Organocatalytic sulfoxidation

Treatment of a sulfide with a catalytic amount of a 1,3 diketone in the presence of silica sulfuric acid as a co-catalyst and hydrogen peroxide (50% aq) as the stoichiometric oxidant leads to the corresponding sulfoxide product. The reaction is effective for diaryl, aryl-alkyl and dialkyl sulfides and is tolerant of oxidisable and acid sensitive functional groups. Investigations have shown that the tris-peroxide 2, formed on reaction of pentane-2,4-dione with hydrogen peroxide under acidic reaction conditions, can oxidise two equivalents of sulfide using the exocyclic peroxide groups whereas the endocyclic peroxide remains intact. Calculations provide a mechanism consistent with experimental observations and suggest the reaction proceeds via an initial acid catalysed ring opening of a protonated tris-peroxide prior to oxygen transfer to a sulfur nucleophile

On scientific understanding with artificial intelligence

Imagine an oracle that correctly predicts the outcome of every particle physics experiment, the products of every chemical reaction, or the function of every protein. Such an oracle would revolutionize science and technology as we know them. However, as scientists, we would not be satisfied with the oracle itself. We want more. We want to comprehend how the oracle conceived these predictions. This feat, denoted as scientific understanding, has frequently been recognized as the essential aim of science. Now, the ever-growing power of computers and artificial intelligence poses one ultimate question: How can advanced artificial systems contribute to scientific understanding or achieve it autonomously? We are convinced that this is not a mere technical question but lies at the core of science. Therefore, here we set out to answer where we are and where we can go from here. We first seek advice from the philosophy of science to understand scientific understanding. Then we review the current state of the art, both from literature and by collecting dozens of anecdotes from scientists about how they acquired new conceptual understanding with the help of computers. Those combined insights help us to define three dimensions of android-assisted scientific understanding: The android as a I) computational microscope, II) resource of inspiration and the ultimate, not yet existent III) agent of understanding. For each dimension, we explain new avenues to push beyond the status quo and unleash the full power of artificial intelligence's contribution to the central aim of science. We hope our perspective inspires and focuses research towards androids that get new scientific understanding and ultimately bring us closer to true artificial scientists.Comment: 13 pages, 3 figures, comments welcome

Stalling chromophore synthesis of the fluorescent protein Venus reveals the molecular basis of the final oxidation step

Fluorescent proteins (FPs) have revolutionised the life sciences, but the mechanism of chromophore maturation is still not fully understood. Here we show that incorporation of a photo-responsive non-canonical amino acid within the chromophore stalls maturation of Venus, a yellow FP, at an intermediate stage; a crystal structure indicates the presence of O2 located above a dehydrated enolate form of the imidazolone (I) ring, close to the strictly conserved Gly67 that occupies a twisted conformation. His148 adopts an “open” conformation so forming a channel that allows O2 access to the immature chromophore. Absorption spectroscopy supported by QM/MM simulations suggest that the first oxidation step involves formation of a hydroperoxyl intermediate in conjunction with dehydrogenation of the methylene bridge. A fully conjugated mature chromophore is formed through release of H2O2 on, both in vitro and in vivo. The possibility of interrupting and photochemically restarting chromophore maturation, and the mechanistic insights opens up new approaches for engineering optically controlled fluorescent proteins

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Navigating through the Maze of Homogeneous Catalyst Design with Machine Learning

The ability to forge difficult chemical bonds through catalysis has transformed society on all fronts, from feeding our ever-growing populations to increasing our life-expectancies through the synthesis of new drugs. However, developing new chemical reactions and catalytic systems is a tedious task that requires tremendous discovery and optimization efforts. Over the past decade, advances in machine learning have revolutionized a whole new way to approach data- intensive problems, and many of these developments have started to enter chemistry. However, similar progress in the field of homogenous catalysis are only in their infancy. In this article, we want to outline our vision for the future of catalyst design and the role of machine learning to navigate this maze.</div

Drawing Catalytic Power from Charge Separation: Stereoelectronic and Zwitterionic Assistance in the Au(I)-Catalyzed Bergman Cyclization

