Federation Boosting Tree for Originator Rights Protection

The problem of data island hinders the application of big data in artificial intelligence model training,so researchers propose a federated learning framework.It enables model training without having to centralize all data in a central storage point.In the current horizontal federated learning scheme,each participant gets the final jointly trained model.No solution is proposed for scenarios where participants only provide training data in exchange for benefits,but do not care about the final jointly trained model.Therefore,this paper proposes a newboosted tree algorithm,calledRPBT(the originator Rights Protected federated Boosted Tree algorithm).Compared with the current horizontal federal learning algorithm,each participant will obtain the final jointly trained model.RPBT can guarantee that the local data of the participants will not be leaked,while the final jointly trained model cannot be obtained.It is worth mentioning that,from the perspective of the participants,the scheme uses the batch idea to make the participants participate in the training in random batches.Therefore,this scheme is more suitable for scenarios where a large number of participants are jointly modeling.Furthermore,a small number of participants will not actually participate in the joint training process.Therefore,the proposed scheme is more secure.Theoretical analysis and experimental evaluations show that RPBT is secure,accurate and efficient.

Blood Sample Image Classification Algorithm Based on SVM and HOG

In the medical field,the classification and analysis of blood samples has always been arduous work.In the previous work of this task,manual classification maneuvers have been used,which are time consuming and laborious.The conventional blood image classification research is mainly focused on the microscopic cell image classification,while the macroscopic reagent processing blood coagulation image classification research is still blank.These blood samples processed with reagents often show some inherent shape characteristics,such as coagulation,attachment,discretization and so on.The shape characteristics of these blood samples also make it possible for us to recognize their classification through computer vision algorithms.Blood sample classification focuses on the texture and shape of the picture.HOG feature is a kind of feature descriptor used for object detection in computer vision and image processing.It can better extract the outline and texture features of the image by calculating and counting the histogram of oriented gradient of the local region of the image.Because the medical machines that need to identify and classify blood samples often lack strong calculation power,the current popular machine-learning classification algorithms cannot play a good role in these machines.In addition,the characteristics of blood samples produced by different types of reagents and processing methods are different,and it is difficult to obtain real samples,so the amount of data that can be used for training is small.Combining the above conditions and the experimental comparison of a variety of classification algorithms,we find that the lightweight SVMmodel has a better performance on this problem,and the combination of HOG and SVM has also been widely used in other research.The experiment demonstrated that the classification algorithm based on SVM and HOG can give a good result of both performance and accuracy in the classification of blood samples problem.

Microglia-Derived NLRP3 Activation Mediates the Pressor Effect of Prorenin in the Rostral Ventrolateral Medulla of Stress-Induced Hypertensive Rats

Increased microglial activation and neuroinflammation within autonomic brain regions such as the rostral ventrolateral medulla(RVLM)have been implicated in stress-induced hypertension(SIH).Prorenin,a member of the brain renin-angiotensin system(RAS),can directly activate microglia.The present study aimed to investigate the effects of prorenin on microglial activation in the RVLM of SIH rats.Rats were subjected to intermittent electric foot-shocks plus noise,this stress was administered for 2 h twice daily for 15 consecutive days,and mean arterial pressure(MAP)and renal sympathetic nerve activity(RSNA)were monitored.The results showed that MAP and RSNA were augmented,and this paralleled increased pro-inflammatory phenotype(M1)switching.Prorenin and its receptor(PRR)expression and the NLR family pyrin domain containing 3(NLRP3)activation were increased in RVLM of SIH rats.In addition,PLX5622(a microglial depletion agent),MCC950(a NLRP3 inhibitor),and/or PRO20(a(Pro)renin receptor antagonist)had antihypertensive effects in the rats.The NLRP3 expression in the RVLM was decreased in SIH rats treated with PLX5622.Mito-tracker staining showed translocation of NLRP3 from mitochondria to the cytoplasm in proreninstimulated microglia.Prorenin increased the ROS-triggering M1 phenotype-switching and NLRP3 activation,while MCC950 decreased the M1 polarization.In conclusion,upregulated prorenin in the RVLM may be involved in the pathogenesis of SIH,mediated by activation of the microglia-derived NLRP3 inflammasome.The link between prorenin and NLRP3 in microglia provides insights for the treatment of stress-related hypertension.

Paraventricular Nucleus P2X7 Receptors Aggravate Acute Myocardial Infarction Injury via ROS-Induced Vasopressin-V1b Activation in Rats

The present study was designed to investigate the mechanisms by which P2X7 receptors(P2X7Rs)mediate the activation of vasopressinergic neurons thereby increasing sympathetic hyperactivity in the paraventricular nucleus(PVN) of the hypothalamus of rats with acute myocardial ischemia(AMI). The left anterior descending branch of the coronary artery was ligated to induce AMI in rats. The rats were pretreated with BBG(brilliant blue G, a P2X7R antagonist), nelivaptan(a vasopressin V1b receptor antagonist), or diphenyleneiodonium(DPI) [an nicotinamide adenine dinucleotide phosphate(NADPH)oxidase inhibitor]. Hemodynamic parameters of the heart were monitored. Myocardial injury and cardiomyocyte apoptosis were assessed. In the PVN of AMI rats, P2X7R mediated microglial activation, while reactive oxygen species(ROS) and NADPH oxidase 2(NOX2) were higher than in the sham group. Intraperitoneal injection of BBG effectively reduced ROS production and vasopressin expression in the PVN of AMI rats. Moreover, both BBG and DPI pretreatment effectively reduced sympathetic hyperactivity and ameliorated AMI injury, as represented by reduced inflammation and apoptosis of cardiomyocytes.Furthermore, microinjection of nelivaptan into the PVN improved cardiac function and reduced the norepinephrine(AE) levels in AMI rats. Collectively, the results suggest that, within the PVN of AMI rats, P2X7R upregulation mediates microglial activation and the overproduction of ROS, which in turn activates vasopressinergic neuron V1b receptors and sympathetic hyperactivity, hence aggravating myocardial injury in the AMI setting.