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PURPOSE To assess diagnostic performance of digital breast tomosynthesis (DBT) alone or combined with technologist-performed handheld screening ultrasound (US) in women with dense breasts. METHODS In an institutional review board–approved, Health Insurance Portability and Accountability Act–compliant multicenter protocol in western Pennsylvania, 6,179 women consented to three rounds of annual screening, interpreted by two radiologist observers, and had appropriate follow-up. Primary analysis was based on first observer results. RESULTS Mean participant age was 54.8 years (range, 40-75 years). Across 17,552 screens, there were 126 cancer events in 125 women (7.2/1,000; 95% CI, 5.9 to 8.4). In year 1, DBT-alone cancer yield was 5.0/1,000, and of DBT+US, 6.3/1,000, difference 1.3/1,000 (95% CI, 0.3 to 2.1; P = .005). In years 2 + 3, DBT cancer yield was 4.9/1,000, and of DBT+US, 5.9/1,000, difference 1.0/1,000 (95% CI, 0.4 to 1.5; P < .001). False-positive rate increased from 7.0% for DBT in year 1 to 11.5% for DBT+US and from 5.9% for DBT in year 2 + 3 to 9.7% for DBT+US ( P < .001 for both). Nine cancers were seen only by double reading DBT and one by double reading US. Ten interval cancers (0.6/1,000 [95% CI, 0.2 to 0.9]) were identified. Despite reduction in specificity, addition of US improved receiver operating characteristic curves, with area under receiver operating characteristic curve increasing from 0.83 for DBT alone to 0.92 for DBT+US in year 1 ( P = .01), with smaller improvements in subsequent years. Of 6,179 women, across all 3 years, 172/6,179 (2.8%) unique women had a false-positive biopsy because of DBT as did another 230/6,179 (3.7%) women because of US ( P < .001). CONCLUSION Overall added cancer detection rate of US screening after DBT was modest at 19/17,552 (1.1/1,000; CI, 0.5- to 1.6) screens but potentially overcomes substantial increases in false-positive recalls and benign biopsies.

Background Breast Imaging Reporting and Data System (BI-RADS) category 3 (BR3) (probably benign) mammographic assessments are reserved for imaging findings known to have likelihood of malignancy of 2% or less. Purpose To determine the effect of age, finding type, and prior mammography on cancer yield for BR3 findings in the National Mammography Database (NMD). Materials and Methods This HIPAA-compliant retrospective cohort institutional review board-exempt study evaluated women recalled from screening mammography followed by BR3 assessment at diagnostic evaluation from January 2009 to March 2018 and from 471 NMD facilities. Only the first BR3 occurrence was included for women with biopsy or imaging follow-up of at least 2 years. Women with a history of breast cancer or who underwent biopsy at time of initial BR3 assessment were excluded. Women were stratified by age in 10-year intervals. Cancer yield was calculated for each age group, with (for presumed new findings) and without prior mammographic comparison, and by lesion type, where available. Linear regression with weighted-age binning was performed to assess for differences between groups

The uses of dipolar shifts due to cobalt(II) substituted for zinc(II) in a consensus zinc finger peptide for refining the NMR-determined structure were examined. Substantial differences between the calculated and observed chemical shift differences between the cobalt(II) and zinc(II) complexes were observed when these dipolar shifts were not used as constraints in the structure refinement. However, inclusion of these constraints resulted in excellent agreement with minor adjustments in the structure and a slight improvement in the precision of the structure determination. Other calculations revealed that the dipolar shifts were not adequate to determine the overall folded structure by themselves, but were useful in increasing the accuracy and precision of a structure determined based only on nuclear Overhauser effects constraints involving only backbone atoms.

