Objective To evaluate the effect of low-dose ¹⁸F-fluorodeoxyglucose (FDG) injection on image quality in pediatric patients, calculate the whole-body effective dose and absorbed doses to critical organs, and provide a reference for clinical protection in pediatric low-dose positron emission tomography/computed tomography (PET/CT) examination. Methods A total of 67 pediatric patients aged 4-14 years who underwent ¹⁸F-FDG whole-body PET/CT imaging in the Department of Nuclear Medicine, The First Affiliated Hospital of Shandong First Medical University between January 2024 and December 2025 were enrolled in a retrospective study. According to the injected ¹⁸F-FDG dose, patients were divided into a full-dose group (37 cases, 2.96-3.7 MBq/kg, PET acquisition duration of 10 min) and a low-dose group (30 cases, 1.85-2.4 MBq/kg, PET acquisition duration of 15 min). All scans were performed using a uEXPLORER PET/CT scanner. The standardized uptake value, standard deviation, and signal-to-noise ratio were measured for the liver and mediastinal blood pool. Image quality was compared between the two groups. The PET effective dose was calculated based on body mass index, and the total effective dose was obtained by combining PET effective dose with CT effective dose. The doses to critical organs were calculated according to ICRP Publication 128. Statistical analysis was performed using SPSS 26.0 and Prism 9.0 software. Differences were compared between groups. Results There were no significant differences in age, sex, weight, height, or body mass index between the two groups (P>0.05), while the injected dose showed a significant difference (P<0.001). In terms of image quality, there were no significant differences in standardized uptake value, standard deviation, and signal-to-noise ratio between the two groups. In terms of radiation dose, compared with the full-dose group, the low-dose group showed a 35.13% reduction in PET effective dose and a 15.22% reduction in total effective dose (P<0.05), whereas the CT effective dose was reduced by 2.4% and the difference was not significant (P=0.0892). The doses to critical organs (gonads, breasts, thyroid, red bone marrow, lungs) in the low-dose group were significantly lower than those in the full-dose group (P<0.01). Conclusion Under the premise of meeting clinical diagnostic requirements, low-dose ¹⁸F-FDG whole-body PET/CT imaging in pediatric patients can reduce the overall radiation exposure by 15%, and decrease the doses to critical organs, including the gonads, by more than 20%.

Objective To evaluate the effect of low-dose ¹⁸F-fluorodeoxyglucose (FDG) injection on image quality in pediatric patients, calculate the whole-body effective dose and absorbed doses to critical organs, and provide a reference for clinical protection in pediatric low-dose positron emission tomography/computed tomography (PET/CT) examination. Methods A total of 67 pediatric patients aged 4-14 years who underwent ¹⁸F-FDG whole-body PET/CT imaging in the Department of Nuclear Medicine, The First Affiliated Hospital of Shandong First Medical University between January 2024 and December 2025 were enrolled in a retrospective study. According to the injected ¹⁸F-FDG dose, patients were divided into a full-dose group (37 cases, 2.96-3.7 MBq/kg, PET acquisition duration of 10 min) and a low-dose group (30 cases, 1.85-2.4 MBq/kg, PET acquisition duration of 15 min). All scans were performed using a uEXPLORER PET/CT scanner. The standardized uptake value, standard deviation, and signal-to-noise ratio were measured for the liver and mediastinal blood pool. Image quality was compared between the two groups. The PET effective dose was calculated based on body mass index, and the total effective dose was obtained by combining PET effective dose with CT effective dose. The doses to critical organs were calculated according to ICRP Publication 128. Statistical analysis was performed using SPSS 26.0 and Prism 9.0 software. Differences were compared between groups. Results There were no significant differences in age, sex, weight, height, or body mass index between the two groups (P>0.05), while the injected dose showed a significant difference (P<0.001). In terms of image quality, there were no significant differences in standardized uptake value, standard deviation, and signal-to-noise ratio between the two groups. In terms of radiation dose, compared with the full-dose group, the low-dose group showed a 35.13% reduction in PET effective dose and a 15.22% reduction in total effective dose (P<0.05), whereas the CT effective dose was reduced by 2.4% and the difference was not significant (P=0.0892). The doses to critical organs (gonads, breasts, thyroid, red bone marrow, lungs) in the low-dose group were significantly lower than those in the full-dose group (P<0.01). Conclusion Under the premise of meeting clinical diagnostic requirements, low-dose ¹⁸F-FDG whole-body PET/CT imaging in pediatric patients can reduce the overall radiation exposure by 15%, and decrease the doses to critical organs, including the gonads, by more than 20%.

