Topic modeling—a text‐mining technique often used to uncover thematic structures in large collections of texts—has been increasingly frequently used in the context of the analysis of scholarly output. In this study, we construct a corpus of 19,488 texts published since 1971 in seven leading journals in the field of bioethics and philosophy of medicine, and we use a machine learning algorithm to identify almost 100 topics representing distinct themes of interest in the field. On the basis of intertopic correlations, we group the content‐based topics into eight clusters, thus providing a novel, fine‐grained intellectual map of bioethics and philosophy of medicine. Moreover, we conduct a number of diachronic analyses, examining how the “prominence” of different topics has changed across time. In this way, we are able to observe the distinct patterns in which bioethics and philosophy of medicine have evolved and changed their focus over the past half a century. The role of journals, because of their rapid production cycle and diversified content, may be more important for the developments in bioethics than monographs, which are essential for many other areas of the humanities or social sciences. First, the practical aims of the important part of this discipline mean that it aspires not only to understand and react quickly to scientific or technological developments, policy decisions, and societal changes but also to influence the legal regulations of biomedical research and clinical practice. Second, the interdisciplinary character of this field (or rather its role as a meeting place of disciplines) not only provides a discussion platform where humanistic insights and social sciences methods face the growing intricacy of biomedical technologies but also includes the voices of practitioners from outside of academia. Such diversity is clearly discernible in the publishing patterns of many leading journals, for example, the The Journal of Philosophy and Medicine, the second oldest bioethics journal in the United States, which defines itself as “the flagship scholarly journal in bioethics and the philosophy of medicine.”The history of bioethics is tightly interwoven with that of its older sibling, the philosophy of medicine, which provides philosophical foundations for many bioethical debates. The inseparability of these two is often highlighted by scholars writing about the history of the intersection of medicine and the humanities. For example, Robert M. Veatch noticed “the gradual convergence of themes in philosophy of science and philosophy of medicine with more specific issues in medical and biomedical ethics.”A standard manner in which practitioners of an academic discipline reflect upon the history and development of their own discipline is through “close reading” of selected texts, which is often mediated by their personal experience and academic interests. This approach is present in the classic books about the history of bioethicsIn contrast, the approach that we adopt in this article takes seriously the epistemological question of how one can justify the belief, for example, that the issue of “enhancement and data/tissue storage” dominated the debates of the 2000s. We use a “distant reading”interpret them, that is, to associate “topics” with actual, discrete themes discussed in the analyzed collection of texts. For instance, if the model's output includes a topic characterized by the terms “gene,” “therapy,” “clone,” “disease,” and “germline,” we can reasonably interpret such a topic as being connected to the classic debate on germline modification and gene therapy.The latent Dirichlet allocation (LDA) algorithm, which we use in this study, identifies “topics,” that is, sets of words that tend to be used together across documents in the corpus.A topic model is able to provide the exact proportions in which different topics discovered by the model contribute to each document in the corpus. This makes a number of interesting analyses easy to conduct: Which topics are the most prominent in the corpus? Which topics tend to occur together in the same documents? How does the average prominence of a given topic change for documents from different periods? These are the kinds of analyses that make topic modeling so useful in analyzing large bodies of scholarly texts.We assume that this method allows us to uncover the pattern of researchers’ interests and the evolution of such interests over time. Our aim is not to replace close reading, which is so typical for the humanities, but rather to present an instrument useful for researchers that may support human interpretive work “by providing evidence for interpretations in a manner that is not only much more scalable but also less subject to biases that derive from the interpreters’ preconceptions.”22.1Following similar analyses conducted in other areas of philosophy,a)The journal is focused on the general philosophy of medicine and/or general bioethics rather than a narrower and more specialized subfield.b)The journal played an important role in shaping the field.c)The journal publishes important work in the field.d)The journal is recognized by the community as a key journal in the field.To establish the list of the most representative journals, we invited experts in bioethics or philosophy of medicine to conduct a free listing task. A request to provide a list of five key journals in philosophy of medicine and/or bioethics was distributed via the Philos‐L mailing list (a large mailing list focused on philosophy‐related news) and—after the initial round of data collection—posted on the “Bioethics International” Facebook page and tweeted out by our department's profile. The following criteria were provided to specify what we mean by “key journal in philosophy of medicine and/or bioethics”:Bioethics (89%) and the Journal of Medical Ethics (85%). The Smith index (dotted line) is a measure of cultural saliency that combines frequency of mention and rank of citation of items on the lists, that is, how early in the lists a journal tends to be mentioned.We received responses from 27 individuals who indicated that they are “teachers and/or researchers in an academic institution.” To analyze the free‐listing data, we used FLARES.Bioethics (89%); the Journal of Medical Ethics ; the American Journal of Bioethics ; Medicine, Health Care and Philosophy ; Hastings Center Report ; the Journal of Medicine and Philosophy ; and Theoretical Medicine and Bioethics .On the basis of the free‐listing analysis, we included the following seven journals (frequency of mention in brackets): 2.2Having identified the target journals, we built a complete corpus of texts published in all seven journals. We included regular‐length articles but also many types of shorter pieces because of their relative importance in the field of bioethics: open‐peer commentaries, replies, letters, book reviews, and so forth. We believe that these types of publications are particularly important in bioethics as it is a practically oriented discipline. However, we excluded types of documents that would typically lack “substantive” content: tables of contents, issue introductions, corrigenda, lists of referees, book notes, calls for papers, obituaries, and so forth.The resulting corpus consisted of 19,448 documents, with 64,326,072 tokens (words) distributed across them. The average length of the main text of a document in the corpus was 3308 words, following the relative prevalence of shorter texts. The vast majority of documents came from three journals: AJOB (27%), JME (26%), and HCR (18%), with the four remaining journals contributing between 6% and 8% each. The time distribution of documents was also rather skewed, with few texts published in the 1970s (4%), the 1980s (9%), or the 1990s (11%) and the vast majority published in the 2000s (28%) and from 2010 onwards (41%). The number of articles in each journal and the average article word count are plotted in Figure We built the corpus in April 2021 and fitted the topic model on all eligible texts published as of that date.2.3NLTK library.Phrases from the Python GenSim librarymale and circumcision tended to occur next to each other, each such occurrence was transformed into a single bigram: male_circumcision). Then, we used the spaCy taggerWhenever possible, we scrapped text from the HTML version of a document from the publisher's website. For documents where it was not possible, we downloaded a PDF version of the article and scrapped the text using GROBID software.document‐term matrix) was the main input to the topic modeling algorithm.However, the vast majority of those appeared in only a couple of documents, which meant that they would not be very useful in fitting a topic model (or they would even be a source of noise). For this reason, we chose to keep only those token types that appeared in at least 25 documents from the corpus and in no more than 50% of all the documents, which allowed us to substantially reduce the size of the dictionary to 20,005 terms. The distribution of those