Geminal-atom catalysis for cross-coupling.

Single-atom catalysts (SACs) have well-defined active sites, making them of potential interest for organic synthesis1-4. However, the architecture of these mononuclear metal species stabilized on solid supports may not be optimal for catalysing complex molecular transformations owing to restricted spatial environment and electronic quantum states5,6. Here we report a class of heterogeneous geminal-atom catalysts (GACs), which pair single-atom sites in specific coordination and spatial proximity. Regularly separated nitrogen anchoring groups with delocalized π-bonding nature in a polymeric carbon nitride (PCN) host7 permit the coordination of Cu geminal sites with a ground-state separation of about 4 Å at high metal density8. The adaptable coordination of individual Cu sites in GACs enables a cooperative bridge-coupling pathway through dynamic Cu-Cu bonding for diverse C-X (X = C, N, O, S) cross-couplings with a low activation barrier. In situ characterization and quantum-theoretical studies show that such a dynamic process for cross-coupling is triggered by the adsorption of two different reactants at geminal metal sites, rendering homo-coupling unfeasible. These intrinsic advantages of GACs enable the assembly of heterocycles with several coordination sites, sterically congested scaffolds and pharmaceuticals with highly specific and stable activity. Scale-up experiments and translation to continuous flow suggest broad applicability for the manufacturing of fine chemicals.

Key role of chemistry versus bias in electrocatalytic oxygen evolution.

The oxygen evolution reaction has an important role in many alternative-energy schemes because it supplies the protons and electrons required for converting renewable electricity into chemical fuels1-3. Electrocatalysts accelerate the reaction by facilitating the required electron transfer4, as well as the formation and rupture of chemical bonds5. This involvement in fundamentally different processes results in complex electrochemical kinetics that can be challenging to understand and control, and that typically depends exponentially on overpotential1,2,6,7. Such behaviour emerges when the applied bias drives the reaction in line with the phenomenological Butler-Volmer theory, which focuses on electron transfer8, enabling the use of Tafel analysis to gain mechanistic insight under quasi-equilibrium9-11 or steady-state assumptions12. However, the charging of catalyst surfaces under bias also affects bond formation and rupture13-15, the effect of which on the electrocatalytic rate is not accounted for by the phenomenological Tafel analysis8 and is often unknown. Here we report pulse voltammetry and operando X-ray absorption spectroscopy measurements on iridium oxide to show that the applied bias does not act directly on the reaction coordinate, but affects the electrocatalytically generated current through charge accumulation in the catalyst. We find that the activation free energy decreases linearly with the amount of oxidative charge stored, and show that this relationship underlies electrocatalytic performance and can be evaluated using measurement and computation. We anticipate that these findings and our methodology will help to better understand other electrocatalytic materials and design systems with improved performance.

A mitochondrial ADXR-ADX-P450 electron transport chain is essential for maternal gametophytic control of embryogenesis in Arabidopsis.

Mitochondrial adrenodoxins (ADXs) are small iron-sulfur proteins with electron transfer properties. In animals, ADXs transfer electrons between an adrenodoxin reductase (ADXR) and mitochondrial P450s, which is crucial for steroidogenesis. Here we show that a plant mitochondrial steroidogenic pathway, dependent on an ADXR-ADX-P450 shuttle, is essential for female gametogenesis and early embryogenesis through a maternal effect. The steroid profile of maternal and gametophytic tissues of wild-type (WT) and adxr ovules revealed that homocastasterone is the main steroid present in WT gametophytes and that its levels are reduced in the mutant ovules. The application of exogenous homocastasterone partially rescued adxr and P450 mutant phenotypes, indicating that gametophytic homocastasterone biosynthesis is affected in the mutants and that a deficiency of this hormone causes the phenotypic alterations observed. These findings also suggest not only a remarkable similarity between steroid biosynthetic pathways in plants and animals but also a common function during sexual reproduction.