Objective To evaluate the effect of low-dose ¹⁸F-fluorodeoxyglucose (FDG) injection on image quality in pediatric patients, calculate the whole-body effective dose and absorbed doses to critical organs, and provide a reference for clinical protection in pediatric low-dose positron emission tomography/computed tomography (PET/CT) examination. Methods A total of 67 pediatric patients aged 4-14 years who underwent ¹⁸F-FDG whole-body PET/CT imaging in the Department of Nuclear Medicine, The First Affiliated Hospital of Shandong First Medical University between January 2024 and December 2025 were enrolled in a retrospective study. According to the injected ¹⁸F-FDG dose, patients were divided into a full-dose group (37 cases, 2.96-3.7 MBq/kg, PET acquisition duration of 10 min) and a low-dose group (30 cases, 1.85-2.4 MBq/kg, PET acquisition duration of 15 min). All scans were performed using a uEXPLORER PET/CT scanner. The standardized uptake value, standard deviation, and signal-to-noise ratio were measured for the liver and mediastinal blood pool. Image quality was compared between the two groups. The PET effective dose was calculated based on body mass index, and the total effective dose was obtained by combining PET effective dose with CT effective dose. The doses to critical organs were calculated according to ICRP Publication 128. Statistical analysis was performed using SPSS 26.0 and Prism 9.0 software. Differences were compared between groups. Results There were no significant differences in age, sex, weight, height, or body mass index between the two groups (P>0.05), while the injected dose showed a significant difference (P<0.001). In terms of image quality, there were no significant differences in standardized uptake value, standard deviation, and signal-to-noise ratio between the two groups. In terms of radiation dose, compared with the full-dose group, the low-dose group showed a 35.13% reduction in PET effective dose and a 15.22% reduction in total effective dose (P<0.05), whereas the CT effective dose was reduced by 2.4% and the difference was not significant (P=0.0892). The doses to critical organs (gonads, breasts, thyroid, red bone marrow, lungs) in the low-dose group were significantly lower than those in the full-dose group (P<0.01). Conclusion Under the premise of meeting clinical diagnostic requirements, low-dose ¹⁸F-FDG whole-body PET/CT imaging in pediatric patients can reduce the overall radiation exposure by 15%, and decrease the doses to critical organs, including the gonads, by more than 20%.

Drug repurposing offers a promising alternative to traditional drug development and significantly re-duces costs and timelines by identifying new therapeutic uses for existing drugs.However,the current approaches often rely on limited data sources and simplistic hypotheses,which restrict their ability to capture the multi-faceted nature of biological systems.This study introduces adaptive multi-view learning(AMVL),a novel methodology that integrates chemical-induced transcriptional profiles(CTPs),knowledge graph(KG)embeddings,and large language model(LLM)representations,to enhance drug repurposing predictions.AMVL incorporates an innovative similarity matrix expansion strategy and leverages multi-view learning(MVL),matrix factorization,and ensemble optimization techniques to integrate heterogeneous multi-source data.Comprehensive evaluations on benchmark datasets(Fdata-set,Cdataset,and Ydataset)and the large-scale iDrug dataset demonstrate that AMVL outperforms state-of-the-art(SOTA)methods,achieving superior accuracy in predicting drug-disease associations across multiple metrics.Literature-based validation further confirmed the model's predictive capabilities,with seven out of the top ten predictions corroborated by post-2011 evidence.To promote transparency and reproducibility,all data and codes used in this study were open-sourced,providing resources for pro-cessing CTPs,KG,and LLM-based similarity calculations,along with the complete AMVL algorithm and benchmarking procedures.By unifying diverse data modalities,AMVL offers a robust and scalable so-lution for accelerating drug discovery,fostering advancements in translational medicine and integrating multi-omics data.We aim to inspire further innovations in multi-source data integration and support the development of more precise and efficient strategies for advancing drug discovery and translational medicine.

