Explore the vast range of titles available.

Accurate quantification of the proteome remains challenging for large sample series and longitudinal experiments. We report a data-independent acquisition method, Scanning SWATH, that accelerates mass spectrometric (MS) duty cycles, yielding quantitative proteomes in combination with short gradients and high-flow (800 µl min –1 ) chromatography. Exploiting a continuous movement of the precursor isolation window to assign precursor masses to tandem mass spectrometry (MS/MS) fragment traces, Scanning SWATH increases precursor identifications by ~70% compared to conventional data-independent acquisition (DIA) methods on 0.5–5-min chromatographic gradients. We demonstrate the application of ultra-fast proteomics in drug mode-of-action screening and plasma proteomics. Scanning SWATH proteomes capture the mode of action of fungistatic azoles and statins. Moreover, we confirm 43 and identify 11 new plasma proteome biomarkers of COVID-19 severity, advancing patient classification and biomarker discovery. Thus, our results demonstrate a substantial acceleration and increased depth in fast proteomic experiments that facilitate proteomic drug screens and clinical studies. Scanning SWATH increases the speed and selectivity of proteomics.

Artificial intelligence (AI) has demonstrated promise in predicting acute kidney injury (AKI), however, clinical adoption of these models requires interpretability and transportability. Non-interoperable data across hospitals is a major barrier to model transportability. Here, we leverage the US PCORnet platform to develop an AKI prediction model and assess its transportability across six independent health systems. Our work demonstrates that cross-site performance deterioration is likely and reveals heterogeneity of risk factors across populations to be the cause. Therefore, no matter how accurate an AI model is trained at the source hospital, whether it can be adopted at target hospitals is an unanswered question. To fill the research gap, we derive a method to predict the transportability of AI models which can accelerate the adaptation process of external AI models in hospitals. Artificial intelligence (AI) has demonstrated promise in predicting acutekidney injury (AKI), however, clinical adoption of these models requires interpretability and transportability across sites. Here, the authors develop an AKI prediction model and a measure for model transportability across six independent health systems.

The assimilation, incorporation, and metabolism of sulfur is a fundamental process across all domains of life, yet how cells deal with varying sulfur availability is not well understood. We studied an unresolved conundrum of sulfur fixation in yeast, in which organosulfur auxotrophy caused by deletion of the homocysteine synthase Met17p is overcome when cells are inoculated at high cell density. In combining the use of self-establishing metabolically cooperating (SeMeCo) communities with proteomic, genetic, and biochemical approaches, we discovered an uncharacterized gene product YLL058Wp, herein named Hydrogen Sulfide Utilizing-1 ( HSU1 ). Hsu1p acts as a homocysteine synthase and allows the cells to substitute for Met17p by reassimilating hydrosulfide ions leaked from met17Δ cells into O-acetyl-homoserine and forming homocysteine. Our results show that cells can cooperate to achieve sulfur fixation, indicating that the collective properties of microbial communities facilitate their basic metabolic capacity to overcome sulfur limitation.

Rab coupling protein (RCP)-induced tumor cell migration has been implicated in tumor pathophysiology and patient outcomes. In the present study, we demonstrate that RCP stabilizes β1 integrin leading to increased β1 integrin levels and activation of a signaling cascade culminating in Slug induction, epithelial-to-mesenchymal transition and increased invasion. Ectopic expression of RCP induced Slug expression. Silencing β1 integrin efficiently inhibited RCP-induced Slug expression and subsequent cancer cell invasion. Conversely, ectopic expression of β1 integrin was sufficient to induce Slug expression. Pharmacological inhibition of integrin linked kinase (ILK), EGFR and NF-κB, as well as transfection of a dominant-negative mutant of Ras (RasN17), significantly inhibited RCP-induced Slug expression and cancer cell invasion. Strikingly, ectopic expression of RCP was sufficient to enhance metastasis of ovarian cancer cells to the lung. Collectively, we demonstrate a mechanism by which RCP promotes cancer cell aggressiveness through sequential β1 integrin stabilization, activation of an ILK/EGFR/Ras/NF-κB signaling cascade and subsequent Slug expression.

MicroRNAs (miRNAs) are small non-protein-coding RNAs that function as endogenous negative gene regulators. Dysfunctions of miRNAs are frequently found in malignancies, including lung cancer. In this review, we summarise the current understanding of miRNAs in lung cancer tumourigenesis, and highlight their potential in overcoming drug resistance, abetting histological sub-classification techniques, and serving as biomarkers for lung cancer risk stratification and outcome prediction.