Machine learning in small sample neuroimaging studies: Novel measures for schizophrenia analysis.

Novel features derived from imaging and artificial intelligence systems are commonly coupled to construct computer-aided diagnosis (CAD) systems that are intended as clinical support tools or for investigation of complex biological patterns. This study used sulcal patterns from structural images of the brain as the basis for classifying patients with schizophrenia from unaffected controls. Statistical, machine learning and deep learning techniques were sequentially applied as a demonstration of how a CAD system might be comprehensively evaluated in the absence of prior empirical work or extant literature to guide development, and the availability of only small sample datasets. Sulcal features of the entire cerebral cortex were derived from 58 schizophrenia patients and 56 healthy controls. No similar CAD systems has been reported that uses sulcal features from the entire cortex. We considered all the stages in a CAD system workflow: preprocessing, feature selection and extraction, and classification. The explainable AI techniques Local Interpretable Model-agnostic Explanations and SHapley Additive exPlanations were applied to detect the relevance of features to classification. At each stage, alternatives were compared in terms of their performance in the context of a small sample. Differentiating sulcal patterns were located in temporal and precentral areas, as well as the collateral fissure. We also verified the benefits of applying dimensionality reduction techniques and validation methods, such as resubstitution with upper bound correction, to optimize performance.

Active Learning-Based Guided Synthesis of Engineered Biochar for CO2 Capture.

Biomass waste-derived engineered biochar for CO2 capture presents a viable route for climate change mitigation and sustainable waste management. However, optimally synthesizing them for enhanced performance is time- and labor-intensive. To address these issues, we devise an active learning strategy to guide and expedite their synthesis with improved CO2 adsorption capacities. Our framework learns from experimental data and recommends optimal synthesis parameters, aiming to maximize the narrow micropore volume of engineered biochar, which exhibits a linear correlation with its CO2 adsorption capacity. We experimentally validate the active learning predictions, and these data are iteratively leveraged for subsequent model training and revalidation, thereby establishing a closed loop. Over three active learning cycles, we synthesized 16 property-specific engineered biochar samples such that the CO2 uptake nearly doubled by the final round. We demonstrate a data-driven workflow to accelerate the development of high-performance engineered biochar with enhanced CO2 uptake and broader applications as a functional material.

NCCR Catalysis at a Glance: A National Research Program on Sustainable Chemistry.

Curious about how chemistry can contribute to sustainable development? In this overview, we explain the essence of NCCR funding, the research focus and structural goals of NCCR Catalysis, and how these align with the sustainable development goals (SDGs). Additionally, we highlight opportunities for getting involved with our program.

The Future of Chemical Sciences is Sustainable.

Chemistry, a vital tool for sustainable development, faces a challenge due to the lack of clear guidance on actionable steps, hindering the optimal adoption of sustainability practices across its diverse facets from discovery to implementation. This Scientific Perspective explores established frameworks and principles, proposing a conciliated set of triple E priorities anchored on Environmental, Economic, and Equity pillars for research and decision making. We outline associated metrics, crucial for quantifying impacts, classifying them according to their focus areas and scales tackled. Emphasizing catalysis as a key driver of sustainable synthesis of chemicals and materials, we exemplify how triple E priorities can practically guide the development and implementation of processes from renewables conversions to complex customized products. We summarize by proposing a roadmap for the community aimed at raising awareness, fostering academia-industry collaboration, and stimulating further advances in sustainable chemical technologies across their broad scope.

Consumer Grade Polyethylene Recycling via Hydrogenolysis on Ultrafine Supported Ruthenium Nanoparticles.

