InpaintNeRF360: Text-Guided 3D Inpainting on Unbounded Neural Radiance Fields

Neural Radiance Fields (NeRF) can generate highly realistic novel views. However, editing 3D scenes represented by NeRF across 360-degree views, particularly removing objects while preserving geometric and photometric consistency, remains a challenging problem due to NeRF's implicit scene representation. In this paper, we propose InpaintNeRF360, a unified framework that utilizes natural language instructions as guidance for inpainting NeRF-based 3D scenes.Our approach employs a promptable segmentation model by generating multi-modal prompts from the encoded text for multiview segmentation. We apply depth-space warping to enforce viewing consistency in the segmentations, and further refine the inpainted NeRF model using perceptual priors to ensure visual plausibility. InpaintNeRF360 is capable of simultaneously removing multiple objects or modifying object appearance based on text instructions while synthesizing 3D viewing-consistent and photo-realistic inpainting. Through extensive experiments on both unbounded and frontal-facing scenes trained through NeRF, we demonstrate the effectiveness of our approach and showcase its potential to enhance the editability of implicit radiance fields

DyNCA: Real-time Dynamic Texture Synthesis Using Neural Cellular Automata

Current Dynamic Texture Synthesis (DyTS) models in the literature can synthesize realistic videos. However, these methods require a slow iterative optimization process to synthesize a single fixed-size short video, and they do not offer any post-training control over the synthesis process. We propose Dynamic Neural Cellular Automata (DyNCA), a framework for real-time and controllable dynamic texture synthesis. Our method is built upon the recently introduced NCA models, and can synthesize infinitely-long and arbitrary-size realistic texture videos in real-time. We quantitatively and qualitatively evaluate our model and show that our synthesized videos appear more realistic than the existing results. We improve the SOTA DyTS performance by $2\sim 4$ orders of magnitude. Moreover, our model offers several real-time and interactive video controls including motion speed, motion direction, and an editing brush tool

VolRecon: Volume Rendering of Signed Ray Distance Functions for Generalizable Multi-View Reconstruction

The success of the Neural Radiance Fields (NeRF) in novel view synthesis has inspired researchers to propose neural implicit scene reconstruction. However, most existing neural implicit reconstruction methods optimize per-scene parameters and therefore lack generalizability to new scenes. We introduce VolRecon, a novel generalizable implicit reconstruction method with Signed Ray Distance Function (SRDF). To reconstruct the scene with fine details and little noise, VolRecon combines projection features aggregated from multi-view features, and volume features interpolated from a coarse global feature volume. Using a ray transformer, we compute SRDF values of sampled points on a ray and then render color and depth. On DTU dataset, VolRecon outperforms SparseNeuS by about 30% in sparse view reconstruction and achieves comparable accuracy as MVSNet in full view reconstruction. Furthermore, our approach exhibits good generalization performance on the large-scale ETH3D benchmark

Spatiotemporal Self-supervised Learning for Point Clouds in the Wild

Self-supervised learning (SSL) has the potential to benefit many applications, particularly those where manually annotating data is cumbersome. One such situation is the semantic segmentation of point clouds. In this context, existing methods employ contrastive learning strategies and define positive pairs by performing various augmentation of point clusters in a single frame. As such, these methods do not exploit the temporal nature of LiDAR data. In this paper, we introduce an SSL strategy that leverages positive pairs in both the spatial and temporal domain. To this end, we design (i) a point-to-cluster learning strategy that aggregates spatial information to distinguish objects; and (ii) a cluster-to-cluster learning strategy based on unsupervised object tracking that exploits temporal correspondences. We demonstrate the benefits of our approach via extensive experiments performed by self-supervised training on two large-scale LiDAR datasets and transferring the resulting models to other point cloud segmentation benchmarks. Our results evidence that our method outperforms the state-of-the-art point cloud SSL methods.Comment: CVPR accepte

Processed meat: the real villain?

