DeepICP: An End-to-End Deep Neural Network for 3D Point Cloud Registration

We present DeepICP - a novel end-to-end learning-based 3D point cloud registration framework that achieves comparable registration accuracy to prior state-of-the-art geometric methods. Different from other keypoint based methods where a RANSAC procedure is usually needed, we implement the use of various deep neural network structures to establish an end-to-end trainable network. Our keypoint detector is trained through this end-to-end structure and enables the system to avoid the inference of dynamic objects, leverages the help of sufficiently salient features on stationary objects, and as a result, achieves high robustness. Rather than searching the corresponding points among existing points, the key contribution is that we innovatively generate them based on learned matching probabilities among a group of candidates, which can boost the registration accuracy. Our loss function incorporates both the local similarity and the global geometric constraints to ensure all above network designs can converge towards the right direction. We comprehensively validate the effectiveness of our approach using both the KITTI dataset and the Apollo-SouthBay dataset. Results demonstrate that our method achieves comparable or better performance than the state-of-the-art geometry-based methods. Detailed ablation and visualization analysis are included to further illustrate the behavior and insights of our network. The low registration error and high robustness of our method makes it attractive for substantial applications relying on the point cloud registration task.Comment: 10 pages, 6 figures, 3 tables, typos corrected, experimental results updated, accepted by ICCV 201

L1 cell adhesion molecule high expression is associated with poor prognosis in surgically resected brain metastases from lung adenocarcinoma

Objectives: Accurate prognosis assessment across the heterogeneous population of brain metastases is very important, which may facilitate clinical decision-making and appropriate stratification of future clinical trials. Previous studies have shown the L1 Cell Adhesion Molecule (L1CAM) is potentially involved in human malignancies of multiple different samples and unfavorable survival. However, no data of L1CAM are available for the brain metastases from lung adenocarcinoma, especially for the one with neurosurgical resection. Method: The authors investigated the L1CAM expression in cranial metastatic lesions for patients with brain metastases from lung adenocarcinoma after neurosurgical resection using tissue microarrays that were obtained from the Department of Neurosurgery at the Cancer Hospital of the Chinese Academy of Medical Sciences. Furthermore, the relationship between L1CAM expression and clinic-pathological parameters, including overall survival time, was analyzed to assess the prognostic value of L1CAM. Results: L1CAM high expression was found in 62.30% of brain metastases from lung adenocarcinoma and significantly correlated with brain metastasis number (p = 0.028) and Lung-molGPA score (p = 0.042). Moreover, L1CAM expression was an independent predictor of survival for brain metastases after neurosurgical resection in a multivariate analysis. Patients with L1CAM high expression had unfavorable overall survival time (p = 0.016). In addition, the multivariate analysis also showed age and extracranial transfer were also the independent prognostic factors for this type of patient with brain metastases. Conclusions: A subset of brain metastases from lung adenocarcinoma aberrantly expresses L1CAM. L1CAM is a novel independent prognostic factor for brain metastasis from lung adenocarcinoma after neurosurgical resection

Defining the threshold: triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio’s non-linear impact on tubular atrophy in primary membranous nephropathy