Catalytic hydrogenolysis has the potential to convert high-density polyethylene (HDPE), which comprises about 30 % of plastic waste, into valuable alkanes. Most investigations have focused on increasing activity for lab grade HDPEs displaying low molecular weight, with limited mechanistic understanding of the product distribution. No efficient catalyst is available for consumer grades due to their lower reactivity. This study targets HDPE used in bottle caps, a waste form generated globally at a rate of approximately one million units per hour. Ultrafine ruthenium particles (1 nm) supported on titania (anatase) achieved up to 80 % conversion into light alkanes (C1 -C45 ) under mild conditions (498 K, 20 bar H2 , 4 h) and were reused for three cycles. Small ruthenium nanoparticles were critical to achieving relevant conversions, as activity sharply decreased with particle size. Selectivity commonalities and peculiarities across HDPE grades were disclosed by a reaction modelling approach applied to products. Isomerization cedes to backbone scission as the reaction progresses. Within this trend, low molecular weight favor isomerization whilst high molecular weight favor cleavage. Commercial caps obeyed this trend with decreased activity, anticipating the influence of additives in realistic processing. This study demonstrates effective hydrogenolysis of consumer grade polyethylene and provides selectivity patterns for product control.

CO Cofeeding Affects Product Distribution in CH3Cl Coupling over ZSM-5 Zeolite: Pressure Twists the Plot.

C1 coupling reactions over zeolite catalysts are central to sustainable chemical production strategies. However, questions persist regarding the involvement of CO in ketene formation, and the impact of this elusive oxygenate intermediate on reactivity patterns. Using operando photoelectron photoion coincidence spectroscopy (PEPICO), we investigate the role of CO in methyl chloride conversion to hydrocarbons (MCTH), a prospective process for methane valorization with a reaction network akin to methanol to hydrocarbons (MTH) but without oxygenate intermediates. Our findings reveal the transformative role of CO in MCTH at the low pressures, inducing ketene formation in MCTH and boosting olefin production, confirming the Koch carbonylation step in the initial stages of C1 coupling. We uncover pressure-dependent product distributions driven by CO-induced ketene formation, and its subsequent desorption from the zeolite surface, which is enhanced at low pressure. Inspired by the above results, extension of the co-feeding approach to CH3OH as another simple oxygenate showcases the additional potential for improved catalyst stability in MCTH at ambient pressure.

Droplet-Based Microfluidics Reveals Insights into Cross-Coupling Mechanisms over Single-Atom Heterogeneous Catalysts.

Single-atom heterogeneous catalysts (SACs) hold promise as sustainable alternatives to metal complexes in organic transformations. However, their working structure and dynamics remain poorly understood, hindering advances in their design. Exploiting the unique features of droplet-based microfluidics, we present the first in-situ assessment of a palladium SAC based on exfoliated carbon nitride in Suzuki-Miyaura cross-coupling using X-ray absorption spectroscopy. Our results confirm a surface-catalyzed mechanism, revealing the distinct electronic structure of active Pd centers compared to homogeneous systems, and providing insights into the stabilizing role of ligands and bases. This study establishes a valuable framework for advancing mechanistic understanding of organic syntheses catalyzed by SACs.

Unraveling Radical and Oxygenate Routes in the Oxidative Dehydrogenation of Propane over Boron Nitride.

Oxidative dehydrogenation of propane (ODHP) is an emerging technology to meet the global propylene demand with boron nitride (BN) catalysts likely to play a pivotal role. It is widely accepted that gas-phase chemistry plays a fundamental role in the BN-catalyzed ODHP. However, the mechanism remains elusive because short-lived intermediates are difficult to capture. We detect short-lived free radicals (CH3•, C3H5•) and reactive oxygenates, C2-4 ketenes and C2-3 enols, in ODHP over BN by operando synchrotron photoelectron photoion coincidence spectroscopy. In addition to a surface-catalyzed channel, we identify a gas-phase H-acceptor radical- and H-donor oxygenate-driven route, leading to olefin production. In this route, partially oxidized enols propagate into the gas phase, followed by dehydrogenation (and methylation) to form ketenes and finally yield olefins by decarbonylation. Quantum chemical calculations predict the >BO dangling site to be the source of free radicals in the process. More importantly, the easy desorption of oxygenates from the catalyst surface is key to prevent deep oxidation to CO2.

