Dlx5 Is a Cell Autonomous Regulator of Chondrocyte Hypertrophy in Mice and Functionally Substitutes for Dlx6 during Endochondral Ossification

The axial and appendicular skeleton of vertebrates develops by endochondral ossification, in which skeletogenic tissue is initially cartilaginous and the differentiation of chondrocytes via the hypertrophic pathway precedes the differentiation of osteoblasts and the deposition of a definitive bone matrix. Results from both loss-of-function and misexpression studies have implicated the related homeobox genes Dlx5 and Dlx6 as partially redundant positive regulators of chondrocyte hypertrophy. However, experimental perturbations of Dlx expression have either not been cell type specific or have been done in the context of endogenous Dlx5 expression. Thus, it has not been possible to conclude whether the effects on chondrocyte differentiation are cell autonomous or whether they are mediated by Dlx expression in adjacent tissues, notably the perichondrium. To address this question we first engineered transgenic mice in which Dlx5 expression was specifically restricted to immature and differentiating chondrocytes and not the perichondrium. Col2a1-Dlx5 transgenic embryos and neonates displayed accelerated chondrocyte hypertrophy and mineralization throughout the endochondral skeleton. Furthermore, this transgene specifically rescued defects of chondrocyte differentiation characteristic of the Dlx5/6 null phenotype. Based on these results, we conclude that the role of Dlx5 in the hypertrophic pathway is cell autonomous. We further conclude that Dlx5 and Dlx6 are functionally equivalent in the endochondral skeleton, in that the requirement for Dlx5 and Dlx6 function during chondrocyte hypertrophy can be satisfied with Dlx5 alone

Debiased Fine-Tuning for Vision-language Models by Prompt Regularization

We present a new paradigm for fine-tuning large-scale visionlanguage pre-trained models on downstream task, dubbed Prompt Regularization (ProReg). Different from traditional fine-tuning which easily overfits to the downstream task data, ProReg uses the prediction by prompting the pretrained model to regularize the fine-tuning. The motivation is: by prompting the large model "a photo of a [CLASS]", the fil-lin answer is only dependent on the pretraining encyclopedic knowledge while independent of the task data distribution, which is usually biased. Specifically, given a training sample prediction during fine-tuning, we first calculate its KullbackLeibler loss of the prompt prediction and Cross-Entropy loss of the ground-truth label, and then combine them with a proposed sample-wise adaptive trade-off weight, which automatically adjusts the transfer between the pretrained and downstream domains. On various out-of-distribution benchmarks, we show the consistently strong performance of ProReg compared with conventional fine-tuning, zero-shot prompt, prompt tuning, and other state-of-the-art methods.Comment: AAAI2023 accepte

Prompt-aligned Gradient for Prompt Tuning

Thanks to the large pre-trained vision-language models (VLMs) like CLIP, we can craft a zero-shot classifier by "prompt", e.g., the confidence score of an image being "[CLASS]" can be obtained by using the VLM provided similarity measure between the image and the prompt sentence "a photo of a [CLASS]". Therefore, prompt shows a great potential for fast adaptation of VLMs to downstream tasks if we fine-tune the prompt-based similarity measure. However, we find a common failure that improper fine-tuning may not only undermine the prompt's inherent prediction for the task-related classes, but also for other classes in the VLM vocabulary. Existing methods still address this problem by using traditional anti-overfitting techniques such as early stopping and data augmentation, which lack a principled solution specific to prompt. We present Prompt-aligned Gradient, dubbed ProGrad, to prevent prompt tuning from forgetting the the general knowledge learned from VLMs. In particular, ProGrad only updates the prompt whose gradient is aligned (or non-conflicting) to the "general direction", which is represented as the gradient of the KL loss of the pre-defined prompt prediction. Extensive experiments demonstrate the stronger few-shot generalization ability of ProGrad over state-of-the-art prompt tuning methods. Codes are available at https://github.com/BeierZhu/Prompt-align.Comment: Accepted by ICCV202

