OPTN/SRTR 2021 Annual Data Report: Lung Valapour, Maryam; Lehr, Carli J.; Schladt, David P. ...
American journal of transplantation,
February 2023, 2023-02-00, 20230201, Letnik:
23, Številka:
2
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The number of lung transplants has continued to decline since 2020, a period that coincides with the onset of the COVID-19 pandemic. Lung allocation policy continues to undergo considerable change in ...preparation for adoption of the Composite Allocation Score system in 2023, beginning with multiple adaptations to the calculation of the Lung Allocation Score that occurred in 2021. The number of candidates added to the waiting list increased after a decline in 2020, while waitlist mortality has increased slightly with a decreased number of transplants. Time to transplant continues to improve, with 38.0% of candidates waiting fewer than 90 days for a transplant. Posttransplant survival remains stable, with 85.3% of transplant recipients surviving to 1 year; 67%, to 3 years; and 54.3%, to 5 years.
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The outbreak of coronavirus disease 2019 (COVID‐19) has rapidly spread globally since being identified as a public health emergency of major international concern and has now been declared a pandemic ...by the World Health Organization (WHO). In December 2019, an outbreak of atypical pneumonia, known as COVID‐19, was identified in Wuhan, China. The newly identified zoonotic coronavirus, severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2), is characterized by rapid human‐to‐human transmission. Many cancer patients frequently visit the hospital for treatment and disease surveillance. They may be immunocompromised due to the underlying malignancy or anticancer therapy and are at higher risk of developing infections. Several factors increase the risk of infection, and cancer patients commonly have multiple risk factors. Cancer patients appear to have an estimated twofold increased risk of contracting SARS‐CoV‐2 than the general population. With the WHO declaring the novel coronavirus outbreak a pandemic, there is an urgent need to address the impact of such a pandemic on cancer patients. This include changes to resource allocation, clinical care, and the consent process during a pandemic. Currently and due to limited data, there are no international guidelines to address the management of cancer patients in any infectious pandemic. In this review, the potential challenges associated with managing cancer patients during the COVID‐19 infection pandemic will be addressed, with suggestions of some practical approaches.
Implications for Practice
The main management strategies for treating cancer patients during the COVID‐19 epidemic include clear communication and education about hand hygiene, infection control measures, high‐risk exposure, and the signs and symptoms of COVID‐19. Consideration of risk and benefit for active intervention in the cancer population must be individualized. Postponing elective surgery or adjuvant chemotherapy for cancer patients with low risk of progression should be considered on a case‐by‐case basis. Minimizing outpatient visits can help to mitigate exposure and possible further transmission. Telemedicine may be used to support patients to minimize number of visits and risk of exposure. More research is needed to better understand SARS‐CoV‐2 virology and epidemiology.
Cancer patients have an increased risk of contracting COVID‐19. This article addresses the challenges associated with managing cancer patients during the COVID‐19 infection pandemic and suggests some practical approaches.
Conventional GEO satellite communication systems rely on a multibeam foot-print with a uniform resource allocation to provide connectivity to users. However, applying uniform resource allocation is ...inefficient in presence of non-uniform demand distribution. To overcome this limitation, the next generation of broadband GEO satellite systems will enable flexibility in terms of power and bandwidth assignment, enabling on-demand resource allocation. In this paper, we propose a novel satellite resource assignment design whose goal is to satisfy the beam traffic demand by making use of the minimum transmit power and utilized bandwidth. The motivation behind the proposed design is to maximize the satellite spectrum utilization by pushing the spectrum reuse to affordable limits in terms of tolerable interference. The proposed problem formulation results in a non-convex optimization structure, for which we propose an efficient tractable solution. We validate the proposed method with extensive numerical results, which demonstrate the efficiency of the proposed approach with respect to benchmark schemes.
OPTN/SRTR 2018 Annual Data Report: Lung Valapour, M.; Lehr, C. J.; Skeans, M. A. ...
American journal of transplantation,
January 2020, 2020-01-00, 20200101, Letnik:
20, Številka:
s1
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The primary goal of US lung allocation policy is to ensure that candidates with the highest risk for mortality receive appropriate access to lung transplant. In 2018, 2562 lung transplants were ...performed in the US, reflecting a 31% increase over the past 5 years. More candidates are being listed for lung transplant, and the number of donors has increased substantially. Despite an increase of 84 lung transplants in 2018, 365 adult candidates died or became too sick to undergo transplant. In 2018, 24 new child (ages 0‐11 years) candidates were added to the lung transplant waiting list. Fifteen lung transplants were performed in recipients aged 0‐11 years, three in recipients aged younger than 1 year, two in recipients aged 1‐5 years, and ten in recipients aged 6‐11 years. Of 27 child candidates removed from the waiting list in 2018, 16 (59.3%) were removed due to undergoing transplant, six (22.2%) due to death, one (3.7%) due to improved condition, and one (3.7%) due to becoming too sick to undergo transplant.
OPTN/SRTR 2016 Annual Data Report: Lung Valapour, M.; Lehr, C. J.; Skeans, M. A. ...
