Notes

Geomorphology controls the particular trophic starting of stream foods webs inside a boreal watershed .
5 years of follow-up. A long-term follow-up would have yielded more events and thus more power to evaluate the effect of evolocumab on all-cause mortality. We conclude that adaptive designs carry a recognized risk of false-positive efficacy results, but the risk of false-negative safety results is underappreciated.The phytostabilization of mine tailings requires a previous assessment of the effects of soil amendments on metal mobility. The goal of this work was to evaluate the response of metal availability (both labile and potentially available pools) to the addition of two organic amendments (a municipal waste biosolid and a tree biochar), separately and in combination, in a mine tailings substrate. For this purpose, a comprehensive comparison among several single extraction procedures and a sequential extraction procedure was performed. The effects on metals phytotoxicity were assessed through a germination test using seeds of Zygophyllum fabago. When evaluating the effect of the amendments in the labile metal pool, the biochar resulted effective in decreasing metal-extractable concentrations, especially for Cd, Mn and Zn. The treatment with biochar also showed better germination parameters (percentage of germinated seeds and sooner germination) than the rest of the unamended and amended treatments. The use of the municipal organic biosolid increased labile metal concentrations and potentially available metal pools assessed with EDTA and did not contribute to achieve better results of seed germination. Compared to the single biosolid treatment, the combination of biochar/biosolid modulated some labile metal concentrations and showed similar germination parameters to those obtained for the treatment amended only with biochar. This positive effect of biochar in modulating the soluble metal concentrations associated with certain urban/agricultural organic materials supported the suitability of using these combinations in field applications, although a higher rate of biochar application would be recommended to obtain a more beneficial effect.Dew is an important water resource for plants in most deserts. The mechanism that allows desert plants to use dew water was studied using an isotopic water tracer approach. Most plants use water directly from the soil; the roots transfer the water to the rest of the plant, where it is required for all metabolic functions. However, many plants can also take up water into their leaves and stems. Examining the dew water uptake pathways in desert plants can lend insight on another all water-use pathways examination. We determined where and how dew water enters plants in the water limited Negev desert. Highly depleted isotopic water was sprayed on three different dominant plant species of the Negev desert-Artemesia sieberi, Salsola inermis and Haloxylon scoparium-and its entry into the plant was followed. Water was sprayed onto the soil only, or on the leaves/stems only (with soil covered to prevent water entry via root uptake). Thereafter, the isotopic composition of water in the roots and stems were measured at various time points. The results show that each plant species used the dew water to a different extent, and we obtained evidence of foliar uptake capacity of dew water that varied depending on the microenvironmental conditions. A. sieberi took up the greatest amount of dew water through both stems and roots, S. inermis took up dew water mainly from the roots, and H. scoparium showed the least dew capture overall.Macrophage proliferation is known to correlate with macrophage accumulation in atherosclerotic plaque, and therefore its inhibition and secondary reduction of plaque inflammation may have therapeutic beneficial effects on atherosclerosis. Recently, we reported that a peptide corresponding to positions 41-51 of royalisin (which consists of 51 amino acid residues), a potent antibacterial protein contained in royal jelly (RJ), can specifically bind to oxidized LDL (Ox-LDL), a major components of atherosclerotic lesions. Here, we investigated the interaction of RJ proteins including royalisin with LDL and Ox-LDL. Measurement of LDL oxidation by the production of thiobarbituric acid reactive substances and conjugated dienes, and by electrophoretic mobility on polyacrylamide gel electrophoresis showed that RJ proteins including royalisin and the degradation products of major RJ protein (MRJP) 1 and MRJP3 can induce oxidation of LDL and Ox-LDL. Surface plasmon resonance experiments showed that these RJ proteins can exhibit much higher binding affinity to LDL than Ox-LDL (the equilibrium dissociation constant, KD = 8.35 and 49.65 μg proteins/mL for LDL and Ox-LDL, respectively). Experiments using cultured mouse J774A.1 macrophage cells proved that these RJ proteins can inhibit macrophage proliferation markedly and concentration-dependently, regardless of the absence or presence of LDL and Ox-LDL, but hardly affect lipid accumulation in macrophages. These results suggest that RJ proteins including royalisin and degradation products of MRJP1/MRJP3 may have therapeutic beneficial effects on atherosclerosis owing to the reduction of plaque inflammation. Further studies of these RJ proteins may lead to the discovery of novel anti-atherosclerotic drugs.The exponential increase in our ability to harness multi-dimensional biological and clinical data from experimental to real-world settings has transformed pharmaceutical research and development in recent years, with increasing applications of artificial intelligence (AI) and machine learning (ML). Patient-centered iterative forward and reverse translation is at the heart of precision medicine discovery and development across the continuum from target validation to optimization of pharmacotherapy. Integration of advanced analytics into the practice of Translational Medicine is now a fundamental enabler to fully exploit information contained in diverse sources of big data sets such as "omics" data, as illustrated by deep characterizations of the genome, transcriptome, proteome, metabolome, microbiome, and exposome. In this commentary, we provide an overview of ML applications in drug discovery and development, aligned with the three strategic pillars of Translational Medicine (target, patient, dose) and offer perspectives on their potential to transform the science and practice of the discipline. Opportunities for integrating ML approaches into the discipline of Pharmacometrics are discussed and will revolutionize the practice of model-informed drug discovery and development. Finally, we posit that joint efforts of Clinical Pharmacology, Bioinformatics, and Biomarker Technology experts are vital in cross-functional team settings to realize the promise of AI/ML-enabled Translational and Precision Medicine.
Surgery is the only cure for neuroendocrine tumors (NETs), with R0 resection being critical for successful tumor removal. TBOPP Early detection of residual disease is key for optimal management, but both imaging and current biomarkers are ineffective post-surgery. NETest, a multigene blood biomarker, identifies NETs with >90% accuracy. We hypothesized that surgery would decrease NETest levels and that elevated scores post-surgery would predict recurrence.

