Data compression is a useful technique in the deployments of resource-constrained wireless sensor networks (WSNs) for energy conservation. In this letter, we present a new lossless data compression ...algorithm in WSNs. Compared to existing WSN data compression algorithms, our proposed algorithm is not only efficient but also highly robust for diverse WSN data sets with very different characteristics. Using various real-world WSN data sets, we show that the proposed algorithm significantly outperforms existing popular lossless compression algorithms for WSNs such as LEC and S-LZW. The robustness of our algorithm has been demonstrated, and the insight is provided. The energy consumption of our devised algorithm is also analyzed.
In this paper, we consider the fractional Hardy–Hénon equations with an isolated singularity. If the isolated singularity is located at the origin, we give a classification of solutions to this ...equation. If the isolated singularity is located at infinity, in the case of exterior domains, we provide decay estimates of solutions and their gradients at infinity. Our results are an extension of the classical work by Caffarelli, Gidas et al.
Mitochondria are highly dynamic organelles and play essential role in ATP synthase, ROS production, innate immunity, and apoptosis. Mitochondria quality control is critical for maintaining the ...cellular function in response to cellular stress, growth, and differentiation Signals. Damaged or unwanted mitochondria are selectively removed by mitophagy, which is a crucial determinant of cell viability. Mitochondria-associated Endoplasmic Reticulum Membranes (MAMs) are the cellular structures that connect the ER and mitochondria and are involved in calcium signaling, lipid transfer, mitochondrial dynamic, and mitophagy. Abnormal mitochondrial quality induced by mitophagy impairment and MAMs dysfunction is associated with many diseases, including cardiovascular diseases (CVDs), metabolic syndrome, and neurodegenerative diseases. As a mitophagy receptor, FUNDC1 plays pivotal role in mitochondrial quality control through regulation of mitophagy and MAMs and is closely related to the occurrence of several types of CVDs. This review covers the regulation mechanism of FUNDC1-mediated mitophagy and MAMs formation, with a particular focus on its role in CVDs.
Acute lung injury is a fatal condition characterized by excessive inflammation responses. Salidroside, the active constituent of Rhodiola rosea, possesses properties including anti-oxidation, ...anti-aging, anti-inflammatory, anti-hypoxia, and anti-cancer activities. In the present study, Salidroside attenuated acute lung injury via inhibition of inflammatory cytokine production. Rats pre-treated with Salidroside showed attenuated lipopolysaccharide (LPS)-induced pathological damage and suppressed tumor necrosis factor-alpha (TNFα) and interleukin 6 (IL-6) secretion in the lung. Furthermore, flow cytometry showed that Salidroside reduced the production of TNFα and IL-6 in NR8383 alveolar macrophages. These findings suggest that Salidroside may attenuate LPS-induced acute lung injury.
•Sal attenuates LPS-induced pathological damage and decreases the W/D lung ratio.•Sal suppresses TNFα, IL-6, and GM-CSF secretion in the ALI model.•Sal inhibits TNFα, IL-6, and GM-CSF transcription in lung tissues in the ALI model.•Sal reduces TNFα and IL-6 production induced by LPS in NR8383 cells.
Tisagenlecleucel is a CD19-specific chimeric antigen receptor T-cell therapy, US Food and Drug Administration-approved for children, adolescents, and young adults (CAYA) with relapsed and/or ...refractory (RR) B-cell acute lymphoblastic leukemia (B-ALL). The US Food and Drug Administration registration for tisagenlecleucel was based on a complete response (CR) rate of 81%, 12-month overall survival (OS) of 76%, and event-free survival (EFS) of 50%. We report clinical outcomes and analyze covariates of outcomes after commercial tisagenlecleucel.
We conducted a retrospective, multi-institutional study of CAYA with RR B-ALL across 15 US institutions, who underwent leukapheresis shipment to Novartis for commercial tisagenlecleucel. A total of 200 patients were included in an intent-to-treat response analysis, and 185 infused patients were analyzed for survival and toxicity.
Intent-to-treat analysis demonstrates a 79% morphologic CR rate (95% CI, 72 to 84). The infused cohort had an 85% CR (95% CI, 79 to 89) and 12-month OS of 72% and EFS of 50%, with 335 days of median follow-up. Notably, 48% of patients had low-disease burden (< 5% bone marrow lymphoblasts, no CNS3, or other extramedullary disease), or undetectable disease, pretisagenlecleucel. Univariate and multivariate analyses associate high-disease burden (HB, ≥ 5% bone marrow lymphoblasts, CNS3, or non-CNS extramedullary) with inferior outcomes, with a 12-month OS of 58% and EFS of 31% compared with low-disease burden (OS; 85%, EFS; 70%) and undetectable disease (OS; 95%, EFS; 72%;
< .0001 for OS and EFS). Grade ≥ 3 cytokine release syndrome and neurotoxicity rates were 21% and 7% overall and 35% and 9% in patients with HB, respectively.
