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We constructed a corpus of digitized texts containing about 4% of all books ever printed. Analysis of this corpus enables us to investigate cultural trends quantitatively. We survey the vast terrain of 'culturomics,' focusing on linguistic and cultural phenomena that were reflected in the English language between 1800 and 2000. We show how this approach can provide insights about fields as diverse as lexicography, the evolution of grammar, collective memory, the adoption of technology, the pursuit of fame, censorship, and historical epidemiology. Culturomics extends the boundaries of rigorous quantitative inquiry to a wide array of new phenomena spanning the social sciences and the humanities.

An abdominal aortic aneurysm (AAA) is a localized dilatation of the infrarenal aorta. AAA is a multifactorial disease, and genetic and environmental factors play a part; smoking, male sex and a positive family history are the most important risk factors, and AAA is most common in men >65 years of age. AAA results from changes in the aortic wall structure, including thinning of the media and adventitia due to the loss of vascular smooth muscle cells and degradation of the extracellular matrix. If the mechanical stress of the blood pressure acting on the wall exceeds the wall strength, the AAA ruptures, causing life-threatening intra-abdominal haemorrhage — the mortality for patients with ruptured AAA is 65–85%. Although AAAs of any size can rupture, the risk of rupture increases with diameter. Intact AAAs are typically asymptomatic, and in settings where screening programmes with ultrasonography are not implemented, most cases are diagnosed incidentally. Modern functional imaging techniques (PET, CT and MRI) may help to assess rupture risk. Elective repair of AAA with open surgery or endovascular aortic repair (EVAR) should be considered to prevent AAA rupture, although the morbidity and mortality associated with both techniques remain non-negligible. An abdominal aortic aneurysm (AAA) is an enlargement of the abdominal aorta. As the AAA grows, the aortic wall becomes progressively thin, and the risk of rupture increases; AAA rupture causes severe intra-abdominal haemorrhage and has a very high mortality.

As the main particulate component of the circulating blood, RBCs play major roles in physiological hemodynamics and impact all arterial wall pathologies. RBCs are the main determinant of blood viscosity, defining the frictional forces exerted by the blood on the arterial wall. This function is used in phylogeny and ontogeny of the cardiovascular (CV) system, allowing the acquisition of vasomotricity adapted to local metabolic demands, and systemic arterial pressure after birth. In pathology, RBCs collide with the arterial wall, inducing both local retention of their membranous lipids and local hemolysis, releasing heme-Fe++ with a high toxicity for arterial cells: endothelial and smooth muscle cells (SMCs) cardiomyocytes, neurons, etc. Specifically, overloading of cells by Fe++ promotes cell death. This local hemolysis is an event associated with early and advanced stages of human atherosclerosis. Similarly, the permanent renewal of mural RBC clotting is the major support of oxidation in abdominal aortic aneurysm. In parallel, calcifications promote intramural hemorrhages, and hemorrhages promote an osteoblastic phenotypic shift of arterial wall cells. Different plasma or tissue systems are able, at least in part, to limit this injury by acting at the different levels of this system.

Roy Kishony and colleagues develop a device for the continuous culture of bacterial populations under constant antibiotic selection pressure. They use this morbidostat, together with whole-genome sequencing of E. coli strains, to follow evolutionary paths leading to high levels of resistance to three individual drugs. Antibiotic resistance can evolve through the sequential accumulation of multiple mutations 1 . To study such gradual evolution, we developed a selection device, the 'morbidostat', that continuously monitors bacterial growth and dynamically regulates drug concentrations, such that the evolving population is constantly challenged 2 , 3 , 4 , 5 . We analyzed the evolution of resistance in Escherichia coli under selection with single drugs, including chloramphenicol, doxycycline and trimethoprim. Over a period of ∼20 days, resistance levels increased dramatically, with parallel populations showing similar phenotypic trajectories. Whole-genome sequencing of the evolved strains identified mutations both specific to resistance to a particular drug and shared in resistance to multiple drugs. Chloramphenicol and doxycycline resistance evolved smoothly through diverse combinations of mutations in genes involved in translation, transcription and transport 3 . In contrast, trimethoprim resistance evolved in a stepwise manner 1 , 6 , through mutations restricted to the gene encoding the enzyme dihydrofolate reductase ( DHFR ) 7 , 8 . Sequencing of DHFR over the time course of the experiment showed that parallel populations evolved similar mutations and acquired them in a similar order 9 .

