Concurrent chemoradiotherapyof different radiation doses and different irradiation fields for locally advanced thoracic esophageal squamous cell carcinoma: A randomized, multicenter, phase III clinical trial.

BACKGROUND: Concurrent chemoradiotherapy (CCRT) is the standard treatment for locally advanced esophageal squamous cell carcinoma (ESCC). However, the optimal radiotherapy regimen, particularly in terms of total dose and planned range of irradiation field, remains unclear. This phase III clinical trial aimed to compare the survival benefits between different radiation doses and different target fields. METHODS: This trial compared two aspects of radiation treatment, total dose and field, using a two-by-two factorial design. The high-dose (HD) group received 59.4 Gy radiation, and the standard-dose (SD) group received 50.4 Gy. The involved field irradiation (IFI) group and elective nodal irradiation (ENI) group adopted different irradiation ranges. The participants were assigned to one of the four groups (HD+ENI, HD+IFI, SD+ENI and SD+IFI). The primary endpoint was overall survival (OS), and the secondary endpoints included progression-free survival (PFS). The synergy indexwas used to measure the interaction effect between dose and field. RESULTS: The interaction analysis did not reveal significant synergistic effects between the dose and irradiation field. In comparison to the target field, patients in IFI or ENI showed similar OS (hazard ratio [HR] = 0.99, 95% CI: 0.80-1.23, p = 0.930) and PFS (HR = 1.02, 95% CI: 0.82-1.25). The HD treatment did not show significantly prolonged OS compared with SD (HR = 0.90, 95% CI: 0.72-1.11, p = 0.318), but it suggested improved PFS (25.2 months to 18.0 months). Among the four groups, the HD+IFI group presented the best survival, while the SD+IFI group had the worst prognosis. No significant difference in the occurrence of severe adverse events was found in dose or field comparisons. CONCLUSIONS: IFI demonstrated similar treatment efficacy to ENI in CCRT of ESCC. The HD demonstrated improved PFS, but did not significantly improve OS. The dose escalation based on IFI (HD+IFI) showed better therapeutic efficacy than the current recommendation (SD+ENI) and is worth further validation.

A comprehensive study on solvent effect and establishment of n-hexane solvent system based normal-phase liquid chromatography × reversed-phase liquid chromatography for isolation of natural products.

Reversed-phase liquid chromatography (RPLC) represents an effective separation method, and is widely employed as the second dimension in most 2D-LC systems. Nevertheless, the solvent effect of the eluent from the first dimension on RPLC presents a challenge to the online coupling of RPLC with other separation modes, particularly normal phase liquid chromatography (NPLC). To address this issue, a comprehensive understanding of the solvent effect is essential. Following a comprehensive investigation into the influence of diverse solvents on RPLC separations, it was observed that alkane solvents, such as n-hexane, exhibited a pronounced tendency to be retained during RPLC separations. Such solvents do not affect the analysis of samples with weaker retention abilities than themselves, even when a large injection volume is used. The solvent effect was thus reduced by employing n-hexane-based solvent dilution. Leveraging the markedly enhanced solvent tolerance and extensive injection volume in RPLC, a versatile integration of the NPLC and RPLC was devised, necessitating merely a purge pump and a 10 port 2 position valve in conjunction with two sample loops. The novel 2D-LC system was then deployed for the analysis of propolis, a naturally occurring complex sample, and demonstrated remarkable separation efficiency.

Segmentation and Vascular Vectorization for Coronary Artery by Geometry-based Cascaded Neural Network.

