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Reproductive toxicity is one of the important issues in chemical safety. Traditional laboratory testing methods are costly and time-consuming with raised ethical issues. Only a few in silico models have been reported to predict human reproductive toxicity, but none of them make full use of the topological information of compounds. In addition, most existing atom-based graph neural network methods focus on attributing model predictions to individual nodes or edges rather than chemically meaningful fragments or substructures. In current studies, we develop a novel fragment-based graph transformer network (FGTN) approach to generate the QSAR model of human reproductive toxicity by considering internal topological structure information of compounds. In the FGTN model, the compound is represented by a graph architecture using fragments to be nodes and bonds linking two fragments to be edges. A super molecule-level node is further proposed to connect all fragment nodes by undirected edges, obtaining global molecular features from fragment embeddings. The FGTN model achieved an accuracy (ACC) of 0.861 and an area under the receiver operating characteristic curve (AUC) value of 0.914 on nonredundant blind tests, outperforming traditional fingerprint-based machine learning models and atom-based GCN model. The FGTN model can attribute toxic predictions to fragments, generating specific structural alerts for the positive compound. Moreover, FGTN may also have the capability to distinguish various chemical isomers. We believe that FGTN can be used as a reliable and effective tool for human reproductive toxicity prediction in contribution to the advancement of chemical safety assessment.

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Background: Chemicals may lead to acute liver injuries, posing a serious threat to human health. Achieving the precise safety profile of a compound is challenging due to the complex and expensive testing procedures. In silico approaches will aid in identifying the potential risk of drug candidates in the initial stage of drug development and thus mitigating the developmental cost. Methods: In current studies, QSAR models were developed for hepatotoxicity predictions using the ensemble strategy to integrate machine learning (ML) and deep learning (DL) algorithms using various molecular features. A large dataset of 2588 chemicals and drugs was randomly divided into training (80%) and test (20%) sets, followed by the training of individual base models using diverse machine learning or deep learning based on three different kinds of descriptors and fingerprints. Feature selection approaches were employed to proceed with model optimizations based on the model performance. Hybrid ensemble approaches were further utilized to determine the method with the best performance. Results: The voting ensemble classifier emerged as the optimal model, achieving an excellent prediction accuracy of 80.26%, AUC of 82.84%, and recall of over 93% followed by bagging and stacking ensemble classifiers method. The model was further verified by an external test set, internal 10-fold cross-validation, and rigorous benchmark training, exhibiting much better reliability than the published models. Conclusion: The proposed ensemble model offers a dependable assessment with a good performance for the prediction regarding the risk of chemicals and drugs to induce liver damage.

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Hepatocellular carcinoma (HCC) is a hypervascular tumor, and accumulating evidence has indicated that stimulation of angiogenesis by hepatitis B virus (HBV) may contribute to HCC malignancy. The small protein of hepatitis B virus surface antigen (HBsAg), SHBs, is the most abundant HBV protein and has a close clinical association with HCC; however, whether SHBs contributes to HCC angiogenesis remains unknown. This study reports that the forced expression of SHBs in HCC cells promoted xenograft tumor growth and increased the microvessel density (MVD) within the tumors. Consistently, HBsAg was also positively correlated with MVD counts in HCC patients' specimens. The conditioned media from the SHBs-transfected HCC cells increased the capillary tube formation and migration of human umbilical vein endothelial cells (HUVECs). Intriguingly, the overexpression of SHBs increased vascular endothelial growth factor A (VEGFA) expression at both the mRNA and protein levels. Higher VEGFA expression levels were also observed in xenograft tumors transplanted with SHBs-expressing HCC cells and in HBsAg-positive HCC tumor tissues than in their negative controls. As expected, in the culture supernatants, the secretion of VEGFA was also significantly enhanced from HCC cells expressing SHBs, which promoted HUVEC migration and vessel formation. Furthermore, all three unfolded protein response (UPR) sensors, inositol-requiring enzyme 1α (IRE1α), protein kinase RNA-like endoplasmic reticulum (ER) kinase (PERK), and activating transcription factor 6 (ATF6), associated with ER stress were found to be activated in SHBs-expressing cells and correlated with VEGFA protein expression and secretion. Taken together, these results suggest an important role of SHBs in HCC angiogenesis and may highlight a potential target for preventive and therapeutic intervention for HBV-related HCC and its malignant progression. IMPORTANCE Chronic hepatitis B virus infection is one of the important risk factors for the development and progression of hepatocellular carcinoma (HCC). HCC is characteristic of hypervascularization even at early phases of the disease due to the overexpression of angiogenic factors like vascular endothelial growth factor A (VEGFA). However, a detailed mechanism of HBV-induced angiogenesis remains to be established. In this study, we demonstrate for the first time that the most abundant HBV protein, i.e., small surface antigen (SHBs), can enhance the angiogenic capacity of HCC cells by the upregulation of VEGFA expression both in vitro and in vivo. Mechanistically, SHBs induced endoplasmic reticulum (ER) stress, which consequently activated unfolded protein response (UPR) signaling to increase VEGFA expression and secretion. This study suggests that SHBs plays an important proangiogenic role in HBV-associated HCC and may represent a potential target for antiangiogenic therapy in HCC.