Meat is a food rich in protein, minerals such as iron and zinc as well as a variety of vitamins, in particular B vitamins. However, the content of cholesterol and saturated fat is higher than in some other food groups. Processed meat is defined as products usually made of red meat that are cured, salted or smoked (e.g. ham or bacon) in order to improve the durability of the food and/or to improve colour and taste, and often contain a high amount of minced fatty tissue (e.g. sausages). Hence, high consumption of processed foods may lead to an increased intake of saturated fats, cholesterol, salt, nitrite, haem iron, polycyclic aromatic hydrocarbons, and, depending upon the chosen food preparation method, also heterocyclic amines. Several large cohort studies have shown that a high consumption of processed (red) meat is related to increased overall and cause-specific mortality. A meta-analysis of nine cohort studies observed a higher mortality among high consumers of processed red meat (relative risk (RR) = 1·23; 95 % CI 1·17, 1·28, top v. bottom consumption category), but not unprocessed red meat (RR = 1·10; 95 % CI 0·98, 1·22). Similar associations were reported in a second meta-analysis. All studies argue that plausible mechanisms are available linking processed meat consumption and risk of chronic diseases such as CVD, diabetes mellitus or some types of cancer. However, the results of meta-analyses do show some degree of heterogeneity between studies, and it has to be taken into account that individuals with low red or processed meat consumption tend to have a healthier lifestyle in general. Hence, substantial residual confounding cannot be excluded. Information from other types of studies in man is needed to support a causal role of processed meat in the aetiology of chronic diseases, e.g. studies using the Mendelian randomisation approach

Contractile Dysfunction Irrespective of the Mutant Protein in Human Hypertrophic Cardiomyopathy With Normal Systolic Function

Background-Hypertrophic cardiomyopathy (HCM), typically characterized by asymmetrical left ventricular hypertrophy, frequently is caused by mutations in sarcomeric proteins. We studied if changes in sarcomeric properties in HCM depend on the underlying protein mutation. Methods and Results-Comparisons were made between cardiac samples from patients carrying a MYBPC3 mutation (MYBPC3(mut); n = 17), mutation negative HCM patients without an identified sarcomere mutation (HCM(mn); n = 11), and nonfailing donors (n = 12). All patients had normal systolic function, but impaired diastolic function. Protein expression of myosin binding protein C (cMyBP-C) was significantly lower in MYBPC3(mut) by 33 +/- 5%, and similar in HCM(mn) compared with donor. cMyBP-C phosphory Conclusions-Changes in sarcomere function reflect the clinical HCM phenotype rather than the specific MYBPC3 mutation. Hypocontractile sarcomeres are a common deficit in human HCM with normal systolic left ventricular function and may contribute to HCM disease progression. (Circ Heart Fail. 2012; 5: 36-46.

FORT-1: Phase II/III Study of Rogaratinib Versus Chemotherapy in Patients With Locally Advanced or Metastatic Urothelial Carcinoma Selected Based on FGFR1/3 mRNA Expression

