Iron-Catalyzed Photoredox Alcohol α-C-H Alkylation and Tandem Intramolecular Cyclization: Facile Access to Multisubstituted 2,3-Dihydrofurans and γ-Butyrolactones.

Multisubstituted furans occupy a pivotal position within the realms of synthetic chemistry and pharmacological science due to their distinctive chemical configurations and inherent properties. We herein introduce a tandem difunctionalization protocol of alcohols for the efficient synthesis of multisubstituted 2,3-dihydrofurans and γ-butyrolactones through the combination of photocatalysis and iron catalysis under mild conditions. Photoredox alcohol α-C(sp3)-H activation and Pinner-type intramolecular cyclization are two key processes. This method features significant convenience, economic benefits, and environmental friendliness.

Portable hydrogel kit based on Michael addition reaction for (E)-2-hexenal gas detection.

Plants exhibit rapid responses to biotic and abiotic stresses by releasing a range of volatile organic compounds (VOCs). Monitoring changes in these VOCs holds the potential for the early detection of plant diseases. This study proposes a method for identifying late blight in potatoes based on the detection of (E)-2-hexenal, one of the major VOC markers released during plant infection by Phytophthora infestans. By combining the Michael addition reaction with cysteine-mediated etching of aggregation-induced emission gold nanoclusters (Au NCs), we have developed a portable hydrogel kit for on-site detection of (E)-2-hexenal. The Michael addition reaction between (E)-2-hexenal and cysteine effectively alleviates the etching of cysteine-mediated Au NCs, leading to a distinct fluorescence color change in the Au NCs, enabling a detection limit of 0.61 ppm. Utilizing the superior loading and diffusion characteristics of the three-dimensional structure of agarose hydrogel, our sensor demonstrated exceptional performance in terms of sensitivity, selectivity, reaction time, and ease of use. Moreover, quantitative measurement of (E)-2-hexenal was made easier by using ImageJ software to transform fluorescent images from the hydrogel kit into digital data. Such method was effectively used for the early detection of potato late blight. This study presents a low-cost, portable fluorescent analytical tool, offering a new avenue for on-site detection of plant diseases.

Challenges and applications of volatile organic compounds monitoring technology in plant disease diagnosis.

Biotic and abiotic stresses are well known to increase the emission of volatile organic compounds (VOCs) from plants. The analysis of VOCs emissions from plants enables timely diagnostic of plant diseases, which is critical for prompting sustainable agriculture. Previous studies have predominantly focused on the utilization of commercially available devices, such as electronic noses, for diagnosing plant diseases. However, recent advancements in nanomaterials research have significantly contributed to the development of novel VOCs sensors featuring exceptional sensitivity and selectivity. This comprehensive review presents a systematic analysis of VOCs monitoring technologies for plant diseases diagnosis, providing insights into their distinct advantages and limitations. Special emphasis is placed on custom-made VOCs sensors, with detailed discussions on their design, working principles, and detection performance. It is noteworthy that the application of VOCs monitoring technologies in the diagnostic process of plant diseases is still in its emerging stage, and several critical challenges demand attention and improvement. Specifically, the identification of specific stress factors using a single VOC sensor remains a formidable task, while environmental factors like humidity can potentially interfere with sensor readings, leading to inaccuracies. Future advancements should primarily focus on addressing these challenges to enhance the overall efficacy and reliability of VOCs monitoring technologies in the field of plant disease diagnosis.

Racial/Ethnic Variability in Use of General Anesthesia for Pediatric Magnetic Resonance Imaging.

BACKGROUND: Children increasingly undergo diagnostic imaging procedures, sometimes with general anesthesia (GA). It is unknown whether the use of GA differs by race/ethnicity among children undergoing magnetic resonance imaging (MRI) scans. METHODS: This is a retrospective cohort study of GA use for pediatric patients from 0 to 21 years of age who underwent MRIs from January 1, 2004 to May 31, 2019. The study sample was stratified into 5 age groups: 0 to 1, 2 to 5, 6 to 11, 12 to 18, and 19 to 21. Analysis was performed separately for each age group. RESULTS: Among 457,314 MRI patients, 29,108 (6.4%) had GA. In the adjusted regression models, Asian patients aged 0 to 1 (adjusted relative risk [aRR] [95% confidence interval {CI}] of 1.11 [1.05-1.17], P < .001) and aged 2 to 5 (aRR [95% CI], 1.04 [1.00-1.09], P = .03), Black patients aged 2 to 5 (aRR [95% CI], 1.04 [1.01-1.08], P = .02) and aged 6 to 11 (aRR [95% CI], 1.13 [1.06-1.20], P < .001), and Hispanic patients aged 0 to 1 (aRR [95% CI], 1.07 [1.03-1.12], P < .001) were more likely to receive GA for MRIs than White patients. CONCLUSIONS: Asian, Black, and Hispanic children of some ages were more likely to receive GA during MRI scans than White children in the same age group. Future research is warranted to delineate whether this phenomenon signifies disparate care for children based on their race/ethnicity.