In 1953, the proposed structure of DNA magnificently linked biological function and structure. By contrast, 4 years later, the first elucidation of the structure of a protein—myoglobin, by Kendrew and colleagues—revealed an inelegant shape, described disdainfully as a “visceral knot.” Additional complexity, as well as some general principles, was revealed as more protein structures were solved over the next decade. In 1971, scientists at Brookhaven National Laboratory launched the Protein Data Bank (PDB) as a repository to collect and make available the atomic coordinates of structures (seven at the time) to interested parties. The PDB now includes more than 180,000 structures, and this resource has fueled an incalculable number of advances, including the recent development of powerful structure prediction tools. Biology takes place in three dimensions, yet most biological information is stored in one-dimensional sequences of DNA that encode the amino acid sequences of proteins. The transition from one to three dimensions is accomplished through the spontaneous folding of a sequence of amino acids into a folded protein structure. Comparing elucidated structures revealed that proteins that are at least 30% identical in amino acid sequence almost always have the same folded structure; evolutionarily, structure is much more conserved than sequence. Conversely, some short stretches of five or more amino acids can adopt completely different structures; structure is context dependent. Thus, the relationship between sequence and structure is not a simple one. Predicting protein structures from sequences has been a grand challenge for decades. By 1994, fueled by the explosion of sequences, biophysicist John Moult and colleagues organized the first Critical Assessment of Structure Prediction (CASP) meeting. CASP is based on blinded assessments, which are common in clinical trials. Sequences of proteins whose structures had been determined but not publicly shared were made available to would-be predictors to develop and submit structural predictions for subsequent independent assessment. The first CASP meeting was somewhat depressing because the results revealed that predictors were doing substantially worse than they thought. CASP meetings have continued every 2 years and have driven the field forward through feedback and competition. The most recent CASP meeting, in November 2020, was shaken by results from the company DeepMind. Its AlphaFold program performed substantially better than other programs had in the past, producing many results that are of similar quality to that of experimental structures. The RoseTTA-Fold program, developed by the laboratory of structural biologist David Baker, builds on this laboratory’s previous work, combined with insights from the DeepMind success (see page 871). The results of both programs are sufficiently good that many are claiming that these represent relatively general (but certainly not perfect, and incomplete) solutions to the structure prediction problem. Notably, both groups have provided their computer code for their methods for others to use, test, and enhance. These programs are based on deep-learning artificial intelligence methods. Such approaches depend on the availability of many thousands of questions with known answers to train the neural networks at their core. Thus, without the sequences with known structures from structural biologists from around the world shared in the PDB, these approaches would not have been feasible. The teams that developed these powerful programs deserve great credit for their accomplishments, but these stand on a foundation of the results from billions of dollars of public fund investments in structural biology and the sustained support of the PDB from around the world (now overseen by the Worldwide PDB). Policies from funders, publishers, and the scientific community have led to requirements that reported structures be promptly deposited in the PDB. As someone who has interacted with the PDB as a consumer, a contributor, a policy-maker, and a funder, I have experienced the power and challenges of trying to optimize such a public resource. The cultural shifts, at the cutting (and often bleeding) edge of open science, were often controversial, but it is hard to argue that they have not both increased the impact of individual determined structures and accelerated scientific progress in many ways. The ever-growing PDB provides researchers with a universe of structures with which to compare their favorite structures. The new structure prediction tools expand this universe further and provide truly compelling evidence of the power of open science. Moreover, these tools bring truth to an old saying in structural biology circles, “The structure prediction problem has been solved; it’s hiding in the PDB.”

At Argonne we have enhanced the AMS capabilities of the Argonne Tandem Linac Accelerator System (ATLAS) to attempt to minimize crosstalk between samples and to quickly move from one (M/Q) setting to another in order to make measurements on a large number of samples provided by the MANTRA (Measurement of Actinide Neutron Transmutation Rates by Accelerator mass spectrometry) project. Those improvements include the use of a picosecond laser to ablate actinide material into the source, a new 20-sample holder that can switch samples within 1–2 min, and a number of accelerator configuration improvements that allow quick and precise switching between species. In principle, AMS can provide production yields of actinide isotopes produced during the irradiation period at a sensitivity exceeding other mass spectrometry techniques. A total of 27 irradiated samples of a variety of actinides have been provided for measurement. We discuss our experience with these facility improvements and how well we have met our performance goals. In addition, we present preliminary results on a number of the irradiated actinide samples with this approach and compare those results to Multi-Collector ICPMS measurements.

Communication of the likelihood that a grant proposal is funded is important for individual researchers and academic institutions. For research project grants (RPGs) funded by the US National Institutes of Health (NIH), this is measured by the success rate, the fraction of grants reviewed in a given fiscal year that are funded. In 2016, I posted a relatively simple computational model that allowed estimation of these success rates from historical data of NIH appropriations and associated data, based largely on the fact that commitments to fund NIH grants are typically made over four fiscal years rather than coming from a single fiscal year’s appropriations. Data for appropriations and success rates for fiscal years 2016-2020 are now available, allowing this model to be tested without no adjustable parameters. Over this period, the NIH appropriation increased by 29.7% to $39.313 billion, yet the RPG success rate increased from 0.183 to 0.201, a relative increase of only 9.8%. This difference is accurately reproduced by the model, indicating that the modest changes in success rate despite large appropriation increases reflect the consequences of the funding grants from multiple fiscal years and the response of the biomedical research community in submitting an increased number of proposals. The model can also be extended to estimate the success rates for individual institutes with reasonable accuracy.