Segmentation of the coronary artery is an important task for the quantitative analysis of coronary computed tomography angiography (CCTA) images and is being stimulated by the field of deep learning. However, the complex structures with tiny and narrow branches of the coronary artery bring it a great challenge. Coupled with the medical image limitations of low resolution and poor contrast, fragmentations of segmented vessels frequently occur in the prediction. Therefore, a geometry-based cascaded segmentation method is proposed for the coronary artery, which has the following innovations: 1) Integrating geometric deformation networks, we design a cascaded network for segmenting the coronary artery and vectorizing results. The generated meshes of the coronary artery are continuous and accurate for twisted and sophisticated coronary artery structures, without fragmentations. 2) Different from mesh annotations generated by the traditional marching cube method from voxel-based labels, a finer vectorized mesh of the coronary artery is reconstructed with the regularized morphology. The novel mesh annotation benefits the geometry-based segmentation network, avoiding bifurcation adhesion and point cloud dispersion in intricate branches. 3) A dataset named CCA-200 is collected, consisting of 200 CCTA images with coronary artery disease. The ground truths of 200 cases are coronary internal diameter annotations by professional radiologists. Extensive experiments verify our method on our collected dataset CCA-200 and public ASOCA dataset, with a Dice of 0.778 on CCA-200 and 0.895 on ASOCA, showing superior results. Especially, our geometry-based model generates an accurate, intact and smooth coronary artery, devoid of any fragmentations of segmented vessels.

Insights into the Injectivity and Propagation Behavior of Preformed Particle Gel (PPG) in a Low-Medium-Permeability Reservoir.

Heterogeneous phase combined flooding (HPCF) has been a promising technology used for enhancing oil recovery in heterogeneous mature reservoirs. However, the injectivity and propagation behavior of preformed particle gel (PPG) in low-medium-permeability reservoir porous media is crucial for HPCF treatment in a low-medium-permeability reservoir. Thus, the injectivity and propagation behavior of preformed particle gel in a low-medium-permeability reservoir were systematically studied by conducting a series of sand pack flooding experiments. The matching factor (δ) was defined as the ratio of the average size of PPG particles to the mean size of pore throats and the pressure difference ratio (ß) was proposed to characterize the injectivity and propagation ability of PPG. The results show that with the increase in particle size and the decrease in permeability, the resistance factor and residual resistance factor increase. With the increase in the matching factor, the resistance factor and residual resistance factor increase. The higher the resistance factor and residual resistance factor are, the worse the injectivity of particles is. By fitting the relationship curve, PPG injection and propagation standards were established: when the matching coefficient is less than 55 and ß is less than 3.4, PPG can be injected; when the matching coefficient is 55-72 and ß is 3.4-6.5, PPG injection is difficult; when the matching coefficient is greater than 72 and ß is greater than 6.5, PPG cannot be injected Thus, the matching relationship between PPG particle size and reservoir permeability was obtained. This research will provide theoretical support for further EOR research and field application of heterogeneous phase combined flooding.

Autophagy Deficiency Induced by SAT1 Potentiates Tumor Progression in Triple-Negative Breast Cancer.

Aggressive triple-negative breast cancer (TNBC) still lacks approved targeted therapies, requiring more exploration of its underlying mechanisms. Previous studies have suggested a potential role of SAT1 (Spermidine/Spermine N1-acetyltransferase 1) in cancer, which needs to be further elucidated in breast cancer. In this study, highly expressed SAT1 in TNBC signified worse patient prognoses. And SAT1 knockdown effectively inhibited the proliferation and migration abilities of TNBC cells in vitro and in vivo. In terms of mechanism, the transcription factor JUN enhanced SAT1 transcriptional activity by binding to its promoter region. Then, SAT1 protein in the cytoplasm engaged in directly binding with YBX1 for sustaining YBX1 protein stability via deubiquitylation mediated by the E3 ligase HERC5. Further, SAT1 was found to suppress autophagy remarkably via stabilization of mTOR mRNA with the accumulation of YBX1-mediated methyl-5-cytosine (m5C) modification. These findings proved that SAT1 drives TNBC progression through the SAT1/YBX1/mTOR axis, which may provide a potential candidate for targeted therapy in advanced TNBC.

QL1209 (pertuzumab biosimilar) versus reference pertuzumab plus trastuzumab and docetaxel in neoadjuvant treatment for HER2-positive, ER/PR-negative, early or locally advanced breast cancer: A multicenter, randomized, double-blinded, parallel-controlled, phase III equivalence trial.