terms across all 19,448 documents , beta (which controls prior term probability distributions over topics),K (the hypothesized number of topics in the corpus). As for alpha and beta, following some fine‐tuning, we chose the rather standard values of 0.01 and 0.31. As for K, we followed a standard practice of manually comparing the output of models with different numbers of topics and picking the one that, according to our judgment, appeared optimal. Typically, the optimal number of topics is neither too low  nor too high (as this would lead to topics that are overlapping and too numerous to make the entire model comprehensible for humans). In the present context, we fitted 10 models  and decided that the model with 100 topics looked the most promising, with almost all of the resulting topics corresponding to what we find to be distinct themes that are present in the literature.LDA is an “unsupervised” algorithm, which means that resulting topics are not in any way guided by researchers’ expectations but, instead, are “discovered” by the algorithm itself on the sole basis of the patterns of co‐occurrence of terms across documents. Researchers, however, still have some control over the operation of the algorithm, as they have to decide on three hyper‐parameters: 2.5meaning—it has yet to be interpreted by researchers. The interpretative task is made easier by the fact that the LDA algorithm guarantees that the probability mass of each such distribution is focused on a relatively small number of highly probable words, so that it is just a small number of such words that characterize a given topic and should suffice for its interpretation. For example, in the context of topic 87, a glimpse at the set of five most probable terms  was sufficient for us to interpret that topic as referring to virtue ethics.A topic resulting from an LDA algorithm is nothing more than a probability distribution over terms (words and collocations), so it does not have any determined Clinical stories; 71: Reviews) or to denote specific methodological approaches used in different contexts ; following an earlier study,In almost every topic model, however, a fraction of the topics resist such an interpretation as they represent stylistic peculiarities or other possibly spurious patterns present across documents. We found three such topics in our model  and discarded them from further analysis.This still left us with 91 topics that we interpreted as denoting distinct areas of research present in the target journals. Such a wide class of topics is not particularly manageable; hence, we aimed to reduce its dimensionality by following the procedure used earlier by Malaterre and colleagues.As a result, we have the following eight clusters of topics: BEGINNING OF LIFE; END OF LIFE; INSTITUTIONS; PATIENTS AND RESEARCH PARTICIPANTS; PHILOSOPHY OF MEDICINE; PHYSICIAN AND RESEARCHER; EMERGING TOPICS; and THEORETICAL BIOETHICS.Dignity to THEORETICAL BIOETHICS; Autonomy and Nudge to PATIENTS AND RESEARCH PARTICIPANTS), five topics from BEGINNING OF LIFE , one topic from INSTITUTIONS , and one topic from END OF LIFE (Addiction to PATIENTS AND RESEARCH PARTICIPANTS). The resulting classification is visualized in Figure On the basis of our expert judgment, we chose to manually correct the output of the clustering algorithm in cases where the assignment of a given topic to a given cluster seemed to be based on correlations that we interpreted as accidental. We therefore proceeded—mostly guided by correlations with other topics—to move three topics originally in the cluster PHILOSOPHY OF MEDICINE (33.1Sports) to 1.86% (Insurance). The most prominent topics in the present corpus were Insurance (1.86%), Law: health (1.85%), Physician (1.78%), Committees (1.78%), Biopolitics (1.47%), Principlism (1.47%), Risk and precaution (1.43%), RCT (1.37%), Autonomy (1.37%), and Confidentiality (1.35%). Joint prominence of all content‐based topics as a group is 77.41%. The most prominent topics within each cluster are the following: BEGINNING OF LIFE: Embryos: research, 0.91%, IVF and surrogacy, 0.89%, Abortion: regulatory, 0.83%; END OF LIFE: Law: health, 1.85%, Death: euthanasia, 1.03%, Death: concept, 1.03%; INSTITUTIONS: Insurance, 1.86%, Hospital, 1.23%, Resources, 1.11%; PATIENTS AND RESEARCH PARTICIPANTS: Committees, 1.78%; Risk and precaution, 1.43%, RCT, 1.37%; PHILOSOPHY OF MEDICINE: Statistics, 1.22%, Science: philosophy, 1.20%, Brain, 0.82%; PHYSICIAN AND RESEARCHER: Physician, 1.78%, Confidentiality, 1.35%, Ethics education, 1.25%; EMERGING TOPICS: Genetic testing, 1.12%, Patenting, 0.87%, Offspring, 0.78%; THEORETICAL BIOETHICS: Biopolitics, 1.47%, Principlism, 1.47%, Metabioethics, 1.25%.Topics differed widely in their overall prominence,3.2We also calculated the joint prominence of topic clusters by adding together the prominence of all individual topics that constitute a given cluster. Clusters range in prominence from 5.25% to 20.37%: PATIENTS AND RESEARCH PARTICIPANTS (20.37%), THEORETICAL BIOETHICS (11.44%), PHYSICIAN AND RESEARCHER (10.67%), INSTITUTIONS (8.50%), END OF LIFE (8.17%), EMERGING TOPICS (7.06%), PHILOSOPHY OF MEDICINE (5.96%), and BEGINNING OF LIFE (5.25%).3.3Moral philosophy (3.10%), Concepts (2.55%), Clinical stories (2.17%), Reviews (1.63%), Qualitative (1.30%), and Quantitative (1.29%). Overall, joint prominence of framing topics is 12.04%.Topic prominence for framing topics ranged from 1.29% to 3.10%: 3.4Consent—Participation (r = 0.19), Phenomenology—Body ownership (0.17), Embryos: identity—Embryos: research (0.16), Monetary incentives—Participation (0.16), Genetics—Genetic testing (0.16), Science: philosophy—Diagnosis (0.15), Death: euthanasia—Sedation (0.15), Participation—RCT (0.15), Biobanking—Consent (0.14), Monetary incentives—Organ donation (0.14), and Disease: concept—Concepts (0.14). Because clusters were based on intertopic correlations, it is unsurprising that all these pairs connect topics within the same cluster . Overall, positive correlations were more pronounced than negative ones .A table of the Pearson's correlations between topics (measuring the tendency of a pair of topics to co‐occur in the same documents) is provided as a supplement.3.5prominence in a respective period . Figure We conducted our diachronic analyses for the period from 1976  to 2020 . To focus on long‐term trends and avoid noise caused by factors such as the publication of special issues, we divided that 45‐year period into nine 5‐year periods and calculated each topic's Figure 4The mean prevalence of topics across 5‐year periods from 1976 to 2020. Topics are grouped by clusters and, within each cluster, ordered by their overall prominence in the corpus.Figure 3.5.1We looked at which topics demonstrated the largest increase and decrease in prominence overall. To do this, we compared the mean prominence of the topic in the first two periods 1976–1985) to its mean prominence in the last two periods (2011–2020). The 10 largest increases and decreases are presented in Table 976–1985 3.5.2To identify and analyze any sudden increases in the prominence of topics—suggesting that a given topic had suddenly become notably more prominent—we developed a method of detecting peaks of topic prominence. The prominence of each topic in a given period was divided by the mean prominence of this topic for the two preceding periods (where a “period” is our 5‐year bin). We also applied a threshold of 1% prominence in the target period to focus on the most notable increases. Given our definition of a peak and the fact that our diachronic analysis starts in 1976, the first period for which we could identify peaks is 1986–1990. Table Nudge 2011–2015 and Race 2016–2020 being the least prominent (0.70%).Because our data set includes bundled texts, most prominently open peer commentaries appended to AJOB's target articles, we wanted to check whether peaks in the full corpus represent robust trends in the discussion rather than artifacts of multiple counting of such bundled short texts. We decided to conduct the same kind of peak analysis on an abridged corpus that contains only relatively long texts (at least 2300 words long).3.5.3The most recent trends are not always clearly visible in the above graphs based on 5‐year periods, so we decided to check for the most recent trends in a more fine‐grained manner. To identify any topics that are currently enjoying an increase in prominence within the corpus Table , we calc44.1Before we discuss how one can use our data to interpret the topical structure and diachronic trends in bioethics and philosophy of medicine, we briefly discuss our main theoretical assumptions.Abortion: regulatory  and (2) Abortion: philosophy . These topics reveal somewhat different contexts in which the term “abortion” is placed.First, the method that we use assumes a contextual approach to meaning because co‐occurrences of terms in the same documents are crucial in the assignment of terms to topics. Moreover, each term is assigned with positive probability to many different topics, which