T2I-CompBench: A Comprehensive Benchmark for Open-world Compositional Text-to-image Generation

Despite the stunning ability to generate high-quality images by recent text-to-image models, current approaches often struggle to effectively compose objects with different attributes and relationships into a complex and coherent scene. We propose T2I-CompBench, a comprehensive benchmark for open-world compositional text-to-image generation, consisting of 6,000 compositional text prompts from 3 categories (attribute binding, object relationships, and complex compositions) and 6 sub-categories (color binding, shape binding, texture binding, spatial relationships, non-spatial relationships, and complex compositions). We further propose several evaluation metrics specifically designed to evaluate compositional text-to-image generation. We introduce a new approach, Generative mOdel fine-tuning with Reward-driven Sample selection (GORS), to boost the compositional text-to-image generation abilities of pretrained text-to-image models. Extensive experiments and evaluations are conducted to benchmark previous methods on T2I-CompBench, and to validate the effectiveness of our proposed evaluation metrics and GORS approach. Project page is available at https://karine-h.github.io/T2I-CompBench/.Comment: Project page: https://karine-h.github.io/T2I-CompBench

Contrastive Latent Space Reconstruction Learning for Audio-Text Retrieval

Cross-modal retrieval (CMR) has been extensively applied in various domains, such as multimedia search engines and recommendation systems. Most existing CMR methods focus on image-to-text retrieval, whereas audio-to-text retrieval, a less explored domain, has posed a great challenge due to the difficulty to uncover discriminative features from audio clips and texts. Existing studies are restricted in the following two ways: 1) Most researchers utilize contrastive learning to construct a common subspace where similarities among data can be measured. However, they considers only cross-modal transformation, neglecting the intra-modal separability. Besides, the temperature parameter is not adaptively adjusted along with semantic guidance, which degrades the performance. 2) These methods do not take latent representation reconstruction into account, which is essential for semantic alignment. This paper introduces a novel audio-text oriented CMR approach, termed Contrastive Latent Space Reconstruction Learning (CLSR). CLSR improves contrastive representation learning by taking intra-modal separability into account and adopting an adaptive temperature control strategy. Moreover, the latent representation reconstruction modules are embedded into the CMR framework, which improves modal interaction. Experiments in comparison with some state-of-the-art methods on two audio-text datasets have validated the superiority of CLSR.Comment: Accepted by The 35th IEEE International Conference on Tools with Artificial Intelligence. (ICTAI 2023

A handcuff model for the cohesin complex

The cohesin complex is responsible for the accurate separation of sister chromatids into two daughter cells. Several models for the cohesin complex have been proposed, but the one-ring embrace model currently predominates the field. However, the static configuration of the embrace model is not flexible enough for cohesins to perform their functions during DNA replication, transcription, and DNA repair. We used coimmunoprecipitation, a protein fragment complement assay, and a yeast two-hybrid assay to analyze the protein–protein interactions among cohesin subunits. The results show that three of the four human cohesin core subunits (Smc1, Smc3, and Rad21) interact with themselves in an Scc3 (SA1/SA2)-dependent manner. These data support a two-ring handcuff model for the cohesin complex, which is flexible enough to establish and maintain sister chromatid cohesion as well as ensure the fidelity of chromosome segregation in higher eukaryotes

The Volumetric Extended-Schmidt Law: A Unity Slope

We investigate the extended-Schmidt (ES) law in volume densities ($\rho_{\rm SFR}$ $\propto$ $(\rho_{\rm gas}\rho_{\rm star}^{0.5})^{\alpha^{\rm VES}}$) for spatially-resolved regions in spiral, dwarf, and ultra-diffuse galaxies (UDGs), and compare to the volumetric Kennicutt-Schmidt (KS) law ($\rho_{\rm SFR}$ $\propto$ $\rho_{\rm gas}^{\alpha^{\rm VKS}}$). We first characterize these star formation laws in individual galaxies using a sample of 11 spirals, finding median slopes $\alpha^{\rm VES}$=0.98 and $\alpha^{\rm VKS}$=1.42, with a galaxy-to-galaxy rms fluctuation that is substantially smaller for the volumetric ES law (0.18 vs 0.41). By combining all regions in spirals with those in additional 13 dwarfs and one UDG into one single dataset, it is found that the rms scatter of the volumetric ES law at given x-axis is 0.25 dex, also smaller than that of the volumetric KS law (0.34 dex). At the extremely low gas density regime as offered by the UDG, the volumetric KS law breaks down but the volumetric ES law still holds. On the other hand, as compared to the surface density ES law, the volumetric ES law instead has a slightly larger rms scatter, consistent with the scenario that the ES law has an intrinsic slope of $\alpha^{\rm VES} \equiv$1 but the additional observational error of the scale height increases the uncertainty of the volume density. The unity slope of the ES law implies that the star formation efficiency (=$\rho_{\rm SFR}$/$\rho_{\rm gas}$) is regulated by the quantity that is related to the $\rho_{\rm star}^{0.5}$.Comment: 15 pages, 8 figures, accepted by MNRA

