Directing mesenchymal stem cells to bone to augment bone formation and increase bone mass.

Aging reduces the number of mesenchymal stem cells (MSCs) that can differentiate into osteoblasts in the bone marrow, which leads to impairment of osteogenesis. However, if MSCs could be directed toward osteogenic differentiation, they could be a viable therapeutic option for bone regeneration. We have developed a method to direct MSCs to the bone surface by attaching a synthetic high-affinity and specific peptidomimetic ligand (LLP2A) against integrin α4β1 on the MSC surface to a bisphosphonate (alendronate, Ale) that has a high affinity for bone. LLP2A-Ale induced MSC migration and osteogenic differentiation in vitro. A single intravenous injection of LLP2A-Ale increased trabecular bone formation and bone mass in both xenotransplantation studies and in immunocompetent mice. Additionally, LLP2A-Ale prevented trabecular bone loss after peak bone acquisition was achieved or as a result of estrogen deficiency. These results provide proof of principle that LLP2A-Ale can direct MSCs to the bone to form new bone and increase bone strength

Instant3D: Instant Text-to-3D Generation

Text-to-3D generation, which aims to synthesize vivid 3D objects from text prompts, has attracted much attention from the computer vision community. While several existing works have achieved impressive results for this task, they mainly rely on a time-consuming optimization paradigm. Specifically, these methods optimize a neural field from scratch for each text prompt, taking approximately one hour or more to generate one object. This heavy and repetitive training cost impedes their practical deployment. In this paper, we propose a novel framework for fast text-to-3D generation, dubbed Instant3D. Once trained, Instant3D is able to create a 3D object for an unseen text prompt in less than one second with a single run of a feedforward network. We achieve this remarkable speed by devising a new network that directly constructs a 3D triplane from a text prompt. The core innovation of our Instant3D lies in our exploration of strategies to effectively inject text conditions into the network. Furthermore, we propose a simple yet effective activation function, the scaled-sigmoid, to replace the original sigmoid function, which speeds up the training convergence by more than ten times. Finally, to address the Janus (multi-head) problem in 3D generation, we propose an adaptive Perp-Neg algorithm that can dynamically adjust its concept negation scales according to the severity of the Janus problem during training, effectively reducing the multi-head effect. Extensive experiments on a wide variety of benchmark datasets demonstrate that the proposed algorithm performs favorably against the state-of-the-art methods both qualitatively and quantitatively, while achieving significantly better efficiency. The project page is at https://ming1993li.github.io/Instant3DProj.Comment: Project page: https://ming1993li.github.io/Instant3DPro

OLIG2 expression level could be used as an independent prognostic factor for patients with cerebellar Glioblastoma (cGBM)

Objectives: The incidence of cerebellar Glioblastoma Multiforme (cGBM) is rare. Database like TCGA have not distinguish cGBM from GBM, our knowledge on cGBM gene expression characteristics is limited. The expression status of Oligodendrocyte Lineage Transcription factor 2 (OLIG2) and its clinical significance in cGBM is still unclear. Methods: The clinical data and tissue specimens of 73 cGBM patients were retrospectively studied. The association between OLIG2 expression level and the demographic characteristics of cGBM patients was identified by the Chi-Square test. The survival curves were drawn by Kaplan-Meier analysis. The independent prognostic factors was calculated according to Cox regression analysis. Results: The OLIG2 high expression was observed in about 57.5% (42/73) of the cGBM patients. Patients with high OLIG2 expression levels had a higher alive ratio at the end of follow-up (alive ratio: 70.6% vs. 29.4%, p = 0.04). The median survival time was 21 months and 13 months for high and low expression of OLIG2 (p < 0 .05). Univariate analysis and Multivariate analysis indicated that EOR (HR = 3.89, 95% CI 1.23‒12.26, p = 0.02), low OLIG2 expression (HR = 5.26, 95% CI 1.13‒24.59, p = 0.04), and without adjuvant therapy (HR = 4.95, 95% CI 1.22‒20.00, p = 0.03) were independent risk factors for the OS of cGBM patients. Conclusion: High expression level of OLIG2 could be used as an independent favorable prognosis indicator in cGBM patients and be recognized as a characteristic biomarker of cGBM

Clinicopathological and molecular markers associated with prognosis and treatment effectiveness of endometrial stromal sarcoma: a retrospective study in China

PURPOSE: To evaluate the clinicopathological and immunophenotypic characteristics of endometrial stromal sarcoma (ESS) in China. METHODS AND MATERIALS: Seventy-two consecutive ESS cases treated between 1995 and 2009 were retrospectively reviewed. RESULTS: Sixty-three patients received surgical treatment. Forty-one patients underwent pelvic lymphadenectomy. In paraffin-embedded specimens, expression of the following molecular markers was detected: CD10 (27/36), vimentin (37/38), HHF35 (3/32), S-100 (0/25), desmin (2/29), CD117 (0/23), CD34 (2/24), alpha-inhibin (0/17), CK (1/34), CD99 (4/9), smooth muscle actin (5/25), EMA (0/7), estrogen receptor (13/16) and progesterone receptor (13/16). CD10 and vimentin were expressed more frequently in these specimens. Tumor classification, CD10 and surgical procedures were significantly associated with disease-free survival (DFS). Surgical procedures were significantly associated with overall survival (OS). Tumor stage (P = 0.024) and surgical procedure (P = 0.042) were found to be significant independent prognostic factors for DFS. No complete or partial response was observed among patients who received radiotherapy or chemotherapy. CONCLUSIONS: Our results indicate that total hysterectomy with bilateral salpingo-oophorectomy followed by pelvic lymphadenectomy is associated with an improved treatment outcome. CD10-negative expression may contribute to the malignant characteristics and recurrence associated with ESS

Integrated cooperative spectrum sensing and access control for cognitive Industrial Internet of Things

Industrial Internet of Things (IIoT) usually utilizes 2.4-GHz unlicensed frequency band, which is also heavily used by many other communication systems, such as ZigBee, WiFi, Bluetooth, etc. Therefore, the lack of spectrum resources has become a key technical bottleneck to restrict the development of IIoT. Integrating cognitive radio (CR) into IIoT, Cognitive IIoT (CIIoT) can cope with the spectrum resource shortage by accessing the frequency bands licensed to primary user (PU). However, spectrum sensing and access control must be performed to avoid bringing severe interference to the PU. In this article, an integrated cooperative spectrum sensing (CSS) and access control model is proposed to improve the transmission performance of the CIIoT while guaranteeing the CSS’s detection probability and controlling the interference to the PU. This model is optimized to maximize the total throughput of IIoT in each frame by jointly optimizing sensing time, the number of sensing nodes and the transmit power for each node under the constraints of the minimum detection probability, the total power control, the interference control, and the minimum rate for each node. The optimization problem is solved by the joint optimization of spectrum sensing and access control. A simultaneous CSS and access control model is also proposed to increase the communication time by using one time slot to perform CSS and access control simultaneously. The simulation results show that there exist optimal sensing and control parameters to maximize the total throughput of CIIoT