Probabilistic Modeling for Image Registration Using Radial Basis Functions: Application to Cardiac Motion Estimation.

Cardiovascular diseases (CVDs) are the leading cause of death, affecting the cardiac dynamics over the cardiac cycle. Estimation of cardiac motion plays an essential role in many medical clinical tasks. This article proposes a probabilistic framework for image registration using compact support radial basis functions (CSRBFs) to estimate cardiac motion. A variational inference-based generative model with convolutional neural networks (CNNs) is proposed to learn the probabilistic coefficients of CSRBFs used in image deformation. We designed two networks to estimate the deformation coefficients of CSRBFs: the first one solves the spatial transformation using given control points, and the second one models the transformation using drifting control points. The given-point-based network estimates the probabilistic coefficients of control points. In contrast, the drifting-point-based model predicts the probabilistic coefficients and spatial distribution of control points simultaneously. To regularize these coefficients, we derive the bending energy (BE) in the variational bound by defining the covariance of coefficients. The proposed framework has been evaluated on the cardiac motion estimation and the calculation of the myocardial strain. In the experiments, 1409 slice pairs of end-diastolic (ED) and end-systolic (ES) phase in 4-D cardiac magnetic resonance (MR) images selected from three public datasets are employed to evaluate our networks. The experimental results show that our framework outperforms the state-of-the-art registration methods concerning the deformation smoothness and registration accuracy.

Ratiometric Fluorescent Metal-Organic Framework Biosensor for Ultrasensitive Detection of Acrylamide.

Acrylamide is a neurotoxin and carcinogen that forms during the thermal processing of food, inflicting irreversible harm to human health. Herein, a ratiometric fluorescence biosensor based on a 6-carboxyfluorescein-labeled aptamer (FAM-ssDNA) and porphyrin metal-organic framework (PCN-224) was developed. PCN-224 exhibits strong adsorption capacity for FAM-ssDNA and also quenches the fluorescence of FAM-ssDNA via fluorescence resonance energy transfer and photoinduced electron transfer. FAM-ssDNA hybridizes with complementary DNA to form double-stranded DNA (FAM-dsDNA), which is liberated from the PCN-224 surface, resulting in fluorescence recovery. However, the intrinsic fluorescence of the ligand remains unchanged. Acrylamide can create an adduct with FAM-ssDNA and inhibit the hybridization of FAM-dsDNA, thus realizing ratiometric sensing of acrylamide. The proposed biosensor displays excellent detection performance from 10 nM∼0.5 mM with a limit of detection of 1.9 nM. In conclusion, a fabricated biosensor was successfully applied to detect acrylamide in thermally processed food, and the results were consistent with those of high-performance liquid chromatography.

Thermal-controlled active sensor module using enzyme-regulated UiO-66-NH2/MnO2 fluorescence probe for total organophosphorus pesticide determination.

An enzyme-regulated UiO-66-NH2/MnO2 fluorescence sensor, fully functionalized with spectrometric capacities, is developed for budget-friendly total organophosphorus pesticides (OPs) determination. The fluorescence probe, UiO-66-NH2/MnO2, is hydrothermally synthesized and morphologically examined. A specialized enzyme-catalyzed reaction, which can be gradually inhibited by OPs, is designed with participations of alkaline phosphatase (ALP) and sodium L-ascorbyl-2-phosphate (AAP). The reaction product of ascorbic acid (AA) decomposes MnO2 and restores UiO-66-NH2 fluorescence, establishing a relationship between OPs level and fluorescence intensity. Interactions among UiO-66-NH2, MnO2, OPs, and AA are clarified. Stepwise optimizations are performed to the UiO-66-NH2/MnO2 probe, ensuring considerable advantages as OPs affinity and fluorescence quenching behavior over rival nanomaterials. Analytical advances are magnified by fabricating an active sensor module, with self-acting thermal regulation for optimal enzyme activity. Under 4 and 20 °C environment, regulation period is less than 40 and 100 s. In total OPs determination for laboratorial and real-vegetable samples, this method exhibits uniform and log-linear responses to common species of OPs in a range as 1.0 × 10-7~10 mg L-1, and limit of detection is established as 8.9 × 10-8 mg L-1. Proposed readouts are validated with certified HPLC and recovery test. Relative errors and recovery rates are found as 2.7-6.4% and 95.8-102.6%, respectively.

Left ventricle motion estimation for cine MR images using sparse representation with shape constraint.

