Uni3D: Exploring Unified 3D Representation at Scale

Scaling up representations for images or text has been extensively investigated in the past few years and has led to revolutions in learning vision and language. However, scalable representation for 3D objects and scenes is relatively unexplored. In this work, we present Uni3D, a 3D foundation model to explore the unified 3D representation at scale. Uni3D uses a 2D initialized ViT end-to-end pretrained to align the 3D point cloud features with the image-text aligned features. Via the simple architecture and pretext task, Uni3D can leverage abundant 2D pretrained models as initialization and image-text aligned models as the target, unlocking the great potential of 2D models and scaling-up strategies to the 3D world. We efficiently scale up Uni3D to one billion parameters, and set new records on a broad range of 3D tasks, such as zero-shot classification, few-shot classification, open-world understanding and part segmentation. We show that the strong Uni3D representation also enables applications such as 3D painting and retrieval in the wild. We believe that Uni3D provides a new direction for exploring both scaling up and efficiency of the representation in 3D domain.Comment: Code and Demo: https://github.com/baaivision/Uni3

GeoDream: Disentangling 2D and Geometric Priors for High-Fidelity and Consistent 3D Generation

Text-to-3D generation by distilling pretrained large-scale text-to-image diffusion models has shown great promise but still suffers from inconsistent 3D geometric structures (Janus problems) and severe artifacts. The aforementioned problems mainly stem from 2D diffusion models lacking 3D awareness during the lifting. In this work, we present GeoDream, a novel method that incorporates explicit generalized 3D priors with 2D diffusion priors to enhance the capability of obtaining unambiguous 3D consistent geometric structures without sacrificing diversity or fidelity. Specifically, we first utilize a multi-view diffusion model to generate posed images and then construct cost volume from the predicted image, which serves as native 3D geometric priors, ensuring spatial consistency in 3D space. Subsequently, we further propose to harness 3D geometric priors to unlock the great potential of 3D awareness in 2D diffusion priors via a disentangled design. Notably, disentangling 2D and 3D priors allows us to refine 3D geometric priors further. We justify that the refined 3D geometric priors aid in the 3D-aware capability of 2D diffusion priors, which in turn provides superior guidance for the refinement of 3D geometric priors. Our numerical and visual comparisons demonstrate that GeoDream generates more 3D consistent textured meshes with high-resolution realistic renderings (i.e., 1024 $\times$ 1024) and adheres more closely to semantic coherence.Comment: Code and Demo: https://github.com/baaivision/GeoDrea

Cell-free miRNAs may indicate diagnosis and docetaxel sensitivity of tumor cells in malignant effusions

<p>Abstract</p> <p>Background</p> <p>Circulating cell-free microRNAs have been identified as potential cancer biomarkers. However, the existence and the potential application of cell-free miRNAs in effusion samples are still uncertain. In order to explore the potential role of cell-free miRNA in malignant effusions, we selected 22 miRNAs differentially expressed in the serum of lung cancer patients and studied their expression levels in body cavity effusion samples.</p> <p>Methods</p> <p>We measured the expression of 22 miRNAs using qRT-PCR in two samples, which were pooled with 18 malignant and 12 benign effusions, respectively. After discarding 9 lowly expressed miRNAs, a panel of 13 miRNAs were measured in 29 samples (benign n = 11, malignant n = 18). We also carried out a WST-8 test to evaluate the docetaxel sensitivity of tumor cells directly isolated from 15 malignant effusions.</p> <p>Results</p> <p>We compared the miRNA expression levels between benign and malignant effusions using a Mann-Whitney U test and found miR-24, miR-26a and miR-30d were expressed differently between the two groups (<it>P </it>= 0.006, 0.021 and 0.011, respectively). Cells isolated from effusions rich in cell-free miR-152 were more sensitive to docetaxel (r = 0.60, <it>P </it>= 0.016).</p> <p>Conclusions</p> <p>Collectively, our study demonstrated that cell-free miRNAs in the supernatant of effusions may aid in the diagnosis of malignancy and predict chemosensitivity to docetaxel.</p

Optimal scheduling of integrated energy systems with exergy and demand responsiveness

