OBJECTIVES: To construct an intelligent analysis model for classifying fetal orientation during intrapartum ultrasound videos based on multi-feature fusion. METHODS: The proposed model consists of the Input, Backbone Network and Classification Head modules. The Input module carries out data augmentation to improve the sample quality and generalization ability of the model. The Backbone Network was responsible for feature extraction based on Yolov8 combined with CBAM, ECA, PSA attention mechanism and AIFI feature interaction module. The Classification Head consists of a convolutional layer and a softmax function to output the final probability value of each class. The images of the key structures (the eyes, face, head, thalamus, and spine) were annotated with frames by physicians for model training to improve the classification accuracy of the anterior occipital, posterior occipital, and transverse occipital orientations. RESULTS: The experimental results showed that the proposed model had excellent performance in the tire orientation classification task with the classification accuracy reaching 0.984, an area under the PR curve (average accuracy) of 0.993, and area under the ROC curve of 0.984, and a kappa consistency test score of 0.974. The prediction results by the deep learning model were highly consistent with the actual classification results. CONCLUSIONS The multi-feature fusion model proposed in this study can efficiently and accurately classify fetal orientation in intrapartum ultrasound videos.
Humans ; Female ; Ultrasonography, Prenatal/methods* ; Pregnancy ; Fetus/diagnostic imaging* ; Neural Networks, Computer ; Video Recording

Acute respiratory distress syndrome (ARDS) is a common respiratory emergency, but current clinical treatment remains at the level of symptomatic support and there is a lack of effective targeted treatment measures. Our previous study confirmed that inhalation of hydrogen gas can reduce the acute lung injury of ARDS, but the application of hydrogen has flammable and explosive safety concerns. Drinking hydrogen-rich liquid or inhaling hydrogen gas has been shown to play an important role in scavenging reactive oxygen species and maintaining mitochondrial quality control balance, thus improving ARDS in patients and animal models. Coral calcium hydrogenation (CCH) is a new solid molecular hydrogen carrier prepared from coral calcium (CC). Whether and how CCH affects acute lung injury in ARDS remains unstudied. In this study, we observed the therapeutic effect of CCH on lipopolysaccharide (LPS) induced acute lung injury in ARDS mice. The survival rate of mice treated with CCH and hydrogen inhalation was found to be comparable, demonstrating a significant improvement compared to the untreated ARDS model group. CCH treatment significantly reduced pulmonary hemorrhage and edema, and improved pulmonary function and local microcirculation in ARDS mice. CCH promoted mitochondrial peripheral division in the early course of ARDS by activating mitochondrial thioredoxin 2 (Trx2), improved lung mitochondrial dysfunction induced by LPS, and reduced oxidative stress damage. The results indicate that CCH is a highly efficient hydrogen-rich agent that can attenuate acute lung injury of ARDS by improving the mitochondrial function through Trx2 activation.

Objective To analyze and explore the analgesic effect of Angelica dahurica in neuropathic pain and its regulatory effect on the Mas-related G-protein coupled receptor member D(MrgprD)-transient receptor potential ankyrin 1(TRPA1)signaling pathway,using a mouse model of sciatic nerve chronic constriction injury(CCI).Methods A CCI mouse model was prepared by sterile surgical ligation and wrapping of the sciatic nerve in 30 mice.Pain-related behavioral changes induced by mechanical stimulation were detected by the VonFrey method,and the thermal hyperalgesic effects of Angelica dahurica were evaluated by thermal radiation experiments.The effects of Angelica dahurica on the protein expression levels MrgprD and TRPA1,the number of dorsal root ganglion(DRG)positive neurons,and mRNA levels of MrgprD and TRPA1 in mice were detected by Western Blot,immunofluorescence,and reverse transcription-polymerase chain reaction,respectively.Differences in fluorescence signal intensity in HEK293 cells after single transfection and co-transfection with MrgprD and TRPA1 plasmids,respectively,were analyzed by calcium imaging experiments.Results A total of 25 CCI mouse models were successfully prepared,with a modeling rate of 83.33％(25/30).The mechanical threshold and foot retraction latency were significantly higher in CCI mice treated with Angelica dahurica compared with the control group(P＜0.05).Expression levels of MrgprD and TRPA1 proteins were significantly lower in CCI mice treated with Angelica dahurica than in the control group(P＜0.05).The number of MrgprD-and TRPA1-positive neurons in the DRG was significantly lower group(P＜0.05)and the mRNA levels of MrgprD and TRPA1 were also significantly lower in CCI mice treated with Angelica dahurica than in the control group(P＜0.05).The fluorescence intensity was significantly higher in HEK293 cells co-transfected with MrgprD and TRPA1 plasmids than in single-transfected and blank control cells(P＜0.05).Conclusions This study demonstrated that the MrgprD-TRPA1 pathway is an important target for neuropathic pain,and indicated that Angelica dahurica can inhibit neuropathic pain by regulating this signal transduction pathway.These result provide a foundation for further research on the development of new clinical analgesic drugs and analgesic mechanisms.

Objective:To compare the therapeutic outcomes of anterior cruciate ligament (ACL) reconstruction between small-sized and normal-sized patients using grafts of different diameters.Methods:The data of 63 patients were selected who had undergone ACL reconstruction at Department of Joint/Sports Medicine, The Third Affiliated Hospital to Southern Medical University from January 2018 to December 2018. They were divided into 2 groups according to body size. In the observation group of 26 small-sized patients who were shorter and lighter, there were 18 males and 8 females with an age of (29.4±8.5) years and a graft of 7.5 mm in diameter was used. In the control group of 37 normal-sized patients, there were 26 males and 11 females with an age of (28.8±8.2) years and a graft of 8.0 mm in diameter was used. The 2 groups were compared in terms of failure rate, kinematic changes in the affected knee joint (taking the 63 normal knee joints in the 2 groups as controls), isokinetic muscle strength and Lysholm knee score.Results:There was no significant difference in the general data or follow-up time between the 2 groups other than height and weight ( P>0.05), indicating comparability between the 2 groups. In the control and observation groups, the failure rates were 2.7% (1/37) and 3.8% (1/26), and the Lysholm knee scores 2 years after surgery (86.6±10.1) points and (90.2±6.9) points, respectively, showing no statistical significance ( P>0.05). The range of flexion and extension was 56.30° (51.10°, 58.10°) in the observation group, significantly smaller than that in the control group [60.15°(58.95°, 63.08°)] and that for a normal knee joint [59.00° (56.45°, 63.00°]; the internal and external displacement in the observation group [7.30 (5.30, 8.30) mm] was significantly smaller than that for a normal knee joint [9.00 (7.00, 12.00) mm]; the external rotation in the observation group [0.97°(-1.59°, 3.01°)] was significantly larger than that for a normal knee joint [-1.54°(-5.30°, 2.28°)]; the knee extension muscle strength at 60°/s in the observation group was (65%±19%), significantly smaller than that in the control group (78%±18%) (all P<0.05). Conclusion:When small-sized and normal-sized patients use a 7.5 mm graft and a 8.0 mm graft respectively in ACL reconstruction, similar therapeutic outcomes can be expected.

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipe-line and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to gen-erate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.