An analysis of 1256 cases of sporadic ruptured cerebral aneurysm in a single Chinese institution

Background: To review the epidemiology of sporadic ruptured cerebral aneurysm. Methods: This is a retrospective study of consecutive 1256 Chinese patients between January 2006 and January 2013, who were admitted to the Second Hospital of Hebei Medical University, China, for spontaneous subarachnoid hemorrhage due to a rupture of cerebral artery aneurysm. In 288 males and 478 females, the size of aneurysms was measured by a neuroradiologist on DSA. In 123 males and 184 females, the size of the ruptured aneurysms was not measured. The remaining patients, with 61 males and 122 females, had multiple aneurysms, and the medical record could not reliably determine the specific aneurysm responsible for the rupture. Results: In total there were 784 females and 472 males with a female/male ratio of 1.66. The female/male ratio was down to 0.50 for patients younger than 35 yrs. For both males and females, aneurysm rupture was most common during the age of 50-59 yrs. Ruptured aneurysms were mostly of 2 mm-5 mm in size (47.1%), followed by 5 mm-10 mm (39.7%). Ruptured single cerebral aneurysm occurred in anterior circulation in 95.0% of the cases, with 5.0% occurred in posterior circulation. Ruptured aneurysm most commonly occurred at posterior communicating artery (34.9%) and anterior communicating artery (29.5%). 183 cases (14.6%) had multiple aneurysms. Conclusions: With younger patients, there is a male predominance in our series. Ninety percent of patients have ruptured aneurysms less than 10 mm in size. © 2014 Zhao et al.published_or_final_versio

Small and mighty: adaptation of superphylum Patescibacteria to groundwater environment drives their genome simplicity.

BackgroundThe newly defined superphylum Patescibacteria such as Parcubacteria (OD1) and Microgenomates (OP11) has been found to be prevalent in groundwater, sediment, lake, and other aquifer environments. Recently increasing attention has been paid to this diverse superphylum including > 20 candidate phyla (a large part of the candidate phylum radiation, CPR) because it refreshed our view of the tree of life. However, adaptive traits contributing to its prevalence are still not well known.ResultsHere, we investigated the genomic features and metabolic pathways of Patescibacteria in groundwater through genome-resolved metagenomics analysis of > 600 Gbp sequence data. We observed that, while the members of Patescibacteria have reduced genomes (~ 1 Mbp) exclusively, functions essential to growth and reproduction such as genetic information processing were retained. Surprisingly, they have sharply reduced redundant and nonessential functions, including specific metabolic activities and stress response systems. The Patescibacteria have ultra-small cells and simplified membrane structures, including flagellar assembly, transporters, and two-component systems. Despite the lack of CRISPR viral defense, the bacteria may evade predation through deletion of common membrane phage receptors and other alternative strategies, which may explain the low representation of prophage proteins in their genomes and lack of CRISPR. By establishing the linkages between bacterial features and the groundwater environmental conditions, our results provide important insights into the functions and evolution of this CPR group.ConclusionsWe found that Patescibacteria has streamlined many functions while acquiring advantages such as avoiding phage invasion, to adapt to the groundwater environment. The unique features of small genome size, ultra-small cell size, and lacking CRISPR of this large lineage are bringing new understandings on life of Bacteria. Our results provide important insights into the mechanisms for adaptation of the superphylum in the groundwater environments, and demonstrate a case where less is more, and small is mighty

Networked Multiagent Safe Reinforcement Learning for Low-carbon Demand Management in Distribution Network

This paper proposes a multiagent based bi-level operation framework for the low-carbon demand management in distribution networks considering the carbon emission allowance on the demand side. In the upper level, the aggregate load agents optimize the control signals for various types of loads to maximize the profits; in the lower level, the distribution network operator makes optimal dispatching decisions to minimize the operational costs and calculates the distribution locational marginal price and carbon intensity. The distributed flexible load agent has only incomplete information of the distribution network and cooperates with other agents using networked communication. Finally, the problem is formulated into a networked multi-agent constrained Markov decision process, which is solved using a safe reinforcement learning algorithm called consensus multi-agent constrained policy optimization considering the carbon emission allowance for each agent. Case studies with the IEEE 33-bus and 123-bus distribution network systems demonstrate the effectiveness of the proposed approach, in terms of satisfying the carbon emission constraint on demand side, ensuring the safe operation of the distribution network and preserving privacy of both sides.Comment: Submitted to IEEE Transactions on Sustainable Energ

Adaptive Model Predictive Control with Data-driven Error Model for Quadrupedal Locomotion

