DebSDF: Delving into the Details and Bias of Neural Indoor Scene Reconstruction.

In recent years, the neural implicit surface has emerged as a powerful representation for multi-view surface reconstruction due to its simplicity and state-of-the-art performance. However, reconstructing smooth and detailed surfaces in indoor scenes from multi-view images presents unique challenges. Indoor scenes typically contain large texture-less regions, making the photometric loss unreliable for optimizing the implicit surface. Previous work utilizes monocular geometry priors to improve the reconstruction in indoor scenes. However, monocular priors often contain substantial errors in thin structure regions due to domain gaps and the inherent inconsistencies when derived independently from different views. This paper presents DebSDF to address these challenges, focusing on the utilization of uncertainty in monocular priors and the bias in SDF-based volume rendering. We propose an uncertainty modeling technique that associates larger uncertainties with larger errors in the monocular priors. High-uncertainty priors are then excluded from optimization to prevent bias. This uncertainty measure also informs an importance-guided ray sampling and adaptive smoothness regularization, enhancing the learning of fine structures. We further introduce a bias-aware signed distance function to density transformation that takes into account the curvature and the angle between the view direction and the SDF normals to reconstruct fine details better. Our approach has been validated through extensive experiments on several challenging datasets, demonstrating improved qualitative and quantitative results in reconstructing thin structures in indoor scenes, thereby outperforming previous work.

Discovery of a Novel Thienopyrimidine Compound as a Urate Transporter 1 and Glucose Transporter 9 Dual Inhibitor with Improved Efficacy and Favorable Druggability.

Gout and hyperuricemia are metabolic diseases characterized with high serum uric acid (SUA) levels that significantly impact human health. Lesinurad, a uricosuric agent, is limited to concurrent use with xanthine oxidase inhibitors (XOIs) in clinical practice due to its restricted efficacy and potential nephrotoxicity. Herein, extensive structural modifications of lesinurad were conducted through scaffold hopping and substituent modification strategies, affording 54 novel derivatives containing pyrimidine-fused cyclic structures. Notably, the thienopyrimidine compound 29 demonstrated a remarkable 2-fold increase in SUA-lowering in vivo activity compared to lesinurad, while exhibiting potent inhibitory activity against the urate transporter 1 (URAT1, IC50 = 2.01 µM) and glucose transporter 9 (GLUT9, IC50 = 18.21 µM). Furthermore, it possessed a lower effective dosage of 0.5 mg/kg, favorable safety profile without any apparent acute toxicity at doses of 1000 mg/kg, and improved pharmacokinetic properties. Overall, we have discovered an efficacious URAT1/GLUT9 dual inhibitor for inhibiting urate reabsorption with favorable pharmacokinetic profiles.

Anatomical Prior and Inter-Slice Consistency for Semi-Supervised Vertebral Structure Detection in 3D Ultrasound Volume.

Three-dimensional (3D) ultrasound imaging technique has been applied for scoliosis assessment, but the current assessment method only uses coronal projection images and cannot illustrate the 3D deformity and vertebra rotation. The vertebra detection is essential to reveal 3D spine information, but the detection task is challenging due to complex data and limited annotations. We propose VertMatch to detect vertebral structures in 3D ultrasound volume containing a detector and classifier. The detector network finds the potential positions of structures on transverse slice globally, and then the local patches are cropped based on detected positions. The classifier is used to distinguish whether the patches contain real vertebral structures and screen the predicted positions from the detector. VertMatch utilizes unlabeled data in a semi-supervised manner, and we develop two novel techniques for semi-supervised learning: 1) anatomical prior is used to acquire high-quality pseudo labels; 2) inter-slice consistency is used to utilize more unlabeled data by inputting multiple adjacent slices. Experimental results demonstrate that VertMatch can detect vertebra accurately in ultrasound volume and outperforms state-of-the-art methods. Moreover, VertMatch is also validated in automatic spinous process angle measurement on forty subjects with scoliosis, and the results illustrate that it can be a promising approach for the 3D assessment of scoliosis.

Genome-Wide Identification and Expression Analysis of the SWEET Gene Family in Capsicum annuum L.

Sugars will eventually be exported transporters (SWEETs) are a novel class of sugar transport proteins that play a crucial role in plant growth, development, and response to stress. However, there is a lack of systematic research on SWEETs in Capsicum annuum L. In this study, 33 CaSWEET genes were identified through bioinformatics analysis. The Ka/Ks analysis indicated that SWEET genes are highly conserved not only among peppers but also among Solanaceae species and have experienced strong purifying selection during evolution. The Cis-elements analysis showed that the light-responsive element, abscisic-acid-responsive element, jasmonic-acid-responsive element, and anaerobic-induction-responsive element are widely distributed in the promoter regions of CaSWEETs. The expression pattern analysis revealed that CaSWEETs exhibit tissue specificity and are widely involved in pepper growth, development, and stress responses. The post-transcription regulation analysis revealed that 20 pepper miRNAs target and regulate 16 CaSWEETs through cleavage and translation inhibition mechanisms. The pathogen inoculation assay showed that CaSWEET16 and CaSWEET22 function as susceptibility genes, as the overexpression of these genes promotes the colonization of pathogens, whereas CaSWEET31 functions as a resistance gene. In conclusion, through systematic identification and characteristic analysis, a comprehensive understanding of CaSWEET was obtained, which lays the foundation for further studies on the biological functions of SWEET genes.