RESUMEN

Lead-free metal halide perovskites can potentially be air- and water-stable photocatalysts for organic synthesis, but there are limited studies on them for this application. Separately, machine learning (ML), a critical subfield of artificial intelligence, has played a pivotal role in identifying correlations and formulating predictions based on extensive datasets. Herein, an iterative workflow by incorporating high-throughput experimental data with ML to discover new lead-free metal halide perovskite photocatalysts for the aerobic oxidation of styrene is described. Through six rounds of ML optimization guided by SHapley Additive exPlanations (SHAP) analysis, BA2CsAg0.95Na0.05BiBr7 as a photocatalyst that afforded an 80% yield of benzoic acid under the standard conditions is identified, which is a 13-fold improvement compared to the 6% with when using Cs2AgBiBr6 as the initial photocatalyst benchmark that is started. BA2CsAg0.95Na0.05BiBr7 can tolerate various functional groups with 22 styrene derivatives, highlighting the generality of the photocatalytic properties demonstrated. Radical scavenging studies and density functional theory calculations revealed that the formation of the reactive oxygen species superoxide and singlet oxygen in the presence of BA2CsAg0.95Na0.05BiBr7 are critical for photocatalysis.

RESUMEN

Studying the ultrafast dynamics of ionized aqueous biomolecules is important for gaining an understanding of the interaction of ionizing radiation with biological matter. Guanine plays an essential role in biological systems as one of the four nucleobases that form the building blocks of deoxyribonucleic acid (DNA). Guanine radicals can induce oxidative damage to DNA, particularly due to the lower ionization potential of guanine compared to the other nucleobases, sugars, and phosphate groups that are constituents of DNA. This study utilizes femtosecond optical pump-probe spectroscopy to observe the ultrafast vibrational wave packet dynamics of the guanine radical anion launched by photodetachment of the aqueous guanine dianion. The vibrational wave packet motion is resolved into 11 vibrational modes along which structural reorganization occurs upon photodetachment. These vibrational modes are assigned with the aid of density functional theory (DFT) calculations. Our work sheds light on the ultrafast vibrational dynamics following the ionization of nucleobases in an aqueous medium.

RESUMEN

Despite an exponential increase in publications on clinical prediction models over recent years, the number of models deployed in clinical practice remains fairly limited. In this paper, we identify common obstacles that impede effective deployment of prediction models in healthcare, and investigate their underlying causes. We observe a key underlying cause behind most obstacles - the improper development and evaluation of prediction models. Inherent heterogeneities in clinical data complicate the development and evaluation of clinical prediction models. Many of these heterogeneities in clinical data are unreported because they are deemed to be irrelevant, or due to privacy concerns. We provide real-life examples where failure to handle heterogeneities in clinical data, or sources of biases, led to the development of erroneous models. The purpose of this paper is to familiarize modeling practitioners with common sources of biases and heterogeneities in clinical data, both of which have to be dealt with to ensure proper development and evaluation of clinical prediction models. Proper model development and evaluation, together with complete and thorough reporting, are important prerequisites for a prediction model to be effectively deployed in healthcare.

Asunto(s)

Reglas de Decisión Clínica , Atención a la Salud , Modelos Estadísticos

RESUMEN

Clinical prediction models are widely used to predict adverse outcomes in patients, and are often employed to guide clinical decision-making. Clinical data typically consist of patients who received different treatments. Many prediction modeling studies fail to account for differences in patient treatment appropriately, which results in the development of prediction models that show poor accuracy and generalizability. In this paper, we list the most common methods used to handle patient treatments and discuss certain caveats associated with each method. We believe that proper handling of differences in patient treatment is crucial for the development of accurate and generalizable models. As different treatment strategies are employed for different diseases, the best approach to properly handle differences in patient treatment is specific to each individual situation. We use the Ma-Spore acute lymphoblastic leukemia data set as a case study to demonstrate the complexities associated with differences in patient treatment, and offer suggestions on incorporating treatment information during evaluation of prediction models. In clinical data, patients are typically treated on a case by case basis, with unique cases occurring more frequently than expected. Hence, there are many subtleties to consider during the analysis and evaluation of clinical prediction models.

RESUMEN

The phenylalanine radical (Phe˙) has been proposed to mediate biological electron transport (ET) and exhibit long-lived electronic coherences following attosecond photoionization. However, the coupling of ultrafast structural reorganization to the oxidation/ionization of biomolecules such as phenylalanine remains unexplored. Moreover, studies of ET involving Phe˙ are hindered by its hitherto unobserved electronic spectrum. Here, we report the spectroscopic observation and coherent vibrational dynamics of aqueous Phe˙, prepared by sub-6 fs photodetachment of phenylalaninate anions. Sub-picosecond transient absorption spectroscopy reveals the ultraviolet absorption signature of Phe˙. Ultrafast structural reorganization drives coherent vibrational motion involving nine fundamental frequencies and one overtone. DFT calculations rationalize the absence of the decarboxylation reaction, a photodegradation pathway previously identified for Phe˙. Our findings guide the interpretation of future attosecond experiments aimed at elucidating coherent electron motion in photoionized aqueous biomolecules and pave way for the spectroscopic identification of Phe˙ in studies of biological ET.