Background Long Intergenic noncoding RNA predicting CARdiac remodeling (LIPCAR) is a long noncoding RNA identified in plasma of patients after myocardial infarction (MI) to be associated with left ventricle remodeling (LVR). LIPCAR was also shown to be a predictor of early death in heart failure (HF) patients. However, no information regarding the expression of LIPCAR and its function in heart as well as the mechanisms involved in its transport to the circulation is known. The aims of this study are (1) to characterize the transporter of LIPCAR from heart to circulation; (2) to determine whether LIPCAR levels in plasma isolated-extracellular vesicles (EVs) reflect the alteration of its expression in total plasma and could be used as biomarkers of LVR post-MI. Methods Since expression of LIPCAR is restricted to human species and the limitation of availability of cardiac biopsy samples, serum-free conditioned culture media from HeLa cells were first used to characterize the extracellular transporter of LIPCAR before validation in EVs isolated from human cardiac biopsies (non-failing and ischemic HF patients) and plasma samples (patients who develop or not LVR post-MI). Differential centrifugation at 20,000 g and 100,000 g were performed to isolate the large (lEVs) and small EVs (sEVs), respectively. Western blot and nanoparticle tracking (NTA) analysis were used to characterize the isolated EVs. qRT-PCR analysis was used to quantify LIPCAR in all samples. Results We showed that LIPCAR is present in both lEVs and sEVs isolated from all samples. The levels of LIPCAR are higher in lEVs compared to sEVs isolated from HeLa conditioned culture media and cardiac biopsies. No difference of LIPCAR expression was observed in tissue or EVs isolated from cardiac biopsies obtained from ischemic HF patients compared to non-failing patients. Interestingly, LIPCAR levels were increased in lEVs and sEVs isolated from MI patients who develop LVR compared to patients who did not develop LVR. Conclusion Our data showed that large EVs are the main extracellular vesicle transporter of LIPCAR from heart into the circulation independently of the status, non-failing or HF, in patients. The levels of LIPCAR in EVs isolated from plasma could be used as biomarkers of LVR in post-MI patients.

Incorrect drug target identification is a major obstacle in drug discovery. Only 15% of drugs advance from Phase II to approval, with ineffective targets accounting for over 50% of these failures 1 – 3 . Advances in data fusion and computational modeling have independently progressed towards addressing this issue. Here, we capitalize on both these approaches with Rosalind, a comprehensive gene prioritization method that combines heterogeneous knowledge graph construction with relational inference via tensor factorization to accurately predict disease-gene links. Rosalind demonstrates an increase in performance of 18%-50% over five comparable state-of-the-art algorithms. On historical data, Rosalind prospectively identifies 1 in 4 therapeutic relationships eventually proven true. Beyond efficacy, Rosalind is able to accurately predict clinical trial successes (75% recall at rank 200) and distinguish likely failures (74% recall at rank 200). Lastly, Rosalind predictions were experimentally tested in a patient-derived in-vitro assay for Rheumatoid arthritis (RA), which yielded 5 promising genes, one of which is unexplored in RA.

IgE type immunoglobulins and their specific effector cells, mast cells (MCs), are associated with abdominal aortic aneurysm (AAA) progression. In parallel, immunoglobulin-producing B cells, organised in tertiary lymphoid organs (TLOs) within the aortic wall, have also been linked to aneurysmal progression. We aimed at investigating the potential role and mechanism linking local MCs, TLO B cells, and IgE production in aneurysmal progression. Through histological assays conducted on human surgical samples from AAA patients, we uncovered that activated MCs were enriched at sites of unhealed haematomas, due to subclinical aortic wall fissuring, in close proximity to adventitial IgE+ TLO B cells. Remarkably, in vitro the IgEs deriving from these samples enhanced MC production of IL-4, a cytokine which favors IgE class-switching and production by B cells. Finally, the role of MCs in aneurysmal progression was further analysed in vivo in ApoE-/- mice subjected to angiotensin II infusion aneurysm model, through MC-specific depletion after the establishment of dissecting aneurysms. MC-specific depletion improved intramural haematoma healing and reduced aneurysmal progression. Our data suggest that MC located close to aortic wall fissures are activated by adventitial TLO B cell-produced IgEs and participate to their own activation by providing support for further IgE synthesis through IL-4 production. By preventing prompt repair of aortic subclinical fissures, such a runaway MC activation loop could precipitate aneurysmal progression, suggesting that MC-targeting treatments may represent an interesting adjunctive therapy for reducing AAA progression.