Direct Electroreduction of Carbonate to Formate.

A cause of losses in energy and carbon conversion efficiencies during the electrochemical CO2 reduction reaction (eCO2RR) can be attributed to the formation of carbonates (CO32-), which is generally considered to be an electrochemically inert species. Herein, using in situ Raman spectroscopy, liquid chromatography, 1H nuclear magnetic resonance spectroscopy, 13C and deuterium isotope labeling, and density functional theory simulations, we show that carbonate intermediates are adsorbed on a copper electrode during eCO2RR in KHCO3 electrolyte from 0.2 to -1.0 VRHE. These intermediates can be reduced to formate at -0.4 VRHE and more negative potentials. This finding is supported by our observation of formate from the reduction of Cu2(CO3)(OH)2. Pulse electrolysis on a copper electrode immersed in a N2-purged K2CO3 electrolyte was also performed. We found that the carbonate anions therein could be first adsorbed at -0.05 VRHE and then directly reduced to formate at -0.5 VRHE (overpotential of 0.28 V) with a Faradaic efficiency of 0.61%. The nature of the active sites generating the adsorbed carbonate species and the mechanism for the pulse-enabled reduction of carbonate to formate were elucidated. Our findings reveal how carbonates are directly reduced to a high-value product such as formate and open a potential pathway to mitigate carbonate formation during eCO2RR.

Alterations in immune cell phenotype and cytotoxic capacity in HER2+ breast cancer patients receiving HER2-targeted neo-adjuvant therapy.

BACKGROUND: The phase II neo-adjuvant clinical trial ICORG10-05 (NCT01485926) compared chemotherapy in combination with trastuzumab, lapatinib or both in patients with HER2+ breast cancer. We studied circulating immune cells looking for alterations in phenotype, genotype and cytotoxic capacity (direct and antibody-dependent cell-mediated cytotoxicity (ADCC)) in the context of treatment response. METHODS: Peripheral blood mononuclear cells (PBMCs) were isolated from pre- (n = 41) and post- (n = 25) neo-adjuvant treatment blood samples. Direct/trastuzumab-ADCC cytotoxicity of patient-derived PBMCs against K562/SKBR3 cell lines was determined ex vivo. Pembrolizumab was interrogated in 21 pre-treatment PBMC ADCC assays. Thirty-nine pre-treatment and 21 post-treatment PBMC samples were immunophenotyped. Fc receptor genotype, tumour infiltrating lymphocyte (TIL) levels and oestrogen receptor (ER) status were quantified. RESULTS: Treatment attenuated the cytotoxicity/ADCC of PBMCs. CD3+/CD4+/CD8+ T cells increased following therapy, while CD56+ NK cells/CD14+ monocytes/CD19+ B cells decreased with significant post-treatment immune cell changes confined to patients with residual disease. Pembrolizumab-augmented ex vivo PBMC ADCC activity was associated with residual disease, but not pathological complete response. Pembrolizumab-responsive PBMCs were associated with lower baseline TIL levels and ER+ tumours. CONCLUSIONS: PBMCs display altered phenotype and function following completion of neo-adjuvant treatment. Anti-PD-1-responsive PBMCs in ex vivo ADCC assays may be a biomarker of treatment response.

Applications of machine learning and deep learning in SPECT and PET imaging: General overview, challenges and future prospects.