A Comprehensive Molecular Interaction Map for Rheumatoid Arthritis

Computational biology contributes to a variety of areas related to life sciences and, due to the growing impact of translational medicine - the scientific approach to medicine in tight relation with basic science -, it is becoming an important player in clinical-related areas. In this study, we use computation methods in order to improve our understanding of the complex interactions that occur between molecules related to Rheumatoid Arthritis (RA).Due to the complexity of the disease and the numerous molecular players involved, we devised a method to construct a systemic network of interactions of the processes ongoing in patients affected by RA. The network is based on high-throughput data, refined semi-automatically with carefully curated literature-based information. This global network has then been topologically analysed, as a whole and tissue-specifically, in order to translate the experimental molecular connections into topological motifs meaningful in the identification of tissue-specific markers and targets in the diagnosis, and possibly in the therapy, of RA.’

Leveraging Modality-specific Representations for Audio-visual Speech Recognition via Reinforcement Learning

Audio-visual speech recognition (AVSR) has gained remarkable success for ameliorating the noise-robustness of speech recognition. Mainstream methods focus on fusing audio and visual inputs to obtain modality-invariant representations. However, such representations are prone to over-reliance on audio modality as it is much easier to recognize than video modality in clean conditions. As a result, the AVSR model underestimates the importance of visual stream in face of noise corruption. To this end, we leverage visual modality-specific representations to provide stable complementary information for the AVSR task. Specifically, we propose a reinforcement learning (RL) based framework called MSRL, where the agent dynamically harmonizes modality-invariant and modality-specific representations in the auto-regressive decoding process. We customize a reward function directly related to task-specific metrics (i.e., word error rate), which encourages the MSRL to effectively explore the optimal integration strategy. Experimental results on the LRS3 dataset show that the proposed method achieves state-of-the-art in both clean and various noisy conditions. Furthermore, we demonstrate the better generality of MSRL system than other baselines when test set contains unseen noises.Comment: Accepted by AAAI202

Reduced EGFR signaling enhances cartilage destruction in a mouse osteoarthritis model

Osteoarthritis (OA) is a degenerative joint disease and a major cause of pain and disability in older adults. We have previously identified epidermal growth factor receptor (EGFR) signaling as an important regulator of cartilage matrix degradation during epiphyseal cartilage development. To study its function in OA progression, we performed surgical destabilization of the medial meniscus (DMM) to induce OA in two mouse models with reduced EGFR activity, one with genetic modification (Egfr Wa5/+ mice) and the other one with pharmacological inhibition (gefitinib treatment). Histological analyses and scoring at 3 months post-surgery revealed increased cartilage destruction and accelerated OA progression in both mouse models. TUNEL staining demonstrated that EGFR signaling protects chondrocytes from OA-induced apoptosis, which was further confirmed in primary chondrocyte culture. Immunohistochemistry showed increased aggrecan degradation in these mouse models, which coincides with elevated amounts of ADAMTS5 and matrix metalloproteinase 13 (MMP13), the principle proteinases responsible for aggrecan degradation, in the articular cartilage after DMM surgery. Furthermore, hypoxia-inducible factor 2α (HIF2α), a critical catabolic transcription factor stimulating MMP13 expression during OA, was also upregulated in mice with reduced EGFR signaling. Taken together, our findings demonstrate a primarily protective role of EGFR during OA progression by regulating chondrocyte survival and cartilage degradation

The critical role of the epidermal growth factor receptor in endochondral ossification

