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The delivery of pediatric surgical care for acute appendicitis involves general surgeons (GS) and pediatric surgeons (PS), but the differences in clinical practice are primarily undescribed. We examined charge differences between GS and PS for the treatment of pediatric acute appendicitis.

We performed a retrospective review of the North Carolina hospital discharge database (2013-2017) in pediatric patients (≤18y) who had surgery for appendiceal pathology (acute or chronic appendicitis and other appendiceal pathology). We performed a bivariate analysis of surgical charges over the type of surgical providers (GS, PS, other specialty, and unassigned surgeons).

Over the study period, 21,049 patients had appendicitis or other diseases of the appendix, and 15,230 (72.4%) underwent appendectomy. Patients who were operated on by PS were younger (10y, interquartile range (IQR) 6-13 versus 13y, IQR 9-16, P<0.001). Acute appendicitis was diagnosed in 2860 (44.3%) and 3173 (49.2%) of the PS and GS cohorts, resp these data demonstrate that increasing value in pediatric appendicitis may require specialty-based targets.

The total charge for operations for appendiceal disease is significantly higher for PS compared to GS. Pediatric surgeons had increased surgical charges compared to GS but decreased radiology charges. The specific reasons for these differences are not clearly delineated in this data set and persist after controlling for relevant covariates. However, these data demonstrate that increasing value in pediatric appendicitis may require specialty-based targets.The immune system is a complex and interconnected system that has evolved to protect its host from foreign pathogens. CD8+ T cells are a type of immune cell that can be directly lethal to tumor cells. However, their tumor killing capabilities can be inhibited by checkpoint molecules. During the last decade, the development of medications that block these checkpoint molecules has revolutionized treatment for some cancer types and indications for use continue to grow. As usage of immunotherapy increases, toxicities and adverse events unique to immunotherapy are becoming more prevalent. Here, we review the commonly targeted inhibitory molecules along with their food and drug administration-approved indications in various cancer therapeutic regimens, immunotherapy-related toxicities, and how this may impact surgical planning.

Pain is commonly reported among those in treatment for substance use disorders (SUD) and is associated with poorer SUD treatment outcomes. The current study examined the trajectory of pain over the course of SUD treatment and associations with substance use outcomes.

This observational study included adults seeking treatment for alcohol, cannabis, or opioid use disorders (N=811). Participants completed a battery of assessments at treatment admission, 30days post admission, and at discharge, including measures of demographics, pain, quality of life, abstinence self-efficacy, and craving.

