A novel arabinose-inducible genetic operation system developed for Clostridium cellulolyticum

<p> Background: Clostridium cellulolyticum and other cellulolytic Clostridium strains are natural producers of lignocellulosic biofuels and chemicals via the consolidated bioprocessing (CBP) route, and systems metabolic engineering is indispensable to meet the cost-efficient demands of industry. Several genetic tools have been developed for Clostridium strains, and an efficient and stringent inducible genetic operation system is still required for the precise regulation of the target gene function.</p

Prevalence of Kaposi’s sarcoma-associated herpesvirus in Uygur and Han populations from the Urumqi and Kashgar regions of Xinjiang, China

Kaposi’s sarcoma-associated herpesvirus (KSHV) is the infectious etiologic agent associated with Kaposi’s sarcoma (KS), primary effusion lymphoma, and multicentric Castleman disease. It has been shown that high KSHV prevalence and high incidence of both classic KS and AIDSassociated KS are found mostly among people of Uygur ethnicity in Xinjiang, while people of Han ethnicity in Xinjiang have a higher KSHV seroprevalence than those of other Han populations in mainland China. However, it is still unclear why there is such geographical and population variation in KSHV distribution in China. In this work, we focused on the populations in the Kashgar region and Urumqi area, where a total of 1294 research subjects were randomly selected to investigate the potential correlation between KSHV prevalence and different ethnicities in endemic areas of Xinjiang, and to determine risk factors that may affect KSHV infection rates or KS incidence. We identified a high seroprevalence of KSHV and high peripheral blood DNA infection in the general Uygur and Han populations in both Urumqi and Kashgar regions of Xinjiang, and determined that advancing age, low education level, and stationary population status affect KSHV infection rates. Further, KSHV-positive Uygur participants were shown to have higher prevalence of neutralizing antibodies and neutralizing antibody titers than KSHV-positive Han participants

p38α MAPK regulates proliferation and differentiation of osteoclast progenitors and bone remodeling in an aging-dependent manner.

Bone mass is determined by the balance between bone formation, carried out by mesenchymal stem cell-derived osteoblasts, and bone resorption, carried out by monocyte-derived osteoclasts. Here we investigated the potential roles of p38 MAPKs, which are activated by growth factors and cytokines including RANKL and BMPs, in osteoclastogenesis and bone resorption by ablating p38α MAPK in LysM+monocytes. p38α deficiency promoted monocyte proliferation but regulated monocyte osteoclastic differentiation in a cell-density dependent manner, with proliferating p38α-/- cultures showing increased differentiation. While young mutant mice showed minor increase in bone mass, 6-month-old mutant mice developed osteoporosis, associated with an increase in osteoclastogenesis and bone resorption and an increase in the pool of monocytes. Moreover, monocyte-specific p38α ablation resulted in a decrease in bone formation and the number of bone marrow mesenchymal stem/stromal cells, likely due to decreased expression of PDGF-AA and BMP2. The expression of PDGF-AA and BMP2 was positively regulated by the p38 MAPK-Creb axis in osteoclasts, with the promoters of PDGF-AA and BMP2 having Creb binding sites. These findings uncovered the molecular mechanisms by which p38α MAPK regulates osteoclastogenesis and coordinates osteoclastogenesis and osteoblastogenesis

SWBT: Similarity Weighted Behavior Transformer with the Imperfect Demonstration for Robotic Manipulation

Imitation learning (IL), aiming to learn optimal control policies from expert demonstrations, has been an effective method for robot manipulation tasks. However, previous IL methods either only use expensive expert demonstrations and omit imperfect demonstrations or rely on interacting with the environment and learning from online experiences. In the context of robotic manipulation, we aim to conquer the above two challenges and propose a novel framework named Similarity Weighted Behavior Transformer (SWBT). SWBT effectively learn from both expert and imperfect demonstrations without interaction with environments. We reveal that the easy-to-get imperfect demonstrations, such as forward and inverse dynamics, significantly enhance the network by learning fruitful information. To the best of our knowledge, we are the first to attempt to integrate imperfect demonstrations into the offline imitation learning setting for robot manipulation tasks. Extensive experiments on the ManiSkill2 benchmark built on the high-fidelity Sapien simulator and real-world robotic manipulation tasks demonstrated that the proposed method can extract better features and improve the success rates for all tasks. Our code will be released upon acceptance of the paper.Comment: 8 pages, 5 figure

Controlling Text-to-Image Diffusion by Orthogonal Finetuning

Large text-to-image diffusion models have impressive capabilities in generating photorealistic images from text prompts. How to effectively guide or control these powerful models to perform different downstream tasks becomes an important open problem. To tackle this challenge, we introduce a principled finetuning method -- Orthogonal Finetuning (OFT), for adapting text-to-image diffusion models to downstream tasks. Unlike existing methods, OFT can provably preserve hyperspherical energy which characterizes the pairwise neuron relationship on the unit hypersphere. We find that this property is crucial for preserving the semantic generation ability of text-to-image diffusion models. To improve finetuning stability, we further propose Constrained Orthogonal Finetuning (COFT) which imposes an additional radius constraint to the hypersphere. Specifically, we consider two important finetuning text-to-image tasks: subject-driven generation where the goal is to generate subject-specific images given a few images of a subject and a text prompt, and controllable generation where the goal is to enable the model to take in additional control signals. We empirically show that our OFT framework outperforms existing methods in generation quality and convergence speed.Comment: NeurIPS 2023 (43 pages, 34 figures, project page: https://oft.wyliu.com/