Claudin-2 promotes breast cancer liver metastasis by enabling seeding and early cancer cell survival. We now demonstrate that Claudin-2 is functionally required for colorectal cancer liver metastasis and that Claudin-2 expression in primary colorectal cancers is associated with poor overall and liver metastasis-free survival. We have examined the role of Claudin-2, and other claudin family members, as potential prognostic biomarkers of the desmoplastic and replacement histopathological growth pattern associated with colorectal cancer liver metastases. Immunohistochemical analysis revealed higher Claudin-2 levels in replacement type metastases when compared to those with desmoplastic features. In contrast, Claudin-8 was highly expressed in desmoplastic colorectal cancer liver metastases. Similar observations were made following immunohistochemical staining of patient-derived xenografts (PDXs) that we have established, which faithfully retain the histopathology of desmoplastic or replacement type colorectal cancer liver metastases. We provide evidence that Claudin-2 status in patient-derived extracellular vesicles may serve as a relevant prognostic biomarker to predict whether colorectal cancer patients have developed replacement type liver metastases. Such a biomarker will be a valuable tool in designing optimal treatment strategies to better manage patients with colorectal cancer liver metastases.Tabariès et al. describe that claudin 2 is a promoter of colorectal cancer liver metastasis. Furthermore, high Claudin-2 expression is associated with shorter time to liver-specific recurrence and is a biomarker of replacement type CRC liver metastases.

Epithelia act as a barrier to the external environment. The extracellular environment constantly changes, and the epithelia are required to regulate their function in accordance with the changes in the environment. It has been reported that a difference of the environment between the apical and basal sides of epithelia such as osmolality and hydrostatic pressure affects various epithelial functions including transepithelial transport, cytoskeleton, and cell proliferation. In this paper, we review the regulation of epithelial functions by the gradients of osmolality and hydrostatic pressure. We also examine the significance of this regulation in pathological conditions especially focusing on the role of the hydrostatic pressure gradient in the pathogenesis of carcinomas. Furthermore, we discuss the mechanism by which epithelia sense the osmotic and hydrostatic pressure gradients and the possible role of the tight junction as a sensor of the extracellular environment to regulate epithelial functions.

Eukaryotic cells can survive the loss of their mitochondrial genome, but consequently suffer from severe growth defects. ‘Petite yeasts’, characterized by mitochondrial genome loss, are instrumental for studying mitochondrial function and physiology. However, the molecular cause of their reduced growth rate remains an open question. Here we show that petite cells suffer from an insufficient capacity to synthesize glutamate, glutamine, leucine and arginine, negatively impacting their growth. Using a combination of molecular genetics and omics approaches, we demonstrate the evolution of fast growth overcomes these amino acid deficiencies, by alleviating a perturbation in mitochondrial iron metabolism and by restoring a defect in the mitochondrial tricarboxylic acid cycle, caused by aconitase inhibition. Our results hence explain the slow growth of mitochondrial genome-deficient cells with a partial auxotrophy in four amino acids that results from distorted iron metabolism and an inhibited tricarboxylic acid cycle. Petite yeast cells lack the mitochondrial genome, which impairs growth. Vowinckel et al. identify the causes behind this growth impairment, linked to amino acid deficiencies that result from iron metabolism defects and an inhibited tricarboxylic cycle.

The transcriptional repressor Slug is best known to control epithelial–mesenchymal transition (EMT) and promote cancer invasion/metastasis. In this study, we demonstrate that Slug is temporally regulated during cell cycle progression. At G1/S transition, cyclin E–cyclin-dependent kinase 2 mediates the phosphorylation of Slug at Ser-54 and Ser-104, resulting in its ubiquitylation and degradation. Non-phosphorylatable Slug is markedly stabilized at G1/S transition compared with wild-type Slug and greatly leads to downregulation of DNA synthesis and checkpoint-related proteins, including TOP1, DNA Ligase IV and Rad17, reduces cell proliferation, delays S-phase progression and contributes to genome instability. Our results indicate that Slug has multifaceted roles in cancer progression by controlling both EMT and genome stability.

Background Likelihood of developing acute kidney injury (AKI) increases with age. We aimed to explore whether the predictability of AKI varies between age groups and assess the volatility of risk factors using electronic medical records (EMR). Methods We constructed a retrospective cohort of adult patients from all inpatient units of a tertiary care academic hospital and stratified it into four age groups: 18–35, 36–55, 56–65, and > 65. Potential risk factors collected from EMR for the study cohort included demographics, vital signs, medications, laboratory values, past medical diagnoses, and admission diagnoses. AKI was defined based on the Kidney Disease Improving Global Outcomes (KDIGO) serum creatinine criteria. We analyzed relative importance of the risk factors in predicting AKI using Gradient Boosting Machine algorithm and explored the predictability of AKI across age groups using multiple machine learning models. Results In our cohort, older patients showed a significantly higher incidence of AKI than younger adults: 18–35 (7.29%), 36–55 (8.82%), 56–65 (10.53%), and > 65 (10.55%) ( p  < 0.001). However, the predictability of AKI decreased with age, where the best cross-validated area under the receiver operating characteristic curve (AUROC) achieved for age groups 18–35, 36–55, 56–65, and > 65 were 0.784 (95% CI, 0.769–0.800), 0.766 (95% CI, 0.754–0.777), 0.754 (95% CI, 0.741–0.768), and 0.725 (95% CI, 0.709–0.737), respectively. We also observed that the relative risk of AKI predictors fluctuated between age groups. Conclusions As complexity of the cases increases with age, it is more difficult to quantify AKI risk for older adults in inpatient population.