Model Predictive Control (MPC) relies heavily on the robot model for its control law. However, a gap always exists between the reduced-order control model with uncertainties and the real robot, which degrades its performance. To address this issue, we propose the controller of integrating a data-driven error model into traditional MPC for quadruped robots. Our approach leverages real-world data from sensors to compensate for defects in the control model. Specifically, we employ the Autoregressive Moving Average Vector (ARMAV) model to construct the state error model of the quadruped robot using data. The predicted state errors are then used to adjust the predicted future robot states generated by MPC. By such an approach, our proposed controller can provide more accurate inputs to the system, enabling it to achieve desired states even in the presence of model parameter inaccuracies or disturbances. The proposed controller exhibits the capability to partially eliminate the disparity between the model and the real-world robot, thereby enhancing the locomotion performance of quadruped robots. We validate our proposed method through simulations and real-world experimental trials on a large-size quadruped robot that involves carrying a 20 kg un-modeled payload (84% of body weight).Comment: 7 Pages, 7 figures, conference(ICRA 2024

An adaptation model for trabecular bone at different mechanical levels

<p>Abstract</p> <p>Background</p> <p>Bone has the ability to adapt to mechanical usage or other biophysical stimuli in terms of its mass and architecture, indicating that a certain mechanism exists for monitoring mechanical usage and controlling the bone's adaptation behaviors. There are four zones describing different bone adaptation behaviors: the disuse, adaptation, overload, and pathologic overload zones. In different zones, the changes of bone mass, as calculated by the difference between the amount of bone formed and what is resorbed, should be different.</p> <p>Methods</p> <p>An adaptation model for the trabecular bone at different mechanical levels was presented in this study based on a number of experimental observations and numerical algorithms in the literature. In the proposed model, the amount of bone formation and the probability of bone remodeling activation were proposed in accordance with the mechanical levels. Seven numerical simulation cases under different mechanical conditions were analyzed as examples by incorporating the adaptation model presented in this paper with the finite element method.</p> <p>Results</p> <p>The proposed bone adaptation model describes the well-known bone adaptation behaviors in different zones. The bone mass and architecture of the bone tissue within the adaptation zone almost remained unchanged. Although the probability of osteoclastic activation is enhanced in the overload zone, the potential of osteoblasts to form bones compensate for the osteoclastic resorption, eventually strengthening the bones. In the disuse zone, the disuse-mode remodeling removes bone tissue in disuse zone.</p> <p>Conclusions</p> <p>The study seeks to provide better understanding of the relationships between bone morphology and the mechanical, as well as biological environments. Furthermore, this paper provides a computational model and methodology for the numerical simulation of changes of bone structural morphology that are caused by changes of mechanical and biological environments.</p

The candidate tumor suppressor gene ECRG4 inhibits cancer cells migration and invasion in esophageal carcinoma

<p>Abstract</p> <p>Background</p> <p>The esophageal cancer related gene 4 (ECRG4) was initially identified and cloned in our laboratory from human normal esophageal epithelium (GenBank accession no.<ext-link ext-link-id="AF325503" ext-link-type="gen">AF325503</ext-link>). ECRG4 was a new tumor suppressor gene in esophageal squamous cell carcinoma (ESCC) associated with prognosis. In this study, we investigated the novel tumor-suppressing function of ECRG4 in cancer cell migration, invasion, adhesion and cell cycle regulation in ESCC.</p> <p>Methods</p> <p>Transwell and Boyden chamber experiments were utilized to examined the effects of ECRG4 expression on ESCC cells migration, invasion and adhesion. And flow cytometric analysis was used to observe the impact of ECRG4 expression on cell cycle regulation. Finally, the expression levels of cell cycle regulating proteins p53 and p21 in human ESCC cells transfected with ECRG4 gene were evaluated by Western blotting.</p> <p>Results</p> <p>The restoration of ECRG4 expression in ESCC cells inhibited cancer cells migration and invasion (<it>P </it>< 0.05), which did not affect cell adhesion capacity (<it>P </it>> 0.05). Furthermore, ECRG4 could cause cell cycle G1 phase arrest in ESCC (<it>P </it>< 0.05), through inducing the increased expression of p53 and p21 proteins.</p> <p>Conclusion</p> <p>ECRG4 is a candidate tumor suppressor gene which suppressed tumor cells migration and invasion without affecting cell adhesion ability in ESCC. Furthermore, ECRG4 might cause cell cycle G1 phase block possibly through inducing the increased expression of p53 and p21 proteins in ESCC.</p