may be interpreted as an ability of the method to capture polysemy or distinguish different uses of the same term on the basis of the context.Abortion: regulatory, a relevant passage clearly refers to “abortion” in its institutional sense: “A growing number of states have banned abortion after twenty weeks on the grounds that ….”Abortion: philosophy, a relevant passage refers to a more abstract sense of “abortion”: “a non‐religious argument against abortion based on what he claims is a morally relevant similarity between killing adult human beings and killing fetuses.”Death: life support; Death: concept; Death: euthanasia).The first use is more regulatory‐oriented, that is, connected with an institutional perspective; the second one is more theory‐oriented, that is, connected with a philosophical perspective on the moral (im)permissibility of abortion. This is clearly discernible if we compare the first uses of the word “abortion” in two papers that are most representative for the two respective topics. In the case of Roe v. Wade, prenatal diagnosis, or the legal liability of physicians. In the second, most of the top papers discuss secular arguments against abortion, such as the “future like ours” argument proposed by Marquis and the substance view that concludes that a human fetus has the same intrinsic value as a typical adult human being.Second, the natural consequence of our contextualism is a document‐grounded approach. Our preferred way of interpreting the topics, patterns, trends, and peaks in the corpus involves looking at documents themselves at every stage of the decision process that requires human interpretation. Let us again refer to the example with the two “abortion” topics. Comparing the top‐10 papers characteristic for these two topics is revealing because they provide evidence in favor of our interpretations of these two topics: In the first case, most documents refer to women's rights, 4.2What can researchers specializing in this field learn from a “distant‐reading” of this large corpus?First, this method provides a data‐driven thematic partition of the field. Any attempt to do so on the basis of close‐reading the texts is much more susceptible to the biases of individual scholars—both because individual researchers cannot realistically read such vast collections of texts and because they cannot be expected to abstain from their own subjective takes on the relative importance of various themes. Intertopic correlations can allow us to see which topics are relatively more closely related, and the clustering of topics based on intertopic correlations offers a useful, and in some regards novel, largely data‐driven, eight‐part division of the field ; ethical issues centered on the professional agents within the healthcare system (PHYSICIAN AND RESEARCHER); and ethical issues centered on the institutional setting in which interactions between these two types of agents occur (INSTITUTIONS). Third, the distinction between PHILOSOPHY OF MEDICINE and THEORETICAL BIOETHICS seems to capture the distinction between topics characteristic of the general philosophy of science as applied to medicine and topics that are more theory‐oriented, covering moral and political philosophy as well as more general phenomenological and narrative approaches.Second, the method allows us to adopt a birds‐eye view of the development of the field. Diachronic changes in the relative prominence of both topics and their clusters can be a welcome addition to the more traditional tools used by historians of philosophy. We can learn which topics and topic clusters have gained or lost in relative prominence over time. Locating local peaks in relative prominence can allow for a more focused search for the precise factors that have shaped these discussions. This is particularly interesting to the extent that bioethics is said to develop in reaction to sudden shocks. For this reason, focusing on the most rapid changes in the topical composition can sometimes offer greater insight than studying long‐term trends.4.3At the most general level, our analyses suggest which areas of research attracted researchers’ attention in the last half century of bioethics and philosophy of medicine. Perhaps the most striking result is that the three clusters concentrated on regulatory and institutional issues related to healthcare systems and medical research  are jointly more prominent than the remaining five content‐based clusters combined. This illustrates how heavily the whole field is invested in issues of clinical and research ethics.Insurance; Law: health; Physician; Committees). The fact that Insurance, Law: health, and Committees are among the three biggest topics reflects research interests in themes typical for the U.S. healthcare system. All of the top‐10 papers characteristic for Insurance discuss Medicaid, U.S. health reforms at different levels , the healthcare programs of American presidential candidates, rising healthcare costs in the United States, and so forth. Similarly, in the case of Law: health, all of the most characteristic papers refer to the U.S. Constitution or mention some U.S. Supreme Court rulings. In turn, among the top‐10 papers in Committees, only one concerns a non‐U.S. context, and the remaining nine discuss The Common Rule, that is, the federal regulations of research with human subjects or the U.S. regulations about IRB. Bioethics and philosophy of medicine started in the United States as a discipline, and our analysis confirms that the themes important from the U.S. perspective loom large in it.At a more detailed level, our analyses can also show which topics in bioethics and philosophy of medicine were the most popular in general over the last 45 years  is strongly associated with Embryos: research. Perhaps more interesting is the list of most negatively correlated pairs of topics, which turn out to be dominated by framing topics. Here, two patterns can be observed. First, some pairs of framing topics are negatively correlated, suggesting that such perspectives are used very rarely in tandem to analyze an issue in bioethics and philosophy of medicine . Second, some framing topics are negatively correlated with some content‐based topics, suggesting that the latter are unlikely to be analyzed from a given perspective .As to the pairs of most strongly correlated topics, they can serve more as a sanity check for the model rather than a source of surprising insights. It is hardly surprising that the topic 4.4In the following pages, we briefly discuss some of the potential ways in which diachronic trends can be interpreted in two dimensions: (1) overall and recent trends and (2) peaks.4.4.1Enhancement (mean prominence from 0.03% to 0.97%), Public health emergencies (from 0.04% to 0.96%), and Circumcision (from 0.04% to 0.37%), whereas the greatest losers are History (from 3.26% to 0.46%), Confidentiality (from 4.37% to 0.62%), and Science: philosophy (from 3.11% to 0.63%).Diachronic analyses suggest changing patterns in research interests and reveal which themes have won or lost the attention of researchers over time. On the one hand, if we zoom in and focus on the popularity of particular themes in the early days of institutionalized bioethics and philosophy of medicine (1976–1985) in comparison with the last 10 years (2011–2020), “the biggest winners” in terms of relative growth are themes represented by the topics we called Enhancement is correlated with Germline and Genetics  are easily interpreted. In particular, taking into account that Public health emergencies) is obviously related to COVID‐19, but the recent pandemic is not enough to do justice to the full scale of its growth. Even after excluding the “pandemic” year 2020 from the analyses , this topic would still be in the third place, just below Circumcision. It suggests that discussions about healthcare emergencies were steadily growing even before the COVID‐19 outbreak, which may be related either to earlier epidemiological crises, such as the 2013–2016 Ebola outbreak, or, more generally, to a growing interest in the bioethical aspects of large‐scale catastrophes, such as natural disasters or terrorist attacks.The second topic among “the biggest winners” ) and revolve around the target article by Benatar and Benatar.The third winner, History may be found in the most characteristic papers for this topic. All of them refer to some classical texts (Gilgamesh) or authors . One might speculate that the fact that the field is becoming more mature provides an explanation: In the early days of bioethics and philosophy of science, authors needed to refer to the classics, whereas now the main discussions concern one another's papers.In the case of the biggest losers, a possible explanation for the relative decline of the topic that we called Confidentiality may be instructive because it may be interpreted as a sign that bioethics and philosophy of medicine were closer to physicians’ professional ethics in their early days and much more focused on physician–patient relations than now . In turn, the relative decline of Science: philosophy may reflect a growing separation between bioethics and philosophy of science . It seems that most papers characteristic for this topic could also be published in philosophy of science journals. This may be a sign that mainstream bioethics and philosophy of medicine journals are increasingly leaning toward an understanding of their own field as one that is more practice‐oriented than theory‐based.The relative decline of Enhancement, Sport, and Genetic testing, among others) and those areas of bioethics that are centered around an individual who encounters the healthcare system , whereas “the biggest losers” are topics characteristic of general philosophy of science as applied to medicine and related to the end of life .On the other hand, we can also adopt a bird‐eye perspective and search for “the biggest winners” in terms of trends larger than a particular topic. From this perspective, the main winners are a group of topics that we interpreted as the cluster EMERGING TOPICS , whereas in the last period (2016–2020), the first cluster represents 23.19% of the corpus, while the second represents only 7.3%. The relative growth of the first cluster is much easier to explain than the relative decline of the second.Circumcision (mean prominence from 0.04% to 0.37%), Nudge (from 0.15% to 0.99%), Participation (from 0.19% to 1.83%), International research (from 0.18% to 1.34%), and Biobanking (from 0.12% to 0.79%) were “the biggest winners” in terms of relative growth . Five topics from this cluster were more popular in the early days of bioethics than they are now, most notably Vulnerability (from 0.61% to 0.31%), Screening (from 1.65% to 0.94%), and Surgery (from 0.84% to 0.58%). However, to explain the growth of the cluster, absolute increases of the topic prominence are more meaningful. As mentioned above, all three content‐based topics that experienced the highest growth in absolute terms  belong to PATIENTS AND RESEARCH PARTICIPANTS.The cluster PATIENTS AND RESEARCH PARTICIPANTS consists of many topics that are steadily gaining in popularity (or at least have done in recent years); in particular, Nudge's dynamic (as well as its peak in 2011–2015) seems to be rather straightforward. Namely, it seems to reflect the uptake of the book by Thaler and Sunstein,The explanation of the Participation. Because most papers characteristic for this topic discuss fairness in the selection of research participants, it may reflect the growing interest and changing awareness of the inclusion of minorities, children, and pregnant women in research, something that has been gradually attracting attention over the last 20 years. Moreover, this topic also had an important peak in 2001–2005 that, judging from the top‐30 papers characteristic for this peak, was stimulated by the problems revolving around paying for research participation. Moreover, this topic is noticeably correlated with many others that have also been growing in popularity, for example, Consent, Monetary incentives, RCT, Children: decisions, Risk and precaution, suggesting a broader trend of interest in many ethical and regulatory issues in research with human participants.More intriguing is the enormous growth (10 times in terms of relative prominence) of Hazards (from 0.94% to 0.25%), Law: health (from 4.04% to 1.27%); Omission (from 1.33% to 0.69%), War and prisons (from 1.2% to 0.67%), and Death: life support (from 1.46% to 0.83%). However, taking into account absolute decreases, the relative decline of END OF LIFE is largely driven by Law: health, which shrunk by 2.77 percentage points . Its most characteristic terms  are typical of papers published in the early days of bioethics, in particular in HCR, and now such issues may have moved to more legally oriented journals. However, the relative decline of the HCR's share in the corpus  does not fully explain the decrease of this particular topic.The reasons why the cluster END OF LIFE as a whole has relatively shrunk is more difficult to explain. The strongest relative decline is visible in the cases of Death: life support is also surprising, particularly if one takes into account the fact that a similar topic, that is, Death: euthanasia (from 0.71% to 0.98%) is rather stable (with one important peak that we will discuss below). Anyway, this trend may be a sign that the popularity of one particular theme in discussions about aid in dying may be decreasing: Artificial nutrition and hydration were discussed in almost all top‐10 papers in the topic Death: life support. It is also worth noticing one particularly important growth in this cluster, namely, Dementia (from 0.51% to 1.1%).The relative decline of Omission is particularly surprising. All top‐10 papers either discuss the doctrine of double effect (DDE) or the distinction between killing and letting die (KLD), which were traditionally treated as crucial for many discussions about practical bioethics dilemmas, and most have been written by well‐known philosophers such as Philippa Foot, Frances M. Kamm, and Warren Quinn. Given the involvement of such prominent philosophers, one might expect sustained influence; yet, it seems that these classic themes are losing their relative popularity in bioethics.Finally, the relative decline of the topic 4.4.2Nudge [2011–2015], Embryos: research [2001–2005], Pharma ethics [2001–2005], Death: euthanasia [1991–1995], and Participation [2001–2005]), we have already mentioned our interpretation of the first and fifth topics.The diachronic analysis of topic prominence allowed us to identify the most pronounced topic peaks, understood as the highest sudden increases of topic prominence . From the top‐5 peaks (Embryos: research (2001–2005 and 1991–1995) may be straightforwardly interpreted as reactions to scientific discoveries and breakthroughs. The most visible peak (2001–2005) represents a clear reaction to the discovery in 1997 and 1998 of methods for deriving and culturing human embryonic stem cells indefinitely and methods for the cloning of adult mammals using nuclear replacement techniques. Many papers that are assigned the highest probability to this peak periodScience,Both peaks of the topic Pharma Ethics 2001–2005 provides a much more diversified picture: Some articles refer to particular political events such as the Congressional investigation in 2004 about the FDA's failure to release a report about the safety of children taking prescription antidepressants or new legal regulations . Some others discuss recently published important books on big pharma,Skimming through the top‐30 documents in Death: euthanasia (1991–1995) can easily be explained by skimming through the top‐30 documents. First, 11 out of 30 papers engage with the Remmelink Committee report in September 1991 about practicing euthanasia in the Netherlands. Second, 12 out of 30 papers discuss contemporary attempts in the United States to legalize euthanasia , court judgments, and the 1993 Dr. Kevorkian case. This is a clear case when the increase of academic interest in a specific theme has a clear social origin.In contrast, 4.5Our approach is mostly data‐driven and automatic, but it also includes “manual interventions” at several important junctures. Primarily, this concerns identifying the corpus and then assigning the number of topics and other parameters of the model, labeling topics, and, finally, clustering them. In particular, there are other possible approaches to constructing the corpus that could result in a different general picture of the field. Instead of delineating the most important bioethics journals, as we did, one could choose to collect the most important articles, defining “importance” as, for example, the most cited articles published in a larger set of journals. Therefore, the picture resulting from our modeling is not self‐evident and should not be treated as a ready‐made object created independently of any human intervention but rather as a useful tool or a piece of evidence that may help researchers in their own interpretive engagement with the original text materials.Embryos: research, first in the late 1980s and the second in the early 2000s, or the very recent prominence of the topic Germline can be interpreted as reactions to actual scientific/technological breakthroughs. Some other trends clearly mirror societal or legal changes , whereas still others reflect the changing landscape of social science and the humanities .We assume that the observed distribution of topics and diachronic trends mirror the changing patterns in research interests, which in turn are reactions to scientific discoveries and breakthroughs, political events and legal decisions, important publications, and broader social trends and transformations. For this reason, in many cases, it is much easier to interpret the growth of interest in a particular theme than a decline. On a more concrete level, two significant increases in the prominence of topic Religion only dropped from 0.98% to 0.75%). However, is this theme still discussed