Double Strain-Release [2π+2σ]-Photocycloaddition.

In pursuit of potent pharmaceutical candidates and to further improve their chemical traits, small ring systems can serve as a potential starting point. Small ring units have the additional merit of loaded strain at their core, making them suitable reactants as they can capitalize on this intrinsic driving force. With the introduction of cyclobutenone as a strained precursor to ketene, the photocycloaddition with another strained unit, bicyclo[1.1.0]butane (BCB), enables the reactivity of both π-units in the transient ketene. This double strain-release driven [2π+2σ]-photocycloaddition promotes the synthesis of diverse heterobicyclo[2.1.1]hexane units, a pharmaceutically relevant bioisostere. The effective reactivity under catalyst-free conditions with a high functional group tolerance defines its synthetic utility. Experimental mechanistic studies and density functional theory (DFT) calculations suggest that the [2π+2σ]-photocycloaddition takes place via a triplet mechanism.

Dearomative ring expansion of thiophenes by bicyclobutane insertion.

Skeletal ring enlargement is gaining renewed interest in synthetic chemistry and has recently focused on insertion of one or two atoms. Strategies for heterocyclic expansion through small-ring insertion remain elusive, although they would lead to the efficient formation of bicyclic products. Here, we report a photoinduced dearomative ring enlargement of thiophenes by insertion of bicyclo[1.1.0]butanes to produce eight-membered bicyclic rings under mild conditions. The synthetic value, broad functional-group compatibility, and excellent chemo- and regioselectivity were demonstrated by scope evaluation and product derivatization. Experimental and computational studies point toward a photoredox-induced radical pathway.

Catalytic Asymmetric Hydrogen Atom Transfer: Enantioselective Hydroamination of Alkenes.

We report a highly enantioselective radical-based hydroamination of enol esters with sulfonamides jointly catalyzed by an Ir photocatalyst, Brønsted base, and tetrapeptide thiol. This method is demonstrated for the formation of 23 protected ß-amino-alcohol products, achieving selectivities up to 97:3 er. The stereochemistry of the product is set through selective hydrogen atom transfer from the chiral thiol catalyst to a prochiral C-centered radical. Structure-selectivity relationships derived from structural variation of both the peptide catalyst and olefin substrate provide key insights into the development of an optimal catalyst. Experimental and computational mechanistic studies indicate that hydrogen-bonding, π-π stacking, and London dispersion interactions are contributing factors for substrate recognition and enantioinduction. These findings further the development of radical-based asymmetric catalysis and contribute to the understanding of the noncovalent interactions relevant to such transformations.

Intramolecular Hydrogen Bonding Enables a Zwitterionic Mechanism for Macrocyclic Peptide Formation: Computational Mechanistic Studies of CyClick Chemistry.

Macrocyclic peptides have become increasingly important in the pharmaceutical industry. We present a detailed computational investigation of the reaction mechanism of the recently developed "CyClick" chemistry to selectively form imidazolidinone cyclic peptides from linear peptide aldehydes, without using catalysts or directing groups (Angew. Chem. Int. Ed. 2019, 58, 19073-19080). We conducted computational mechanistic to investigate the effects of intramolecular hydrogen bonds (IMHBs) in promoting a kinetically facile zwitterionic mechanism in "CyClick" of pentapeptide aldehyde AFGPA. Our DFT calculations highlighted the importance of IMHB in pre-organization of the resting state, stabilization of the zwitterion intermediate, and the control of the product stereoselectivity. Furthermore, we have also identified that the low ring strain energy promotes the "CyClick" of hexapeptide aldehyde AAGPFA to form a thermodynamically more stable 15+5 imidazolidinone cyclic peptide product. In contrast, large ring strain energy suppresses "CyClick" reactivity of tetra peptide aldehyde AFPA from forming the 9+5 imidazolidinone cyclic peptide product.

ortho-Selective Dearomative [2π + 2σ] Photocycloadditions of Bicyclic Aza-Arenes.