Analyses indicated linear reductions in pain intensity and interference over time. Significant interactive effects were observed for opioid use disorder (OUD) and time, such that participants with OUD had greater reductions in pain intensity and interference over time compared to those without OUD. Elevated pain intensity was associated with negative treatment outcomes, including reduced quality of life and abstinence seindings among diverse samples and further characterize the trajectory of pain during and after SUD treatment.Aiming at solving the problems of prototype network that the label information is not reliable enough and that the hyperparameters of the loss function cannot follow the changes of image feature information, we propose a method that combines label smoothing and hyperparameters. First, the label information of an image is processed by label smoothing regularization. Then, according to different classification tasks, the distance matrix and logarithmic operation of the image feature are used to fuse the distance matrix of the image with the hyperparameters of the loss function. Finally, the hyperparameters are associated with the smoothed label and the distance matrix for predictive classification. The method is validated on the miniImageNet, FC100 and tieredImageNet datasets. The results show that, compared with the unsmoothed label and fixed hyperparameters methods, the classification accuracy of the flexible hyperparameters in the loss function under the condition of few-shot learning is improved by 2%-3%. The result shows that the proposed method can suppress the interference of false labels, and the flexibility of hyperparameters can improve classification accuracy.This work concentrates on the issue of leader-following bipartite synchronization of multiple memristive neural networks with Markovian jump topology. In contrast to conventional coupled neural network systems, the coupled neural network model under consideration possesses both cooperative and competitive connections among neuron nodes. Specifically, the interaction between neighbors' nodes is described by a signed graph, in which a positive weight represents an alliance relationship between two neuron nodes while a negative weight represents an adversarial relationship between two neuron nodes. By designing a pinning discontinuous controller that makes full use of the mode information, some effective criteria that ensure the stability of bipartite synchronization error states are obtained. All network nodes can synchronize the target node state bipartitely. Finally, two simulation examples are provided to demonstrate the viability of the suggested bipartite synchronization control approach.Adversarial attacks pose a security challenge for deep neural networks, motivating researchers to build various defense methods. Consequently, the performance of black-box attacks turns down under defense scenarios. A significant observation is that some feature-level attacks achieve an excellent success rate to fool undefended models, while their transferability is severely degraded when encountering defenses, which give a false sense of security. In this paper, we explain one possible reason caused this phenomenon is the domain-overfitting effect, which degrades the capabilities of feature perturbed images and makes them hardly fool adversarially trained defenses. To this end, we study a novel feature-level method, referred to as Decoupled Feature Attack (DEFEAT). Unlike the current attacks that use a round-robin procedure to estimate gradient estimation and update perturbation, DEFEAT decouples adversarial example generation from the optimization process. In the first stage, DEFEAT learns an distribution full of perturbations with high adversarial effects. And it then iteratively samples the noises from learned distribution to assemble adversarial examples. On top of that, we can apply transformations of existing methods into the DEFEAT framework to produce more robust perturbations. We also provide insights into the relationship between transferability and latent features that helps the community to understand the intrinsic mechanism of adversarial attacks. Extensive experiments evaluated on a variety of black-box models suggest the superiority of DEFEAT, i.e., our method fools defenses at an average success rate of 88.4%, remarkably outperforming state-of-the-art transferable attacks by a large margin of 11.5%. The code is publicly available at https//github.com/mesunhlf/DEFEAT.Multi-agent deep reinforcement learning algorithms with centralized training with decentralized execution (CTDE) paradigm has attracted growing attention in both industry and research community. However, the existing CTDE methods follow the action selection paradigm that all agents choose actions at the same time, which ignores the heterogeneous roles of different agents. Motivated by the human wisdom in cooperative behaviors, we present a novel leader-following paradigm based deep multi-agent cooperation method (LFMCO) for multi-agent cooperative games. Specifically, we define a leader as someone who broadcasts a message representing the selected action to all subordinates. After that, the followers choose their individual action based on the received message from the leader. To measure the influence of leader's action on followers, we introduced a concept of information gain, i.e., the change of followers' value function entropy, which is positively correlated with the influence of leader's action. We evaluate the LFMCO on several cooperation scenarios of StarCraft2. Cell Cycle inhibitor Simulation results confirm the significant performance improvements of LFMCO compared with four state-of-the-art benchmarks on the challenging cooperative environment.

Subgroup analyses of randomized controlled trials are very common in oncology; nevertheless, the methodological approach has not been systematically evaluated. The present analysis was conducted with the aim of describing the prevalence and methodological characteristics of the subgroup analyses in randomized controlled trials in patients with advanced cancer.

A systematic literature search using PubMed was carried out to identify all phase III randomized controlled trials conducted in adult patients affected by locally advanced or metastatic solid tumours, published between 2017 and2020.

Overall, 253 publications were identified. Subgroup analyses were reported in 217 (86%) publications. A statistically significant association of presence of subgroup analysis with study sponsor was observed subgroup analyses were reported in 157 (94%) for-profit trials compared with 60 (70%) non-profit trials (P < 0.001). Description of the methodology of subgroup analysis was completely lacking in 82 trials (38%), ers, but also by authors, journal editors and reviewers.

The very high prevalence of subgroup analyses in published papers, together with their methodological weaknesses, makes advisable an adequate education about their correct presentation and correct reading. More attention about proper planning and conduction of subgroup analysis should be paid not only by readers, but also by authors, journal editors and reviewers.Carbon nanotube (CNT), has been demonstrated as a promising high-value product from thermal chemical conversion of waste plastics and securing new applications is an important prerequisite for large-scale production of CNT from waste-plastic recycling. In this study, CNT, produced from waste plastic through chemical vapor deposition (pCNT), was applied as a nanofiller in phase change material (PCM), affording pCNT-PCM composites. Compared with pure PCM, the addition of 5.0 wt% pCNT rendered the peak melting temperature increase by 1.3 ℃, latent heat retain by 90.7%, and thermal conductivity increase by 104%. The results of morphological analysis and leakage testing confirmed that pCNT has similar PCM encapsulation performance and shape stability to those of commercial CNT. The formation of uniform pCNT cluster networks allowed for a large CNT loading into the PCM on the premise of free phase change, responsible for the high thermal conductivity inside the homogeneous phase. Thus, the resulting capillary forces retained a high latent heat capacity and suitable melting temperature and prohibited PCM leakage from the matrix to the outside during re-melting as the pCNT loading ratio increased.