Background The literature supports the use of short-interval follow-up as an alternative to biopsy for lesions assessed as probably benign, Breast Imaging Reporting and Data System (BI-RADS) category 3, with an expected malignancy rate of less than 2%. Purpose To assess outcomes from 6-, 12-, and 24-month follow-up of probably benign findings first identified at recall from screening mammography in the National Mammography Database (NMD). Materials and Methods This retrospective study included women recalled from screening mammography with BI-RADS category 3 assessment at additional evaluation from January 2009 through March 2018 from 471 NMD facilities. Only the first BI-RADS category 3 occurrence for women aged 25 years or older with no personal history of breast cancer was analyzed, with biopsy or 2-year imaging follow-up. Cancer yield and positive predictive value of biopsies performed (PPV3) were determined at each follow-up. Results Among 45 202 women (median age, 55 years; range, 25-90 years) with a BI-RADS category 3 lesion, 1574 (3.5%) underwent biopsy at the time of lesion detection, yielding 72 cancers (cancer yield, 4.6%; 72 of 1574 women). For the remaining 43 628 women who accepted surveillance, 922 were seen within 90 days (with 78 lesions biopsied and 12 [15%] classified as malignant). The women still in surveillance (31 465 of 43 381 women [72.5%]) underwent follow-up mammography at 6 months. Of 3001 (9.5%) lesions biopsied, 456 (15.2%) were malignant (cancer yield, 1.5%; 456 of 31 465 women; 95% confidence interval [CI]: 1.3%, 1.6%). Among 18 748 of 25 997 women (72.1%) in surveillance who underwent follow-up at 12 months, 1219 (6.5%) underwent biopsy with 230 (18.9%) malignant lesions found (cancer yield, 1.2%; 230 of 18 748 women; 95% CI: 1.1%, 1.4%). Through 2-year follow-up, the biopsy rate was 11.2% (4894 of 43 628 women) with a cancer yield of 1.86% (810 malignancies found among 43 628 women; 95% CI: 1.73%, 1.98%) and a PPV3 of 16.6% (810 malignancies found among 4894 women). Conclusion In the National Mammography Database, Breast Imaging Reporting and Data System (BI-RADS) category 3 use is appropriate, with 1.86% cumulative cancer yield through 2-year follow-up. Of 810 malignancies, 468 (57.8%) were diagnosed at or before 6 months, validating necessity of short-interval follow-up of mammographic BI-RADS category 3 findings. © RSNA, 2020

I (G.J.Y.) was a graduate student the first time I met Dr. Salvatores in February 1994 in Cadarache, France. He was teaching a class (in French) on fast reactor physics. Among us was a bright Chinese student who had come to learn reactor physics the French way. The student’s French was a little less than perfect, so I was surprised when, at the end of the class, he raised his hand and asked Dr. Salvatores, “Are you really French?” Dr. Salvatores looked at him and replied with a smile, “Eh, non, je ne suis qu’un pauvre paysan italien!” (No, I’m only a poor Italian peasant!) The class had a good laugh. It did not take long for me to realize Dr. Salvatores was more than just a “pauvre paysan italien”. Massimo would later become my Ph.D. director, and we had many occasions to meet and share laughs around the world over the next 25 years. He was an outstanding scientist, mentor, and bon vivant. He was a model and an inspiration for several generations of French nuclear reactor physicists involved in the development of fast reactors and advanced fuel cycles. Dr. Salvatores initiated the integral experiment that is the subject of this article.

