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The human gut microbiota plays a critical role in host physiology, particularly in immune regulation and cancer progression. Notably, gut microbiota-derived metabolites have emerged as crucial regulators of anti-tumor immunity and immunotherapy efficacy. This review synthesizes recent findings on how microbial metabolites, such as short-chain fatty acids (SCFAs), bile acid derivatives, and tryptophan metabolites, interact with immune cells and signaling pathways to influence cancer immunotherapy outcomes. In terms of mechanism, they coordinate innate and adaptive immune processes, reshape the tumor microenvironment, and may enhance the anti-tumor effect. In clinical practice, interventions such as fecal microbiota transplantation (FMT), probiotic supplementation and metabolite supplementation have shown the potential to improve the response rate of treatment. However, there are still many challenges. Differences between individuals, unresolved long-term safety issues, and the complexity of the interaction between the microbiota and the immune system all hinder progress in this area. A comprehensive clarification of these mechanisms is crucial to the rational design of microbial interventions aimed at improving the effectiveness of cancer immunotherapy.

Using low-altitude platform stations (LAPSs) in the agricultural Internet of Things (IoT) enables the efficient and precise monitoring of vast and hard-to-reach areas, thereby enhancing crop management. By integrating edge computing servers into LAPSs, data can be processed directly at the edge in real time, significantly reducing latency and dependency on remote cloud servers. Motivated by these advancements, this paper explores the application of LAPSs and edge computing in the agricultural IoT. First, we introduce an LAPS-aided edge computing architecture for the agricultural IoT, in which each task is segmented into several interdependent subtasks for processing. Next, we formulate a total task processing delay minimization problem, taking into account constraints related to task dependency and priority, as well as equipment energy consumption. Then, by treating the task dependencies as directed acyclic graphs, a heuristic task processing algorithm with priority selection is developed to solve the formulated problem. Finally, the numerical results show that the proposed edge computing scheme outperforms state-of-the-art works and the local computing scheme in terms of the total task processing delay.

Background Fulminant myocarditis is a severe cardiac condition characterized by rapid progression and high mortality. In recent years, advancements in medical technology, particularly the application of mechanical circulatory support, have significantly improved patient outcomes. Case presentation A 36-year-old male patient was admitted with a history of “fever for 5 days and chest tightness and pain for 2 days”.He was diagnosed with acute myocarditis and subsequently experienced cardiac arrest. After resuscitation, he was transferred to the medical ICU, where he received VA-ECMO and IABP support therapy, eventually recovering and being discharged. Conclusion Early recognition, timely intervention, and mechanical circulatory support are crucial in the treatment of fulminant myocarditis, significantly enhancing patient survival rates.

In view of the current problems of spectrum resource scarcity, return congestion, and insufficient energy utilization in the unmanned aerial vehicle (UAV)-assisted Internet of Vehicles (IoV), this paper investigates the cooperative caching and power control, and proposes a joint optimization method to improve the overall Energy Efficiency (EE) . In this method, we first propose a communication establishment threshold to control the V2V communication distance and serve as a joint optimization factor. Then we derive the closed form expressions of offloading ratio and EE of the UAV-assisted IoV, and formulate the optimization problem of maximizing EE. Due to the coupling relationship between caching strategy and transmission power, it is difficult for us to directly solve the optimization problem. Furthermore, we propose an alternating optimization algorithm for solving the optimization problem. Finally, the experimental simulation compare the propose joint optimization method with other existing optimization methods, and the simulation results prove the effectiveness and superiority of the propose joint optimization method.

In this paper, we propose a mobile edge computing (MEC)-enabled unmanned aerial vehicle (UAV)-assisted vehicular ad hoc network (VANET) architecture, based on which a number of vehicles are served by UAVs equipped with computation resource. Each vehicle has to offload its computing tasks to the proper MEC server on the UAV due to the limited computation ability. To counter the problems above, we first model and analyze the transmission model and the security assurance model from the vehicle to the MEC server on UAV, and the task computation model of the local vehicle and the edge UAV. Then, the vehicle offloading problem is formulated as a multi-objective optimization problem by jointly considering the task offloading, the resource allocation, and the security assurance. For tackling this hard problem, we decouple the multi-objective optimization problem as two subproblems and propose an efficient iterative algorithm to jointly make the MEC selection decision based on the criteria of load balancing and optimize the offloading ratio and the computation resource according to the Lagrangian dual decomposition. Finally, the simulation results demonstrate that our proposed scheme achieves significant performance superiority compared with other schemes in terms of the successful task processing ratio and the task processing delay.

With the continuous update of technical means, it is possible to store and process a large amount of data in news dissemination. This research mainly discusses the development of the news industry in the context of big data. Entering the era of big data, with the update of data collection and analysis and processing technology, audience feedback in news dissemination can directly through the in-depth mining of audience data and full sample analysis, fully and timely present the audience’s needs, preferences and behavior patterns. The value of audience feedback. Big data analysis of users can not only be applied to the overall analysis of users, but also can be refined to individual analysis. Through big data-based charts, the originally singular information presents different expressions, which greatly enhances the readability of news information. The main factors that affect users’ use of mobile news clients are the speed of news updates and the professionalism and comprehensiveness of news content, which account for 30% and 20% respectively. This research helps to propose a feasible development path for the future development of traditional news production.

