Bloomorr9501

com/AChavignon/PALA and https//doi.org/10.5281/zenodo.4343435 , will facilitate the identification or generation of optimal microbubble-localization algorithms for specific applications.Hydroxyurea is an antimetabolite drug that induces fetal haemoglobin in sickle cell disease. However, its clinical usefulness in β-thalassaemia is unproven. We conducted a randomised, double-blind, placebo-controlled clinical trial to evaluate the efficacy and safety of hydroxyurea in transfusion-dependent β-thalassaemia. Sixty patients were assigned 11 to oral hydroxyurea 10-20 mg/kg/day or placebo for 6 months by stratified block randomisation. Hydroxyurea treatment did not alter the blood transfusion volume overall. However, a significantly higher proportion of patients on hydroxyurea showed increases in fetal haemoglobin percentage (89% vs. 59%; p  1.5%), 44% of patients were identified as hydroxyurea-responders. Hydroxyurea-responders, required significantly lower blood volume (77 ± SD27ml/kg) compared to hydroxyurea-non-responders (108 ± SD24ml/kg; p  less then  0.01) and placebo-receivers (102 ± 28ml/kg; p  less then  0.05). Response to hydroxyurea was significantly higher in patients with HbE β-thalassaemia genotype (50% vs. 0%; p  less then  0.01) and Xmn1 polymorphism of the γ-globin gene (67% vs. 27%; p  less then  0.05). We conclude that oral hydroxyurea increased fetal haemoglobin percentage and reduced erythropoietic stress of ineffective erythropoiesis in patients with transfusion-dependent β-thalassaemia. Hydroxyurea reduced the transfusion burden in approximately 40% of patients. Response to hydroxyurea was higher in patients with HbE β-thalassaemia genotype and Xmn1 polymorphism of the γ-globin gene.We developed an empirical soil wetting geometry model for silty clay loam and coarse sand soils under a semi-permeable porous wall line source Moistube Irrigation (MTI) lateral irrigation. The model was developed to simulate vertical and lateral soil water movement using the Buckingham pi (π) theorem. This study was premised on a hypothesis that soil hydraulic properties influence soil water movement under MTI. Two independent, but similar experiments, were conducted to calibrate and validate the model using MTI lateral placed at a depth of 0.2 m below the soil surface in a soil bin with a continuous water supply (150 kPa). Soil water content was measured every 5 min for 100 h using MPS-2 sensors. Model calibration showed that soil texture influenced water movement ([Formula see text]  less then  0.05) and showed a good fit for wetted widths and depths for both soils ([Formula see text] = 0.5-10%; [Formula see text] 0.50; and d-index [Formula see text] 0.50. The percentage bias [Formula see text] statistic revealed that the models' under-estimated wetted depth after 24 h by 21.9% and 3.9% for silty clay loam and sandy soil, respectively. Sensitivity analysis revealed agreeable models' performance values. This implies the model's applicability for estimating wetted distances for an MTI lateral placed at 0.2 m and MTI operating pressure of 150 kPa. We concluded that the models are prescriptive and should be used to estimate wetting geometries for conditions under which they were developed. Further experimentation under varying scenarios for which MTI would be used, including field conditions, is needed to further validate the model and establish robustness. MTI wetting geometry informs placement depth for optimal irrigation water usage.Light-harvesting complexes (LHCs) are pigment-protein complexes whose main function is to capture sunlight and transfer the energy to reaction centers of photosystems. In response to varying light conditions, LH complexes also play photoregulation and photoprotection roles. In algae and mosses, a sub-family of LHCs, light-harvesting complex stress-related (LHCSR), is responsible for photoprotective quenching. Despite their functional and evolutionary importance, no direct structural information on LHCSRs is available that can explain their unique properties. In this work, we propose a structural model of LHCSR1 from the moss P. LY3473329 solubility dmso patens, obtained through an integrated computational strategy that combines homology modeling, molecular dynamics, and multiscale quantum chemical calculations. The model is validated by reproducing the spectral properties of LHCSR1. Our model reveals the structural specificity of LHCSR1, as compared with the CP29 LH complex, and poses the basis for understanding photoprotective quenching in mosses.We investigate regional features nearby the subway station using the clustering method called the funFEM and propose a two-step procedure to predict a subway passenger transport flow by incorporating the geographical information from the cluster analysis to functional time series prediction. A massive smart card transaction dataset is used to analyze the daily number of passengers for each station in Seoul Metro. First, we cluster the stations into six categories with respect to their patterns of passenger transport. Then, we forecast the daily number of passengers with respect to each cluster. By comparing our predicted results with the actual number of passengers, we demonstrate the predicted number of passengers based on the clustering results is more accurate in contrast to the result without considering the regional properties. The result from our data-driven approach can be applied to improve the subway service plan and relieve infectious diseases as we can reduce the congestion by controlling train intervals based on the passenger flow. Furthermore, the prediction result can be utilized to plan a 'smart city' which seeks shorter commuting time, comfortable ridership, and environmental sustainability.In the past few decades, quantum computation has become increasingly attractive due to