Donald A. B. Lindberg, influential director of the United States National Library of Medicine (NLM) and unsung hero of medical research and science, died on 17 August. He was 85. Thanks to his vision and leadership, more than a million people a day can use PubMed to look up biomedical information and nearly 150,000 people a day can look up trials on [ClinicalTrials.gov][1]. Researchers in artificial intelligence, computational biology, and health care policy routinely use the mapping between hundreds of different biomedical vocabularies and ontologies provided by the NLM's Unified Medical Language System. Many of the current leaders in biomedical computing have been trained by programs funded by the NLM, which Don directed from 1984 to 2015, starting well before big data, precision and genomic medicine, or deep learning for medicine were even recognizable terms, let alone vibrant disciplines of their own. Don grew up in Brooklyn, New York. He became passionately interested in human biology at Amherst College in Massachusetts. After graduating in 1954 with a bachelor's degree in biology, he considered going to graduate school. Persuaded that medical training would provide more opportunities, he enrolled instead at Columbia University's College of Physicians and Surgeons in New York. It was a very good school, Don acknowledged, but “very far from the study of human biology” and “a high-class trade school at best.” Although the medical school experience was “thrilling,” the large amount of required memorization was “almost antithetical to experimental science.” After graduation in 1958 and a residency in pathology, Don served on the faculty of the University of Missouri for 24 years. In 1984, he left to direct the NLM. Early on, Don recognized that medicine needed to be more data driven. During his residency training, his data-driven approach to medicine landed him in hot water with the surgery department when he showed that silicon used for cardiac bypass was causing extensive embolization and death. Only upon showing the surgeons the imaging data was he able to change their practice. This pattern was to be repeated throughout his career. At NLM, he used data to convince members of the U.S. Congress and influential commercial stakeholders to better serve the public interest by, for example, requiring prior registration of expected outcomes for clinical trials. Don was a pioneer in medical computing. In the 1960s, he developed some of the earliest laboratory information systems, consisting of a punch card–fed clinical reporting program running on a Datatron-205 computer with 20 KB of memory. Twenty years later, he led the development of Artificial Intelligence Rheumatology Consultant System Ontology, an AI program that could diagnose complex cases of rheumatological disease. ![][2] PHOTO: JESSICA MARCOTTE One key to Don's success was his ability to attract top talent to lead NLM initiatives and implement his vision, including computational biologist David Lipman, biomedical informaticist Alexa McCray, medical librarian Betsy Humphreys, and health informaticist Milton Corn. Don helped lead initiatives that spanned the mission of the National Institutes of Health. He delegated many program responsibilities to his NLM colleagues and could seem detached. However, he was deeply knowledgeable about the programs he oversaw and preferred to lead by helping to set the agenda and then empowering his colleagues to work out the implementation details themselves, making himself available for guidance when needed. He had a dry sense of humor and used it to lighten what are often dry subjects, as when he named an early NLM resource Grateful Med. Don surrounded himself with expert advisers, such as Nobel laureates in Physiology or Medicine Richard Roberts and Joshua Lederberg, who understood the importance of computing to biomedical investigation and helped him develop long-term strategic plans for the NLM. Don's rare combination of strong scientific vision and leadership skills allowed him to work well both on Capitol Hill and across U.S. universities and academic health centers. Because he could bring parties with opposing perspectives together to develop a shared view of the public good in the applications of information technology, he was frequently in demand for leadership challenges that extended beyond the remit of the NLM. From 1992 to 1995, he served as founding director of the National Coordination Office for High Performance Computing and Communications in the Office of Science and Technology Policy, Executive Office of the President. In 1996, the Health and Human Services Secretary appointed him to serve as the U.S. coordinator for the G7 Global Health Applications Project. He was also a founding member of the American Medical Informatics Association and its first president. Those who run libraries are frequently underappreciated, as many take for granted the important and far-reaching services that they provide to their communities. Even with all of his accomplishments, this was true for Don in many circles outside the informatics community. Many forget how different the research world was before resources such as PubMed were commonplace. These advances have been driven by technological developments, most notably the internet, but Don's vision predated them. Much of the difficult foundational work and a corps of well-trained and engaged scientists and physicians were already in place when the technological capabilities came to be. Don found the recent (re)discovery of the importance of data science in science and medicine somewhat amusing. Don's wife of more than 60 years, Mary, became well known to those of us who worked with the NLM. Ever since their second date in 1957, when they started planning their life together, Don and Mary embodied joint decision-making. She survives him, along with his brother, two sons, and two grandchildren. Don's work lives on with millions of patients, doctors, and scientists who depend on access to and investigations of the exponentially growing corpus of biomedical knowledge. [1]: http://ClinicalTrials.gov [2]: /embed/graphic-1.gif

BRK phosphorylates and targets SMAD4 for proteasomal degradation to regulate aspects of the epithelial-mesenchymal transition., The tumor-suppressing function of SMAD4 is frequently subverted during mammary tumorigenesis, leading to cancer growth, invasion, and metastasis. A long-standing concept is that SMAD4 is not regulated by phosphorylation but ubiquitination. Our search for signaling pathways regulated by breast tumor kinase (BRK), a nonreceptor protein tyrosine kinase that is up-regulated in ~80% of invasive ductal breast tumors, led us to find that BRK competitively binds and phosphorylates SMAD4 and regulates transforming growth factor–β/SMAD4 signaling pathway. A constitutively active BRK (BRK-Y447F) phosphorylates SMAD4, resulting in its recognition by the ubiquitin-proteasome system, which accelerates SMAD4 degradation. Activated BRK–mediated degradation of SMAD4 is associated with the repression of tumor suppressor gene FRK and increased expression of mesenchymal markers, SNAIL, and SLUG. Thus, our data suggest that combination therapies targeting activated BRK signaling may have synergized the benefits in the treatment of SMAD4 repressed cancers.

