study, ST34, SP10, EX-LE2, EX-LE5, GB39 and BL40, may be good choices for the acupuncture treatment of knee OA. Please cite this article as: Tu JF, Wang XZ, Yan SY, Wang YR, Yang JW, Shi GX, Zhang WZ, Jing LN, Yang LS, Liu DH, Wang LQ, Mi BH. Thermal sensitization of acupoints in patients with knee osteoarthritis: A cross-sectional case-control study. J Integr Med. 2025; 23(3): 289-296.
Humans ; Osteoarthritis, Knee/physiopathology* ; Male ; Cross-Sectional Studies ; Middle Aged ; Female ; Acupuncture Points ; Case-Control Studies ; Aged ; Skin Temperature ; Acupuncture Therapy