The \ion{H}{I}-rich Ultra-diffuse Galaxies follow the Extended Schmidt Law

The \ion{H}{I}-rich ultra-diffuse galaxies (HUDGs) offer a unique case for studies of star formation laws (SFLs) as they host low star formation efficiency (SFE) and low-metallicity environments where gas is predominantly atomic. We collect a sample of six HUDGs in the field and investigate their location in the extended Schmidt law($\Sigma_{\text {SFR }} \propto \left(\Sigma_{\text{star}}^{0.5} \Sigma_{\text{gas}}\right)^{1.09}$). They are consistent with this relationship well (with deviations of only 1.1 sigma). Furthermore, we find that HUDGs follow the tight correlation between the hydrostatic pressure in the galaxy mid-plane and the quantity on the x-axis ($\rm log(\Sigma_{star}^{0.5}\Sigma_{gas})$) of the extended Schmidt law. This result indicates that these HUDGs can be self-regulated systems that reach the dynamical and thermal equilibrium. In this framework, the stellar gravity compresses the disk vertically and counteracts the gas pressure in the galaxy mid-plane to regulate the star formation as suggested by some theoretical models.Comment: 6 pages, 4 figures, accepted for publication in MNRA

Study on Calculation Method of Soluble Aerosol Removal Efficiency Under High Humidity Condition

Pool scrubbing is a potential method to remove aerosol particles under accident conditions of nuclear power plants. The relative humidity of aerosol laden gas will increase significantly when passing through the water pool, which will most likely induce hygroscopic growth of soluble aerosol. The hygroscopic growth of soluble aerosol can lead to the deviation of the size distribution of aerosol at the outlet of the water pool, resulting in a large evaluation error of the removal efficiency. In order to solve this problem, the size distributions of sodium chloride at the upstream and downstream of bubble column were measured at a gas flow rate of 4 lpm and a liquid height of 80 cm, respectively. Two methods of calculating aerosol actual size-dependency removal efficiency were proposed and compared. One method is directly calculating the removal efficiency by adding a diffusion drying tube installed at the upstream of Scanning Mobility Particle Sizer (SMPS) to reduce the relative humidity of sample gas below the efflorescence point. Another method is modifying the aerosol size distribution and concentration curve by using the hygroscopic growth theory of soluble aerosols. The experiment results obtained by the two methods are in good agreement

CD8(+) T Cells Involved in Metabolic Inflammation in Visceral Adipose Tissue and Liver of Transgenic Pigs

Anti-inflammatory therapies have the potential to become an effective treatment for obesity-related diseases. However, the huge gap of immune system between human and rodent leads to limitations of drug discovery. This work aims at constructing a transgenic pig model with higher risk of metabolic diseases and outlining the immune responses at the early stage of metaflammation by transcriptomic strategy. We used CRISPR/Cas9 techniques to targeted knock-in three humanized disease risk genes, GIPR(dn) , hIAPP and PNPLA3(I148M) . Transgenic effect increased the risk of metabolic disorders. Triple-transgenic pigs with short-term diet intervention showed early symptoms of type 2 diabetes, including glucose intolerance, pancreatic lipid infiltration, islet hypertrophy, hepatic lobular inflammation and adipose tissue inflammation. Molecular pathways related to CD8(+) T cell function were significantly activated in the liver and visceral adipose samples from triple-transgenic pigs, including antigen processing and presentation, T-cell receptor signaling, co-stimulation, cytotoxicity, and cytokine and chemokine secretion. The similar pro-inflammatory signaling in liver and visceral adipose tissue indicated that there might be a potential immune crosstalk between the two tissues. Moreover, genes that functionally related to liver antioxidant activity, mitochondrial function and extracellular matrix showed distinct expression between the two groups, indicating metabolic stress in transgenic pigs' liver samples. We confirmed that triple-transgenic pigs had high coincidence with human metabolic diseases, especially in the scope of inflammatory signaling at early stage metaflammation. Taken together, this study provides a valuable large animal model for the clinical study of metaflammation and metabolic diseases.Peer reviewe