BackgroundHyperlipidemia is common in primary membranous nephropathy (PMN) patients, and tubular atrophy (TA) is an unfavorable prognostic factor. However, the correlation between the triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio and TA is controversial. Therefore, our study aimed to investigate the association between the TG/HDL-C ratio and TA in PMN patients.MethodsWe conducted a cross-sectional study and collected data from 363 PMN patients at Shenzhen Second People’s Hospital from January 2008 to April 2023. The primary objective was to evaluate the independent correlation between the TG/HDL-C ratio and TA using binary logistic regression model. We used a generalized additive model along with smooth curve fitting and multiple sensitivity analyses to explore the relationship between these variables. Additionally, subgroup analyses were conducted to delve deeper into the results.ResultsOf the 363 PMN patients, 75 had TA (20.66%). The study population had a mean age of 46.598 ± 14.462 years, with 217 (59.78%) being male. After adjusting for sex, age, BMI, hypertension, history of diabetes, smoking, alcohol consumption, UPRO, eGFR, HB, FPG, and ALB, we found that the TG/HDL-C ratio was an independent risk factor for TA in PMN patients (OR=1.29, 95% CI: 1.04, 1.61, P=0.0213). A non-linear correlation was observed between the TG/HDL-C ratio and TA, with an inflection point at 4.25. The odds ratios (OR) on the left and right sides of this inflection point were 1.56 (95% CI: 1.17, 2.07) and 0.25 (95% CI: 0.04, 1.54), respectively. Sensitivity analysis confirmed these results. Subgroup analysis showed a consistent association between the TG/HDL-C ratio and TA, implying that factors such as gender, BMI, age, UPRO, ALB, hypertension and severe nephrotic syndrome had negligible effects on the link between the TG/HDL-C ratio and TA.ConclusionOur study demonstrates a non-linear positive correlation between the TG/HDL-C ratio and the risk of TA in PMN patients, independent of other factors. Specifically, the association is more pronounced when the ratio falls below 4.25. Based on our findings, it would be advisable to decrease the TG/HDL-C ratio below the inflection point in PMN patients as part of treatment strategies

Mechanical and structural investigation of porous bulk metallic glasses

The intrinsic properties of advanced alloy systems can be altered by changing their microstructural features. Here, we present a highly efficient method to produce and characterize structures with systematically-designed pores embedded inside. The fabrication stage involves a combination of photolithography and deep reactive ion etching of a Si template replicated using the concept of thermoplastic forming. Pt- and Zr-based bulk metallic glasses (BMGs) were evaluated through uniaxial tensile test, followed by scanning electron microscope (SEM) fractographic and shear band analysis. Compositional investigation of the fracture surface performed via energy dispersive X-ray spectroscopy (EDX), as well as Auger spectroscopy (AES) shows a moderate amount of interdiffusion (5 at.% maximum) of the constituent elements between the deformed and undeformed regions. Furthermore, length-scale effects on the mechanical behavior of porous BMGs were explored through molecular dynamics (MD) simulations, where shear band formation is observed for a material width of 18 nm

Downregulation of T-cell cytotoxic marker IL18R1 promotes cancer proliferation and migration and is associated with dismal prognosis and immunity in lung squamous cell carcinoma

Immunotherapy can improve the survival of patients with advanced lung squamous cell carcinoma (LUSC). T cytotoxic cells are one of the main members of the immune microenvironment. Herein, we aimed to identify the roles of T-cell cytotoxic markers interleukin 18 (IL18) receptor 1 (IL18R1) in the LUSC progression using bioinformatics, clinical tissue specimen, and cell experiment. We assessed the association between the IL18R1 expression and immune infiltration and IL18R1-related competing RNA network. The IL18R1 expression was downregulated in the LUSC tissues. The IL18R1 expression downregulation was associated with diagnosis and short overall survival and disease-specific survival, and it was also an independent risk factor for dismal survival time in LUSC. IL18R1-related nomograms predicted the survival time of patients with LUSC. IL18R1 overexpression inhibited the proliferation, migration, and invasion of LUSC cells. The IL18R1 expression was significantly associated with the microenvironment (stromal, immune, and estimate scores), immune cells (such as the T cells, cytotoxic cells, CD8 T cells), and immune cell markers (such as the CD8A, PD-1, and CTLA4) in LUSC. AC091563.1 and RBPMS-AS1 downregulation was positively associated with the IL18R1 expression, negatively associated with the miR-128-3p expression, and associated with short disease-specific survival and progression in LUSC. In conclusion, IL18R1 was significantly downregulated and associated with the prognosis and immune microenvironment. IL18R1 overexpression inhibits the growth and migration of cancer cells in LUSC. Furthermore, AC091563.1 and RBPMS-AS1 might compete with IL18R1 to bind miR-128-3p for participating in LUSC progression. These results showed that IL18R1 is a biomarker for evaluating the prognosis of patients with LUSC