The integration of positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging techniques with machine learning (ML) algorithms, including deep learning (DL) models, is a promising approach. This integration enhances the precision and efficiency of current diagnostic and treatment strategies while offering invaluable insights into disease mechanisms. In this comprehensive review, we delve into the transformative impact of ML and DL in this domain. Firstly, a brief analysis is provided of how these algorithms have evolved and which are the most widely applied in this domain. Their different potential applications in nuclear imaging are then discussed, such as optimization of image adquisition or reconstruction, biomarkers identification, multimodal fusion and the development of diagnostic, prognostic, and disease progression evaluation systems. This is because they are able to analyse complex patterns and relationships within imaging data, as well as extracting quantitative and objective measures. Furthermore, we discuss the challenges in implementation, such as data standardization and limited sample sizes, and explore the clinical opportunities and future horizons, including data augmentation and explainable AI. Together, these factors are propelling the continuous advancement of more robust, transparent, and reliable systems.

Light-Driven Two-Step Preparation of 4-Chromanone Fused to Estrone Derivatives.

A protocol involving the irradiation of some 3-(2-alkenyl)estrone and 3-(2-alkenyl)-17-norestrone derivatives under a nitrogen atmosphere in organic solvents (both hexane and MeOH) followed by base-mediated intramolecular oxa-Michael cyclization reaction was investigated under steady-state conditions. The solvent effect and nature of the acyl group on the preparative photoreaction were studied and the multiplicity of the excited state was also demonstrated. The ortho-regioisomers were obtained in modest to good yields. Intramolecular based-mediate cyclization reaction of these synthons led to the formation of a set of novel substituted 4-chromanone moieties fused to estrone (and 17-norestrone) in good yields. This two-step sequential procedure involving a photochemical/intramolecular thermal cyclization strategy will be useful for the preparation of wide heterocyclic-fused-steroid compounds.

lncRNAs dysregulation in monocytes from primary antiphospholipid syndrome patients: a bioinformatic and an experimental proof-of-concept approach.

BACKGROUND: Antiphospholipid syndrome (APS) is the main cause of acquired thrombophilia where peripheral circulating cells such as monocytes have a key role. Currently, several studies have linked long non-coding RNAs (lncRNAs) in different inflammatory and autoimmune processes, including lupus. However, the role of lncRNAs in antiphospholipid syndrome is unknown, therefore, we aimed to select and measure expression levels of three lncRNAs based on its abundance in monocytes from APS patients. METHODS: Selection of lncRNAs candidates were carried out based on its abundance in monocytes and their relationship with Perez-Sanchez miRNA signature by using miRNet 2.0 bioinformatic tool, then lncRNAs expression levels was measured in monocytes by RT-qPCR. RESULTS: This is the first study to report that lncRNAs: FGD5-AS1, OIP5-AS1 and GAS5 are promising candidates for play a role on APS monocytes and they are expressed differently between patients and controls. CONCLUSIONS: OIP5-AS1, FGD5-AS1 and GAS5 are downregulated on monocytes from APS patients.

Mapping the risk of respiratory infections using suburban district areas in a large city in Colombia.

BACKGROUND: Acute respiratory infections (ARI) in Cúcuta -Colombia, have a comparatively high burden of disease associated with high public health costs. However, little is known about the epidemiology of these diseases in the city and its distribution within suburban areas. This study addresses this gap by estimating and mapping the risk of ARI in Cúcuta and identifying the most relevant risk factors. METHODS: A spatial epidemiological analysis was designed to investigate the association of sociodemographic and environmental risk factors with the rate of ambulatory consultations of ARI in urban sections of Cúcuta, 2018. The ARI rate was calculated using a method for spatial estimation of disease rates. A Bayesian spatial model was implemented using the Integrated Nested Laplace Approximation approach and the Besag-York-Mollié specification. The risk of ARI per urban section and the hotspots of higher risk were also estimated and mapped. RESULTS: A higher risk of IRA was found in central, south, north and west areas of Cúcuta after adjusting for sociodemographic and environmental factors, and taking into consideration the spatial distribution of the city's urban sections. An increase of one unit in the percentage of population younger than 15 years; the Index of Multidimensional Poverty and the rate of ARI in the migrant population was associated with a 1.08 (1.06-1.1); 1.04 (1.01-1.08) and 1.25 (1.22-1.27) increase of the ARI rate, respectively. Twenty-four urban sections were identified as hotspots of risk in central, south, north and west areas in Cucuta. CONCLUSION: Sociodemographic factors and their spatial patterns are determinants of acute respiratory infections in Cúcuta. Bayesian spatial hierarchical models can be used to estimate and map the risk of these infections in suburban areas of large cities in Colombia. The methods of this study can be used globally to identify suburban areas and or specific communities at risk to support the implementation of prevention strategies and decision-making in the public and private health sectors.