BACKGROUND: This randomized, parallel-controlled, double-blinded, phase III equivalence study evaluated the equivalence of a proposed pertuzumab biosimilar QL1209 to the pertuzumab (Perjeta®) each with trastuzumab and docetaxel in neoadjuvant treatment of early or locally advanced breast cancer patients with HER2-positive, ER/PR-negative. METHODS: Eligible patients were randomly (1:1) assigned to receive 4 cycles of neoadjuvant QL1209 or pertuzumab each with trastuzumab and docetaxel, and adjuvant treatment. The primary endpoint was total pathologic complete response (tpCR), with equivalence margins of 0.76 to 1.32. RESULTS: Among the 585 patients enrolled, 257 and 259 patients were assigned to the QL1209 and pertuzumab groups, respectively. The tpCR rates were comparable in the QL1209 (109/255, 42.75%; 90% CI 37.65 to 47.84) and pertuzumab (117/259, 45.17%; 90% CI 40.09 to 50.26) groups. The tpCR risk ratio was 0.95 (90% CI, 0.80 to 1.11), and the 90% CI fell within the predefined equivalence margin. The most common grade ≥3 treatment-related adverse event was decreased neutrophil count (10. 9% vs. 12.7%) in the QL1209 and pertuzumab groups. CONCLUSIONS: QL1209 demonstrated equivalent efficacy and comparable safety profile to the reference pertuzumab in neoadjuvant treatment of HER2-positive, ER/PR-negative, early, or locally advanced breast cancer. TRIAL REGISTRATION: Chinadrugtrials.org CTR20201073; ClinicalTrials.gov NCT04629846.

Early detection of nicosulfuron toxicity and physiological prediction in maize using multi-branch deep learning models and hyperspectral imaging.

The misuse of herbicides in fields can cause severe toxicity in maize, resulting in significant reductions in both yield and quality. Therefore, it is crucial to develop early and efficient methods for assessing herbicide toxicity, protecting maize production, and maintaining the field environment. In this study, we utilized maize crops treated with the widely used nicosulfuron herbicide and their hyperspectral images to develop the HerbiNet model. After 4 d of nicosulfuron treatment, the model achieved an accuracy of 91.37 % in predicting toxicity levels, with correlation coefficient R² values of 0.82 and 0.73 for soil plant analysis development (SPAD) and water content, respectively. Additionally, the model exhibited higher generalizability across datasets from different years and seasons, which significantly surpassed support vector machines, AlexNet, and partial least squares regression models. A lightweight model, HerbiNet-Lite, exhibited significantly low complexity using 18 spectral wavelengths. After 4 d of nicosulfuron treatment, the HerbiNet-Lite model achieved an accuracy of 87.93 % for toxicity prediction and R² values of 0.80 and 0.71 for SPAD and water content, respectively, while significantly reducing overfitting. Overall, this study provides an innovative approach for the early and accurate detection of nicosulfuron toxicity within maize fields.

Tumor-associated macrophage subtypes on cancer immunity along with prognostic analysis and SPP1-mediated interactions between tumor cells and macrophages.

Tumor-associated macrophages (TAM) subtypes have been shown to impact cancer prognosis and resistance to immunotherapy. However, there is still a lack of systematic investigation into their molecular characteristics and clinical relevance in different cancer types. Single-cell RNA sequencing data from three different tumor types were used to cluster and type macrophages. Functional analysis and communication of TAM subpopulations were performed by Gene Ontology-Biological Process and CellChat respectively. Differential expression of characteristic genes in subpopulations was calculated using zscore as well as edgeR and Wilcoxon rank sum tests, and subsequently gene enrichment analysis of characteristic genes and anti-PD-1 resistance was performed by the REACTOME database. We revealed the heterogeneity of TAM, and identified eleven subtypes and their impact on prognosis. These subtypes expressed different molecular functions respectively, such as being involved in T cell activation, apoptosis and differentiation, or regulating viral bioprocesses or responses to viruses. The SPP1 pathway was identified as a critical mediator of communication between TAM subpopulations, as well as between TAM and epithelial cells. Macrophages with high expression of SPP1 resulted in poorer survival. By in vitro study, we showed SPP1 mediated the interactions between TAM clusters and between TAM and tumor cells. SPP1 promoted the tumor-promoting ability of TAM, and increased PDL1 expression and stemness of tumor cells. Inhibition of SPP1 attenuated N-cadherin and ß-catenin expression and the activation of AKT and STAT3 pathway in tumor cells. Additionally, we found that several subpopulations could decrease the sensitivity of anti-PD-1 therapy in melanoma. SPP1 signal was a critical pathway of communication between macrophage subtypes. Some specific macrophage subtypes were associated with immunotherapy resistance and prognosis in some cancer types.