Dearomative photocycloadditions are valuable chemical transformations, serving as an efficient platform to create three-dimensional molecular complexity. However, the photolability of the original addition product especially within the context of ortho cycloadditions often causes undesired consecutive rearrangements, rendering these ortho cycloadducts elusive. Herein, we report an ortho-selective intermolecular photocycloaddition of bicyclic aza-arenes including (iso)quinolines, quinazolines, and quinoxalines by utilizing a strain-release approach. With bicyclo[1.1.0]butanes as coupling partners, this dearomative [2π + 2σ] cycloaddition enables the straightforward construction of C(sp3)-rich bicyclo[2.1.1]hexanes directly connected to N-heteroarenes. Photophysical experiments and DFT calculations revealed the origin of the [2π + 2σ] selectivity and indicate that, in addition to the originally proposed energy transfer or direct excitation pathways, a chain reaction mechanism is operative depending on the reaction conditions.

Initiation of fatty acid biosynthesis in Pseudomonas putida KT2440.

Deciphering the mechanisms of bacterial fatty acid biosynthesis is crucial for both the engineering of bacterial hosts to produce fatty acid-derived molecules and the development of new antibiotics. However, gaps in our understanding of the initiation of fatty acid biosynthesis remain. Here, we demonstrate that the industrially relevant microbe Pseudomonas putida KT2440 contains three distinct pathways to initiate fatty acid biosynthesis. The first two routes employ conventional ß-ketoacyl-ACP synthase III enzymes, FabH1 and FabH2, that accept short- and medium-chain-length acyl-CoAs, respectively. The third route utilizes a malonyl-ACP decarboxylase enzyme, MadB. A combination of exhaustive in vivo alanine-scanning mutagenesis, in vitro biochemical characterization, X-ray crystallography, and computational modeling elucidate the presumptive mechanism of malonyl-ACP decarboxylation via MadB. Given that functional homologs of MadB are widespread throughout domain Bacteria, this ubiquitous alternative fatty acid initiation pathway provides new opportunities to target a range of biotechnology and biomedical applications.

A new machine learning algorithm with high interpretability for improving the safety and efficiency of thrombolysis for stroke patients: A hospital-based pilot study.

Background: Thrombolysis is the first-line treatment for patients with acute ischemic stroke. Previous studies leveraged machine learning to assist neurologists in selecting patients who could benefit the most from thrombolysis. However, when designing the algorithm, most of the previous algorithms traded interpretability for predictive power, making the algorithms hard to be trusted by neurologists and be used in real clinical practice. Methods: Our proposed algorithm is an advanced version of classical k-nearest neighbors classification algorithm (KNN). We achieved high interpretability by changing the isotropy in feature space of classical KNN. We leveraged a cohort of 189 patients to prove that our algorithm maintains the interpretability of previous models while in the meantime improving the predictive power when compared with the existing algorithms. The predictive powers of models were assessed by area under the receiver operating characteristic curve (AUC). Results: In terms of interpretability, only onset time, diabetes, and baseline National Institutes of Health Stroke Scale (NIHSS) were statistically significant and their contributions to the final prediction were forced to be proportional to their feature importance values by the rescaling formula we defined. In terms of predictive power, our advanced KNN (AUC 0.88) outperformed the classical KNN (AUC 0.75, p = 0.0192 ). Conclusions: Our preliminary results show that the advanced KNN achieved high AUC and identified consistent significant clinical features as previous clinical trials/observational studies did. This model shows the potential to assist in thrombolysis patient selection for improving the successful rate of thrombolysis.

The feasibility and accuracy of machine learning in improving safety and efficiency of thrombolysis for patients with stroke: Literature review and proposed improvements.

In the treatment of ischemic stroke, timely and efficient recanalization of occluded brain arteries can successfully salvage the ischemic brain. Thrombolysis is the first-line treatment for ischemic stroke. Machine learning models have the potential to select patients who could benefit the most from thrombolysis. In this study, we identified 29 related previous machine learning models, reviewed the models on the accuracy and feasibility, and proposed corresponding improvements. Regarding accuracy, lack of long-term outcome, treatment option consideration, and advanced radiological features were found in many previous studies in terms of model conceptualization. Regarding interpretability, most of the previous models chose restrictive models for high interpretability and did not mention processing time consideration. In the future, model conceptualization could be improved based on comprehensive neurological domain knowledge and feasibility needs to be achieved by elaborate computer science algorithms to increase the interpretability of flexible algorithms and shorten the processing time of the pipeline interpreting medical images.

Augmented Features Synergize Radiomics in Post-Operative Survival Prediction and Adjuvant Therapy Recommendation for Non-Small Cell Lung Cancer.

