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Background: Low‐serum levels of magnesium, phosphate, and zinc are observed in many intensive care unit (ICU) patients, but clinical equipoise exists regarding supplementation strategies. We aimed to assess the desirable and undesirable effects of supplementation with magnesium, phosphate, or zinc in adult ICU patients. Methods: We conducted a systematic review with meta‐analysis of randomised clinical trials assessing the effects of supplementation with magnesium, phosphate, or zinc in adult ICU patients. Primary outcomes were mortality and duration of mechanical ventilation. We registered the protocol, followed the Preferred Reporting Items for Systematic Review and Meta‐Analysis statement, used the Cochrane risk of bias 2 tool, and the grading of recommendations, assessment, development and evaluation (GRADE) approach for assessing the certainty of the evidence. Results: We identified no low risk of bias trials. For magnesium supplementation, we included three trials (n = 235); the relative risk (RR) for mortality was 0.54, 95% confidence interval (CI) 0.30–0.96 compared to no supplementation (very low certainty of evidence). For zinc supplementation, two trials were included (n = 168); the RR for mortality was 0.73, 95% CI 0.41–1.28 compared to control. No trials assessed the effects of phosphate supplementation on mortality. For outcomes other than mortality, only zero or one trial was available. Conclusions: In adult ICU patients, the certainty of evidence for the effects of supplementation with magnesium, phosphate, or zinc was very low. High‐quality trials are needed to assess the value of supplementation strategies in these patients. [ABSTRACT FROM AUTHOR]

Objective: Candidate genes for non-alcoholic fatty liver disease (NAFLD) identified by a bioinformatics approach were examined for variant associations to quantitative traits of NAFLD-related phenotypes. Research Design and Methods: By integrating public database text mining, trans-organism protein-protein interaction transferal, and information on liver protein expression a protein-protein interaction network was constructed and from this a smaller isolated interactome was identified. Five genes from this interactome were selected for genetic analysis. Twentyone tag single-nucleotide polymorphisms (SNPs) which captured all common variation in these genes were genotyped in 10,196 Danes, and analyzed for association with NAFLD-related quantitative traits, type 2 diabetes (T2D), central obesity, and WHO-defined metabolic syndrome (MetS). Results: 273 genes were included in the protein-protein interaction analysis and EHHADH, ECHS1, HADHA, HADHB, and ACADL were selected for further examination. A total of 10 nominal statistical significant associations (P<0.05) to quantitative metabolic traits were identified. Also, the case-control study showed associations between variation in the five genes and T2D, central obesity, and MetS, respectively. Bonferroni adjustments for multiple testing negated all associations. Conclusions: Using a bioinformatics approach we identified five candidate genes for NAFLD. However, we failed to provide evidence of associations with major effects between SNPs in these five genes and NAFLD-related quantitative traits, T2D, central obesity, and MetS. [ABSTRACT FROM AUTHOR]

The last two years have seen the publication of three genome-wide gene expression studies of the fission yeast cell cycle. While these microarray papers largely agree on the main patterns of cell cycle-regulated transcription and its control, there are discrepancies with regard to the identity and numbers of periodically expressed genes. We present benchmark and reproducibility analyses showing that the main discrepancies do not reflect differences in the data themselves (microarray or synchronization methods seem to lead only to minor biases) but rather in the interpretation of the data. Our reanalysis of the three datasets reveals that combining all independent information leads to an improved identification of periodically expressed genes. These evaluations suggest that the available microarray data do not allow reliable identification of more than about 500 cell cycle-regulated genes. The temporal expression pattern of the top 500 periodically expressed genes is generally consistent across experiments and the three studies, together with our integrated analysis, provide a coherent and rich source of information on cell cycle-regulated gene expression in Schizosaccharomyces pombe. The reanalysed datasets and other supplementary information are available from an accompanying website: . We hope that this paper will resolve the apparent discrepancies between the previous studies and be useful both for wet-lab biologists and for theoretical scientists who wish to take advantage of the data for follow-up work. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