Cardiovascular mortality by cancer risk stratification in patients with localized prostate cancer: a SEER-based study

PurposeThe risk of cardiovascular disease (CVD) mortality in patients with localized prostate cancer (PCa) by risk stratification remains unclear. The aim of this study was to determine the risk of CVD death in patients with localized PCa by risk stratification.Patients and methodsPopulation-based study of 340,806 cases in the Surveillance, Epidemiology, and End Results (SEER) database diagnosed with localized PCa between 2004 and 2016. The proportion of deaths identifies the primary cause of death, the competing risk model identifies the interaction between CVD and PCa, and the standardized mortality rate (SMR) quantifies the risk of CVD death in patients with PCa.ResultsCVD-related death was the leading cause of death in patients with localized PCa, and cumulative CVD-related death also surpassed PCa almost as soon as PCa was diagnosed in the low- and intermediate-risk groups. However, in the high-risk group, CVD surpassed PCa approximately 90 months later. Patients with localized PCa have a higher risk of CVD-related death compared to the general population and the risk increases steadily with survival (SMR = 4.8, 95% CI 4.6–5.1 to SMR = 13.6, 95% CI 12.8–14.5).ConclusionsCVD-related death is a major competing risk in patients with localized PCa, and cumulative CVD mortality increases steadily with survival time and exceeds PCa in all three stratifications (low, intermediate, and high risk). Patients with localized PCa have a higher CVD-related death than the general population. Management of patients with localized PCa requires attention to both the primary cancer and CVD

Multiple Roles of BRIT1/MCPH1 in DNA Damage Response, DNA Repair, and Cancer Suppression

Mammalian cells are frequently at risk of DNA damage from both endogenous and exogenous sources. Accordingly, cells have evolved the DNA damage response (DDR) pathways to monitor and assure the integrity of their genome. In cells, the intact and effective DDR is essential for the maintenance of genomic stability and it acts as a critical barrier to suppress the development of cancer in humans. Two central kinases for the DDR pathway are ATM and ATR, which can phosphorylate and activate many downstream proteins for cell cycle arrest, DNA repair, or apoptosis if the damages are irreparable. In the last several years, we and others have made significant progress to this field by identifying BRIT1 (also known as MCPH1) as a novel key regulator in the DDR pathway. BRIT1 protein contains 3 breast cancer carboxyl terminal (BRCT) domains which are conserved in BRCA1, MDC1, 53BP1, and other important molecules involved in DNA damage signaling, DNA repair, and tumor suppression. Our in vitro studies revealed BRIT1 to be a chromatin-binding protein required for recruitment of many important DDR proteins (ATM, MDC1, NBS1, RAD51, BRCA2) to the DNA damage sites. We recently also generated the BRIT1 knockout mice and demonstrated its essential roles in homologous recombination DNA repair and in maintaining genomic stability in vivo. In humans, BRIT1 is located on chromosome 8p23.1, where loss of hetero-zigosity is very common in many types of cancer. In this review, we will summarize the novel roles of BRIT1 in DDR, describe the relationship of BRIT1 deficiency with cancer development, and also discuss the use of synthetic lethality approach to target cancers with HR defects due to BRIT1 deficiency

siRNA-Based Targeting of Cyclin E Overexpression Inhibits Breast Cancer Cell Growth and Suppresses Tumor Development in Breast Cancer Mouse Model

Cyclin E is aberrantly expressed in many types of cancer including breast cancer. High levels of the full length as well as the low molecular weight isoforms of cyclin E are associated with poor prognosis of breast cancer patients. Notably, cyclin E overexpression is also correlated with triple-negative basal-like breast cancers, which lack specific therapeutic targets. In this study, we used siRNA to target cyclin E overexpression and assessed its ability to suppress breast cancer growth in nude mice. Our results revealed that cyclin E siRNA could effectively inhibit overexpression of both full length and low molecular weight isoforms of cyclin E. We found that depletion of cyclin E promoted apoptosis of cyclin E-overexpressing cells and blocked their proliferation and transformation phenotypes. Significantly, we further demonstrated that administration of cyclin E siRNA could inhibit breast tumor growth in nude mice. In addition, we found that cyclin E siRNA synergistically enhanced the cell killing effects of doxorubicin in cell culture and this combination greatly suppressed the tumor growth in mice. In conclusion, our results indicate that cyclin E, which is overexpressed in 30% of breast cancer, may serve as a novel and effective therapeutic target. More importantly, our study clearly demonstrates a very promising therapeutic potential of cyclin E siRNA for treating the cyclin E-overexpressing breast cancers, including the very malignant triple-negative breast cancers