BACKGROUND: Owing to the cytotoxic effect, it is challenging for clinicians to decide whether post-operative adjuvant therapy is appropriate for a non-small cell lung cancer (NSCLC) patient. Radiomics has proven its promising ability in predicting survival but research on its actionable model, particularly for supporting the decision of adjuvant therapy, is limited. METHODS: Pre-operative contrast-enhanced CT images of 123 NSCLC cases were collected, including 76, 13, 16, and 18 cases from R01 and AMC cohorts of The Cancer Imaging Archive (TCIA), Jiangxi Cancer Hospital and Guangdong Provincial People's Hospital respectively. From each tumor region, 851 radiomic features were extracted and two augmented features were derived therewith to estimate the likelihood of adjuvant therapy. Both Cox regression and machine learning models with the selected main and interaction effects of 853 features were trained using 76 cases from R01 cohort, and their test performances on survival prediction were compared using 47 cases from the AMC cohort and two hospitals. For those cases where adjuvant therapy was unnecessary, recommendations on adjuvant therapy were made again by the outperforming model and compared with those by IBM Watson for Oncology (WFO). RESULTS: The Cox model outperformed the machine learning model in predicting survival on the test set (C-Index: 0.765 vs. 0.675). The Cox model consists of 5 predictors, interestingly 4 of which are interactions with augmented features facilitating the modulation of adjuvant therapy option. While WFO recommended no adjuvant therapy for only 13.6% of cases that received unnecessary adjuvant therapy, the same recommendations by the identified Cox model were extended to 54.5% of cases (McNemar's test p = 0.0003). CONCLUSIONS: A Cox model with radiomic and augmented features could predict survival accurately and support the decision of adjuvant therapy for bettering the benefit of NSCLC patients.

Defining the Macromolecules of Tomorrow through Synergistic Sustainable Polymer Research.

Transforming how plastics are made, unmade, and remade through innovative research and diverse partnerships that together foster environmental stewardship is critically important to a sustainable future. Designing, preparing, and implementing polymers derived from renewable resources for a wide range of advanced applications that promote future economic development, energy efficiency, and environmental sustainability are all central to these efforts. In this Chemical Reviews contribution, we take a comprehensive, integrated approach to summarize important and impactful contributions to this broad research arena. The Review highlights signature accomplishments across a broad research portfolio and is organized into four wide-ranging research themes that address the topic in a comprehensive manner: Feedstocks, Polymerization Processes and Techniques, Intended Use, and End of Use. We emphasize those successes that benefitted from collaborative engagements across disciplinary lines.

Ligand Conformational Flexibility Enables Enantioselective Tertiary C-B Bond Formation in the Phosphonate-Directed Catalytic Asymmetric Alkene Hydroboration.

Conformationally flexible ancillary ligands have been widely used in transition metal catalysis. However, the benefits of using flexible ligands are often not well understood. We performed density functional theory (DFT) and experimental studies to elucidate the mechanisms and the roles of conformationally flexible α,α,α',α'-tetraaryldioxolane-4,5-dimethanol (TADDOL)-derived ligands on the reactivity and selectivity in the Rh-catalyzed asymmetric hydroboration (CAHB) of alkenes. DFT calculations and deuterium labeling studies both indicated that the most favorable reaction pathway involves an unusual tertiary C-B bond reductive elimination to give high levels of regio- and enantioselectivities. Here, the asymmetric construction of the fully substituted carbon center is promoted by the flexibility of the TADDOL backbone, which leads to two ligand conformations with distinct steric environments in different steps of the catalytic cycle. A pseudo-chair ligand conformation is preferred in the rate-determining tertiary benzylic C-B reductive elimination. The less hindered steric environment with this conformation allows the benzylic group to bind to the Rh center in an η3 fashion, which stabilizes the C-B reductive elimination transition state. On the other hand, a pseudo-boat ligand conformation is involved in the selectivity-determining alkene migratory insertion step, where the more anisotropic steric environment leads to greater ligand-substrate steric interactions to control the π-facial selectivity. Thus, using a conformationally flexible ligand is beneficial for enhancing both reactivity and enantioselectivity by controlling ligand-substrate interactions in two different elementary steps.

Cascade CuH-Catalysed Conversion of Alkynes to Enantioenriched 1,1-Disubstituted Products.