its remarkable performance. Quantum image scaling is considered a common geometric transformation in quantum image processing, however, the quantum floating-point data version of which does not exist. Is there a corresponding scaling for 2-D and 3-D floating-point data? The answer is yes. In this paper, we present a quantum scaling up and down scheme for floating-point data by using trilinear interpolation method in 3-D space. This scheme offers better performance (in terms of the precision of floating-point numbers) for realizing the quantum floating-point algorithms than previously classical approaches. The Converter module we proposed can solve the conversion of fixed-point numbers to floating-point numbers of arbitrary size data with [Formula see text] qubits based on IEEE-754 format, instead of 32-bit single-precision, 64-bit double-precision and 128-bit extended-precision. Usually, we use nearest-neighbor interpolation and bilinear interpolation to achieve quantum image scaling algorithms, which are not applicable in high-dimensional space. This paper proposes trilinear interpolation of floating-point data in 3-D space to achieve quantum algorithms of scaling up and down for 3-D floating-point data. Finally, the quantum scaling circuits of 3-D floating-point data are designed.Health-focused apps with chatbots ("healthbots") have a critical role in addressing gaps in quality healthcare. There is limited evidence on how such healthbots are developed and applied in practice. Our review of healthbots aims to classify types of healthbots, contexts of use, and their natural language processing capabilities. Eligible apps were those that were health-related, had an embedded text-based conversational agent, available in English, and were available for free download through the Google Play or Apple iOS store. Apps were identified using 42Matters software, a mobile app search engine. Apps were assessed using an evaluation framework addressing chatbot characteristics and natural language processing features. The review suggests uptake across 33 low- and high-income countries. Most healthbots are patient-facing, available on a mobile interface and provide a range of functions including health education and counselling support, assessment of symptoms, and assistance with tasks such as scheduling. Most of the 78 apps reviewed focus on primary care and mental health, only 6 (7.59%) had a theoretical underpinning, and 10 (12.35%) complied with health information privacy regulations. Our assessment indicated that only a few apps use machine learning and natural language processing approaches, despite such marketing claims. Most apps allowed for a finite-state input, where the dialogue is led by the system and follows a predetermined algorithm. Healthbots are potentially transformative in centering care around the user; however, they are in a nascent state of development and require further research on development, automation and adoption for a population-level health impact.Traumatic brain injury (TBI) is an important cause of death in young adults and children. Till now, the treatment of TBI in the short- and long-term complications is still a challenge. Our previous evidence implied aquaporin 4 (AQP4) and hypoxia inducible factor-1α (HIF-1α) might be potential targets for TBI. In this study, we explored the roles of AQP4 and HIF-1α on brain edema formation, neuronal damage and neurological functional deficits after TBI using the controlled cortical injury (CCI) model. The adult male Sprague Dawley rats were randomly divided into sham and TBI group, the latter group was further divided into neutralized-AQP4 antibody group, 2-methoxyestradiol (2-ME2) group, and their corresponding control, IgG and isotonic saline groups, respectively. Brain edema was examined by water content. Hippocampal neuronal injury was assessed by neuron loss and neuronal skeleton related protein expressions. Spatial learning and memory deficits were evaluated by Morris water maze test and memory-related proteins were detected by western blot. Our data showed that increased AQP4 protein level was closely correlated with severity of brain edema after TBI. Compared with that in the control group, both blockage of AQP4 with neutralized-AQP4 antibody and inhibition of HIF-1α with 2-ME2 for one-time treatment within 30-60 min post TBI significantly ameliorated brain edema on the 1st day post-TBI, and markedly alleviated hippocampal neuron loss and spatial learning and memory deficits on the 21st day post-TBI. In summary, our preliminary study revealed the short-term and long-term benefits of targeting HIF-1α-AQP4 axis after TBI, which may provide new clues for the selection of potential therapeutic targets for TBI in clinical practice.The Weddell seal (Leptonychotes weddellii) thrives in its extreme Antarctic environment. We generated the Weddell seal genome assembly and a high-quality annotation to investigate genome-wide evolutionary pressures that underlie its phenotype and to study genes implicated in hypoxia tolerance and a lipid-based metabolism. Genome-wide analyses included gene family expansion/contraction, positive selection, and diverged sequence (acceleration) compared to other placental mammals, identifying selection in coding and non-coding sequence in five pathways that may shape cardiovascular phenotype. Lipid metabolism as well as hypoxia genes contained more accelerated regions in the Weddell seal compared to genomic background. Top-significant genes were SUMO2 and EP300; both regulate hypoxia inducible factor signaling. Liver expression of four genes with the strongest acceleration signals differ between Weddell seals and a terrestrial mammal, sheep. We also report a high-density lipoprotein-like particle in Weddell seal serum not present in other mammals, including the shallow-diving harbor seal.