The role of VEGF-C/D and Flt-4 in the lymphatic metastasis of early-stage invasive cervical carcinoma

<p>Abstract</p> <p>Background</p> <p>To investigate the role of vascular endothelial growth factors (VEGF)-C/D and their receptor Flt-4 in the lymphatic metastasis of early-stage invasive cervical carcinoma.</p> <p>Methods</p> <p>Immunohistochemical (IHC) staining with the antibodies against VEGF-C, VEGF-D, and Flt-4 was used to examine the expression of them in 97 cases of early-stage cervical carcinoma (Ia-IIa). Meanwhile, the lymphatic vessel density (LVD) was measured using the antibody against lymphatic vessel endothelial hyaluronan receptor-1 (LYVE-1). We then analyzed the correlation between Flt-4-positive vessel density (FVD), LVD and clinicopathological features of the tumors.</p> <p>Results</p> <p>(1) The positive rates of VEGF-C, VEGF-D, and Flt-4 were 57.7%, 60.8%, and 52.6% in the cervical tumor samples, respectively. (2) The expression levels of VEGF-C, VEGF-D, and Flt-4 were significantly correlated with lymphatic metastasis and lymphatic vessel invasion. LVD was significantly associated with lymph node metastasis and lymphatic vessel invasion. On the other hand, FVD was strongly associated with clinical staging. (3) The expression levels of VEGF-C and VEGF-D were significantly correlated with LVD and FVD, while Flt-4 levels showed no correlation with LVD or FVD.</p> <p>Conclusion</p> <p>VEGF-C/D and Flt-4 may play an important role in the process of lymphatic metastasis of early-stage invasive cervical carcinoma through paracrine and autocrine mechanisms.</p

CrossFusion: Interleaving Cross-modal Complementation for Noise-resistant 3D Object Detection

The combination of LiDAR and camera modalities is proven to be necessary and typical for 3D object detection according to recent studies. Existing fusion strategies tend to overly rely on the LiDAR modal in essence, which exploits the abundant semantics from the camera sensor insufficiently. However, existing methods cannot rely on information from other modalities because the corruption of LiDAR features results in a large domain gap. Following this, we propose CrossFusion, a more robust and noise-resistant scheme that makes full use of the camera and LiDAR features with the designed cross-modal complementation strategy. Extensive experiments we conducted show that our method not only outperforms the state-of-the-art methods under the setting without introducing an extra depth estimation network but also demonstrates our model's noise resistance without re-training for the specific malfunction scenarios by increasing 5.2\% mAP and 2.4\% NDS

Retrieval-Enhanced Visual Prompt Learning for Few-shot Classification

Prompt learning has become a popular approach for adapting large vision-language models, such as CLIP, to downstream tasks. Typically, prompt learning relies on a fixed prompt token or an input-conditional token to fit a small amount of data under full supervision. While this paradigm can generalize to a certain range of unseen classes, it may struggle when domain gap increases, such as in fine-grained classification and satellite image segmentation. To address this limitation, we propose Retrieval-enhanced Prompt learning (RePrompt), which introduces retrieval mechanisms to cache the knowledge representations from downstream tasks. we first construct a retrieval database from training examples, or from external examples when available. We then integrate this retrieval-enhanced mechanism into various stages of a simple prompt learning baseline. By referencing similar samples in the training set, the enhanced model is better able to adapt to new tasks with few samples. Our extensive experiments over 15 vision datasets, including 11 downstream tasks with few-shot setting and 4 domain generalization benchmarks, demonstrate that RePrompt achieves considerably improved performance. Our proposed approach provides a promising solution to the challenges faced by prompt learning when domain gap increases. The code and models will be available

Dataset: Global seamless tidal simulation using a 3D unstructured-grid model

Dataset: We present a new 3D unstructured-grid global ocean model to study both tidal and non-tidal processes, with a focus on the total water elevation. Unlike existing global ocean models, the new model resolves estuaries and rivers down to ~8m without the need for grid nesting. The model is validated with both satellite and in-situ observations for elevation, temperature and salinity. Tidal elevation solutions have a mean complex RMSE of 4.2 cm for M2 and 5.4 cm for all 5 major constituents in the deep ocean (the RMSEs for the other 4 constituents (S2, N2, K1, O1) are respectively: 2.05cm, 0.93cm, 2.08cm, 1.34cm). The non-tidal residual assessed by a tide gauge dataset (GESLA) has a mean RMSE of 7 cm. For the first time ever, we demonstrate the potential for seamless simulation, on a single mesh, from the global ocean into several estuaries along the US west coast. The model is able to accurately capture the total elevation, even at some upstream stations. The model can therefore potentially serve as the backbone in a global tide-surge and compound flooding forecasting framework

Supreme laryngeal mask airway for cesarean section under general anesthesia: a 10-year retrospective cohort study

BackgroundPrevious research showed the use of supraglottic airways in obstetric anesthesia. The relevant evidence of laryngeal mask airway (LMA) on maternal and neonatal outcomes is still limited. We aimed to assess the maternal and neonatal outcomes when the LMA Supreme was used for cesarean section under general anesthesia.MethodsWe included all patients who underwent general anesthesia for cesarean section between January 2010 and December 2019. Propensity score matching was used to reduce potential bias from non-random selection of airway intervention. The primary outcome was adverse maternal and neonatal outcomes defined as maternal regurgitation, aspiration, hypoxemia, and low neonatal Apgar scores. Secondary outcomes included patient admission to the intensive care unit, neonate required tracheal intubation, external cardiac massage, and admission to the neonatal intensive care unit.ResultsA total of 723 patients were included in the analysis; of whom, 221 received Supreme laryngeal mask airway (LMA group) and 502 were intubated with an endotracheal tube (ETT group). After propensity score matching, 189 patients remained in each group. No episode of regurgitation and aspiration occurred in both groups. There was no difference in the rates of Apgar score below 7 at 1 min (14.3% LMA group vs. 15.3% ETT group, OR 0.931, 95% CI 0.574 to 1.510, P = 0.772) and 5 min (3.7% vs. 4.2%, OR 0.875, 95% CI 0.324 to 2.365, P = 0.792). No difference was observed in the secondary outcomes between the two groups.ConclusionThe LMA Supreme was not associated with higher adverse maternal and neonatal outcomes when compared to an endotracheal tube for cesarean section under general anesthesia. It might be considered an alternative to tracheal intubation in obstetric practice