This was a multicenter evaluation of surgically treated primary NETs (n=153). Blood sampling was performed at day 0 and postoperative day (POD)30. Follow-up included computed tomography/magnetic resonance imaging (CT/MRI), and messenger RNA (mRNA) quantification was performed by polymerase chain reaction (PCR; NETest score 0-100; normal ≤20). Statistical analyses were performed using the Mann-Whitney U-test, Chi-square test, Kaplan-Meier survival, and area under the receiver operating characteristic curve (AUROC), as appropriate. Data are presented as mean±4±28 to 45±24, p=0.0012; R2 72±24 to 60±28, p=non-significant). At POD30, 100% of NETest scores were elevated despite surgery (p<0.0001).

The preoperative NETest accurately identified all NETs (100%). All resections decreased NETest levels and a POD30 NETest score >20 predicted radiologically recurrent disease with 94% accuracy and 100% sensitivity. R0 resection appears to be ineffective in approximately 30% of patients. NET mRNA blood levels provide early objective genomic identification of residual disease and may facilitate management.
20 predicted radiologically recurrent disease with 94% accuracy and 100% sensitivity. R0 resection appears to be ineffective in approximately 30% of patients. NET mRNA blood levels provide early objective genomic identification of residual disease and may facilitate management.State transition models are used to inform health technology reimbursement decisions. Within state transition models, the movement of patients between the model health states over discrete time intervals is determined by transition probabilities (TPs). Estimating TPs presents numerous issues, including missing data for specific transitions, data incongruence and uncertainty around extrapolation. Inappropriately estimated TPs could result in biased models. There is limited guidance on how to address common issues associated with TP estimation. To assess current methods for estimating TPs and to identify issues that may introduce bias, we reviewed National Institute for Health and Care Excellence Technology Appraisals published from 1 January, 2019 to 27 May, 2020. Twenty-eight models (from 26 Technology Appraisals) were included in the review. Several methods for estimating TPs were identified survival analysis (n = 11); count method (n = 9); multi-state modelling (n = 7); logistic regression (n = 2); negative binomial regression (n = 2); Poisson regression (n = 1); and calibration (n = 1). Evidence Review Groups identified several issues relating to TP estimation within these models, including important transitions being excluded (n = 5); potential selection bias when estimating TPs for post-randomisation health states (n = 2); issues concerning the use of multiple data sources (n = 4); potential biases resulting from the use of data from different populations (n = 2), and inappropriate assumptions around extrapolation (n = 3). These issues remained unresolved in almost every instance. Failing to address these issues may bias model results and lead to sub-optimal decision making. Further research is recommended to address these methodological problems.
In Canada, Indigenous people experience racism across diverse settings, including within the health sector. This has negatively impacted boththe quality of care that Indigenous people receive as well as how research related to Indigenous populations is conducted. Therefore, an Indigenous-led council at a kidney research network, in partnership with other key stakeholders, sought to create a learning pathway that aims to distill the racism that Indigenous people face, and build cultural competence, within the health sector.

The learning pathway was designed for researchers, health care providers, patient partners and administrators.

Various components of the pathway are established trainings in healthcare and research settings at provincial and national levels. Provincially, some components are implemented in British Columbia, Alberta, Saskatchewan, Manitoba and Ontario.

The pathway, called Wabishki Bizhiko Skaanj (meaning "White Horse" in Anishinaabemowin), involves six key steps a culturally tailored blanket exercise that walks participants through the history of local Indigenous Nations/peoples; a more detailed online training program (San'yas); a series of webinars on Indigenous research ethics and protocols; an educational booklet about engaging Knowledge Keepers in research, as well as sharing details about their traditional knowledge and culture; two certification programs about Indigenous ownership of data; and a "book club," wherein the conversation of racism-and the goal for finding solutions-is continually discussed.
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