Background: Bushen Zhuanggu Formula (BZF), derived from the classic Yougui Pills, has shown favorable clinical efficacy in treating advanced nontraumatic osteonecrosis of the femoral head (NONFH), particularly by promoting bone repair. However, its underlying mechanisms remain unclear. Objective: This study aimed to explore the mechanisms by which BZF promotes bone repair in advanced NONFH. Materials and methods: A total of 518 potential BZF targets were identified from the ETCM v2.0 database. Transcriptomic profiling of clinical cohorts revealed 485 differentially expressed genes in advanced NONFH patients compared to healthy controls. A drug target-disease gene interaction network was constructed to identify candidate BZF targets involved in NONFH pathogenesis. In vivo experiments were conducted to validate the effects of BZF in a rat model of advanced NONFH. Results: Network analysis identified key pathways associated with blood circulation obstruction, immune-inflammatory imbalance, and abnormal bone metabolism. Protein kinase C alpha (PKCA), Ras proto-oncogene (RAS), mitogen-activated protein kinase 3(ERK), ETS proto-oncogene 1 (ETS1), and receptor activator of nuclear factor-κB ligand (RANKL) formed a signaling axis implicated in NONFH pathogenesis. BZF treatment alleviated joint inflammation, preserved trabecular bone morphology, reduced bone loss, and promoted bone repair. Mechanistically, BZF significantly downregulated the expression of PKCA, RAS, ERK, ETS1, and RANKL, improved blood circulation, and inhibited osteoclast activation while promoting osteoblast activation. Conclusion: BZF may promote bone repair in advanced NONFH by enhancing blood circulation and modulating the PKC-RAS-ERK-ETS1-RANKL signaling axis, thereby reversing dysregulated bone metabolism.

With the rapid development of artificial intelligence, computational pathology has been seamlessly integrated into the entire clinical workflow, which encompasses diagnosis, treatment, prognosis, and biomarker discovery. This integration has significantly enhanced clinical accuracy and efficiency while reducing the workload for clinicians. Traditionally, research in this field has depended on the collection and labeling of large datasets for specific tasks, followed by the development of task-specific computational pathology models. However, this approach is labor intensive and does not scale efficiently for open-set identification or rare diseases. Given the diversity of clinical tasks, training individual models from scratch to address the whole spectrum of clinical tasks in the pathology workflow is impractical, which highlights the urgent need to transition from task-specific models to foundation models (FMs). In recent years, pathological FMs have proliferated. These FMs can be classified into three categories, namely, pathology image FMs, pathology image-text FMs, and pathology image-gene FMs, each of which results in distinct functionalities and application scenarios. This review provides an overview of the latest research advancements in pathological FMs, with a particular emphasis on their applications in oncology. The key challenges and opportunities presented by pathological FMs in precision oncology are also explored.
Humans ; Precision Medicine/methods* ; Medical Oncology/methods* ; Artificial Intelligence ; Neoplasms/pathology* ; Computational Biology/methods*

The processing mechanism of the human brain for speech information is a significant source of inspiration for the study of speech enhancement technology. Attention and lateral inhibition are key mechanisms in auditory information processing that can selectively enhance specific information. Building on this, the study introduces a dual-branch U-Net that integrates lateral inhibition and feedback-driven attention mechanisms. Noisy speech signals input into the first branch of the U-Net led to the selective feedback of time-frequency units with high confidence. The generated activation layer gradients, in conjunction with the lateral inhibition mechanism, were utilized to calculate attention maps. These maps were then concatenated to the second branch of the U-Net, directing the network's focus and achieving selective enhancement of auditory speech signals. The evaluation of the speech enhancement effect was conducted by utilising five metrics, including perceptual evaluation of speech quality. This method was compared horizontally with five other methods: Wiener, SEGAN, PHASEN, Demucs and GRN. The experimental results demonstrated that the proposed method improved speech signal enhancement capabilities in various noise scenarios by 18% to 21% compared to the baseline network across multiple performance metrics. This improvement was particularly notable in low signal-to-noise ratio conditions, where the proposed method exhibited a significant performance advantage over other methods. The speech enhancement technique based on lateral inhibition and feedback-driven attention mechanisms holds significant potential in auditory speech enhancement, making it suitable for clinical practices related to artificial cochleae and hearing aids.
Humans ; Attention/physiology* ; Speech Perception/physiology* ; Neural Networks, Computer ; Speech ; Noise ; Feedback