DNA microarrays have been used extensively to identify cell cycle regulated genes in yeast; however, the overlap in the genes identified is surprisingly small. We show that certain protein features can be used to distinguish cell cycle regulated genes from other genes with high confidence (features include protein phosphorylation, glycosylation, subcellular location and instability/degradation). We demonstrate that co-expressed, periodic genes encode proteins which share combinations of features, and provide an overview of the proteome dynamics during the cycle. A large set of novel putative cell cycle regulated proteins were identified, many of which have no known function. [Copyright &y& Elsevier]

The animal, landscape and man simulation system (ALMaSS) was designed as a predictive tool for answering policy questions regarding the effect of changing landscape structure or management on key animal species in the Danish landscape. By combining agent-based models of animals with a comprehensive and dynamic landscape simulation, it aims to improve predictive ability. The landscape model comprises detailed mapping, weather, farm management, and vegetation growth. Each vegetated area has its own growth model and in the case of farmed areas, management is modelled in detail. Animal models are agent-based, designed using the state/transition concept, and are rule-based. Each animal may interact with others and directly with its local environment. Field vole (Microtus agrestis) is used as an example of the extent to which dynamic landscapes can influence the population dynamics. Simulations of crop diversity and rotation demonstrate significant effects of spatial and temporal heterogeneity on population sizes, population fluctuations and landscape permeability. These two factors interact and thus different responses to temporal factors occur at different levels of spatial heterogeneity. Spatial and temporal heterogeneity in both the model and the real world are often related to changes in land-use and management. Consequently, the impact of landscape changes on any population can be enormous and heavily spatially influenced. Therefore, the use of dynamic landscapes is seen as an important addition to the modeller’s toolkit. [Copyright &y& Elsevier]

Background: Intravenous fluids are recommended for the treatment of patients who are in septic shock, but higher fluid volumes have been associated with harm in patients who are in the intensive care unit (ICU)., Methods: In this international, randomized trial, we assigned patients with septic shock in the ICU who had received at least 1 liter of intravenous fluid to receive restricted intravenous fluid or standard intravenous fluid therapy; patients were included if the onset of shock had been within 12 hours before screening. The primary outcome was death from any cause within 90 days after randomization., Results: We enrolled 1554 patients; 770 were assigned to the restrictive-fluid group and 784 to the standard-fluid group. Primary outcome data were available for 1545 patients (99.4%). In the ICU, the restrictive-fluid group received a median of 1798 ml of intravenous fluid (interquartile range, 500 to 4366); the standard-fluid group received a median of 3811 ml (interquartile range, 1861 to 6762). At 90 days, death had occurred in 323 of 764 patients (42.3%) in the restrictive-fluid group, as compared with 329 of 781 patients (42.1%) in the standard-fluid group (adjusted absolute difference, 0.1 percentage points; 95% confidence interval [CI], -4.7 to 4.9; P = 0.96). In the ICU, serious adverse events occurred at least once in 221 of 751 patients (29.4%) in the restrictive-fluid group and in 238 of 772 patients (30.8%) in the standard-fluid group (adjusted absolute difference, -1.7 percentage points; 99% CI, -7.7 to 4.3). At 90 days after randomization, the numbers of days alive without life support and days alive and out of the hospital were similar in the two groups., Conclusions: Among adult patients with septic shock in the ICU, intravenous fluid restriction did not result in fewer deaths at 90 days than standard intravenous fluid therapy. (Funded by the Novo Nordisk Foundation and others; CLASSIC ClinicalTrials.gov number, NCT03668236.)., (Copyright © 2022 Massachusetts Medical Society.)

