Label-free Raman spectroscopy reveals tumor microenvironmental changes induced by intermittent fasting for the prevention of breast cancer in animal model.

The development of tools that can provide a holistic picture of the evolution of the tumor microenvironment in response to intermittent fasting on the prevention of breast cancer is highly desirable. Here, we show, for the first time, the use of label-free Raman spectroscopy to reveal biomolecular alterations induced by intermittent fasting in the tumor microenvironment of breast cancer using a dimethyl-benzanthracene induced rat model. To quantify biomolecular alterations in the tumor microenvironment, chemometric analysis of Raman spectra obtained from untreated and treated tumors was performed using multivariate curve resolution-alternative least squares and support vector machines. Raman measurements revealed remarkable and robust differences in lipid, protein, and glycogen content prior to morphological manifestations in a dynamically changing tumor microenvironment, consistent with the proteomic changes observed by quantitative mass spectrometry. Taken together with its non-invasive nature, this research provides prospective evidence for the clinical translation of Raman spectroscopy to identify biomolecular variations in the microenvironment induced by intermittent fasting for the prevention of breast cancer, providing new perspectives on the specific molecular effects in the tumorigenesis of breast cancer.

Cobalt-Catalyzed Selective Hydroboration of 1,3-Enynes with HBpin toward 1,3-Dienylboronate Esters.

An efficient cobalt-catalyzed selective hydroboration of 1,3-enynes with HBpin toward 1,3-dienylboronate esters is disclosed. With a commercially available catalytic system of Co(acac)2 and dppf, the hydroboration reactions proceeded well to afford a wide range of 1,3-dienylborates in moderate to high yields. This protocol features a cheap base-metal catalytic system, broad substrate scope, excellent selectivity, easy gram-scale preparation, and good functional group tolerance and provides access to synthetically valuable 1,3-dienylborates.

Interpretable Machine Learning To Accelerate the Analysis of Doping Effect on Li/Ni Exchange in Ni-Rich Layered Oxide Cathodes.

In Ni-rich layered oxide cathodes, one effective way to adjust the performance is by introducing dopants to change the degree of Li/Ni exchange. We calculated the formation energy of Li/Ni exchange defects in LiNi0.8Mn0.1X0.1O2 with different doping elements X, using first-principles calculations. We then proposed an interpretable machine learning method combining the Random Forest (RF) model and the Shapley Additive Explanation (SHAP) analysis to accelerate identification of the key factors influencing the formation energy among the complex variables introduced by doping. The valence state of the doping element effectively regulates Li/Ni exchange defects through changing the valence state of Ni and the strength of the superexchange interaction, and COOPSU-SD and MagO were proposed as two indicators to assess superexchange interaction. The volume change also affects the Li/Ni exchange defects, with a larger volume reduction corresponding to fewer Li/Ni exchange defects.

Human vulnerability assessment based on bullet motion and cavity expansion model with tissue identification.

In human vulnerability assessment, the wound characteristics are derived from a single soft media penetration experiment, and there is a lack of mathematical model or algorithm to accurately describe the bullet motion (consider bullet rolling) and temporary cavity variation during bullet penetration into different soft media. This paper derives a bullet motion and cavity expansion-contraction model for bullet penetration into soft tissue; Established a dynamic wound reconstruction model based on neural networks that considers tissue differences. Assessment of damage to tissues using the Abbreviated Injury Scale; Developed software for assessing human vulnerability based on dynamic wound reconstruction. Research results show that the bullet motion model and the cavity expansion-contraction model can predict the characteristic volume of the wound and the temporary cavity profile changes during bullet penetration more accurately; the maximum temporary cavity diameters of the muscle wound, the cardiac wound, and the muscle-cardiac-muscle coupling wound are 183.6, 158.06, and 174.74 mm respectively, and using the cavity in a single target as the basis for human injury assessment will introduce errors. The process of bullet penetration into soft tissue can be accurately described based on a predictive model that considers tissue differences. This paper provides the model that improves the accuracy of human injury assessment compared to existing penetration models.