The synergy between bond formation and bond breaking that is typical for pericyclic reactions is lost in their mechanistic cousins, cycloaromatization reactions. In these reactions, exemplified by the Bergman cyclization (BC), two bonds are sacrificed to form a single bond, and the reaction progress is interrupted at the stage of a cyclic diradical intermediate. The catalytic power of Au­(I) in BC stems from a combination of two sources: stereoelectronic assistance of C–C bond formation (i.e., “LUMO umpolung”) and crossover from a diradical to a zwitterionic mechanism that takes advantage of the catalyst’s dual ability to stabilize both negative and positive charges. Not only does the synergy between the bond-forming and charge-delocalizing interactions lead to a dramatic (>hundred-billion-fold) acceleration, but the evolution of the two effects results in continuous reinforcement of the substrate/catalyst interaction along the cyclization path. This cooperativity converts the BC into the first example of an aborted [3,3] sigmatropic shift where the pericyclic “transition state” becomes the most stable species on the reaction hypersurface. Aborting the pericyclic path facilitates trapping of cyclic intermediate by a variety of further reactions and provides a foundation for the discovery of new modes of reactivity of polyunsaturated substrates. The application of distortion/interaction analysis allows us to quantify the increased affinity of Au-catalysts to the Bergman cyclization transition state as one of the key components of the large catalytic effect

Isonitriles as Stereoelectronic Chameleons: The Donor-Acceptor Dichotomy in Radical Additions

This study started from a simple question of why isonitriles and alkynes (the two functional groups that look so much alike in their ground states) provide drastically different type of products in addition reactions. Whereas addition to alkynes proceeds in a “1,2-addition” where the new bonds are formed at the different alkyne carbons, isonitriles can react via “1,1-insertion” by forming both new bonds at the same terminal carbon of the isonitrile moiety. Such outcome is consistent with the hidden carbene nature of the isonitrile functionality. Due to the ability of serving as 1,1-synthons, isonitriles lend themselves to a variety of annulations where they serve as a one-carbon component in assembly of carbo- or heterocycles (e.g., [4+1] annulations pioneered by Curran) or, with a change of reactant topology, as two-atom components in the assembly of heterocycles. Our hypothesis was this behavior should be associated wtih additional state-crossings that corresponds to intramolecular charge and spin-transfer between nitrogen and carbon. Understanding of such dynamic state interconversion may unlock new electronic effects, not available to alkynes. From the practical perspective, such conceptual understanding can lead to the design of more efficient radical cascades.Indeed, computational analysis of isonitrile\u27s interaction with alkyl, aryl, heteroatom-substituted and heteroatom-centered radicals found a number of intriguing electronic, supramolecular and conformational effects. In general, the evolution of electronic changes in the process of radical addition to isonitriles reveals that this reaction starts and continues all the way to the TS mostly as a simple addition to a polarized pi-bond. Only at the later stages, after the TS has been passed, intramolecular electron transfer from the lone pair of carbon to the nitrogen moves the spin density to the a-carbon to form the imidoyl radical, the hallmark intermediate of the 1,1-addition-mediated cascades. Computational Details:Calculations were carried with the Gaussian 09 software package, using the (U)M06-2X DFT functional (with an ultrafine integration grid of 99,590 points) with the 6-311++G(d,p) basis set for all atoms except of Sn and Ge, for which we have used the Def2-QZVPP basis set. Grimme’s D3 version (zero damping)for empirical dispersion was also included. Frequency calculations were conducted for all structures to confirm them as either a minimum or a Transition State (TS). Intrinsic Reaction Coordinates (IRC) were determined for the TS of interest. Barriers were evaluated from isolated species due to formation of complexes for some systems, but not all of them. We performed Natural Bond Orbital (NBO) analysis on key intermediates and transition states. NBO deletions were performed at the UHF/6-311G(d) level of theory unless otherwise noted. Spin density was evaluated from the NBO analysis data. The Gibbs Free energy values are reported at 298 K, unless noted otherwise. We have used GoodVibes by Funes-Ardoiz and Paton to obtain the temperature-corrected Gibbs Free energies for calculating the temperature effects on selectivity in multifunctional substrates.</div