[][1] CREDIT: TERRY CLARK A bipartisan proposal to modify restraints in patent law was debated before the United States Senate Judiciary Committee this month. Immediately following the third hearing last week, leading scientists called for a study of the relevant issues by the U.S. National Academies of Sciences, Engineering, and Medicine, prior to the draft legislation moving forward ([www.patenteligibility.com][2]). This study should be initiated soon, with a short timeline, to ensure that appropriate information and analysis can inform the legislative processes that will substantially affect how the benefits of science and innovation are delivered to society. ![][3] CREDIT: BORTONIA, ADAPTED BY M. ATAROD/ SCIENCE Patents balance providing incentives to take the financial risks necessary to convert an invention into useful products with the benefits of sharing information to drive other useful inventions. Since the advent of DNA sequencing and gene identification methods, patenting human genes has been controversial. A notable example involves patents for the genes BRCA1 and BRCA2 , variations in which modulate risks for breast and ovarian cancer. These patents supported increased costs and hence, limited accessibility, for diagnostic tests for cancer patients and their families. In 2013, the U.S. Supreme Court ruled that these patents were invalid ( Association for Molecular Pathology v. Myriad Genetics ). The Myriad decision shifted the landscape not only for gene patents but also for patents on other “products of nature.” The current bill is directed toward clarifying the concepts and language underlying the issues involved in patenting products of nature. It is essential that these issues be examined thoroughly and thoughtfully prior to enshrining language in law that could easily have unintended consequences. To avoid overly restricting research, there are certain exclusions from patentability, namely for abstract ideas, natural laws, and products of nature. However, for products of nature, exceptions have been made for identifying and isolating substances whose properties differ substantially from the source from which they were obtained. For more than a century, natural products, such as adrenaline, have been deemed patentable in their purified forms because of the enhancement of their activities through purification. Natural products have been quite important as drugs or in driving drug discovery, such as the immunosuppressive compounds cyclosporine and tacrolimus (FK506), which enabled solid organ transplantation. Isolation of natural substances also enables “composition of matter” patents. These are valuable because they cover the material regardless of its use or the processes in which they are components. The Myriad patents involved the composition of matter of the BRCA1/2 genes. The Supreme Court ruled that these substances were not eligible as exceptions from the product of nature exclusion because isolation of the BRCA genes from their chromosomal environment did not transform their character sufficiently. Moreover, the item of value was information in the gene sequences rather than the materials themselves. However, the language in the Court opinions was subject to different interpretations. Some have interpreted them as applying only to the patenting of genes, whereas others suggested that they change the scope of natural products that can be patented. Because of the great importance of these somewhat esoteric issues for facilitating the generation of new diagnostics and drugs and for advancing basic research, it is crucial that appropriate steps be taken to guide modification of existing patent law. At this point, case law based on particular court rulings is controlling the evolution of these patent rulings. However, a more intentional approach implemented through legislation has the potential to address these issues in a more comprehensive manner. This task should be informed by a thorough process that the National Academies can effectuate—bringing together stakeholders including academic scientists, industry leaders, patent experts, and patient advocates. Striking the right balance with language that clearly conveys the intended interpretations should strengthen patent protection, bolster science, and improve societal well-being. [1]: /embed/graphic-1.gif [2]: http://www.patenteligibility.com [3]: /embed/graphic-2.gif