Loss of epidermal growth factor receptor (EGFR) activity in mice alters growth plate development, impairs endochondral ossification, and retards growth. However, the detailed mechanism by which EGFR regulates endochondral bone formation is unknown. Here, we show that administration of an EGFR-specific small-molecule inhibitor, gefitinib, into 1-month-old rats for 7 days produced profound defects in long bone growth plate cartilage characterized by epiphyseal growth plate thickening and massive accumulation of hypertrophic chondrocytes. Immunostaining demonstrated that growth plate chondrocytes express EGFR, but endothelial cells and osteoclasts show little to no expression. Gefitinib did not alter chondrocyte proliferation or differentiation and vascular invasion into the hypertrophic cartilage. However, osteoclast recruitment and differentiation at the chondro-osseous junction were attenuated owing to decreased RANKL expression in the growth plate. Moreover, gefitinib treatment inhibited the expression of matrix metalloproteinases (MMP-9, -13, and -14), increased the amount of collagen fibrils, and decreased degraded extracellular matrix products in the growth plate. In vitro, the EGFR ligand transforming growth factor α (TGF-α) strongly stimulated RANKL and MMPs expression and suppressed osteoprotegerin (OPG) expression in primary chondrocytes. In addition, a mouse model of cartilage-specific EGFR inactivation exhibited a similar phenotype of hypertrophic cartilage enlargement. Together our data demonstrate that EGFR signaling supports osteoclastogenesis at the chondro-osseous junction and promotes chondrogenic expression of MMPs in the growth plate. Therefore, we conclude that EGFR signaling plays an essential role in the remodeling of growth plate cartilage extracellular matrix into bone during endochondral ossification. © 2011 American Society for Bone and Mineral Research

WNT signaling regulates self-renewal and differentiation of prostate cancer cells with stem cell characteristics

Prostate cancer cells with stem cell characteristics were identified in human prostate cancer cell lines by their ability to form from single cells self-renewing prostaspheres in non-adherent cultures. Prostaspheres exhibited heterogeneous expression of proliferation, differentiation and stem cell-associated makers CD44, ABCG2 and CD133. Treatment with WNT inhibitors reduced both prostasphere size and self-renewal. In contrast, addition of Wnt3a caused increased prostasphere size and self-renewal, which was associated with a significant increase in nuclear Β-catenin, keratin 18, CD133 and CD44 expression. As a high proportion of LNCaP and C4-2B cancer cells express androgen receptor we determined the effect of the androgen receptor antagonist bicalutamide. Androgen receptor inhibition reduced prostasphere size and expression of PSA, but did not inhibit prostasphere formation. These effects are consistent with the androgen-independent self-renewal of cells with stem cell characteristics and the androgen-dependent proliferation of transit amplifying cells. As the canonical WNT signaling effector Β-catenin can also associate with the androgen receptor, we propose a model for tumour propagation involving a balance between WNT and androgen receptor activity. That would affect the self-renewal of a cancer cell with stem cell characteristics and drive transit amplifying cell proliferation and differentiation. In conclusion, we provide evidence that WNT activity regulates the self-renewal of prostate cancer cells with stem cell characteristics independently of androgen receptor activity. Inhibition of WNT signaling therefore has the potential to reduce the self-renewal of prostate cancer cells with stem cell characteristics and improve the therapeutic outcome.Peer reviewe

3D transient heat transfer numerical analysis of multiple energy piles

This paper presents a three-dimensional (3D) transient heat transfer numerical model for multiple energy piles based on the finite volume method (FVM). The initial and boundary conditions are established and the effects of “thermal short-circulating” between two pipes of a U-tube in energy pile are investigated. Thermal partial differential equations are discretized at the spatial nodal points and solved by linear approximation method. Temperature variations of working fluid, energy pile and its surrounding soil from simulation program are compared with experimental data to validate the developed model. In addition, the influences of fluid flow rate and U-tube shank spacing are analysed. It is established that the shank spacing should be set in a range of 0.06m to 0.10m to reduce heat transfer between the two pipes and meet the structural requirement. Meanwhile, the flow rate should be controlled in a range of 0.5m3/h to 0.7m3/h to avoid the low outlet fluid temperature and decrease the influence of “thermal short-circuiting”