Abstract
Radiation exposure results in DNA damage and apoptosis of lymphocytes, including memory T cells, leading to the loss of vaccine immunity and resulting in a potentially lethal susceptibility ...to infection. We have shown that memory CD8+ T cells are preserved by revaccination within 3–4 days after exposure to sub-lethal γ radiation. This study explores therapeutics selected to replicate the effects of revaccination. These therapeutics may promote memory T cell survival by acting on survival pathways stimulated by T cell activation. Using a Listeria monocytogenes (LM) model in mice, nicotine tartrate and isoproterenol were chosen from a screen of 22 therapeutic candidates. Both drugs have been shown to act on the AKT and ERK1/2 survival pathways to prevent apoptosis and promote cell survival and DNA repair. Thirty days after vaccination against LM, mice were irradiated and treated 1 day later with one of the therapeutics. Thirty days later, mice were challenged with wild-type LM, followed by harvest and plating of the spleen. Colonies were counted as a measure of vaccine immunity to LM. Nicotine significantly decreased the number of LM colonies when administered subcutaneously in a TiterMax adjuvant emulsion, as well as transdermally in the form of a patch. The decrease in LM was comparable to revaccination. Similarly, pilot experiments using isoproterenol show decreased colony counts, indicating potential preservation of vaccine immunity. Further studies will include varying doses of isoproterenol and varying routes of administration, as well as combinations of treatments. These therapeutics offer a practical effective means of preserving vaccine memory as a potential new medical countermeasure for Acute Radiation Syndrome.
Renovascular hypertension (RVH) can induce cardiac damage that is reversible using adipose tissue-derived mesenchymal stromal/stem cells (A-MSCs). However, A-MSCs isolated from patients with obesity ...are less effective than lean-A-MSC in blunting hypertensive cardiomyopathy in mice with RVH. We tested the hypothesis that this impairment extends to their obese A-MSC-extracellular vesicles (EVs) progeny. MSCs were harvested from the subcutaneous fat of obese and lean human subjects, and their EVs were collected and injected into the aorta of mice 2 wk after renal artery stenosis or sham surgery. Cardiac left ventricular (LV) function was studied with MRI 2 wk later, and myocardial tissue ex vivo. Blood pressure, LV myocardial wall thickness, mass, and fibrosis that were elevated in RVH mice were suppressed only by lean EVs. Hence, human A-MSC-derived lean EVs are more effective than obese EVs in blunting hypertensive cardiac injury in RVH mice. These observations highlight impaired paracrine repair potency of endogenous MSCs in patients with obesity.
Injection of A-MSC-derived EVs harvested from patients who are lean can resolve myocardial injury in mice with experimental renovascular hypertension more effectively than A-MSC-derived EVs from patients with obesity. These observations underscore and might have important ramifications for the self-healing capacity of patients with obesity and for the use of autologous EVs as a regenerative tool.
MR elastography (MRE) typically requires manual ROI placement to generate liver shear stiffness measurements. Among 419 patients (primarily children and young adults), a computer-based automated MRE ...processing tool and clinically reported manual ROI-based measurements generated similar results (mean bias = 0.13 kPa). The intraclass correlation coefficient was 0.94 and was at least 0.90 across common indications in male and female patients and in patients with and without elevated liver fat fraction. Automated analysis may promote postprocessing standardization and decrease reporting variability.
Although mRNA COVID‐19 vaccines have proven to be safe and effective against SARS‐CoV‐2, vaccination rates have slowed, with some individuals citing impotence as a concern. Therefore, we conducted a ...survey of the US males to evaluate the impact of COVID‐19 vaccination on erectile function. We hypothesized that vaccinated men would not have a higher risk of ED compared to unvaccinated men. Amazon Mechanical Turk (MTurk) was utilized to survey the US adult male population between August 26 and September 2, 2021. Survey participation was open to 1000 males over the age of 18 and currently living in the United States regardless of vaccination status or the past medical history of COVID‐19. Selection criteria included respondents ≥45 years old, no history of physician‐diagnosed ED, biologically born, and identify as male. Participants completed an anonymous 16‐question survey that included a multidimensional scale used to evaluate ED, the International Index of Erectile Function (IIEF‐5). Among vaccinated men, the median IIEF‐5 score was 20 16–24 compared to 22 17.5–25 in the unvaccinated group (p = 0.195). The multivariable‐adjusted analysis demonstrated that vaccination against COVID‐19 was not associated with increased risk of ED. Overall, this cross‐sectional survey showed that COVID‐19 vaccination was not associated with an increased risk of erectile dysfunction in males 45 years and older.
Abstract BACKGROUND Pediatric low-grade gliomas (pLGGs) have variable prognosis and treatment responses. Complete resection cannot be achieved for all tumors, especially for highly infiltrative or ...deep-seated tumors, necessitating additional therapy, from chemotherapy to targeted inhibitors. We integrated imaging-derived phenotypes with genotypic traits from transcriptional analysis, offering an in-depth characterization of pLGG immune microenvironment, progression risk, and likelihood of multiple treatments. METHODS Analyzing 549 treatment-naïve pLGGs with multiparametric MRI and RNA sequencing, we identified distinct immunological groups using XCell scores based on immune cell infiltration. We developed a radiomic signature using conventional MRI and machine learning techniques (support vector machines with a linear kernel and nested cross-validation) to distinguish the ‘immune-hot’ group, and incorporated diffusion MRI to improve signature accuracy. Additionally, a clinicoradiomic model predicting tumor progression risk and treatment response was trained, integrating clinical and radiomic data. Transcriptomic analysis was conducted to identify pathways correlated with clinicoradiomic risk, predictive of pLGG progression. RESULTS Three immunological groups were revealed, the ‘immune-hot’ group characterized by poor prognosis due to a high concentration of pro-tumorigenic M2-polarized macrophages, despite a higher preponderance of T-lymphocytes. The radiomic signature effectively distinguished the ‘immune-hot’ group with balanced accuracies of 76.8%/86.0% in discovery/replication sets, improved by diffusion MRI to 81.5%/84.4%. The clinicoradiomic model showed concordance indices of 0.71 (discovery) and 0.77 (replication), predicting patient progression risk. Significant differences (p=0.0010) were found in clinicoradiomic risk scores between patients undergoing one versus multiple treatments post-diagnosis, linking higher scores to a likelihood of multiple treatments. Transcriptomic pathways associated with higher clinicoradiomic risk highlighted the importance of fatty acid oxidation, a tumor-promoting mechanism that drives adaptive resistance to cytolytic immune cell effectors. CONCLUSIONS This first large-scale radiogenomic analysis in pLGGs aids in prognostication, assessing progression risk, predicting treatment response to standard-of-care therapies, and stratification of patients to identify potential candidates for novel therapies targeting aberrantly regulated pathways.