Background Amoebic liver abscess is a hepatic infection due to the invasion of Entamoeba histolytica. This parasitic infection is globally distributed, particularly in tropical and subtropical regions. A remarkable decline in the incidence of amoebic liver abscesses has been observed in recent years thanks to economic and public health progress. Case presentation This case report describes the symptoms of a 32-year-old male with an amoebic liver abscess. Despite the diagnostic difficulties encountered, favorable outcomes were obtained after the appropriate drainage of the abscess and the appropriate anti-amoebic therapy by the administration of metronidazole. Conclusions The management of amoebic liver abscess requires a meticulous evaluation of the patient’s clinical manifestations, the severity of the condition, and the response to therapeutic interventions. Early identification, combined with timely and effective treatment, is essential to reduce the risk of complications and the mortality rate. Clinical trial number Not applicable.

Multiple sclerosis (MS) is a chronic autoimmune neuroinflammatory disease found mostly in young adults in the western world. Oxidative stress induced neuronal apoptosis plays an important role in the pathogenesis of MS. In current study, astragaloside IV (ASI), a natural saponin molecule isolated from Astragalus membranceus, given at 20 mg/kg daily attenuated the severity of experimental autoimmune encephalomyelitis (EAE) in mice significantly. Further studies disclosed that ASI treatment inhibited the increase of ROS and pro-inflammatory cytokine levels, down-regulation of SOD and GSH-Px activities, and elevation of iNOS, p53 and phosphorylated tau in central nervous system (CNS) as well as the leakage of BBB of EAE mice. Meanwhile, the decreased ratio of Bcl-2/Bax was reversed by ASI. Moreover, ASI regulated T-cell differentiation and infiltration into CNS. In neuroblast SH-SY5Y cells, ASI dose-dependently reduced cellular ROS level and phosphorylation of tau in response to hydrogen peroxide challenge by modulation of Bcl-2/Bax ratio. ASI also inhibited activation of microglia both in vivo and in vitro. iNOS up-regulation induced by IFNγ stimulation was abolished by ASI dose-dependently in BV-2 cells. In summary, ASI prevented the severity of EAE progression possibly by counterbalancing oxidative stress and its effects via reduction of cellular ROS level, enhancement of antioxidant defense system, increase of anti-apoptotic and anti-inflammatory pathways, as well as modulation of T-cell differentiation and infiltration into CNS. The study suggested ASI may be effective for clinical therapy/prevention of MS.

In this paper, we propose a high-altitude platform (HAP) and unmanned aerial vehicles (UAVs) collaboration framework in non-orthogonal multiple access (NOMA)-enabled Internet of Things (IoT) networks with the presence of an eavesdropping UAV. For the considered framework, we investigate the uplink secure transmission by optimizing channel allocation from UAVs to HAP, users’ power, and UAVs’ three-dimensional (3D) position. To solve this non-convex problem, we adopt the K-means cluster pair algorithm to divide paired users into different groups and each cluster can be served by a corresponding UAV. Then, the formulated optimization problem is decoupled into three subproblems and tackled iteratively based on the block coordinate descent (BCD) algorithm. Finally, simulation results verify that the proposed network architecture can achieve a higher secure rate, faster convergence evolution, and lower complexity in comparison with the current works.

Type A aortic dissection (TAAD) complicated by cardiac tamponade represents a life-threatening cardiovascular emergency. Acute pericardial effusion can severely compromise cardiac function. Although emergent surgical repair remains the gold standard, preoperative hemodynamic instability substantially increases surgical risk. Controlled pericardial drainage (CPD) has been proposed as a bridging intervention to rapidly relieve tamponade symptoms while mitigating the complications associated with excessive drainage. However, its clinical utility remains controversial because of concerns that the elevation in post-drainage blood pressure may accelerate dissection progression or trigger rupture. This case report highlights the successful use of CPD to stabilize a patient with TAAD and cardiac tamponade, facilitating a safe transition to definitive surgery. It also discusses the clinical utility of this strategy. A 48-year-old man presented to the emergency department with an acute onset of altered mental status lasting 50 min. Bedside ultrasound and aortic computed tomography angiography confirmed a TAAD diagnosis complicated by pericardial tamponade. After the examination, the patient experienced sudden hypotension, which was promptly managed with emergency CPD, resulting in rapid stabilization of blood pressure. Subsequently, the patient underwent \"Sun's procedure\" and artificial vascular replacement, during which 500 mL of pericardial blood was extracted. The patient recovered well and was discharged 24 days after the surgery. With rigorous hemodynamic monitoring and a multidisciplinary framework, CPD effectively functions as a preoperative stabilization approach in patients with TAAD complicated by pericardial tamponade, securing valuable time for subsequent surgical interventions.