OBJECTIVE: To investigate the effectiveness of using 3 hollow compression screws combined with 1 screw off-axis fixation under the guidance of three-dimensional (3D) printed guide plate with mortise-tenon joint structure (mortise-tenon joint plate) for the treatment of Pauwels type Ⅲ femoral neck fractures. METHODS: A clinical data of 78 patients with Pauwels type Ⅲ femoral neck fractures, who were admitted between August 2022 and August 2023 and met the selection criteria, was retrospectively analyzed. The operations were assisted with mortise-tenon joint plates in 26 cases (mortise-tenon joint plate group) and traditional guide plates in 28 cases (traditional plate group), and without guide plates in 24 cases (control group). There was no significant difference in the baseline data of gender, age, body mass index, cause of injury, and fracture side between groups ( P>0.05). The operation time, intraoperative blood loss, frequency of intraoperative fluoroscopy, incision length, incidence of postoperative deep vein thrombosis of lower extremity, pain visual analogue scale (VAS) score at 1 week after operation, and Harris score of hip joint at 3 months after operation were recorded and compared. X-ray re-examination was taken to check the quality of fracture reduction, fracture healing, and the shortening length of the femoral neck at 3 months after operation, and the incidences of internal fixation failure and osteonecrosis of the femoral head during operation. RESULTS: Compared with the control group, the operation time, intraoperative blood loss, and frequency of intraoperative fluoroscopy reduced in the two plate groups, and the quality of fracture reduction was better, but the incision was longer, and the differences were significant ( P<0.05). The operation time and intraoperative blood loss were significantly higher in the traditional plate group than in the mortise-tenon joint plate group ( P<0.05), the incision was significantly longer ( P<0.05); and the difference in fracture reduction quality and the frequency of intraoperative fluoroscopy was not significant between two plate groups ( P>0.05). There was 1 case of deep vein thrombosis of lower extremity in the traditional plate group and 1 case in the control group, while there was no thrombosis in the mortise-tenon joint plate group. There was no significant difference in the incidence between groups ( P>0.05). All patients were followed up 12-15 months (mean, 13 months). There was no significant difference in VAS score at 1 week and Harris score at 3 months between groups ( P>0.05). Compared with the control group, the fracture healing time and the length of femoral neck shortening at 3 months after operation were significantly shorter in the two plate groups ( P<0.05). There was no significant difference between the two plate groups ( P>0.05). There was no significant difference in the incidences of non-union fractures, osteonecrosis of the femoral head, or internal fixation failure between groups ( P>0.05). CONCLUSION For Pauwels type Ⅲ femoral neck fractures, the use of 3D printed guide plate assisted reduction and fixation can shorten the fracture healing time, reduce the incidence of postoperative complications, and be more conducive to the early functional exercise of the affected limb. Compared with the traditional guide plate, the mortise-tenon joint plate can reduce the intraoperative bleeding and shorten the operation time.
Humans ; Femoral Neck Fractures/diagnostic imaging* ; Bone Plates ; Fracture Fixation, Internal/instrumentation* ; Male ; Female ; Retrospective Studies ; Middle Aged ; Bone Screws ; Adult ; Aged ; Treatment Outcome ; Printing, Three-Dimensional ; Operative Time

Drug repurposing offers a promising alternative to traditional drug development and significantly reduces costs and timelines by identifying new therapeutic uses for existing drugs. However, the current approaches often rely on limited data sources and simplistic hypotheses, which restrict their ability to capture the multi-faceted nature of biological systems. This study introduces adaptive multi-view learning (AMVL), a novel methodology that integrates chemical-induced transcriptional profiles (CTPs), knowledge graph (KG) embeddings, and large language model (LLM) representations, to enhance drug repurposing predictions. AMVL incorporates an innovative similarity matrix expansion strategy and leverages multi-view learning (MVL), matrix factorization, and ensemble optimization techniques to integrate heterogeneous multi-source data. Comprehensive evaluations on benchmark datasets (Fdataset, Cdataset, and Ydataset) and the large-scale iDrug dataset demonstrate that AMVL outperforms state-of-the-art (SOTA) methods, achieving superior accuracy in predicting drug-disease associations across multiple metrics. Literature-based validation further confirmed the model's predictive capabilities, with seven out of the top ten predictions corroborated by post-2011 evidence. To promote transparency and reproducibility, all data and codes used in this study were open-sourced, providing resources for processing CTPs, KG, and LLM-based similarity calculations, along with the complete AMVL algorithm and benchmarking procedures. By unifying diverse data modalities, AMVL offers a robust and scalable solution for accelerating drug discovery, fostering advancements in translational medicine and integrating multi-omics data. We aim to inspire further innovations in multi-source data integration and support the development of more precise and efficient strategies for advancing drug discovery and translational medicine.