To fairly use demand response to regulate customer load , support the economic and environmental protection, and assess the quantity and quality of the synergistic growth of the integrated energy system, a multi-objective optimum scheduling model and a solution method considering exergy efficiency and demand response are presented. To begin with, a mathematical model of each energy gadget is created. The electricity–gas load demand response model is then built using the price elasticity matrix, while the cooling load demand response model is built taking into account the user’s comfort temperature. On this basis, a multi-objective optimal dispatching model is developed with the optimization goals of minimizing system operation costs, reducing carbon emissions, and increasing exergy efficiency. Finally, the model is solved using NSGA-II to produce the Pareto optimal frontier solution set in various situations, and the VIKOR decision procedure is utilized to identify the complete best dispatching solution. The simulation results suggest that the proposed model can match the system’s scheduling needs in terms of numerous objectives such as economy, environmental protection, and exergy efficiency while also assuring user’s comfort

Comparative studies of salinomycin-loaded nanoparticles prepared by nanoprecipitation and single emulsion method

To establish a satisfactory delivery system for the delivery of salinomycin (Sal), a novel, selective cancer stem cell inhibitor with prominent toxicity, gelatinase-responsive core-shell nanoparticles (NPs), were prepared by nanoprecipitation method (NR-NPs) and single emulsion method (SE-NPs). The gelatinase-responsive copolymer was prepared by carboxylation and double amination method. We studied the stability of NPs prepared by nanoprecipitation method with different proportions of F68 in aqueous phase to determine the best proportion used in our study. Then, the NPs were prepared by nanoprecipitation method with the best proportion of F68 and single emulsion method, and their physiochemical traits including morphology, particle size, zeta potential, drug loading content, stability, and in vitro release profiles were studied. The SE-NPs showed significant differences in particle size, drug loading content, stability, and in vitro release profiles compared to NR-NPs. The SE-NPs presented higher drug entrapment efficiency and superior stability than the NR-NPs. The drug release rate of SE-NPs was more sustainable than that of the NR-NPs, and in vivo experiment indicated that NPs could prominently reduce the toxicity of Sal. Our study demonstrates that the SE-NPs could be a satisfactory method for the preparation of gelatinase-responsive NPs for intelligent delivery of Sal

Influence of body mass index and waist–hip ratio on male semen parameters in infertile men in the real world: a retrospective study

BackgroundIt is suggested that body mass index (BMI) can affect male semen quality; however, the results remain controversial. In addition, most studies have focused on the effect of obesity on semen quality. Evidence on the relationship of underweight or waist-hip ratio (WHR) with semen quality is rare. This study aimed to assess the association of BMI and WHR with semen quality.MethodsData, including BMI and WHR, was collected from 715.00 men who underwent a fertility evaluation. BMI (kg/m2) was categorized as &lt;18.50 (underweight), 18.50–24.90 (normal), 25.00–27.90 (overweight), and ≥28.00 (obese) kg/m2 for analysis. WHR was categorized as &lt;0.81 (normal) and ≥0.81 (high). Semen volume, sperm concentration, progressive motility, and total motile sperm count were detected by experienced clinical technicians.ResultsSpearman’s correlation showed that BMI was weakly associated with sperm progressive motility (r = 0.076, P &lt; 0.05), while WHR showed no relationship with semen parameters. The azoospermia rate was significantly higher (33.33% vs. 2.10%, P &lt; 0.001) and the sperm concentration was lower (P &lt; 0.05) in the underweight group. The nonlinear correlation analysis showed that BMI was negatively associated with sperm concentration while BMI was more than 22.40 kg/m2 (P &lt; 0.05), while WHR was negatively related to sperm progressive motility within 0.82 to 0.89 (P &lt; 0.05). Furthermore, the multivariate logistic analysis showed that follicular stimulating hormone (FSH) was an independent risk factor for normal sperm concentration (odds ratio [OR]: 0.791, P = 0.001) and morphology (OR: 0.821, P = 0.002), BMI was an independent risk factor for normal sperm progressive motility, and testosterone was an independent risk factor for sperm morphology (OR: 0.908, P = 0.023).ConclusionBMI and WHR were significantly associated with semen parameters, while BMI was an independent risk factor for normal sperm progressive motility. Reproductive hormones, including FSH and testosterone, had a significant influence on sperm concentration and sperm morphology