Enantioenriched α-aminoboronic acids play a unique role in medicinal chemistry and have emerged as privileged pharmacophores in proteasome inhibitors. Additionally, they represent synthetically useful chiral building blocks in organic synthesis. Recently, CuH-catalyzed asymmetric alkene hydrofunctionalization has become a powerful tool to construct stereogenic carbon centers. In contrast, applying CuH cascade catalysis to achieve reductive 1,1-difunctionalization of alkynes remains an important, but largely unaddressed, synthetic challenge. Herein, we report an efficient strategy to synthesize α-aminoboronates via CuH-catalyzed hydroboration/hydroamination cascade of readily available alkynes. Notably, this transformation selectively delivers the desired 1,1-heterodifunctionalized product in favor of alternative homodifunctionalized, 1,2-heterodifunctionalized, or reductively monofunctionalized byproducts, thereby offering rapid access to these privileged scaffolds with high chemo-, regio- and enantioselectivity.

Cu-Catalyzed Hydroboration of Benzylidenecyclopropanes: Reaction Optimization, (Hetero)Aryl Scope, and Origins of Pathway Selectivity.

The copper-catalyzed hydroboration of benzylidenecyclopropanes, conveniently accessed in one step from readily available benzaldehydes, is reported. Under otherwise identical reaction conditions, two distinct phosphine ligands grant access to different products by either suppressing or promoting cyclopropane opening via ß-carbon elimination. Computational studies provide insight into how the rigidity and steric environment of these different bis-phosphine ligands influence the relative activation energies of ß-carbon elimination versus protodecupration from the key benzylcopper intermediate. The method tolerates a wide variety of heterocycles prevalent in clinical and pre-clinical drug development, giving access to valuable synthetic intermediates. The versatility of the tertiary cyclopropylboronic ester products is demonstrated through several derivatization reactions.

Disentangling Ligand Effects on Metathesis Catalyst Activity: Experimental and Computational Studies of Ruthenium-Aminophosphine Complexes.

Second-generation ruthenium olefin metathesis catalysts bearing aminophosphine ligands were investigated with systematic variation of the ligand structure. The rates of phosphine dissociation ( k1; initiation rate) and relative phosphine reassociation ( k-1) were determined for two series of catalysts bearing cyclohexyl(morpholino)phosphine and cyclohexyl(piperidino)phosphine ligands. In both cases, incorporating P-N bonds into the architecture of the dissociating phosphine accelerates catalyst initiation relative to the parent [Ru]-PCy3 complex; however, this effect is muted for the tris(amino)phosphine-ligated complexes, which exhibit higher ligand binding constants in comparison to those with phosphines containing one or two cyclohexyl substituents. These results, along with X-ray crystallographic data and DFT calculations, were used to understand the influence of ligand structure on catalyst activity. Especially noteworthy is the application of phosphines containing incongruent substituents (PR1R'2); detailed analyses of factors affecting ligand dissociation, including steric effects, inductive effects, and ligand conformation, are presented. Computational studies of the reaction coordinate for ligand dissociation reveal that ligand conformational changes contribute to the rapid dissociation for the fastest-initiating catalyst of these series, which bears a cyclohexyl-bis(morpholino)phosphine ligand. Furthermore, the effect of amine incorporation was examined in the context of ring-opening metathesis polymerization, and reaction rates were found to correlate well with catalyst initiation rates. The combined experimental and computational studies presented in this report reveal important considerations for designing efficient ruthenium olefin metathesis catalysts.

Origins of the Stereoretentive Mechanism of Olefin Metathesis with Ru-Dithiolate Catalysts.

A comprehensive computational study of stereoretentive olefin metathesis with Ru-dithiolate catalysts has been performed. We have determined how the dithiolate ligand enforces a side-bound mechanism and how the side-bound mechanism allows for stereochemical control over the forming olefin. We have used density functional theory (DFT) and ligand steric contour maps to elucidate the origins of stereoretentive metathesis with the goal of understanding how to design a new class of E-selective metathesis catalysts.

A Ring-Opening Metathesis Polymerization Catalyst That Exhibits Redox-Switchable Monomer Selectivities.

A ring-opening metathesis polymerization catalyst supported by a redox-active N-heterocyclic carbene was synthesized and found to undergo reversible reduction. In its neutral form, the catalyst polymerized 1,5-cis,cis-cyclooctadiene at a higher rate than that of a norbornene derivative; however, upon reduction, the selectivity was found to reverse. Utilizing this oxidation state dependent selectivity, a series of copolymers with controlled compositions, microstructures, and physical properties were prepared by redox-switching the catalyst over the course of a series of polymerization reactions.