Importance: A daily dose with 6 mg of dexamethasone is recommended for up to 10 days in patients with severe and critical COVID-19, but a higher dose may benefit those with more severe disease., Objective: To assess the effects of 12 mg/d vs 6 mg/d of dexamethasone in patients with COVID-19 and severe hypoxemia., Design, Setting, and Participants: A multicenter, randomized clinical trial was conducted between August 2020 and May 2021 at 26 hospitals in Europe and India and included 1000 adults with confirmed COVID-19 requiring at least 10 L/min of oxygen or mechanical ventilation. End of 90-day follow-up was on August 19, 2021., Interventions: Patients were randomized 1:1 to 12 mg/d of intravenous dexamethasone (n = 503) or 6 mg/d of intravenous dexamethasone (n = 497) for up to 10 days., Main Outcomes and Measures: The primary outcome was the number of days alive without life support (invasive mechanical ventilation, circulatory support, or kidney replacement therapy) at 28 days and was adjusted for stratification variables. Of the 8 prespecified secondary outcomes, 5 are included in this analysis (the number of days alive without life support at 90 days, the number of days alive out of the hospital at 90 days, mortality at 28 days and at 90 days, and ≥1 serious adverse reactions at 28 days)., Results: Of the 1000 randomized patients, 982 were included (median age, 65 [IQR, 55-73] years; 305 [31%] women) and primary outcome data were available for 971 (491 in the 12 mg of dexamethasone group and 480 in the 6 mg of dexamethasone group). The median number of days alive without life support was 22.0 days (IQR, 6.0-28.0 days) in the 12 mg of dexamethasone group and 20.5 days (IQR, 4.0-28.0 days) in the 6 mg of dexamethasone group (adjusted mean difference, 1.3 days [95% CI, 0-2.6 days]; P = .07). Mortality at 28 days was 27.1% in the 12 mg of dexamethasone group vs 32.3% in the 6 mg of dexamethasone group (adjusted relative risk, 0.86 [99% CI, 0.68-1.08]). Mortality at 90 days was 32.0% in the 12 mg of dexamethasone group vs 37.7% in the 6 mg of dexamethasone group (adjusted relative risk, 0.87 [99% CI, 0.70-1.07]). Serious adverse reactions, including septic shock and invasive fungal infections, occurred in 11.3% in the 12 mg of dexamethasone group vs 13.4% in the 6 mg of dexamethasone group (adjusted relative risk, 0.83 [99% CI, 0.54-1.29])., Conclusions and Relevance: Among patients with COVID-19 and severe hypoxemia, 12 mg/d of dexamethasone compared with 6 mg/d of dexamethasone did not result in statistically significantly more days alive without life support at 28 days. However, the trial may have been underpowered to identify a significant difference., Trial Registration: ClinicalTrials.gov Identifier: NCT04509973 and ctri.nic.in Identifier: CTRI/2020/10/028731.

Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (InWeb&#95;InBioMap, or InWeb&#95;IM) with severalfold more interactions (>500,000) and better functional biological relevance than comparable resources. We illustrate that InWeb&#95;InBioMap enables functional interpretation of >4,700 cancer genomes and genes involved in autism.

Eukaryotic cells replicate by a complex series of evolutionarily conserved events that are tightly regulated at defined stages of the cell division cycle. Progression through this cycle involves a large number of dedicated protein complexes and signaling pathways, and deregulation of this process is implicated in tumorigenesis. We applied high-resolution mass spectrometry-based proteomics to investigate the proteome and phosphoproteome of the human cell cycle on a global scale and quantified 6027 proteins and 20,443 unique phosphorylation sites and their dynamics. Co-regulated proteins and phosphorylation sites were grouped according to their cell cycle kinetics and compared to publicly available messenger RNA microarray data. Most detected phosphorylation sites and more than 20% of all quantified proteins showed substantial regulation, mainly in mitotic cells. Kinase-motif analysis revealed global activation during S phase of the DNA damage response network, which was mediated by phosphorylation by ATM or ATR or DNA-dependent protein kinases. We determined site-specific stoichiometry of more than 5000 sites and found that most of the up-regulated sites phosphorylated by cyclin-dependent kinase 1 (CDK1) or CDK2 were almost fully phosphorylated in mitotic cells. In particular, nuclear proteins and proteins involved in regulating metabolic processes have high phosphorylation site occupancy in mitosis. This suggests that these proteins may be inactivated by phosphorylation in mitotic cells.