in the same way? Or is it that, earlier, religious traditions used to be a source of inspiration for bioethical reflection, while today they are just another object of study? A topic model  does not offer a conclusive answer (as texts arguing in favor of the continuing importance of religion might be associated with the same topic as those pointing to the irrelevance of religion).However, interpreting the trends is not always an easy task. A topic model does not allow us to uncover the motives that made a given author use terms characteristic for one of our topics, and not the other, in a given text. Let us take the theme of religion as a concrete example: It appears that an average article in bioethics and philosophy of medicine is almost as likely to discuss religion today as it was half a century ago . Given that the whole corpus is expanding massively in time, a relative decline in prominence (at least) in many cases still means growth in absolute terms. Therefore, it is not clear whether (relative) decline actually signals a decrease in interest. It is also worth mentioning that some trends may merely result from the choices or preferences of editors, although the fact that we took seven journals into account should offset the editorial preferences of a single editor or an editorial board.and in the last 50 years. The reason behind the first limitation is a simple result of the fact that a text‐mining technique of the sort used here would not operate well on a multilingual corpus. We had to choose one language, and English has dominated the field for longer than the 50 years analyzed. Second, we chose the period not because we think that bioethics and philosophy of medicine started in 1971, but because it was only then that specialist journals started to emerge, marking the consolidation of the research community. None of these should be treated as suggesting that bioethics and philosophy of medicine consist solely of texts written in this language and in this period, nor as an endorsement of the state of affairs in which texts written in English dominate the debate in bioethics and philosophy of medicine. Philosophy of medicine may be traced back to Hippocratic tradition, and systematic humanistic reflection on ethical issues in medicine developed in the 19th century.We limited our study to papers published in English 5The topic model described in this article, at the most basic level, is a testament to the heterogeneity of bioethics and philosophy of medicine. The model consists of 100 topics, out of which 91 are interpreted as representing clearly distinct substantive areas of interest in the field. Even when we tried to reduce the dimensionality of this structure, it was only with eight different communities based on intertopic correlations that we found a satisfactory clustering. It is virtually impossible that any approach based on close reading would have resulted in such a fine‐grained, yet firmly rooted map of this diverse field.History, Confidentiality, Science: philosophy), whereas others have emerged as new and important areas of research . This type of dynamic is arguably shared with most other academic disciplines: Scholarly interests typically resist rapid changes. However, what is more characteristic of the analyzed field is the second type of observed changes: sudden, rapid peaks in interest in some themes . We interpret this second pattern as reflecting the aspiration of bioethics to react quickly to changing circumstances: on the one hand, to keep pace with most recent scientific and technological breakthroughs, while commenting on urgent social, political, and legal challenges on the other. Finally, despite the inherently dynamic nature of bioethics and philosophy of medicine, we still observed themes that perhaps surprisingly have not experienced any noticeable decline (or rise) in interest .The heterogeneity of this area is also reflected in the diverse set of diachronic trends that we have identified. First, there are themes that seem to follow a steady, monotonic trend throughout the analyzed period: some have been gradually going out of fashion (in particular, Although this paper focused on partitioning the field of bioethics and philosophy of medicine into topics and describing diachronic trends, the model can also be used for further analyses. For instance, it can be used to characterize journals in terms of topic mixtures or look for correlations between topics and the demographic characteristics of authors.The authors declare no conflict of interest.


The labelingstrategy provided detailed structural information via NMR—downto individual enantiomers—which overcomes a crucial blind spotin the analysis of InsPs. We uncovered a novel branch of InsP dephosphorylationin human cells which is dependent on MINPP1, a phytase-like enzymecontributing to cellular homeostasis. Detailed characterization ofMINPP1 activity in vitro and in cells showcased the unique reactivityof this phosphatase. Our results demonstrate that metabolic labelingwith stable isotopomers in conjunction with NMR spectroscopy and CE-MSconstitutes a powerful tool to annotate InsP networks in a varietyof biological contexts.The water-solubleinositol phosphates (InsPs) representa functionallydiverse group of small-molecule messengers involved in a myriad ofcellular processes. Despite their centrality, our understanding ofhuman InsP metabolism is incomplete because the available analyticaltoolset to characterize and quantify InsPs in complex samples is limited.Here, we have synthesized and applied symmetrically and unsymmetrically  myo-inositol (phosphate) isotopomers,unprecedented insight into thesecentral eukaryotic messengers and their metabolism in human cellswas obtained.Using chemoenzymaticallysynthesized  Myo-inositol polyphosphates(InsPs) are ubiquitous,water-soluble small molecules found in all eukaryotes. InsPs are involvedin a wide spectrum of biological functions as they are key to fundamentalphysiological processes. A well-characterized example is inositol-1,4,5-trisphosphateP3) as a Ca2+ release factor. Morerecently, InsPs were shown to regulate the activity of class I histonedeacetylases as well as Bruton’s tyrosine kinase (Btk), whichimplies a wider role for InsPs in transcriptional regulation and ingoverning intracellular signal transduction.37 The most abundant InsPs in mammalian cells are inositol-1,3,4,5,6-pentakisphosphate(InsP5[2OH]) and inositol hexakisphosphate , with cellular concentrations rangingfrom the lower micromolar range to >100 μM in human cellsandeven in the sub-millimolar range in slime molds.9 InsP5[2OH] and InsP6 are precursors for the biosynthesisof inositol pyrophosphates (PP-InsPs), which have recently drawn increasingattention due to their dense phosphorylation patterns and their involvementin central signaling processes.10 InsP6 is also found in a growing number of proteins and proteincomplexes as a structural cofactor or as a “molecular glue”for protein–protein interactions.14The InsPsvary greatly with respect to their phosphorylation patterns,and over 20 different InsPs are currently thought to be part of mammalianInsP metabolism.15 especiallywith respect to the higher phosphorylated members. To date, MINPP1(Multiple Inositol Polyphosphate Phosphatase 1) is the only recognizedenzyme in the human genome capable of dephosphorylating InsP6.17 MINPP1 is related to phytases, a highlyconserved group of enzymes in many other organisms that can dephosphorylatevarious InsPs.18 MINPP1 has been shownto play a role in apoptosis, ER-related stress, and bone and cartilagetissue formation.19 Recently, MINPP1 was connectedto a genetic disorder: patients with loss-of-function mutations inMINPP1 exhibit pontocerebellar hypoplasia (PCH), a neurodegenerativedisease severely impacting cognitive functions and life expectancy.21 Therefore, it is important to understand the molecular mechanismsof MINPP1-governed functions in healthy and diseased states.While the kinase-mediatedpathways of InsP biosynthesis are fairlywell studied, there is limited information on dephosphorylation ofInsPs in mammalian cells,6,22 MINPP1 is also able to dephosphorylateseveral InsPs at different positions with varying affinities and kinetics.24 The current assumption is that MINPP1 dephosphorylates InsP6 to hitherto only sparsely annotated InsP4/3 species in a mixture with isobaric sugar phosphates remaindifficult. Our group recently established a metabolic labeling strategyusing isotopically labeled [13C6]myo-inositol. Analysis of the extracted metabolites by 2D nuclear magneticresonance (NMR) spectroscopy enabled the quantification of higherphosphorylated InsPs -based fractionation in combinationwith radiolabeling and scintillation counting, high-density polyacrylamideelectrophoresis with cationic staining, or, more recently, capillaryelectrophoresis coupled to mass spectrometry (CE-MS).13C-labeled andasymmetrically 13C-labeled isotopomers of myo-inositol andInsPs in both biochemical and cellular metabolic labeling experiments.Making use of