American journal of transplantation,
January 2018, 2018-01-00, 20180101, Letnik:
18, Številka:
S1
Journal Article
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In 2016, 2692 candidates aged 12 years or older were added to the lung transplant waiting list; 2345 transplants were performed, the largest number of any prior year. The median waiting time for ...listed candidates in 2016 was 2.5 months, and waiting times were shortest for group D candidates. The transplant rate increased to 191.9 transplants per 100 waitlist years in 2016, with a slight decrease in waitlist mortality to 15.1 deaths per 100 waitlist years. Short‐term survival continued to improve, with a 6‐month death rate of 6.6% and a 1‐year death rate of 10.8% among recipients in 2015 compared with 8.0% and 13.3%, respectively, among recipients in 2014. Long‐term survival rates remained unchanged; 55.6% of recipients were alive at 5 years. In 2016, 23 new candidates aged 0‐11 years were added to the waiting list and 16 lung transplants were performed. Incidence of posttransplant mortality for lung transplant recipients aged 0‐11 years who underwent transplant in 2014‐2015 was 13.8% at 6 months and 19.6% at 1 year. Changes in waitlist and transplant demographic features continued to evolve following implementation of the revised lung allocation score in 2015. Some early trends that may be attributable to the revised LAS are shorter waiting times, stabilization of the number of group D candidates listed for transplant, and convergence of LAS with lower prevalence of extremely high scores.
The widespread application of wireless services and dense devices access has triggered huge energy consumption. Because of the environmental and financial considerations, energy-efficient design in ...wireless networks has become an inevitable trend. To the best of our knowledge, energy-efficient orthogonal frequency division multiple access (OFDMA) heterogeneous small cell optimization comprehensively considering energy efficiency maximization, power allocation, wireless backhaul bandwidth allocation, and user quality of service is a novel approach and research direction, and it has not been investigated. In this paper, we study the energy-efficient power allocation and wireless backhaul bandwidth allocation in OFDMA heterogeneous small cell networks. Different from the existing resource allocation schemes that maximize the throughput, the studied scheme maximizes energy efficiency by allocating both transmit power of each small cell base station to users and bandwidth for backhauling, according to the channel state information and the circuit power consumption. The problem is first formulated as a non-convex nonlinear programming problem and then it is decomposed into two convex subproblems. A near optimal iterative resource allocation algorithm is designed to solve the resource allocation problem. A suboptimal low-complexity approach is also developed by exploring the inherent structure and property of the energy-efficient design. Simulation results demonstrate the effectiveness of the proposed algorithms by comparing with the existing schemes.
In this paper, the convergence time of federated learning (FL), when deployed over a realistic wireless network, is studied. In particular, a wireless network is considered in which wireless users ...transmit their local FL models (trained using their locally collected data) to a base station (BS). The BS, acting as a central controller, generates a global FL model using the received local FL models and broadcasts it back to all users. Due to the limited number of resource blocks (RBs) in a wireless network, only a subset of users can be selected to transmit their local FL model parameters to the BS at each learning step. Moreover, since each user has unique training data samples, the BS prefers to include all local user FL models to generate a converged global FL model. Hence, the FL training loss and convergence time will be significantly affected by the user selection scheme. Therefore, it is necessary to design an appropriate user selection scheme that can select the users who can contribute toward improving the FL convergence speed more frequently. This joint learning, wireless resource allocation, and user selection problem is formulated as an optimization problem whose goal is to minimize the FL convergence time and the FL training loss. To solve this problem, a probabilistic user selection scheme is proposed such that the BS is connected to the users whose local FL models have significant effects on the global FL model with high probabilities. Given the user selection policy, the uplink RB allocation can be determined. To further reduce the FL convergence time, artificial neural networks (ANNs) are used to estimate the local FL models of the users that are not allocated any RBs for local FL model transmission at each given learning step, which enables the BS to improve the global model, the FL convergence speed, and the training loss. Simulation results show that the proposed approach can reduce the FL convergence time by up to 56% and improve the accuracy of identifying handwritten digits by up to 3%, compared to a standard FL algorithm.
This paper studies a federated learning (FL) system, where multiple FL services co-exist in a wireless network and share common wireless resources. It fills the void of wireless resource allocation ...for multiple simultaneous FL services in the existing literature. Our method designs a two-level resource allocation framework comprising intra-service resource allocation and inter-service resource allocation. The intra-service resource allocation problem aims to minimize the length of FL rounds by optimizing the bandwidth allocation among the clients of each FL service. Based on this, an inter-service resource allocation problem is further considered, which distributes bandwidth resources among multiple simultaneous FL services. We consider both cooperative and selfish providers of the FL services. For cooperative FL service providers, we design a distributed bandwidth allocation algorithm to optimize the overall performance of multiple FL services, meanwhile catering it to the fairness among FL services and the privacy of clients. For selfish FL service providers, a new auction scheme is designed with the FL service providers as the bidders and the network operator as the auctioneer. The designed auction scheme strikes a balance between the overall FL performance and fairness. Our simulation results show that the proposed algorithms outperform other benchmarks under various network conditions.
Summary
Trade‐offs among carbon sinks constrain how trees physiologically, ecologically, and evolutionarily respond to their environments. These trade‐offs typically fall along a productive growth to ...conservative, bet‐hedging continuum. How nonstructural carbohydrates (NSCs) stored in living tree cells (known as carbon stores) fit in this trade‐off framework is not well understood.
We examined relationships between growth and storage using both within species genetic variation from a common garden, and across species phenotypic variation from a global database.
We demonstrate that storage is actively accumulated, as part of a conservative, bet‐hedging life history strategy. Storage accumulates at the expense of growth both within and across species. Within the species Populus trichocarpa, genetic trade‐offs show that for each additional unit of wood area growth (in cm2 yr−1) that genotypes invest in, they lose 1.2 to 1.7 units (mg g−1 NSC) of storage. Across species, for each additional unit of area growth (in cm2 yr−1), trees, on average, reduce their storage by 9.5% in stems and 10.4% in roots.
Our findings impact our understanding of basic plant biology, fit storage into a widely used growth‐survival trade‐off spectrum describing life history strategy, and challenges the assumptions of passive storage made in ecosystem models today.
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