As both the proportion of older people and the length of life increases globally, a rise in age-related degenerative diseases, disability, and prolonged dependency is projected. However, more ...sophisticated biomedical materials, as well as an improved understanding of human disease, is forecast to revolutionize the diagnosis and treatment of conditions ranging from osteoarthritis to Alzheimer’s disease as well as impact disease prevention. Another, albeit quieter, revolution is also taking place within society: human augmentation. In this context, humans seek to improve themselves, metamorphosing through self-discipline or more recently, through use of emerging medical technologies, with the goal of transcending aging and mortality. In this review, and in the pursuit of improved medical care following aging, disease, disability, or injury, we first highlight cutting-edge and emerging materials-based neuroprosthetic technologies designed to restore limb or organ function. We highlight the potential for these technologies to be utilized to augment human performance beyond the range of natural performance. We discuss and explore the growing social movement of human augmentation and the idea that it is possible and desirable to use emerging technologies to push the boundaries of what it means to be a healthy human into the realm of superhuman performance and intelligence. This potential future capability is contrasted with limitations in the right-to-repair legislation, which may create challenges for patients. Now is the time for continued discussion of the ethical strategies for research, implementation, and long-term device sustainability or repair.
Mesenchymal stem/stromal cell-derived extracellular vesicles (MSC-EVs) are paracrine vectors with therapeutic functions comparable to their parent cells. However, it remains unclear if donor obesity ...affects their therapeutic functions. We tested the hypothesis that the curative effect of human adipose tissue-derived MSC-EVs (A-MSC-EVs) is blunted by obesity.
MSC-EVs were isolated by ultracentrifugation from mesenchymal stem/stromal cells (MSCs) collected from abdominal subcutaneous fat of obese and lean human subjects (obese and lean-MSC-EVs, respectively) and injected into the aorta of mice 2 weeks after renal artery stenosis (RAS) induction. Magnetic resonance imaging studies were conducted 2 weeks after MSC-EVs delivery to determine renal function. The effect of MSC-EVs on tissue injury was assessed by histology and gene expression of inflammatory factors, including interleukin (IL)-1β, IL-6, monocyte chemotactic protein-1 (MCP-1), and tumor necrosis factor alpha (TNF-α). Oxidative damage, macrophage infiltration, plasma renin, and hypoxia inducible factor-1α (HIF-1α) were also assessed.
Tracking showed that MSC-EVs localized in the kidney tissue, including glomeruli and tubules. All MSC-EVs decreased systolic blood pressure (SBP) and plasma renin and improved the poststenotic kidney (STK) volume, but obese-MSC-EVs were less effective than lean-MSC-EVs in improving medullary hypoxia, fibrosis, and tubular injury. Lean-MSC-EVs decreased inflammation, whereas obesity attenuated this effect. Only lean-MSC-EVs decreased STK cortical HIF-1α expression.
Obesity attenuates the antihypoxia, antifibrosis, antiinflammation, and tubular repair functions of human MSC-EVs in chronic ischemic kidney disease. These observations may have implications for the self-repair potency of obese subjects and for the use of autologous MSC-EVs in regenerative medicine.
Hate speech detection has been the subject of high research attention, due to the scale of content created on social media. In spite of the attention and the sensitive nature of the task, privacy ...preservation in hate speech detection has remained under-studied. The majority of research has focused on centralised machine learning infrastructures which risk leaking data. In this paper, we show that using federated machine learning can help address privacy the concerns that are inherent to hate speech detection while obtaining up to 6.81% improvement in terms of F1-score.
Deep Learning, a branch of Machine Learning is a rapidly expanding field in the Industry 4.0 revolution. The number of applications of Deep Learning are enormous - finding multiple uses in a single ...domain. Deep Learning enhances current research and provides better perception to a wide spectrum of domains, including Music Information Retrieval. Music is an art, that is widely celebrated worldwide, with countless songs being released or published every day. Music can be classified into many "genres". A statistical study conducted in 2018 shows that there are more than 10 genres of music, with 'Hip-Hop/Rap 'being the most with most music composed. When one decides to listen to music, one usually has a particular genre in mind, and expects the music application he or she is using to provide numerous songs falling in that genre. A good music application would not only provide many songs, but also increase the ease of access to a particular song or genre. Due to tremendous increase in the amount of digital data available on the internet, the task of accurately classifying music files has become a major problem for music applications like YouTube Music, iTunes or Spotify, which can be solved with the help of Deep Learning techniques. This paper includes an indepth comparison of four transfer learning architectures, i.e. Resnet34, Resnet50, VGG16 and AlexNet, which were the best performing models during different times in ImageNet, to accomplish the task of classification of different songs on the basis of their genre.