Asunto(s)

Fenilalanina , Vibración , Electrones , Análisis Espectral , Agua

RESUMEN

Emerging studies have recently shown the potential importance of ketone bodies in cardio-metabolic health. However, techniques to determine myocardial ketone body utilization in vivo are lacking. In this work, we developed a novel method to assess myocardial ketone body utilization in vivo using hyperpolarized [3-13C]acetoacetate and investigated the alterations in myocardial ketone body metabolism in diabetic rats. Within a minute upon injection of [3-13C]acetoacetate, the production of [5-13C]glutamate and [1-13C] acetylcarnitine can be observed real time in vivo. In diabetic rats, the production of [5-13C]glutamate was elevated compared to controls, while [1-13C]acetylcarnitine was not different. This suggests an increase in ketone body utilization in the diabetic heart, with the produced acetyl-CoA channelled into the tricarboxylic acid cycle. This observation was corroborated by an increase activity of succinyl-CoA:3-ketoacid-CoA transferase (SCOT) activity, the rate-limiting enzyme of ketone body utilization, in the diabetic heart. The increased ketone body oxidation in the diabetic hearts correlated with cardiac hypertrophy and dysfunction, suggesting a potential coupling between ketone body metabolism and cardiac function. Hyperpolarized [3-13C]acetoacetate is a new probe with potential for non-invasive and real time monitoring of myocardial ketone body oxidation in vivo, which offers a powerful tool to follow disease progression or therapeutic interventions.

Asunto(s)

Acetoacetatos/análisis , Cardiomegalia/diagnóstico por imagen , Diabetes Mellitus Experimental/fisiopatología , Cetonas/química , Miocardio/química , Animales , Espectroscopía de Resonancia Magnética con Carbono-13 , Cardiomegalia/metabolismo , Diabetes Mellitus Experimental/diagnóstico por imagen , Imagen por Resonancia Cinemagnética , Masculino , Oxidación-Reducción , Ratas , Volumen Sistólico

RESUMEN

AIM: To investigate the effects of the sodium-glucose co-transporter-2 inhibitor empagliflozin on myocardial ketone body utilization in diabetic, obese rats with spontaneously hypertensive heart failure (SHHF), after 6 months of treatment. MATERIALS AND METHODS: Myocardial ketone body utilization was measured in vivo real time using a novel ketone probe (hyperpolarized [3-13 C]acetoacetate) and magnetic resonance spectroscopy (MRS). Myocardial glucose utilization and cardiac function were also determined in vivo using hyperpolarized [1-13 C]pyruvate MRS and magnetic resonance imaging (MRI), respectively. Myocardial fatty acid uptake and liver ketogenesis were assessed via protein expression. RESULTS: At baseline, myocardial ketone and glucose utilization were both higher in SHHF compared with control rats. Six months of empagliflozin treatment in SHHF rats was associated with less obesity, lower blood pressure, reduced blood glucose and insulin levels, and increased fasting blood ß-hydroxybutyrate levels, as expected. Contrary to the hypothesis, myocardial ketone body utilization was lower in empagliflozin-treated SHHF rats, while glucose utilization and cardiac function were unaltered and hepatic congestion was reduced, compared with vehicle-treated SHHF rats. CONCLUSIONS: In diabetic hypertensive heart disease, empagliflozin reduces afterload without altering myocardial function and glucose utilization in the face of falling blood glucose levels, but does not enhance myocardial ketone utilization despite increased circulating levels.

Asunto(s)

Compuestos de Bencidrilo/uso terapéutico , Espectroscopía de Resonancia Magnética con Carbono-13 , Diabetes Mellitus Experimental , Angiopatías Diabéticas/diagnóstico , Glucosa/metabolismo , Glucósidos/uso terapéutico , Cetonas/metabolismo , Miocardio/metabolismo , Animales , Presión Sanguínea/efectos de los fármacos , Espectroscopía de Resonancia Magnética con Carbono-13/métodos , Diabetes Mellitus Experimental/complicaciones , Diabetes Mellitus Experimental/diagnóstico , Diabetes Mellitus Experimental/tratamiento farmacológico , Diabetes Mellitus Experimental/metabolismo , Angiopatías Diabéticas/metabolismo , Angiopatías Diabéticas/patología , Angiopatías Diabéticas/prevención & control , Corazón/diagnóstico por imagen , Masculino , Miocardio/química , Obesidad/complicaciones , Obesidad/diagnóstico , Obesidad/metabolismo , Obesidad/patología , Ratas , Ratas Endogámicas SHR , Ratas Sprague-Dawley , Aumento de Peso/efectos de los fármacos

RESUMEN

Glycine decarboxylase (GLDC) gene is frequently upregulated in various types of cancer including lung, prostate and brain. It catabolizes glycine to yield 5,10-methylenetetrahydrofolate, an important substrate in one-carbon metabolism for nucleotide synthesis. In this study, we used exon splicing modulating steric hindrance antisense oligonucleotide (shAON) to suppress GLDC expression and investigated its effect on pyruvate metabolism via hyperpolarized carbon-13 magnetic resonance spectroscopy (MRS). The MRS technique allows us to study in vivo metabolic flux in tumor tissues with/without GLDC-shAON intervention. Here, we show that GLDC-shAON treatment is able to suppress lung cancer cell growth and tumorigenesis, both in vitro and in vivo. The carbon-13 MRS results indicated that the conversion of pyruvate into lactate in GLDC-shAON-treated tumor tissues was significantly reduced, when compared with the control groups. This observation corroborated with the reduced activity of lactate dehydrogenase and pyruvate dehydrogenase in GLDC-shAON-treated lung cancer cells and tumor tissues. Glycolysis stress test showed that extracellular acidification rate was significantly suppressed after GLDC-shAON treatment. Besides lung cancer, the antitumor effect of GLDC-shAON was also observed in brain, liver, cervical, and prostate cancer cell lines. Furthermore, it enhanced the treatment efficacy of cisplatin in lung cancer cells. Taken together, our findings illustrate that pyruvate metabolism decreases upon GLDC inhibition, thereby starving cancer cells from critical metabolic fuels.