Whole Blood Expression Levels of Long Noncoding RNAs: HOTAIRM1, GAS5, MZF1-AS1, and OIP5-AS1 as Biomarkers in Adolescents with Obesity-Related Asthma.

Asthma is a heterogeneous entity encompassing distinct endotypes and varying phenotypes, characterized by common clinical manifestations, such as shortness of breath, wheezing, and variable airflow obstruction. Two major asthma endotypes based on molecular patterns are described: type 2 endotype (allergic-asthma) and T2 low endotype (obesity-related asthma). Long noncoding RNAs (lncRNAs) are transcripts of more than 200 nucleotides in length, currently involved in many diverse biological functions, such as chromatin remodeling, gene transcription, protein transport, and microRNA processing. Despite the efforts to accurately classify and discriminate all the asthma endotypes and phenotypes, if long noncoding RNAs could play a role as biomarkers in allergic asthmatic and adolescent obesity-related asthma, adolescents remain unknown. To compare expression levels of lncRNAs: HOTAIRM1, OIP5-AS1, MZF1-AS1, and GAS5 from whole blood of Healthy Adolescents (HA), Obese adolescents (O), allergic asthmatic adolescents (AA) and Obesity-related asthma adolescents (OA). We measured and compared expression levels from the whole blood of the groups mentioned above through RT-q-PCR. We found differentially expressed levels of these lncRNAs between the groups of interest. In addition, we found a discriminative value of previously mentioned lncRNAs between studied groups. Finally, we generated an interaction network through bioinformatics. Expression levels of OIP5-AS1, MZF1-AS1, HOTAIRM1, and GAS5 in whole blood from the healthy adolescent population, obese adolescents, allergic asthma adolescents, and obesity-related asthma adolescents are differently expressed. Moreover, these lncRNAs could act as molecular biomarkers that help to discriminate between all studied groups, probably through molecular mechanisms with several genes and miRNAs implicated.

Operando Photoelectron Photoion Coincidence Spectroscopy to Detect Short-lived Intermediates in Catalysis.

Understanding the reaction mechanism is critical yet challenging in heterogeneous catalysis. Reactive intermediates, e.g., radicals and ketenes, are short-lived and often evade detection. In this review, we summarize recent developments with operando photoelectron photoion coincidence (PEPICO) spectroscopy as a versatile tool capable of detecting elusive intermediates. PEPICO combines the advantages of mass spectrometry and the isomer-selectivity of threshold photoelectron spectroscopy. Recent applications of PEPICO in understanding catalyst synthesis and catalytic reaction mechanisms involving gaseous and surface-confined radical and ketene chemistry will be summarized.

The Environmental Feasibility of Decentralised Solar Ammonia.

Intense efforts have been devoted to developing green and blue centralised Haber-Bosch processes (gHB and bHB, respectively), but the feasibility of a decentralised and sustainable scheme has yet to be assessed. Here we reveal the conditions under which small-scale systems based on the electrocatalytic reduction of nitrogen (eN2R) powered by photovoltaic energy (NH3-leaf) could become a competitive technology in terms of environmental criteria. To this end, we calculated energy efficiency targets based on solar irradiation atlases to guide research in the incipient eN2R field. Even under this germinal state, the NH3-leaf technology would compete favourably in sunny locations relative to the business-as-usual production scenario. The disclosed sustainability potential of NH3-leaf makes it a strong ally of gHB toward a non-fossil ammonia production.