their inherent properties (position-specific NMR activityand different molecular masses), we uncovered an uncharacterized branchof human InsP metabolism. InsP2 and Ins(2)P were identifiedas major InsPs species in human cells, and their levels are dependenton MINPP1 activity toward InsP6 in vitro and in cellula.Through in vitro characterization, computational kinetic modeling,and metabolic flux via CE-MS analysis, we dissect the complex reactivityof MINPP1. We envision that this combined application of myo-inositol isotopomers in NMR and CE-MS experiments will help unravelcomplex InsP networks in different biological contexts in the future.Here, we combined fully 1H,13C}HMQC-NMR spectra of 19 different InsPs and PP-InsPs  were recorded and assigned. The collectivedata of these spectra illustrate that the NMR signals of InsPs clusterin a systematic manner (S1). NMR signals correspondingto methine groups adjacent to a nonphosphorylated hydroxyl substituent(CH–OH) are separated from methine group signalswith a phosphate substituent (CH–O–PO32–), which are collectively shifted downfieldin both 1H and 13C dimensions. Within thesetwo groups, clusters for the different positions on the myo-inositol ring are apparent. The 2- and 5-positions form clustersof their own, while positions 1 and 3 as well as positions 4 and 6are intertwined due to the symmetry plane of the myo-inositol ring. These combined spectra illustrate that a completeset of NMR signals of an InsP can be used to determine the phosphorylationpattern, and thus the identity, of a given InsP. In the case of chiralInsPs, their NMR spectra cannot be used for a definitive assignmentbut can narrow the identity down to a pair of enantiomers. For distinguishingtwo InsP enantiomers, a desymmetrization strategy has to be employed,such as unsymmetrical isotopic labeling of the myo-inositol ring with 13C, as will be discussed below.The analysis ofcomplex mixtures of InsP metabolites still constitutes a significantanalytical challenge. To identify inositol-derived signals in biologicalsamples via NMR in a methodical way, BIRD-{c manner 2 and S1.13C6]myo-inositol . After the cells incorporated the 13C label into their InsP pool to equilibrium (over 2 passages), cellswere harvested and their water-soluble metabolites extracted and analyzedby BIRD-{1H,13C}HMQC-NMR. This NMR experimentdetects 13CH groups selectively over nonlabeled CH groups,making it particularly suitable for measuring the 13C-labeledInsP pool within a complex background. The information from 13C-labeled species from such extracts.Quantification was performed through relative integration of the signalcorresponding to the 2-position against an internal standard and back-calculatedto packed cell volumes. The annotation of the different InsPs in anHCT116 metabolic extract is shown exemplarily in Figure S2). The same set of InsP species wasobserved in all other cell lines as well (S3): themajor labeled species include InsP6, InsP5[2OH],1/3-glycerophospho-myo-inositol (1/3-GroPI), inositol1- or 3-monophosphate (Ins(1/3)P), inositol 1,2- or 2,3-bisphosphateP2), inositol 2-monophosphate (Ins(2)P), and myo-inositol. All of these metabolite assignments were validatedthrough spike-in experiments with commercially available InsP standardsinto 13C-labeled metabolic extracts . Interestingly, labeling of Schizosaccharomycespombe  revealeda somewhat different metabolite composition.We next performed metabolic labeling of human cell lines  with [inositol 1b.38 In  as well 3b and S313C-labeled myo-inositols following our previously published protocol.38 Using the singly labeled isotopomer 1[13C1]myo-inositol and doubly labeled 4,5[13C2]Ins, respectively, we repeated the metaboliclabeling in HEK293 and HCT116 cells. Focusing on the 1[13C1]myo-inositol labeling, the resultingspectra (S6a) show thatthe signals that correspond to the phosphorylated 1/3-positions of1/3-GroPI and Ins(1/3)P are labeled, i.e., the enantiomers presentin mammalian cells are 1-GroPI and Ins(1)P. The phosphorylated 1/3-positionof InsP2 is not labeled, which identifies InsP2 as the prevalent enantiomer, an observation that was reproduciblein both cell lines. To confirm this conclusion, HEK293 cells werealso labeled with 3[13C1]myo-inositol. Now, the phosphorylated position of the putative InsP2 remains labeled, unambiguously identifying InsP2 as the main InsP2 enantiomer present in humancell lines P2 and Ins(2)P in the micromolarrange P have not been associated with any establishedInsP-related pathway so far. Although Ins(2)P and InsP2 were detected in 1995 by Mitchell and colleagues,40 these metabolites received little attention and have been neglectedsince then.GroPI and Ins(1)P are established products of cellularphosphatidylinositideturnover;13C-labeled speciesin mammalian cells, and in combination with the asymmetrical inositolisotopomers, enantiomers could be resolved spectroscopically. Thisanalysis uncovered high amounts of previously poorly characterizedlower InsPs, which were not easily accessible with other analyticalmethods.Overall, the structural information contained inthe HMQC-NMR spectracould be used to assign all detectable 6 there are no InsP intermediates that are phosphorylated at the 2-position.The 2-phosphoryl group of InsP6 is installed only in thelast step, in which IPPK (inositol pentakisphosphate 2-kinase) convertsInsP5[2OH] to InsP6. InsP2 andIns(2)P may therefore be generated downstream of InsP6.A central InsP phosphatase is the mammalian phytase-like enzyme MINPP1,the only recognized InsP6 phosphatase. To investigate possiblerelationships between InsP2, Ins(2)P, and MINPP1,we turned our attention to cells lacking MINPP1. MINPP1–/– HEK293 cells were labeledwith [13C6]myo-inositol, andthe metabolites were analyzed by NMR . InsP5[1/3OH]was not present in any investigated WT cell line. Labeling of MINPP1–/– HEK293cells with the asymmetric isotopomers 1[13C1]myo-inositol, 3[13C1] myo-inositol, and 4,5[13C2]myo-inositol unambiguously identified the InsP5 in question as InsP5[3OH] .In the biosynthetic pathway toward InsPd by NMR 4. The MIMINPP1–/– cellextracts was thecomplete absence of InsP2 and Ins(2)P, establishinga connection between MINPP1 and these lower phosphorylated InsPs.The lack of an undefined InsP2 species was also noted ina previous analysis of the same cell line using a radiolabeling approach.21 Taking into consideration the only sparselyannotated intermediates and products of MINPP1-mediated dephosphorylationof InsP6, it seemed possible that MINPP1 could generateInsP2 and Ins(2)P directly from InsP6.Strikingly, another change observed in the E. coli was optimized to isolateprotein yields compatible with biochemical reactions on an NMR scale. Next, MINPP1 was incubatedwith fully 13C6-labeled InsP5[2OH],and the reaction was monitored using 2D NMR measurements. In thefirst experiments we chose a substrate concentration of 50 μM,which is in the middle to upper range of physiological concentrations.41 To enable the detection and assignment of all intermediates,we subsequently increased the substrate concentration to 175 μM,which did not alter the overall outcome P4 andsubsequently InsP3. MINPP1 therefore directly reversesthe phosphorylation reactions catalyzed by IPMK (inositol phosphatemultikinase).43 InsP3 is subsequently converted slowly to a mixtureof different InsP1/2s .To validate this hypothesis,we next sought to investigate the in vitro activity of MINPP1 againstdifferent InsPs. The expression and purification of recombinant MINPP1in trationsS9.41 To trationsS9.41 To trationsS9.41 To 6. In contrast to InsP5[2OH] as a substrate,we observed a complex mixture of intermediates : Onedephosphorylation sequence proceeds via InsP5[3OH] andInsP3 as intermediates, and a second pathway generatesInsP3 as an intermediate via an unidentified (dueto low abundance) InsP5 isomer. Importantly, InsP2 and Ins(2)P were observed as the final products of the dephosphorylationof InsP6, validating that MINPP1 is capable of generatingthese InsPs directly from InsP6.We then proceeded to probe MINPP1-mediated dephosphorylationofInsPmediates 5c. In ad6, we synthesized 1[13C1]InsP6.38 TheInsP5, InsP4, and InsP3 intermediateswhich are produced by MINPP1 from 1[13C1]InsP6 are enantiopure, as no dephosphorylation of the 1-positionwas observed . Surprisingly though, a mixture ofInsP2 and InsP2 was formed duringthe later stages of the reaction . The rather high ratio of InsP2 toInsP2 suggests that InsP2 is formedexclusively via InsP3, and InsP3 is selectively converted to InsP2. Both InsP2s are, in turn, dephosphorylated to Ins(2)P. Our in vitroassessment of MINPP1 activity thus confirms the notion that MINPP1can directly generate the novel cellular InsP species from InsP6.To assess whichenantiomers were formed during MINPP1-mediateddephosphorylation of InsP46 is that thedephosphorylation sequences for InsP6 and InsP5[2OH] do not share any overlap  becauseMINPP1 seems to be incapable of removing the phosphoryl group at the2-position. Likely, the charged phosphoryl group