Purpose: Rogaratinib, an oral pan-fibroblast growth factor receptor (FGFR1-4) inhibitor, showed promising phase I efficacy and safety in patients with advanced urothelial carcinoma (UC) with FGFR1-3 mRNA overexpression. We assessed rogaratinib efficacy and safety versus chemotherapy in patients with FGFR mRNA-positive advanced/metastatic UC previously treated with platinum chemotherapy. Methods: FORT-1 (ClinicalTrials.gov identifier: NCT03410693) was a phase II/III, randomized, open-label trial. Patients with FGFR1/3 mRNA-positive locally advanced or metastatic UC with ≥ 1 prior platinum-containing regimen were randomly assigned (1:1) to rogaratinib (800 mg orally twice daily, 3-week cycles; n = 87) or chemotherapy (docetaxel 75 mg/m2, paclitaxel 175 mg/m2, or vinflunine 320 mg/m2 intravenously once every 3 weeks; n = 88). The primary end point was overall survival, with objective response rate (ORR) analysis planned following phase II accrual. Because of comparable efficacy between treatments, enrollment was stopped before progression to phase III; a full interim analysis of phase II was completed. Results: ORRs were 20.7% (rogaratinib, 18/87; 95% CI, 12.7 to 30.7) and 19.3% (chemotherapy, 17/88; 95% CI, 11.7 to 29.1). Median overall survival was 8.3 months (95% CI, 6.5 to not estimable) and 9.8 months (95% CI, 6.8 to not estimable; hazard ratio, 1.11; 95% CI, 0.71 to 1.72; P = .67). Grade 3/4 events occurred in 37 (43.0%)/4 (4.7%) patients and 32 (39.0%)/15 (18.3%), respectively. No rogaratinib-related deaths occurred. Exploratory analysis of patients with FGFR3 DNA alterations showed ORRs of 52.4% (11/21; 95% CI, 29.8 to 74.3) for rogaratinib and 26.7% (4/15; 95% CI, 7.8 to 55.1) for chemotherapy. Conclusion: To our knowledge, these are the first data to compare FGFR-directed therapy with chemotherapy in patients with FGFR-altered UC, showing comparable efficacy and manageable safety. Exploratory testing suggested FGFR3 DNA alterations in association with FGFR1/3 mRNA overexpression may be better predictors of rogaratinib response

Estrogens stimulate serotonin neurons to inhibit binge-like eating in mice

Binge eating afflicts approximately 5% of US adults, though effective treatments are limited. Here, we showed that estrogen replacement substantially suppresses binge-like eating behavior in ovariectomized female mice. Estrogen-dependent inhibition of binge-like eating was blocked in female mice specifically lacking estrogen receptor-α (ERα) in serotonin (5-HT) neurons in the dorsal raphe nuclei (DRN). Administration of a recently developed glucagon-like peptide-1–estrogen (GLP-1–estrogen) conjugate designed to deliver estrogen to GLP1 receptor–enhanced regions effectively targeted bioactive estrogens to the DRN and substantially suppressed binge-like eating in ovariectomized female mice. Administration of GLP-1 alone reduced binge-like eating, but not to the same extent as the GLP-1–estrogen conjugate. Administration of ERα-selective agonist propylpyrazole triol (PPT) to murine DRN 5-HT neurons activated these neurons in an ERα-dependent manner. PPT also inhibited a small conductance Ca2+-activated K+ (SK) current; blockade of the SK current prevented PPT-induced activation of DRN 5-HT neurons. Furthermore, local inhibition of the SK current in the DRN markedly suppressed binge-like eating in female mice. Together, our data indicate that estrogens act upon ERα to inhibit the SK current in DRN 5-HT neurons, thereby activating these neurons to suppress binge-like eating behavior and suggest ERα and/or SK current in DRN 5-HT neurons as potential targets for anti-binge therapies

Dendritic position is a major determinant of presynaptic strength

Different regulatory principles influence synaptic coupling between neurons, including positional principles. In dendrites of pyramidal neurons, postsynaptic sensitivity depends on synapse location, with distal synapses having the highest gain. In this paper, we investigate whether similar rules exist for presynaptic terminals in mixed networks of pyramidal and dentate gyrus (DG) neurons. Unexpectedly, distal synapses had the lowest staining intensities for vesicular proteins vGlut, vGAT, Synaptotagmin, and VAMP and for many nonvesicular proteins, including Bassoon, Munc18, and Syntaxin. Concomitantly, distal synapses displayed less vesicle release upon stimulation. This dependence of presynaptic strength on dendritic position persisted after chronically blocking action potential firing and postsynaptic receptors but was markedly reduced on DG dendrites compared with pyramidal dendrites. These data reveal a novel rule, independent of neuronal activity, which regulates presynaptic strength according to dendritic position, with the strongest terminals closest to the soma. This gradient is opposite to postsynaptic gradients observed in pyramidal dendrites, and different cell types apply this rule to a different extent