Commercial tisagenlecleucel in CAYA RR B-ALL demonstrates efficacy and tolerability. This first analysis of commercial tisagenlecleucel stratified by disease burden identifies HB preinfusion to associate with inferior OS and EFS and increased toxicity.
Data acquisition from multi-hop large-scale outdoor wireless sensor network (WSN) deployments for environmental monitoring is full of challenges. This is because of the severe resource constraints on ...tiny battery-operated motes (e.g., bandwidth, memory, power, and computing capacity), the data acquisition volume from large-scale WSNs, and the highly dynamic wireless link conditions in outdoor harsh communication environments. We present a novel compressed sensing approach, which can recover the sensing data at the sink with high fidelity when a very few data packets need to be collected, leading to a significant reduction of the network transmissions and thus an extension of the WSN lifetime. Interplaying with the dynamic WSN routing topology, the proposed approach is both efficient and simple to implement on the resource-constrained motes without motes' storing of any part of the random projection matrix, as opposed to other existing compressed sensing-based schemes. We further propose a systematic method via machine learning to find a suitable representation basis, for any given WSN deployment and data field, which is both sparse and incoherent with the random projection matrix in compressed sensing for data collection. We validate our approach and evaluate its performance using a real-world outdoor multi-hop WSN testbed deployment in situ . The results demonstrate that our approach significantly outperforms existing compressed sensing approaches by reducing data recovery errors by an order of magnitude for the entire WSN observation field while drastically reducing wireless communication costs at the same time.
Prostate cancer is the most common cancer after non-melanoma skin cancer and the second leading cause of cancer deaths in US men. Its incidence and mortality rates vary substantially across ...geographical regions and over time, with large disparities by race, geographic regions (i.e., Appalachia), among others. The widely used Cox proportional hazards model is usually not applicable in such scenarios owing to the violation of the proportional hazards assumption. In this paper, we fit Bayesian accelerated failure time models for the analysis of prostate cancer survival and take dependent spatial structures and temporal information into account by incorporating random effects with multivariate conditional autoregressive priors. In particular, we relax the proportional hazards assumption, consider flexible frailty structures in space and time, and also explore strategies for handling the temporal variable. The parameter estimation and inference are based on a Monte Carlo Markov chain technique under a Bayesian framework. The deviance information criterion is used to check goodness of fit and to select the best candidate model. Extensive simulations are performed to examine and compare the performances of models in different contexts. Finally, we illustrate our approach by using the 2004-2014 Pennsylvania Prostate Cancer Registry data to explore spatial-temporal heterogeneity in overall survival and identify significant risk factors.
The application of deep learning techniques to the detection and automated classification of Alzheimer's disease (AD) has recently gained considerable attention. The rapid progress in neuroimaging ...and sequencing techniques has enabled the generation of large-scale imaging genetic data for AD research. In this study, we developed a deep learning approach, IGnet, for automated AD classification using both magnetic resonance imaging (MRI) data and genetic sequencing data. The proposed approach integrates computer vision (CV) and natural language processing (NLP) techniques, with a deep three-dimensional convolutional network (3D CNN) being used to handle the three-dimensional MRI input and a Transformer encoder being used to manage the genetic sequence input. The proposed approach has been applied to the Alzheimer's Disease Neuroimaging Initiative (ADNI) data set. Using baseline MRI scans and selected single-nucleotide polymorphisms on chromosome 19, it achieved a classification accuracy of 83.78% and an area under the receiver operating characteristic curve (AUC-ROC) of 0.924 with the test set. The results demonstrate the great potential of using multi-disciplinary AI approaches to integrate imaging genetic data for the automated classification of AD.
Background
Childhood cancer survivors (CCS) are at increased risk for thyroid disease, and many require definitive management with thyroid surgery. Despite this, there is limited evidence on surgical ...outcomes among CCS. We sought to evaluate postoperative outcomes at our institution among CCS undergoing thyroid surgery compared to patients without a history of primary childhood malignancy.
Procedure
Medical records were reviewed for 638 patients treated at the Children's Hospital of Philadelphia Pediatric Thyroid Center between 2009 and 2020. Rates of surgical complications, including recurrent laryngeal nerve (RLN) paralysis and hypoparathyroidism, among CCS were compared to patients with sporadic/familial thyroid cancer, Graves’ disease, and other benign thyroid conditions. Operative time and intraoperative parathyroid hormone levels were also evaluated.
Results
There were no significant differences in long‐term surgical complication rates, such as permanent RLN paralysis and hypoparathyroidism, between CCS and patients without a history of primary childhood malignancy (all p > .05). For all surgical outcomes, there were no significant differences in complication rates when CCS were compared to those undergoing surgery for sporadic/familial thyroid cancer or Graves’ disease (all p > .05). CCS with benign final pathology had significantly higher rates of transient hypoparathyroidism compared to patients with benign thyroid conditions (p < .001).
Conclusions
Our study suggests that CCS are not at higher risk of long‐term complications from thyroid surgery when treated by high‐volume surgeons within a multidisciplinary team.
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