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This study analysed the landing performance and muscle activity of athletes in forefoot strike (FFS) and rearfoot strike (RFS) patterns. Ten male college participants were asked to perform two foot strikes patterns, each at a running speed of 6 km/h. Three inertial sensors and five EMG sensors as well as one 24 G accelerometer were synchronised to acquire joint kinematics parameters as well as muscle activation, respectively. In both the FFS and RFS patterns, according to the intraclass correlation coefficient, excellent reliability was found for landing performance and muscle activation. Paired t tests indicated significantly higher ankle plantar flexion in the FFS pattern. Moreover, biceps femoris (BF) and gastrocnemius medialis (GM) activation increased in the pre-stance phase of the FFS compared with that of RFS. The FFS pattern had significantly decreased tibialis anterior (TA) muscle activity compared with the RFS pattern during the pre-stance phase. The results demonstrated that the ankle strategy focused on controlling the foot strike pattern. The influence of the FFS pattern on muscle activity likely indicates that an athlete can increase both BF and GM muscles activity. Altered landing strategy in cases of FFS pattern may contribute both to the running efficiency and muscle activation of the lower extremity. Therefore, neuromuscular training and education are required to enable activation in dynamic running tasks.

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BACKGROUND@#Methylene blue is the most commonly used tracer for sentinel lymph node (SLN) biopsy (SLNB) in China. This study aimed to investigate the feasibility of clinical application of SLNB using methylene blue dye (MBD) for early breast cancer and the prognosis of patients with different SLN and non-SLN statuses.@*METHODS@#We retrospectively analyzed the clinicopathological data of patients with early breast cancer treated at the Peking University First Hospital between 2013 and 2018. We calculated the SLN identification rate (IR) in SLNB with MBD and the false-negative rate (FNR), and analyzed the prognosis of patients with different SLN and non-SLN statuses using Kaplan-Meier curves.@*RESULTS@#Between January 2013 and December 2018, 1603 patients with early breast cancer underwent SLNB with MBD. The SLN IR was 95.8% (1536/1603). Two SLNs (median) were detected per patient. There were significant differences in FNR between patients with SLN micrometastasis and macrometastasis (19.0% vs. 4.5%, χ2 = 12.771, P < 0.001). Chi-square test showed that there were significant differences in SLN successful detection rates among patients with different vascular tumor embolism status (96.3% vs. 90.8%, χ2 = 9.013, P = 0.003) and tumor (T) stages (96.6% vs. 94.1%, χ2 = 5.189, P = 0.023). Multivariate analysis showed that vascular tumor embolism was the only independent factor for SLN successful detection (odds ratio: 0.440, 95% confidence interval: 0.224-0.862, P = 0.017). Survival analysis showed a significant difference in disease-free survival (DFS) between patients with non-SLN metastasis and patients without non-SLN metastasis (P = 0.006).@*CONCLUSION@#Our single-center data show that, as a commonly used tracer in SLNB in China, MBD has an acceptable SLN IR and a low FNR in frozen sections. This finding is consistent with reports of dual tracer-guided SLNB. Positive SLNs with non-SLN metastasis are associated with DFS.

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RATIONALE: A horseshoe kidney is the most common congenital fusion abnormality in the kidney, occurring in approximately 1 in 400 live births. Several complications including renal malignancies, ureteropelvic junction obstruction, urolithiasis, vesicoureteral reflux, and hydronephrosis can occur in this patient population. PATIENT CONCERNS: A 28-year-old woman was admitted to hospital because of chronic left low back pain. Microscopic hematuria was not seen. Computed tomography showed the horseshoe kidney and left hydronephrosis. DIAGNOSES: On the basis of these findings and clinical manifestations, the final diagnosis was the horseshoe kidney with left renal hydronephrosis and inflammation. INTERVENTIONS: A retroperitoneoscopic nephrectomy on the left kidney was performed. OUTCOMES: Histopathological examination of the specimen confirmed massive dilatation of the pelvicaliceal system and chronic pyelonephritic inflammation. The patient was discharged on the 7th postoperative day with no complications and no back pain. She remained well at 3 months with normal activity and good cosmetic result. LESSONS: Retroperitoneoscopic nephrectomy can be a safe and minimally invasive surgery for horseshoe kidney treatment.

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