PURPOSE: To propose a left ventricle (LV) motion estimation method based on sparse representation, in order to handle the spatial-varying intensity distortions caused by tissue deformation. METHODS: For each myocardial landmark, an adaptive dictionary was generated by learning transformations from a training dataset. Then the landmark was tracked using sparse representation. Next, a point distribution model was applied to the overall tracking results. Finally, the dense displacement field of the LV myocardium was estimated based on the correspondence between each landmark. Using the dense displacement field estimated, the circumferential strain was calculated to assess the myocardial function. The performance of the proposed method was quantified by the average perpendicular distance (APD), the Dice metric, and the mean symmetric contour distance (SCD). RESULTS: Comparing to the state-of-the-art techniques, the smallest value of APD and SCD, and the highest value of Dice can be obtained using the proposed method, for three public cardiac datasets. Moreover, the mean value of strain difference between the proposed method and the commercial software Medis Suite MR was -0.01, while the intraclass correlation coefficient between these two methods was 0.91. CONCLUSIONS: The proposed method could estimate the dense displacement field of the LV accurately, which outperforms other state-of-the-art techniques. The circumferential strain derived from the proposed method was in excellent agreement with that derived from the Medis Suite MR software, while segmental strain abnormalities were detected for most of the subjects with heart diseases, which indicates the potential of the proposed method for clinical usage.

A portable test strip based on fluorescent europium-based metal-organic framework for rapid and visual detection of tetracycline in food samples.

Residual tetracycline (TC) in animal food caused by abuse of antibiotics leads to many chronic diseases in the human body. The development of a simple and on-site visualization method for TC detection is need of the hour. Herein, a fluorescent europium-based metal-organic framework (Eu-MOF) sensor for visual and rapid detection of TC was developed. Eu-MOF displays a red emission being excited at 260 nm. Upon exposure to TC, significant fluorescence quenching was observed due to the inner filter effect and photoinduced electron transfer. Moreover, the developed sensor was applied for the detection of TC in milk and beef samples with recoveries of 96.1% to 106.3%, respectively. More importantly, a portable test strip based on Eu-MOF was manufactured. It is a highly selective and sensitive portable device for TC detection. The results can be distinguished immediately by naked eyes, making it become an excellent choice to detect TC in real-time application.

Green one-step synthesis of carbon quantum dots from orange peel for fluorescent detection of Escherichia coli in milk.

Carbon quantum dots (CQDs) prepared by a green one-step approach was used for sensitive and selective assay of Escherichia coli O157: H7 (E. coli). CQDs was synthesized from orange peel as a carbon source via a microwave-assisted method. The CQDs displayed strong green fluorescence under excitation wavelength of 420 nm. A fluorescent probe (CQDs-MNPs) for E. coli was fabricated based on CQDs labeled with aptamer (aptamer-CQDs) and magnetic nanoparticles labeled with complementary DNA (cDNA-MNPs). Fluorescent intensity of the CQDs-MNPs was decreased with addition of E. coli. The linearity between fluorescent intensity and E. coli concentration was used for developing a fluorescent method with detecting range of 500-106 CFU/mL and detection limit of 487 CFU/mL. Milk samples contaminated by E. coli were analyzed by this method, and the results agreed with that achieved by plate-counting methods. This fluorescent probe exhibits great potential in guaranteeing food quality and safety.

Photocatalyst-Free Visible-Light-Promoted C(sp2)-S Coupling: A Strategy for the Preparation of S-Aryl Dithiocarbamates.

We have successfully developed a green and efficient multicomponent reaction protocol to synthesize S-aryl dithiocarbamates under visible light. Most appealingly, the reaction can proceed smoothly without adding any transition-metal catalysts, ligands, or photocatalysts while minimizing chemical wastes and metal residues in the end products. The advantages of this method meet the requirements of sustainable and green synthetic chemistry, and it provides a straightforward way to create valuable S-aryl dithiocarbamates.

Dissolution and homogeneous photocatalysis of polymeric carbon nitride.

As a metal-free conjugated polymer, carbon nitride (CN) has attracted tremendous attention as a heterogeneous (photo)catalyst. By following the example of enzymes, making all of the catalytic sites accessible via homogeneous reactions is a promising approach toward maximizing CN activity, but hindered due to the poor solubility of CN. Herein, we report the dissolution of CN in environmentally friendly methanesulfonic acid, and homogeneous photocatalysis (two biomimetic/pharmaceutical photocatalytic oxidation reactions) driven by CN for the first time with the activity boosted up to 10-times compared to the heterogeneous counterparts. Moreover, facile recycling and reusability, the hallmarks of heterogeneous catalysts, were kept for the homogeneous CN photocatalyst via reversible precipitation using poor solvents. This study opens a new vista for CN in homogeneous catalysis and offers a successful example of a polymeric catalyst that bridges the gap between homo/heterogeneous catalysis.