on the only axialposition of the myo-inositol scaffold plays a rolein positioning the InsPs inside MINPP1’s catalytic pocket.47Another interestingobservation,which runs counter to assumptions on MINPP1 activity,49 The reaction rates for the MINPP1 reaction starting with InsP5[2OH] as a substrate are shown in Figure S10).The calculated rates predict progress curves (S25) thatare in good agreement with the experimental data, which supports theassumption of time-independent rates and thus the absence of inhibitionprocesses. The highest reaction rate ) also corresponds to the canonical MINPP1 activity towardInsP5[2OH] in the literature.23To characterizethe kineticproperties of MINPP1, we next numerically determined the reactionrates of the dephosphorylation steps from the respective experimentaldata based on a time-independent rate model. We formulated the kineticsof the reaction network as a Master equation and approximated thecorresponding rate matrix with a least-squares method that iterativelyoptimized the rates with respect to the scaled experimental data.6, the computationalanalysisof the experimental data . The poor fits indicate that the rates inthe InsP6 dephosphorylation network might not be time independentbut are instead affected by inhibition processes that implicitly introducea time dependence. Because of its relative stability and slow dephosphorylation,it seemed possible that InsP6 could act as an inhibitorfor the dephosphorylation of the MINPP1-generated intermediates.23 This notion is further reinforced by the factthat the conversion of the intermediates progressed notably fasterwith lower InsP6 starting concentrations . To test this, [13C6]InsP5[2OH] was incubated with MINPP1 in the presence of differentamounts of [13C6]InsP6. Indeed, aclear inhibitory effect of InsP6 on the dephosphorylationof InsP5[2OH] by MINPP1 was observed with an apparent IC50 value of 2 μM .50However, in the case of InsPtal data 5c with t5[3OH], InsP2, and Ins(2)P in vitro, we sought to perform metabolic fluxanalysis to confirm this reaction sequence in living cells. HEK293or MINPP1–/– HEK293 cells were labeled with [13C6]myo-inositol to equilibrium and subsequently exposed tomedium containing 4,5[13C2]myo-inositol for various periods of time before harvesting , which presumably stems from inositol neogenesis fromglucose-6-phosphate.51 The metabolic fluxanalysis P2 . This incorporation sequence supports the hypothesisthat InsP2 is indeed derived from InsP6 in human cells and is not an intermediate in the biosynthesis ofInsP5[2OH] or InsP6 P2 was observed abovethe limit of detection, although the sensitivity of CE-MS is superiorto NMR. Thus, CE-MS analysis confirms that generation of InsP2 is dependent on MINPP1. Similarly, in the biosynthetic sequence,InsP5[3OH] is generated after InsP6 , respectively). These activities are in linewith previous kinetic analyses of mammalian MINPP1 (211 and 12 nmol/(minmg enzyme), respectively).23 The subsequentslow dephosphorylation of InsP3 in vitro (rate constantof 10–4 min–1 or 0.3 nmol/(minmg)) is likely not biologically significant as there are several otherInsP3 dephosphorylating enzymes with 4–5magnitudes higher activity (5300–25 000 nmol/(min mg)).54 Interestingly, depletion of cellular MINPP1did not significantly alter InsP5[2OH] levels, suggestingthat other enzymes are able to dephosphorylate InsP5[2OH]in a cellular setting.53Taking advantage of our labeled 5[2OH] dephosphorylation by MINPP1,the dephosphorylation ofInsP6 occurs via an intricate network of intermediates.The first observable intermediates can be attributed to the 3-phosphataseactivity of MINPP1; however, a significant portion of InsP6 must initially be dephosphorylated at a different position becausethe symmetrical InsP3 accumulates as an intermediate.Despite this complicated dephosphorylation network, the InsP6 dephosphorylation sequence converges to two final compounds, InsP2 and Ins(2)P in vitro. In all human cells we tested, InsP2 and Ins(2)P were present at notable concentrations and constitutea hitherto uncharacterized part of mammalian InsP metabolism. It wassomewhat surprising that InsP2 is the predominantInsP2 species within cells, given that MINPP1 is annotatedas a 3-phosphatase. Our in vitro data demonstrate that MINPP1 is capableof producing both enantiomers, InsP2 and InsP2, via the aforementioned dephosphorylation pathways from InsP6. It thus seems feasible that InsP2 can alsobe generated by MINPP1 in cells but may be depleted faster to Ins(2)Pby either MINPP1  or a separate phosphatase altogether.In contrast to the straightforwardreaction paths for InsP6 do not overlap with any intermediates of InsP5[2OH] dephosphorylation, because MINPP1 appears incapable of removingthe phosphoryl group at the 2-position of the inositol ring P4 and InsP3 in vitro, InsP6 onthe other hand is exclusively dephosphorylated to metabolites, whichkeep the phosphoryl group at the 2-position. This data is in starkcontrast to the common assumption that MINPP1 would convert InsP6 to InsP5[2OH], as is often depicted in overviewschemes on InsP metabolism.46 It was shown in the past that the phosphoryl groupat the 2-position of the myo-inositol ring  can play an important role for proper recognitionof InsPs by protein binding partners.56 Our data furthercorroborates the importance of the phosphorylation status of the 2-position(and thus IPPK activity) because it appears that InsPs may be “sorted”into the known and reversible InsP network (when InsPs contain a freehydroxyl group at the 2-position) or InsPs enter the slower, and potentiallyirreversible, MINPP1-mediated circuit where they remain phosphorylatedat the 2-position.Remarkably, the many different dephosphorylation products of InsPtol ring 7d. While5[2OH] and InsP6 likely alsoplays a role. We found that the dephosphorylation of InsP5[2OH] was strongly inhibited by low concentrations of InsP6 in vitro (S15). In the cellular context, thispotent inhibitory effect of the abundant InsP6 metaboliteraises the question if, and how, MINPP1 can dephosphorylate InsP5[2OH] at all. MINPP1 would need to access localized poolsof said InsPs that are tightly regulated to either avoid or make useof the inhibitory effect. Interestingly, MINPP1 is thought to predominantlylocalize to the ER,28 so how it accessescytosolic (and presumably nuclear) InsPs is a question that has yetto be answered. While some studies have shown that MINPP1 (isoforms)might also be localized in cellular compartments other than the ER,30 or could be even secreted,31 tools to measure intracellular concentrations ofdifferent InsPs with spatial resolution are currently not available.An intriguing avenue for regulation could be that MINPP1 remains localizedto intracellular organelles (ER or lysosomes) into which InsPs arecontrollably translocated and then dephosphorylated. This dephosphorylationcould potentially proceed all the way to myo-inositol—withthe aid of additional phosphatases—which could then be releasedthrough inositol transporters like SLC2A13 (HMIT). HMIT is known tobe localized in intracellular membranes due to its ER-retention sequenceand internalization sequence.59While this sorting could be accomplishedsolely by the preferreddephosphorylation by MINPP1, the accessibility to the two differentsubstrates InsPmyo-inositol,it was possible to assign the uncharacterized InsP5 isomerthat accumulates in MINPP1–/– cells as InsP5[3OH]. This accumulation appearscounterintuitive, since MINPP1 is currently the only known enzymein the human genome capable of generating InsP5[3OH]. Nevertheless,Chi et al. also observed a residual 3-phosphatase activity in MINPP1–/– mice.16 An analogous activity in human cells could beresponsible for producing InsP5[3OH] from InsP6, as illustrated by our CE-MS-based metabolic flux analysis. Elucidatingthe identity of this 3-phosphatase will be of interest in the futureas it constitutes an additional point of regulation within the InsPnetwork. Furthermore, two recently reported cell lines with elevatedintracellular phosphate levels were shown to contain a nonannotatedInsP5 isomer .60 Once the absolute configuration of these InsP5 isomershas been determined, and ideally the enzymatic activities responsiblefor generating these isomers, the impact of cellular phosphate homeostasison InsP signaling could be further explored.Using asymmetrically isotope-labeled 6 and its intermediates has yet to be explored.The InsPs produced by MINPP1 could be part of a recycling system convertingInsP6 back to Ins(2)P, which might be converted to myo-inositol by an inositol monophosphatase P61). As MINPP1 is a homologue of phytases, which take part in inositolrecycling/scavenging, this possibility does not seem far fetched.18 We cannot exclude the existence of other unknownphosphatases that contribute to this dephosphorylation pathway; however,the accumulation of InsP5[3OH] in –/–MINPP1 cells suggests that MINPP1 is obligatory for the dephosphorylationof InsP5[3OH]. Furthermore, the complete absence of InsP2 in –/–MINPP1 cellsindicates