A biophoton method for identifying the quality states of fresh Chinese herbs

Introduction: The quality of Chinese herbs is the basis for ensuring their safety and efficacy. However, the quality evaluation system is imperfect. In particular, there is a lack of quality evaluation methods for fresh Chinese herbs during growth. The biophoton is a common phenomenon and provides complete information about the interior of the living system, which is consistent with the holistic concept of traditional Chinese medicine. Therefore, we aim to correlate the biophoton characteristics with the quality states to find the biophoton parameters that can characterize the quality states of fresh Chinese herbs.Methods: The biophoton characteristics of motherwort and safflower were measured and characterized by the counts per second (CPS) in the steady state and the initial intensity (I0) and coherent time (T) of delayed luminescence. The active ingredient content was measured by ultra-high-performance liquid chromatography (UPLC). The pigment content of motherwort leaves was measured by UV spectrophotometry. The t-test and correlation analysis were performed on the experimental results.Results: The CPS and I0 of motherwort and I0 of safflower showed a significant downward trend during the growth process, and their active ingredient content showed a trend that increased and then decreased. The CPS, I0, and the content of active ingredients and pigments in a healthy state were significantly higher than those in a poor state, while T showed the opposite results. The CPS and I0 were all significantly and positively correlated with the content of active ingredients and pigments, while the T of motherwort showed the opposite results.Conclusion: It is feasible to identify the quality states of fresh Chinese herbs by using their biophoton characteristics. Both CPS and I0 have better correlations with the quality states and can be considered characteristic parameters of the quality of fresh Chinese herbs

Cathepsins and cancer risk: a Mendelian randomization study

BackgroundPrevious observational epidemiological studies reported an association between cathepsins and cancer, however, a causal relationship is uncertain. This study evaluated the causal relationship between cathepsins and cancer using Mendelian randomization (MR) analysis.MethodsWe used publicly available genome-wide association study (GWAS) data for bidirectional MR analysis. Inverse variance weighting (IVW) was used as the primary MR method of MR analysis.ResultsAfter correction for the False Discovery Rate (FDR), two cathepsins were found to be significantly associated with cancer risk: cathepsin H (CTSH) levels increased the risk of lung cancer (OR = 1.070, 95% CI = 1.027–1.114, P = 0.001, PFDR= 0.009), and CTSH levels decreased the risk of basal cell carcinoma (OR = 0.947, 95% CI = 0.919–0.975, P = 0.0002, PFDR= 0.002). In addition, there was no statistically significant effect of the 20 cancers on the nine cathepsins. Some unadjusted low P-value phenotypes are worth mentioning, including a positive correlation between cathepsin O (CTSO) and breast cancer (OR = 1.012, 95% CI = 1.001–1.025, P = 0.041), cathepsin S (CTSS) and pharyngeal cancer (OR = 1.017, 95% CI = 1.001–1.034, P = 0.043), and CTSS and endometrial cancer (OR = 1.055, 95% CI = 1.012–1.101, P = 0.012); and there was a negative correlation between cathepsin Z and ovarian cancer (CTSZ) (OR = 0.970, 95% CI = 0.949–0.991, P = 0.006), CTSS and prostate cancer (OR = 0.947, 95% CI = 0.902–0.944, P = 0.028), and cathepsin E (CTSE) and pancreatic cancer (OR = 0.963, 95% CI = 0.938–0.990, P = 0.006).ConclusionOur MR analyses showed a causal relationship between cathepsins and cancers and may help provide new insights for further mechanistic and clinical studies of cathepsin-mediated cancer

Use of Radiomics Combined With Machine Learning Method in the Recurrence Patterns After Intensity-Modulated Radiotherapy for Nasopharyngeal Carcinoma: A Preliminary Study