Photobiomodulation therapy moderates cancer cachexia-associated muscle wasting through activating PI3K/AKT/FoxO3a pathway.

Cancer cachexia-associated muscle wasting as a multifactorial wasting syndrome, is an important factor affecting the long-term survival rate of tumor patients. Photobiomodulation therapy (PBMT) has emerged as a promising tool to cure and prevent many diseases. However, the effect of PBMT on skeletal muscle atrophy during cancer progression has not been fully demonstrated yet. Here, we found PBMT alleviated the atrophy of myotube diameter induced by cancer cells in vitro, and prevented cancer-associated muscle atrophy in mice bearing tumor. Mechanistically, the alleviation of muscle wasting by PBMT was found to be involved in inhibiting E3 ubiquitin ligases MAFbx and MuRF-1. In addition, transcriptomic analysis using RNA-seq and GSEA revealed that PI3K/AKT pathway might be involved in PBMT-prevented muscle cachexia. Next, we showed the protective effect of PBMT against muscle cachexia was totally blocked by AKT inhibitor in vitro and in vivo. Moreover, PBMT-activated AKT promoted FoxO3a phosphorylation and thus inhibiting the nucleus entry of FoxO3a. Lastly, in cisplatin-treated muscle cachexia model, PBMT had also been shown to ameliorate muscle atrophy through enhancing PI3K/AKT pathway to suppress MAFbx and MuRF-1 expression. These novel findings revealed that PBMT could be a promising therapeutic approach in treating muscle cachexia induced by cancer.

Construction and validation of a hypoxia-related gene signature to predict the prognosis of breast cancer.

BACKGROUND: Among the most common forms of cancer worldwide, breast cancer posed a serious threat to women. Recent research revealed a lack of oxygen, known as hypoxia, was crucial in forming breast cancer. This research aimed to create a robust signature with hypoxia-related genes to predict the prognosis of breast cancer patients. The function of hypoxia genes was further studied through cell line experiments. MATERIALS AND METHODS: In the bioinformatic part, transcriptome and clinical information of breast cancer were obtained from The Cancer Genome Atlas(TCGA). Hypoxia-related genes were downloaded from the Genecards Platform. Differentially expressed hypoxia-related genes (DEHRGs) were identified. The TCGA filtered data was evenly split, ensuring a 1:1 distribution between the training and testing sets. Prognostic-related DEHRGs were identified through Cox regression. The signature was established through the training set. Then, it was validated using the test set and external validation set GSE131769 from Gene Expression Omnibus (GEO). The nomogram was created by incorporating the signature and clinicopathological characteristics. The predictive value of the nomogram was evaluated by C-index and receiver operating characteristiccurve. Immune microenvironment and mutation burden were also examined. In the experiment part, the function of the two most significant hypoxia-related genes were further explored by cell-line experiments. RESULTS: In the bioinformatic part, 141 up-regulated and 157 down-regulated DEHRGs were screened out. A prognostic signature was constructed containing nine hypoxia genes (ALOX15B, CA9, CD24, CHEK1, FOXM1, HOTAIR, KCNJ11, NEDD9, PSME2) in the training set. Low-risk patients exhibited a much more favorable prognosis than higher-risk ones (P < 0.001). The signature was double-validated in the test set and GSE131769 (P = 0.006 and P = 0.001). The nomogram showed excellent predictive value with 1-year OS AUC: 0.788, 3-year OS AUC: 0.783, and 5-year OS AUC: 0.817. Patients in the high-risk group had a higher tumor mutation burden when compared to the low-risk group. In the experiment part, the down-regulation of PSME2 inhibited cell growth ability and clone formation capability of breast cancer cells, while the down-regulation of KCNJ11 did not have any functions. CONCLUSION: Based on 9 DEHRGs, a reliable signature was established through the bioinformatic method. It could accurately predict the prognosis of breast cancer patients. Cell line experiment indicated that PSME2 played a protective role. Summarily, we provided a new insight to predict the prognosis of breast cancer by hypoxia-related genes.