Abdominal Aortic Aneurysms (AAAs) represent a particular form of atherothrombosis where neutrophil proteolytic activity plays a major role. We postulated that neutrophil recruitment and activation participating in AAA growth may originate in part from repeated episodes of periodontal bacteremia. Our results show that neutrophil activation in human AAA was associated with Neutrophil Extracellular Trap (NET) formation in the IntraLuminal Thrombus, leading to the release of cell-free DNA. Human AAA samples were shown to contain bacterial DNA with high frequency (11/16), and in particular that of Porphyromonas gingivalis (Pg), the most prevalent pathogen involved in chronic periodontitis, a common form of periodontal disease. Both DNA reflecting the presence of NETs and antibodies to Pg were found to be increased in plasma of patients with AAA. Using a rat model of AAA, we demonstrated that repeated injection of Pg fostered aneurysm development, associated with pathological characteristics similar to those observed in humans, such as the persistence of a neutrophil-rich luminal thrombus, not observed in saline-injected rats in which a healing process was observed. Thus, the control of periodontal disease may represent a therapeutic target to limit human AAA progression.

Extracellular vesicles (EVs) are considered as transporters of biomarkers for the diagnosis of cardiac diseases, playing an important role in cell-to-cell communication during physiological and pathological processes. However, specific markers for the isolation and analysis of cardiac EVs are missing, imposing limitation on understanding their function in heart tissue. For this, we performed multiple proteomic approaches to compare EVs isolated from neonate rat cardiomyocytes and cardiac fibroblasts by ultracentrifugation, as well as EVs isolated from minced cardiac tissue and plasma by EVtrap. We identified Ldb3, a cytoskeletal protein which is essential in maintaining Z-disc structural integrity, as enriched in cardiac EVs. This result was validated using different EV isolation techniques showing Ldb3 in both large and small EVs. In parallel, we showed that Ldb3 is almost exclusively detected in the neonate rat heart when compared to other tissues, and specifically in cardiomyocytes compared to cardiac fibroblasts. Furthermore, Ldb3 levels, specifically higher molecular weight isoforms, were decreased in the left ventricle of ischemic heart failure patients compared to control groups, but not in the corresponding EVs. Our results suggest that Ldb3 could be a potential cardiomyocytes derived-EV marker and could be useful to identify cardiac EVs in physiological and pathological conditions.

Words on the brink As a language evolves, grammatical rules emerge and exceptions die out. Lieberman et al . have calculated the rate at which a language grows more regular, based on 1,200 years of English usage. Of 177 irregular verbs, 79 became regular in the last millennium. And the trend follows a simple rule: a verb's half-life scales as the square root of its frequency. Irregular verbs that are 100 times as rare regularize 10 times faster. The emergence of a rule (such as adding – ed for the past tense) spells death for exceptional forms. The cover graphic makes the point: verb size corresponds to usage frequency, so large verbs stay at the top, and small verbs fall to the bottom. ' Wed ', the next irregular verb to go, is on the brink. In a separate study, Pagel et al . looked at changing word meanings. Across the Indo-European languages, words like ' tail ' or ' bird ' evolve rapidly and are expressed by many unrelated words. Others, like ' two ', are expressed by closely related word forms across the whole language family. Data from over 80 modern languages show that the more a word is used, the less it changes. During language evolution, rules emerge and exceptions decline. A quantitative study measures the rate at which a human language becomes more regular over time. Specifically, the regularization of English verbs over the last 1200 years was studied, and it was found that half-life of a verb scales as the square root of its frequency, meaning that irregular verbs that are 100 times as rare regularize ten times faster. Human language is based on grammatical rules 1 , 2 , 3 , 4 . Cultural evolution allows these rules to change over time 5 . Rules compete with each other: as new rules rise to prominence, old ones die away. To quantify the dynamics of language evolution, we studied the regularization of English verbs over the past 1,200 years. Although an elaborate system of productive conjugations existed in English’s proto-Germanic ancestor, Modern English uses the dental suffix, ‘-ed’, to signify past tense 6 . Here we describe the emergence of this linguistic rule amidst the evolutionary decay of its exceptions, known to us as irregular verbs. We have generated a data set of verbs whose conjugations have been evolving for more than a millennium, tracking inflectional changes to 177 Old-English irregular verbs. Of these irregular verbs, 145 remained irregular in Middle English and 98 are still irregular today. We study how the rate of regularization depends on the frequency of word usage. The half-life of an irregular verb scales as the square root of its usage frequency: a verb that is 100 times less frequent regularizes 10 times as fast. Our study provides a quantitative analysis of the regularization process by which ancestral forms gradually yield to an emerging linguistic rule.