Personal genomics is enjoying increased visibility, yet much remains cloudy about its true potential. We see advertisements from direct-to-consumer companies and media coverage of scientific studies reporting new genomic associations with a range of traits. With this deluge of information, individuals need to become educated consumers to judge how valid these associations are, particularly if individuals are inclined to change their actions based on the results. > “Genomic information has great potential to enrich our lives…” Some traits, such as adult height, are readily measured. The heritability of this trait is ∼60 to 80%. Attempts to characterize “height genes” have resulted in the identification of tens of thousands of genes, each of which contributes a small amount to this heritability. The plethora of factors is almost inevitable, given the vast number of cellular and physiological steps involved in the development of an adult human being. A model that accounts for ∼40% of height variability predicts individual heights to within 4 cm for 50% of people, but with errors of more than 10 cm for 5%. Thus, a sophisticated genomic analysis can predict height to some extent, but not well enough for use in ordering tailored clothing. Most direct-to-consumer genomic results are based on much less detailed analyses and many involve complex traits, so considerable skepticism is appropriate. Caution, however, should not dampen optimism for all aspects of this field. An area with exciting recent progress involves genomics as it relates to differences between people in the efficacy or dosing of particular drugs, a field known as pharmacogenomics. The U.S. Food and Drug Administration now includes pharmacogenomic information in the product labeling for more than 200 drugs, but use of this information in clinical practice remains limited. One example is clopidogrel (Plavix), a drug that prevents blood clotting to decrease the risk for heart attack and stroke. The compound present in clopidogrel pills does not, itself, have activity but is converted to an active form by an enzyme called cytochrome P450 2C19 (CYP2C19). Approximately 30% of individuals have one or two copies of a version of the gene encoding CYP2C19 that produces little to no active enzyme, meaning that clopidogrel may not be effectively activated. A pragmatic, multicenter clinical trial was conducted involving patients receiving cardiac stents who were offered a genotype-based prescription of either clopidogrel or related drugs that do not require CYP2C19 for activation. Those with a genotype suggesting inefficient clopidogrel activation who were treated with alternative drugs were significantly less likely to suffer major adverse cardiovascular events than those treated with clopidogrel. With alternative therapy in these patients, outcomes were similar to those of patients without the at-risk genotype who were treated with clopidogrel. These results illustrate the importance of thoughtful studies that help move compelling visions for pharmacogenomics into reality. A major challenge at present is that genotyping is required as an extra step, introducing costs and logistical issues. However, it is easy to envision a future where one-time genomic tests covering the few hundred genes that are associated with commonly used drugs are available to physicians, pharmacists, or consumers, to inform drug-use decisions in real time. A consumer of genomic information should question the data supporting the interpretation of genome–trait association tests. Some traits given in direct-to-consumer reports such as “lactose intolerance” involve genes with known biological mechanisms and well-characterized variants that largely determine outcomes. Other traits such as “wake-up time” involve models with hundreds of genes with no known mechanism, clear importance of nongenomic factors, and poor predictive value. In addition, many direct-to-consumer tests report only common variants of genes such as BRCA1 , potentially giving individuals a false sense of security. Ancestry results can be relatively robust because they involve the segregation of many genetic markers and do not require biological mechanisms. Genomic information has great potential to enrich our lives, but a critical eye is required to avoid overinterpretation and, potentially, inappropriate actions.

Traumatic brain injury (TBI) results in systemic inflammatory responses that affect the lung. This is especially critical in the setting of lung transplantation, where more than half of donor allografts are obtained postmortem from individuals with TBI. The mechanism by which TBI causes pulmonary dysfunction remains unclear but may involve the interaction of high-mobility group box-1 (HMGB1) protein with the receptor for advanced glycation end products (RAGE). To investigate the role of HMGB1 and RAGE in TBI-induced lung dysfunction, RAGE-sufficient (wild-type) or RAGE-deficient (RAGE(-/-)) C57BL/6 mice were subjected to TBI through controlled cortical impact and studied for cardiopulmonary injury. Compared to control animals, TBI induced systemic hypoxia, acute lung injury, pulmonary neutrophilia, and decreased compliance (a measure of the lungs' ability to expand), all of which were attenuated in RAGE(-/-) mice. Neutralizing systemic HMGB1 induced by TBI reversed hypoxia and improved lung compliance. Compared to wild-type donors, lungs from RAGE(-/-) TBI donors did not develop acute lung injury after transplantation. In a study of clinical transplantation, elevated systemic HMGB1 in donors correlated with impaired systemic oxygenation of the donor lung before transplantation and predicted impaired oxygenation after transplantation. These data suggest that the HMGB1-RAGE axis plays a role in the mechanism by which TBI induces lung dysfunction and that targeting this pathway before transplant may improve recipient outcomes after lung transplantation.