[18F]AlF-ND-bisFAPI PET imaging of fibroblast activation protein as a biomarker to monitor the progression of liver fibrosis.

BACKGROUND: Hepatic fibrosis is a progressive disease, which is reversible in the early stages. The current monitoring methods have notable limitations that pose a challenge to early detection. In this study, we evaluated the utility of [18F]AlF-ND-bisFAPI positron emission tomography imaging of fibroblast activation protein (FAP) to monitor the progression of liver fibrosis. METHODS: Two mouse models of liver fibrosis were established by bile duct ligation and carbon tetrachloride administration, respectively. Positron emission tomography imaging was performed with the FAP-specific radiotracer [18F]AlF-ND-bisFAPI for the evaluation of rat HSCs and mouse models of fibrosis and combined with histopathology, immunohistochemical staining, and immunoblotting to elucidate the relationships among radioactivity uptake, FAP levels, and liver fibrosis progression. Furthermore, [18F]AlF-ND-bisFAPI autoradiography was performed to assess tracer binding in liver sections from patients with varying degrees of liver fibrosis. RESULTS: Cell experiments demonstrated that [18F]AlF-ND-bisFAPI uptake was specific in activated HSCs. Compared with control mice, [18F]AlF-ND-bisFAPI uptake in livers increased in the early stages of fibrosis and increased significantly further with disease progression. Immunohistochemistry and western blot analyses demonstrated that FAP expression increased with fibrosis severity. In accordance with the findings in animal models, ex vivo autoradiography on human fibrotic liver sections showed that radioactivity increased as fibrosis progressed from mild to severe. CONCLUSIONS: [18F]AlF-ND-bisFAPI positron emission tomography imaging is a promising noninvasive method for monitoring the progression of liver fibrosis.

The RNA sequencing results revealed the expression of different genes and signaling pathways during chemotherapy resistance in peripheral T-cell lymphoma.

BACKGROUND: Peripheral T-cell lymphoma (PTCL) is a subtype of non-Hodgkin's lymphoma that occurs primarily at extranodal sites and is commonly treated using chemotherapy and radiotherapy. PTCL is more malignant than other lymphoid tumors, resulting in a poor prognosis.The 5-year recurrence rate remains high, and there is a lack of standard treatment for patients with relapse-resistant disease. However, the molecular mechanisms underlying the resistance of peripheral T-cell lymphoma cells to chemotherapeutic drugs, as well as identifying strategies to overcome drug resistance remains unclear. In this study, we aimed to identify pivotal genes and signaling pathways associated with chemotherapy resistance in PTCL. METHODS: In this study, a total of 5 healthy controls and 7 clinical patients were enrolled; 4 patients were classified as chemotherapy sensitive, and 3 patients were classified as chemotherapy resistant. Peripheral blood samples were collected from each participant, and total RNA was extracted from the white blood cells. RNA sequencing was conducted on the Illumina HiSeq platform to obtain comprehensive gene expression profiles. Subsequently, the expression patterns of the DEGs associated with the most enriched signaling pathways, with a special focus on cancer-related genes, were validated using quantitative real-time polymerase chain reaction (qRT-PCR) in peripheral TCL patients. RESULTS: RNA sequencing (RNA-seq) analysis revealed 4063 differentially expressed genes (DEGs) in peripheral T-cell lymphoma specimens from patients with chemotherapy resistance, of which 1128 were upregulated and 2935 were downregulated. Subsequent quantitative gene expression analysis confirmed a differential expression pattern in all the libraries, with 9 downregulated genes and 10 upregulated genes validated through quantitative real-time PCR in 6 clinical specimens from patients with chemotherapy resistance. KEGG pathway analysis revealed significant alterations in several pathways, with 6 downregulated pathways and 9 upregulated pathways enriched in the DEGs. Notably, the TNF signaling pathway, which is extensively regulated, was among the pathways that exhibited significant changes. These findings suggest that DEGs and the TNF signaling pathway may play crucial roles in chemotherapy resistance in peripheral T-cell lymphoma. CONCLUSION: Our study revealed that the expression of specific genes, including TNFRSF1B, TRADD2, and MAP3K7, may play an important role in chemotherapy resistance in peripheral T-cell lymphoma. Moreover, we identified the downregulation of the TNF signaling pathway, a crucial pathway involved in cell survival, death, and differentiation, as a potential contributor to the development of chemotherapy resistance in peripheral T-cell lymphoma. These findings provide valuable insights into the molecular mechanisms underlying chemotherapy resistance and highlight potential targets for overcoming treatment resistance in this challenging disease.