Objective: To analyze the recurrence patterns and reasons in patients with nasopharyngeal carcinoma (NPC) treated with intensity-modulated radiotherapy (IMRT) and to investigate the feasibility of radiomics for analysis of radioresistance.Methods: We analyzed 306 NPC patients treated with IMRT from Jul-2009 to Aug-2016, 20 of whom developed with recurrence. For the NPCs with recurrence, CT, MR, or PET/CT images of recurrent disease were registered with the primary planning CT for dosimetry analysis. The recurrences were defined as in-field, marginal or out-of-field, according to dose-volume histogram (DVH) of the recurrence volume. To explore the predictive power of radiomics for NPCs with in-field recurrences (NPC-IFR), 16 NPCs with non-progression disease (NPC-NPD) were used for comparison. For these NPC-IFRs and NPC-NPDs, 1117 radiomic features were quantified from the tumor region using pre-treatment spectral attenuated inversion-recovery T2-weighted (SPAIR T2W) magnetic resonance imaging (MRI). Intraclass correlation coefficients (ICC) and Pearson correlation coefficient (PCC) was calculated to identify influential feature subset. Kruskal-Wallis test and receiver operating characteristic (ROC) analysis were employed to assess the capability of each feature on NPC-IFR prediction. Principal component analysis (PCA) was performed for feature reduction. Artificial neural network (ANN), k-nearest neighbor (KNN), and support vector machine (SVM) models were trained and validated by using stratified 10-fold cross validation.Results: The median follow up was 26.5 (range 8–65) months. 9/20 (45%) occurred in the primary tumor, 8/20 (40%) occurred in regional lymph nodes, and 3/20 (15%) patients developed a primary and regional failure. Dosimetric and target volume analysis of the recurrence indicated that there were 18 in-field, and 1 marginal as well as 1 out-of-field recurrence. With pre-therapeutic SPAIR T2W MRI images available, 11 NPC-IFRs (11 of 18 NPC-IFRs who had available pre-therapeutic MRI) and 16 NPC-NPDs were subsequently employed for radiomic analysis. Results showed that NPC-IFRs vs. NPC-NPDs could be differentiated by 8 features (AUCs: 0.727–0.835). The classification models showed potential in prediction of NPC-IFR with higher accuracies (ANN: 0.812, KNN: 0.775, SVM: 0.732).Conclusion: In-field and high-dose region relapse were the main recurrence patterns which may be due to the radioresistance. After integration in the clinical workflow, radiomic analysis can be served as imaging biomarkers to facilitate early salvage for NPC patients who are at risk of in-field recurrence

Efficacy and safety of second-line therapy by S-1 combined with sintilimab and anlotinib in pancreatic cancer patients with liver metastasis: a single-arm, phase II clinical trial

BackgroundPancreatic adenocarcinoma carries a grim prognosis, and there are few recognized effective second-line treatment strategies. We attempted to evaluate the efficacy and safety of a combination of S-1, sintilimab, and anlotinib as a second-line treatment in pancreatic cancer patients with liver metastasis.MethodsPancreatic cancer patients with liver metastases were recruited. S-1 was administered orally at 25 mg/m2 bid, anlotinib was administered orally at 12 mg qd from day 1 to day 14, and sintilimab was administered intravenously at 200 mg on day 1. This method was repeated every 21 days, and the therapeutic effect was evaluated every 3 cycles. The primary outcome was the objective response rate (ORR).ResultsOverall, 23 patients were enrolled in this study of whom 19 patients had objective efficacy evaluation. The ORR was 10.5% (95% CI 0.4%–25.7%) in the evaluable population. The progression-free survival (PFS) was 3.53 (95% CI 2.50–7.50) months, and the overall survival (mOS) was 8.53 (95% CI 4.97–14.20) months. Grade 3 adverse events were 26.1%, and no grade 4 or above adverse events occurred. High-throughput sequencing was performed on the tumor tissues of 16 patients; patients with HRD-H (n = 10) had shorter PFS than those with HRD-L (n = 6) (2.43 vs. 5.45 months; P = 0.043), but there was no significant difference in OS between the two groups (4.43 vs. 9.35 months; P = 0.11).ConclusionsThis study suggests the advantage of S-1 combined with sintilimab and anlotinib in extending OS as a second-line therapy in pancreatic cancer patients with liver metastasis.Clinical Trial Registration: ChiCTR200003065