We have heard from readers with concerns about the publication of the Letter “Harassment charges: Injustice done?” (A. Moya et al. , 17 August, p. [655][1]). At Science , we take harassment issues very seriously. We are working to develop policies that adhere to our editorial principle of airing a wide range of perspectives and that also prevent causing further harm to the targets of harassment. Publication of a Letter does not represent an endorsement by the editorial staff at Science . Past practice has been based on the understanding that reader-submitted Letters are intended to reflect conversations taking place in the scientific community. The published Letter in question did that by raising concerns about the transparency of the investigatory process. This point touched on the challenges institutions face when determining how the processes and outcomes of harassment investigations should be shared, decisions that must weigh the benefits of transparency against important privacy concerns. However, the Letter also discussed the personal conduct and scientific accomplishments of the individual found guilty of harassment. In the future, we will not publish Letters in which authors argue that an individual accused or found guilty of harassment is likely innocent because others have interacted with that person without incident; this argument is logically flawed. In addition, although some information about a person's scientific achievements is at times necessary to establish context, we will not publish Letters in which authors argue that professional achievements have any bearing at all on the likelihood that the individual engaged in harassment. Such arguments not only lack relevance to harassment behavior but also may result in further harm to the targets of harassment and exacerbate the already daunting process that targets face in coming forward publicly. We are striving to increase our understanding of all facets of the issue of harassment and to review and modify our editorial processes accordingly. [1]: http://www.sciencemag.org/content/361/6403/655.3

Our planet is in a perilous state. The combined effects of climate change, pollution, and loss of biodiversity are putting our health and well-being at risk. Given that human actions are largely responsible for these global problems, humanity must now nudge Earth onto a trajectory toward a more stable, harmonious state. Many of the challenges are daunting, but solutions can be found. In this issue of Science , we launch a series of monthly articles that call attention to some of the choices we can still make for shaping tomorrow's Earth—commentaries and analyses that will hopefully provoke us to making thoughtful choices (see [scim.ag/TomorrowsEarth][1]). Many of today's challenges can be traced back to the[“Tragedy of the Commons”][2] identified by Garrett Hardin in his landmark essay, published in Science 50 years ago. Hardin warned of a coming population–resource collision based on individual self-interested actions adversely affecting the common good. In 1968, the global population was about 3.5 billion; since then, the human population has more than doubled, a rise that has been accompanied by large-scale changes in land use, resource consumption, waste generation, and societal structures. Science 's “State of the Planet” articles (published between 2003 and 2008; see [scim.ag/StateofthePlanet][3]) articulated the stresses and possible solutions to these growing human-induced impacts on the Earth system. Donald Kennedy, then Science 's Editor-in-Chief, aptly asserted: “The big question in the end is not whether science can help. Plainly it could. Rather, it is whether scientific evidence can successfully overcome social, economic, and political resistance.” Through collective action, we can indeed achieve planetary-scale mitigation of harm. A case in point is the Montreal Protocol on Substances that Deplete the Ozone Layer, the first treaty to achieve universal ratification by all countries in the world. In the 1970s, scientists had shown that chemicals used as refrigerants and propellants for aerosol cans could catalyze the destruction of ozone. Less than a decade later, these concerns were exacerbated by the discovery of seasonal ozone depletion over Antarctica. International discussions on controlling the use of these chemicals culminated in the Montreal Protocol in 1987. Three decades later, research has shown that ozone depletion appears to be decreasing in response to industrial and domestic reforms that the regulations facilitated. More recent efforts include the Paris Agreement of 2015, which aims to keep a global temperature rise this century well below 2°C and to strengthen the ability of countries to deal with the impacts of climate change, and the United Nations Sustainable Development Goals. As these examples show, there is widespread recognition that we must reverse damaging planetary change for the sake of the next generation. However, technology alone will not rescue us. For changes to be willingly adopted by a majority of people, technology and engineering will have to be integrated with social sciences and psychology. In this special series, we aim to raise some of the issues that we face, from food security to land-use changes and from health equality to synthetic chemical pollution. We start with some of our most basic needs: energy, materials, chemicals, and food. Although human population growth is escalating, we have never been so affluent. Along with affluence comes increasing use of energy and materials, which puts more pressure on the environment. How can humanity maintain high living standards without jeopardizing the basis of our survival? As our “Tomorrow's Earth” series (see [scim.ag/TomorrowsEarth][1]) will highlight, rapid research and technology developments across the sciences can help to facilitate the implementation of potentially corrective options. There will always be varying expert opinions on what to do and how to do it. But as long as there are options, we can hope to find the right paths forward. Read more articles online at [scim.ag/TomorrowsEarth][1] [1]: http://scim.ag/TomorrowsEarth [2]: http://science.sciencemag.org/content/162/3859/1243.full [3]: http://scim.ag/StateofthePlanet