Single-cell sequencing reveals the immune landscape of breast cancer patients with brain metastasis.

BACKGROUND: Breast cancer has the highest incidence rate of cancer worldwide, and brain metastases (BrM) are among the most malignant cases. While some patients have benefited from immune checkpoint inhibitors (ICIs), the complex anatomical structure of the brain and the heterogeneity of metastatic tumors have made it difficult to characterize the tumor immune microenvironment (TME) of metastatic tumors. METHODS: To address this, we used single-cell RNA sequencing (scRNA-seq) to analyze immune cells in the cerebrospinal fluid (CSF) of BrM patients with breast cancer, thereby providing a comprehensive view of the immune microenvironment landscape of BrM. RESULTS: Based on canonical marker genes, we identified nine cell types, and further identified their subtypes through differential expression gene (DEG) analysis. We compared the changes in cells and functions in the immune microenvironment of patients with different prognoses. Our analysis revealed a series of genes that promote tumor immune function (CCR5, LYZ, IGKC, MS4A1, etc.) and inhibit tumor immune function (SCGB2A2, CD24, etc.). CONCLUSIONS: The scRNA-seq in CSF provides a noninvasive method to describe the TME of breast cancer patients and guide immunotherapy.

Expression of PD-1 mitigates phagocytic activities TAM in osteosarcoma.

The high expression of programmed death 1 (PD-1) is a hallmark of T cell exhaustion, consequently inhibiting the anti-tumor immunity, tumor-associated macrophages (TAMs) aggravate Osteosarcoma (OS) progression. However, PD-1 expression on TAMs in OS metastasis remains unclear. Here, we used scRNA-Seq of 15500 individual cells from human OS lung metastatic lesion, identified thirteen major cell clusters. Our data revealed that tumor-infiltrating lymphocytes (TILs) OS lung metastatic accompanied by accumulation of exhausted T cells and regulatory T cells (Tregs). CD3+ T cells from human OS lung metastatic exhibited lower proliferation than in primary tissue. Importantly, TAMs mainly comprise immunosuppressive M2 phenotype in OS metastasis. Mechanistically, we found that PD-1 of TAMs inhibits the phagocytic potency, further promoting the progression of OS metastasis. Therefore, the study provides a strong technical support for OS immunotherapy based on PD-1 inhibitors.

Mapping of multiple neurotransmitter receptor subtypes and distinct protein complexes to the connectome.