that MINPP1 must carry out the key dephosphorylation ofInsP6 on the path toward InsP2. In addition,it remains to be investigated which enzymes can utilize the hereinidentified InsP2 as substrates. Whether any of theInsP6-derived MINPP1 products have signaling functionsthemselves is also an open question. It is possible that some MINPP1-generatedInsPs (or the lack thereof) could be important contributing factorsin MINPP1-regulated processes, i.e., ER stress, endochondral ossification,and neuronal function.21 For example, it would be interesting to investigate if the hyperaccumulationof InsP5[3OH] or the absence of InsP2 andIns(2)P is partially responsible for causing PCH in patients withMINPP1 loss-of-function mutations.21 Ucuncu etal. proposed that hyperaccumulation of InsP6 in neuronalcells of PCH patients might be a mechanistic cause of this diseaseby chelating iron ions.21 In fact, allInsP species which possess the 1,2,3-phosphorylated motif might becapable of binding iron ions.62 In contrastto their reported 3–4-fold increase of [3H]InsP6 levels  in MINPP1–/– HEK293cells compared to WT cells, we only observed a slight increase usingthe same cell line but normalizing against packed cell volume. Thisdiscrepancy points toward several interesting possibilities: (a) PIPlevels, or the incorporation of exogenous myo-inositol,could be (indirectly) influenced by MINPP1 activity, (b) radioactivity-inducedcell stress could have an effect on MINPP1 expression,17 or (c) knockout of MINPP1 changes the cell shape/volume.To differentiate between these possibilities, different quantificationmethods should be compared in the future, and the composition of PIP isotopomersduring metabolic labeling experiments could be probed with mass spectrometry-basedmethods.65The physiologicalrole of the herein described dephosphorylationpathway for InsP17 Another interesting application would be todetermine the fate of inositol (phosphates) in pathogenic parasitessuch as T. cruzi, in which InsP metabolism is essentialfor the developmental cycle.66 The questionif or how InsP metabolism of the host cell and the parasite influenceseach other might lead to new therapeutic avenues for these parasitoses.The dissection of InsP degradation in an extracellular context, namely,how InsPs contained in food are converted by digestive processes orthe gut microbiome and if the resulting metabolites might have beneficialor detrimental effects on health, is also a fascinating question.68 With the tools and methods reportedhere, these topics now become addressable.As a next step, the combination of inositolisotopomers, NMR andCE-MS which we used in this study could be useful to probe InsP metabolismin a variety of biological contexts. For example, it could be investigatedhow the InsP pool changes during ER-related stress, during which MINPP1is upregulated, and how this might correlate with the onset of apoptosis.All experimentaland computational methodsare described in the


Recent interest has surged in the anterolateral ligament (ALL) and complex (ALC) of the knee. Its existence and role in rotary stability of the knee, particularly in the setting of anterior cruciate ligament (ACL) reconstruction, remains a contentious and controversial topic.We must review our history and recognize the pioneers who pushed our understanding of the ALL forward before it was popularly recognized as a discrete structure. Additionally, given that many eponyms remain in common use related to the ALC, we must standardize our nomenclature to prevent misuse or misunderstanding of terms in the literature. In this review, modern understanding of the anterolateral ligament complex (ALC) is traced to 1829 by exploring eponymous terms first in anatomy and then in surgical technique. Understanding our history and terminology will allow us to better understand the ALC itself.This review aims to provide historical context, define terminology, and provide insight into the clinical relevance of the ALC. Throughout its history, medicine, and in particular orthopedic surgery, has used eponymous terms to describe common presentations, often attributed to the first to describe said structure or pathology. Eponyms continue to be frequently used in orthopedic surgery , 2, inclThe anterolateral ligament (ALL) is a portion of the anterolateral ligament complex (ALC), and an anatomic structure that has had a long and controversial history with a recent surge of interest, particularly when considering primary and revision anterior cruciate ligament (ACL) reconstructions –16. ACL Born in 1797, Pierre Nicholas Gerdy began his studies of anatomy at age 16 when he enrolled in a military surgeon program to avoid the general draft in France . His stuAnother French surgeon, Paul Segond, trained in general surgery in the nineteenth century and was predominantly interested in urology and gynecology –32. His Journal of Bone and Joint Surgery, American Volume [Born in Ukraine at the turn of the twentieth century, Emanual B. Kaplan’s early medical career was defined by wartime through World War I followed by the Russian civil war . It was n Volume . He examn Volume .While a few anatomic eponyms remain in common use for the ALC, countless describe surgical techniques that attempt to reconstruct the disrupted ALC. Andrews, Brückner, Ellison, Hughston, Lemaire, Losee, MacIntosh, Marcacci, Marshall, and Müller procedures represent just a sample of many names associated with published lateral extra-articular tenodesis (LET) techniques , 38. ThrAnother French surgeon is remembered in the story of the anterolateral ligament complex through the work of Marcel Lemaire. Little is published regarding his personal history as a general surgeon, but his contribution to the orthopedic realm continues to be valuable. He noted poor results in some of his patients treated for meniscal pathology for whom only the meniscus was addressed, ultimately attributing these poor outcomes to deficiency of the ACL. Thus he began to perform an anterolateral tenodesis to provide stability to the ACL-deficient knee, initially publishing his technique in a series of 46 cases . In his bandelette de Maissiat,” a still used French eponym not utilized in English [Of interest, Lemaire utilizes the eponym Gerdy’s tubercle as well as referring to the ITB as the “ English . Lemaire English , 41. Chr English . Many su English –46. The  English .While Marcel Lemaire operated in France, across the Atlantic David L. MacIntosh was simultaneously working towards developing his lateral tenodesis technique in Toronto, Canada. As the orthopedic surgeon for University of Toronto in the 1950s, he noted instability contributing to poor outcomes in some of his varsity athletes . He and In his treatment of these patients with instability, MacIntosh would go on to develop his eponymous soft-tissue LET technique. In his method, a strip of the middle third of the ITB is dissected, leaving it attached distally to Gerdy’s. This graft is then passed retrograde under the LCL, through a soft-tissue subperiosteal tunnel posterior to the femoral origin of the LCL, through the lateral intramuscular septum and turned distal, passed back under the LCL, and sutured back onto itself at Gerdy’s tubercle Fig. A 51, 5252. This An American surgeon and longtime resident of New England, Arthur E. Ellison was passionate about sports surgery with a particular interest in skiing . He servIn 1979, Ellison published the results of this procedure on 18 patients with good results and return to sport, concluding that “stability can be restored by retaining the lateral tibial condyle posteriorly by transplanting the iliotibial band posteriorly, in a flexor position, thus preventing it from going into an anterior or subluxing position” . StandinThe purpose of this review was threefold. First, we aimed to compile the history of pioneers in orthopedic surgery and discoveries surrounding the ALC of the knee into one manuscript. The contributions to anatomy made by Gerdy, Segond, and Kaplan and to surgical techniques by Lemaire, Macintosh, and Ellison should be remembered. Second, we aimed clarify and define these commonly used eponyms to ensure our use of eponyms is accurate and consistent. Eponyms can be useful in areas such as ALC surgical techniques, where each name serves as a single distinct identifier for a specific technique. However, they also pose challenges, as the plethora of names and minor nuances between procedures can be lost and, when the initial surgeons’ works are not reviewed and remembered, their names can be easily misused. Herein, the original texts leading to eponyms were reviewed to assure the most accurate and precise terminology. Third, with controversy regarding the ALC and ALL, history has the unique potential to provide insights into where we have obtained our current foundation of knowledge. By investigating our history closely and standardizing the nomenclature surrounding the ALC, we can forge ahead to a greater understanding of this controversial and clinically relevant area of the knee.