We are writing in response to a proposed rule announced by the Environmental Protection Agency (EPA) in a 24 April 2018 press release (1). The release reads, “The rule will ensure that the regulatory science underlying Agency actions is fully transparent, and that underlying scientific information is publicly available in a manner sufficient for independent validation.” Data sharing is a feature that contributes to the robustness of published scientific results. Many peer-reviewed … [↵][1]1To whom correspondence should be addressed. Email: jberg{at}aaas.org. [1]: #xref-corresp-1-1

Die Lipiddoppelschicht biologischer Membranen ist von sich aus fur Ionen und polare Molekule impermeabel. Eine gewisse Durchlassigkeit fur diese Molekularten ist jedoch fur die normale Zellfunktion unerlasslich. Diese Durchlassigkeit wird von drei Klassen von Membranproteinen vermittelt: Pumpen, Carrier und Kanale. Pumpen greifen auf Quellen freier Enthalpie wie beispielsweise ATP-Hydrolyse oder Lichtabsorption zuruck, um den Transport von Ionen oder Molekulen thermodynamisch bergauf anzutreiben. Hierbei handelt es sich um ein Beispiel fur aktiven Transport. Carrier bewirken dagegen den Transport von Ionen und kleinen Molekulen durch die Membran ohne den Verbrauch von ATP. Kanale bilden dagegen eine Pore in der Membran, durch die Ionen in einer thermodynamisch begunstigten Richtung stromen. Der Mechanismus von Kanalen ist ein Beispiel fur den passiven Transport oder die erleichterte Diffusion.

Wie Angehorige einer Menschenfamilie verfugen auch die Angehorigen einer Molekulfamilie uber viele gemeinsame Merkmale. Solche Familienahnlichkeiten lassen sich am einfachsten auffinden, indem man die dreidimensionale Molekulstruktur untersucht, jene Eigenschaft, die am engsten mit der Funktion des Molekuls korreliert ist. Man denke beispielsweise an die Ribonuclease aus Rindern, die wir bei unseren Erlauterungen zur Faltung von Proteinen vorgestellt haben (Abschnitt 2.6). Strukturvergleiche haben gezeigt, dass sich die dreidimensionale Struktur dieses Proteins von der einer menschlichen Ribonuclease nur unwesentlich unterscheidet. Obwohl in diesem Fall die ausere Ahnlichkeit nicht allzu sehr uberrascht, wenn man bedenkt, wie ahnlich diese Enzyme ihrer Funktion nach sind, so konnen solche Vergleiche gelegentlich grose Uberraschungen mit sich bringen. Beim Angiogenin beispielsweise, einem Protein, das das Wachstum neuer Blutgefase anregt, ergab der Strukturvergleich eine grose Ahnlichkeit mit den Ribonucleasen – eine so grose Ahnlichkeit, dass man davon ausgehen muss, dass beide derselben Proteinfamilie angehoren.

Durch die Verdauung von Proteinen aus der Nahrung im Darm und den Proteinabbau innerhalb der Zellen werden den Zellen fortwahrend Aminosauren zugefuhrt. Viele zellulare Proteine werden standig abgebaut und neu synthetisiert, andere wurden falsch gefaltet oder geschadigt und mussen ebenfalls abgebaut werden. Nicht benotigte oder defekte Proteine werden fur den Abbau markiert, indem sich Ketten des kleinen Proteins Ubiquitin kovalent an sie binden; anschliesend werden sie durch einen grosen ATP-abhangigen Komplex, das sogenannte Proteasom, abgebaut. Verwendung finden die Aminosauren aus Proteinabbau und -verdauung in erster Linie als Bausteine fur die Synthese von Proteinen und anderen Stickstoffverbindungen wie Nucleotidbasen.

Die DNA speichert genetische Information in einer stabilen Form, die leicht zu replizieren ist. Die Expression dieser genetischen Information macht es jedoch notwendig, dass sie von der DNA uber die RNA normalerweise zum Protein fliest, wie in Kapitel 4 einfuhrend beschrieben wird. Das hier folgende Kapitel behandelt die RNA-Synthese oder Transkription. Dabei wird ein RNA-Transkript synthetisiert und die Sequenzinformation von der DNA-Matrize ubertragen. Zu Beginn wollen wir uns mit RNA-Polymerasen beschaftigen. Das sind grose und komplexe Enzyme, die den Syntheseprozess durchfuhren. Dann wenden wir uns der Transkription bei Bakterien zu und betrachten die drei Phasen der Transkription: Promotorbindung und Initiation, Verlangerung (Elongation) des entstehenden RNA-Transkripts sowie die Termination. Anschliesend befassen wir uns mit der Transkription bei Eukaryoten und mit den Unterschieden zwischen prokaryotischer und eukaryotischer Transkription.