Neurons express various combinations of neurotransmitter receptor (NR) subunits and receive inputs from multiple neuron types expressing different neurotransmitters. Localizing NR subunits to specific synaptic inputs has been challenging. Here, we use epitope-tagged endogenous NR subunits, expansion light-sheet microscopy, and electron microscopy (EM) connectomics to molecularly characterize synapses in Drosophila. We show that in directionally selective motion-sensitive neurons, different multiple NRs elaborated a highly stereotyped molecular topography with NR localized to specific domains receiving cell-type-specific inputs. Developmental studies suggested that NRs or complexes of them with other membrane proteins determine patterns of synaptic inputs. In support of this model, we identify a transmembrane protein selectively associated with a subset of spatially restricted synapses and demonstrate its requirement for synapse formation through genetic analysis. We propose that mechanisms that regulate the precise spatial distribution of NRs provide a molecular cartography specifying the patterns of synaptic connections onto dendrites.

Unified 3D and 4D Panoptic Segmentation via Dynamic Shifting Networks.

With the rapid advances in autonomous driving, it becomes critical to equip its sensing system with more holistic 3D perception. However, widely explored tasks like 3D detection or point cloud semantic segmentation focus on parsing either the objects or scenes. In this work, we propose to address the challenging task of LiDAR-based Panoptic Segmentation, which aims to parse both objects and scenes in a unified manner. In particular, we propose Dynamic Shifting Network (DS-Net), which serves as an effective panoptic segmentation framework in the point cloud realm. DS-Net features a dynamic shifting module for complex LiDAR point cloud distributions. We present an efficient learnable clustering module, dynamic shifting, which adapts kernel functions for different instances. To further explore the temporal information, we extend the single-scan processing framework to its temporal version, 4D-DS-Net, for the task of 4D Panoptic Segmentation, where the same instance across multiple frames should be given the same ID prediction. Instead of naively appending a tracking module to DS-Net, we propose to solve the 4D panoptic segmentation in a more unified way. Specifically, 4D-DS-Net first constructs 4D data volume by aligning consecutive LiDAR scans, upon which the temporally unified instance clustering is performed to obtain the final results. Extensive experiments on two large-scale autonomous driving LiDAR datasets, SemanticKITTI and Panoptic nuScenes, are conducted to demonstrate the effectiveness and superior performance of the proposed solution.

RNNPose: 6-DoF Object Pose Estimation via Recurrent Correspondence Field Estimation and Pose Optimization.

6-DoF object pose estimation from a monocular image is a challenging problem, where a post-refinement procedure is generally needed for high-precision estimation. In this paper, we propose a framework, dubbed RNNPose, based on a recurrent neural network (RNN) for object pose refinement, which is robust to erroneous initial poses and occlusions. During the recurrent iterations, object pose refinement is formulated as a non-linear least squares problem based on the estimated correspondence field (between a rendered image and the observed image). The problem is then solved by a differentiable Levenberg-Marquardt (LM) algorithm enabling end-to-end training. The correspondence field estimation and pose refinement are conducted alternately in each iteration to improve the object poses. Furthermore, to improve the robustness against occlusion, we introduce a consistency-check mechanism based on the learned descriptors of the 3D model and observed 2D images, which downweights the unreliable correspondences during pose optimization. We evaluate RNNPose on several public datasets, including LINEMOD, Occlusion-LINEMOD, YCB-Video and TLESS. We demonstrate state-of-the-art performance and strong robustness against severe clutter and occlusion in the scenes. Extensive experiments validate the effectiveness of our proposed method. Besides, the extended system based on RNNPose successfully generalizes to multi-instance scenarios and achieves top-tier performance on the TLESS dataset.

M6A demethylase ALKBH5 regulates FOXO1 mRNA stability and chemoresistance in triple-negative breast cancer.

