Notes

Self-reported perform productivity throughout those with multiple sclerosis and its particular association with mental and physical wellbeing.
Chlorothalonil also induced oxidative stress as indicated by elevated biochemical markers. The highest recorded mortalities were associated with p53 expression. Additional feeding experiments were conducted with fucoidan (8 g/kg diet), following acute (40 μg/L for seven days) and sub-chronic (20 μg/L for six weeks) chlorothalonil application in Nile tilapia. Many of these same biochemical biomarkers of stress, oxidative damage response, and tissue pathology (evidence for hepatic neoplasm) were ameliorated by fucoidan, suggesting a protective effect of the compound. Agrochemicals are ubiquitous on a global scale, and the use of fucoidan as a feed additive may be beneficial for protecting aquatic animal health and aquaculture species from the impacts of chemical run-off.Clinical decision support systems are assisting physicians in providing care to patients. However, in the context of clinical pathway management such systems are rather limited as they only take the current state of the patient into account and ignore the possible evolvement of that state in the future. In the past decade, the availability of big data in the healthcare domain did open a new era for clinical decision support. Machine learning technologies are now widely used in the clinical domain, nevertheless, mostly as a tool for disease prediction. A tool that not only predicts future states, but also enables adaptive clinical pathway management based on these predictions is still in need. This paper introduces weighted state transition logic, a logic to model state changes based on actions planned in clinical pathways. Weighted state transition logic extends linear logic by taking weights - numerical values indicating the quality of an action or an entire clinical pathway - into account. It allows us to predict the future states of a patient and it enables adaptive clinical pathway management based on these predictions. We provide an implementation of weighted state transition logic using semantic web technologies, which makes it easy to integrate semantic data and rules as background knowledge. Executed by a semantic reasoner, it is possible to generate a clinical pathway towards a target state, as well as to detect potential conflicts in the future when multiple pathways are coexisting. The transitions from the current state to the predicted future state are traceable, which builds trust from human users on the generated pathway.
Identifying symptoms and characteristics highly specific to coronavirus disease 2019 (COVID-19) would improve the clinical and public health response to this pandemic challenge. Here, we describe a high-throughput approach - Concept-Wide Association Study (ConceptWAS) - that systematically scans a disease's clinical manifestations from clinical notes. We used this method to identify symptoms specific to COVID-19 early in the course of the pandemic.

We created a natural language processing pipeline to extract concepts from clinical notes in a local ER corresponding to the PCR testing date for patients who had a COVID-19 test and evaluated these concepts as predictors for developing COVID-19. We identified predictors from Firth's logistic regression adjusted by age, gender, and race. We also performed ConceptWAS using cumulative data every two weeks to identify the timeline for recognition of early COVID-19-specific symptoms.

We processed 87,753 notes from 19,692 patients subjected to COVID-19 PCR testingication.Visual analytics techniques are useful tools to support decision-making and cope with increasing data, particularly to monitor natural or artificial phenomena. When monitoring disease progression, visual analytics approaches help decision-makers to understand or even prevent dissemination paths. In this paper, we propose a new visual analytics tool for monitoring COVID-19 dissemination. We use k-nearest neighbors of cities to mimic neighboring cities and analyze COVID-19 dissemination based on comparing a city under consideration and its neighborhood. Moreover, such analysis is performed within periods, which facilitates the assessment of isolation policies. We validate our tool by analyzing the progression of COVID-19 in neighboring cities of São Paulo state, Brazil.Triple-negative breast cancer (TNBC) have been considered as the most malignant subtype of breast cancer with leading incidence and mortality among females. Herein, photo-responsive prodrug nanoparticles (AlP/CPT-NPs) were designed with efficient cytoplasmic delivery of anti-cancer agent for cooperative photodynamic-chemotherapy. AlP/CPT-NPs were prepared using photosensitizer Al(III) phthalocyanine chloride disulfonic acid (AlP) and ROS-activatable camptothecin prodrug (CPT-PD). AlP/CPT-NPs could induce intracellular 1O2 generation upon light exposure, which not only initiate immediate disassembly of AlP/CPT-NPs but also promote cytoplasmic delivery of CPT through 1O2-mediated lysosomal rupture. The released intracellular CPT could be translocated into nuclei in only 5 min post-irradiation. Bcr-Abl inhibitor Consequently, AlP/CPT-NPs efficiently suppressed the tumor growth and metastasis of TNBC in a spatiotemporally controlled manner, providing a promising option for effective treatment of metastatic TNBC. STATEMENT OF SIGNIFICANCE Breast cancer is a complex disease with leading incidence among females, in which triple-negative breast cancer (TNBC) is considered as the most malignant subtype with increased risk of resistance, recurrence and metastasis. Herein, we designed photo-responsive prodrug nanoparticles (AlP/CPT-NPs) for synergistic treatment of metastatic TNBC. Upon 660 nm light exposure, the 1O2 generated by AlP/CPT-NPs could initiate immediate disassembly of AlP/CPT-NPs and further promote cytoplasmic delivery of the therapeutic payloads (camptothecin, CPT). The prepared AlP/CPT-NPs induced potent in vivo phototherapeutic damage through photodynamic-chemotherapy, resulting in complete tumor ablation with metastasis suppression.Glaucoma, a major cause of irreversible blindness worldwide, is associated with elevated intraocular pressure (IOP) and progressive loss of retinal ganglion cells (RGCs) that undergo apoptosis. A mechanism for RGCs injury involves impairment of neurotrophic support and exogenous supply of neurotrophic factors has been shown to be beneficial. However, neurotrophic factors can have widespread effects on neuronal tissues, thus targeting neurotrophic support to injured neurons may be a better neuroprotective strategy. In this study, we have encapsulated LM22A-4, a small neurotrophic factor mimetic, into Annexin V-conjugated cubosomes (L4-ACs) for targeted delivery to injured RGCs in a model of acute IOP elevation, which is induced by acute IOP elevation. We have tested cubosomes formulations that encapsulate from 9% to 33% LM22A-4. Our data indicated that cubosomes encapsulating 9% and 17% LM22A-4 exhibited a mixture of Pn3m/Im3m cubic phase, whereas 23% and 33% showed a pure Im3m cubic phase. We found that 17% L4-ACs with Pn3m/Im3m symmetries showed better in-situ and in-vitro lipid membrane interactions than the 23% and 33% L4-ACs with Im3m symmetry.
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