Resistance to chemotherapy is the main reason for treatment failure and poor prognosis in patients with triple-negative breast cancer (TNBC). Although the association of RNA N6-methyladenosine (m6A) modifications with therapy resistance is noticed, its role in the development of therapeutic resistance in TNBC is not well documented. This study aimed to investigate the potential mechanisms underlying reactive oxygen species (ROS) regulation in doxorubicin (DOX)-resistant TNBC. Here, we found that DOX-resistant TNBC cells displayed low ROS levels because of increased expression of superoxide dismutase (SOD2), thus maintaining cancer stem cells (CSCs) characteristics and DOX resistance. FOXO1 is a master regulator that reduces cellular ROS in DOX-resistant TNBC cells, and knockdown of FOXO1 significantly increased ROS levels by inhibiting SOD2 expression. Moreover, the m6A demethylase ALKBH5 promoted m6A demethylation of FOXO1 mRNA and increased FOXO1 mRNA stability in DOX-resistant TNBC cells. The analysis of clinical samples revealed that the increased expression levels of ALKBH5, FOXO1, and SOD2 were significantly positively correlated with chemoresistance and poor prognosis in patients with TNBC. To our knowledge, this is the first study to highlight that ALKBH5-mediated FOXO1 mRNA demethylation contributes to CSCs characteristics and DOX resistance in TNBC cells. Furthermore, pharmacological targeting of FOXO1 profoundly restored the response of DOX-resistant TNBC cells, both in vitro and in vivo. In conclusion, we demonstrated a critical function of ALKBH5-mediated m6A demethylation of FOXO1 mRNA in restoring redox balance, which in turn promoting CSCs characteristics and DOX resistance in TNBC, and suggested that targeting the ALKBH5/FOXO1 axis has therapeutic potential for patients with TNBC refractory to chemotherapy.

CGOF++: Controllable 3D Face Synthesis With Conditional Generative Occupancy Fields.

Capitalizing on the recent advances in image generation models, existing controllable face image synthesis methods are able to generate high-fidelity images with some levels of controllability, e.g., controlling the shapes, expressions, textures, and poses of the generated face images. However, previous methods focus on controllable 2D image generative models, which are prone to producing inconsistent face images under large expression and pose changes. In this paper, we propose a new NeRF-based conditional 3D face synthesis framework, which enables 3D controllability over the generated face images by imposing explicit 3D conditions from 3D face priors. At its core is a conditional Generative Occupancy Field (cGOF++) that effectively enforces the shape of the generated face to conform to a given 3D Morphable Model (3DMM) mesh, built on top of EG3D (Chan et al. 2022), a recent tri-plane-based generative model. To achieve accurate control over fine-grained 3D face shapes of the synthesized images, we additionally incorporate a 3D landmark loss as well as a volume warping loss into our synthesis framework. Experiments validate the effectiveness of the proposed method, which is able to generate high-fidelity face images and shows more precise 3D controllability than state-of-the-art 2D-based controllable face synthesis methods.

177Lu-Labeled Bivalent Ligands of Prostate-Specific Membrane Antigen for Endoradiotherapy of Prostate Cancer.

Recently, we developed a bivalent prostate-specific membrane antigen (PSMA) radioligand ([18F]AlF-Bi-PSMA), which showed higher tumor uptake and retention in PSMA-positive mouse models than the clinically used radioligands, [68Ga]Ga-PSMA-11 and [18F]PSMA-1007. Here, we developed two 177Lu-labeled bivalent PSMA ligands with (DOTA-Alb-Bi-PSMA) or without an albumin-binding motif (DOTA-Bi-PSMA) to enhance radiotherapeutic efficacy with minimal toxicity. The results demonstrated that both 177Lu-labeled bivalent radioligands showed good stability, high binding affinity, and PSMA-targeting specificity in vitro. Compared with [177Lu]Lu-PSMA-617, both [177Lu]Lu-Bi-PSMA and [177Lu]Lu-Alb-Bi-PSMA showed a higher area under the curve (AUC) of tumor accumulation and superior therapeutic efficacy. However, [177Lu]Lu-Alb-Bi-PSMA exhibited a dose-dependent increase in acute damage to kidneys. In terms of the radionuclide therapy efficacy and side effects, [177Lu]Lu-Bi-PSMA exhibited well-balanced action with high tumor-to-organs AUC ratios, resulting in remarkable therapeutic efficacy and negligible side effects. These promising results warrant further investigations to achieve the clinical translation of [177Lu]Lu-Bi-PSMA.