Derived the bullet motion model and temporary cavity expansion- contraction model when the projectile penetrates a soft medium.Derived a dynamic wound reconstruction model based on feed-forward neural networks that considers tissue variation.Developed a wound visualization program that is more consistent with experimental phenomena.Analysis of the differences in wound channels when projectile penetrating different tissues shows that using the results of penetrating a single medium as the basis for assessment introduces errors.

Asymmetric Oxidative Lactonization of Enynyl Boronates.

Oxidation of C-B bonds is extensively used in organic synthesis, materials science, and chemically biology. However, these oxidations are usually limited to the oxidation of C(sp3 )-B and C(sp2 )-B bonds. The C(sp)-B bond oxidation is rarely developed. Herein we present a novel strategy for the preparation of γ-lactones via the oxidation of enynyl boronates. This process successively involves the C(sp)-B bond oxidation, the epoxidation of C-C double bond and the lactonization. This protocol provided various γ-lactones and unsaturated butenolides efficiently that are prevalent in numerous nature products and bioactive molecules. Most importantly, asymmetric oxidative lactonization of enynyl boronates was also achieved, providing chiral γ-lactones in high enantioselectivities and diastereoselectivities. The versatile transformations and ubiquity of γ-lactones shed light on the importance of this strategy in the construction and late-stage functionalization of complex molecules.

Iron Single Atoms Anchored on Carbon Matrix/g-C3N4 Hybrid Supports by Single-Atom Migration-Trapping Based on MOF Pyrolysis.

Numerous efforts have been devoted to realizing the high loading and full utilization of single-atom catalysts (SACs). As one of the representative methods, atom migration-trapping (AMT) is a top-down strategy that converts a certain volume of metal nanoparticles (NPs) or metal-based precursors into mobile metal species at high temperature, which can then be trapped by suitable supports. In this study, high-loading iron single atoms anchored onto carbon matrix/g-C3N4 hybrid supports were obtained through a single-atom migration-trapping method based on metal-organic framework (MOF) pyrolysis. It is confirmed, by high-angle annular dark field scanning transmission electron microscopy (HAADF-STEM), X-ray absorption near-edge structure (XANES) and extended X-ray absorption fine structure (EXAFS), that the Fe(acac)3 precursor is reduced to Fe single atoms (SAs), which are not only anchored onto the original N-doped carbon (NC), but also onto g-C3N4, with an Fe-N coordination bond. Further electrochemical results reveal that Fe-C3N4-0.075 possesses a better half-wave potential of 0.846 V and onset potential of 0.96 V compared to Fe-N-C, the product obtained after pyrolysis of Fe(acac)3@ZIF-8. As opposed to SAs prepared by the pyrolysis process only, SAs prepared by AMT are commonly anchored onto the surface of the supports, which is a simple and effective way to make full use of the source metal and prepare SACs with higher exposing active sites.

Iron Single Atoms Anchored on Nitrogen-Doped Carbon Matrix/Nanotube Hybrid Supports for Excellent Oxygen Reduction Properties.

Single-atom non-precious metal oxygen reduction reaction (ORR) catalysts have attracted much attention due to their low cost, high selectivity, and high activity. Herein, we successfully prepared iron single atoms anchored on nitrogen-doped carbon matrix/nanotube hybrid supports (FeSA-NC/CNTs) by the pyrolysis of Fe-doped zeolitic imidazolate frameworks. The nitrogen-doped carbon matrix/carbon nanotube hybrid supports exhibit a specific surface area of 1626.814 m2 g-1, which may facilitate electron transfer and oxygen mass transport within the catalyst and be beneficial to ORR performance. Further electrochemical results revealed that our FeSA-NC/CNTs catalyst exhibited excellent ORR activity (half-wave potential: 0.86 V; kinetic current density: 39.3 mA cm-2 at 0.8 V), superior to that of commercial Pt/C catalyst (half-wave potential: 0.846 V; kinetic current density: 14.4 mA cm-2 at 0.8 V). It also has a great stability, which makes it possible to be a valuable non-noble metal electrode material that may replace the latest commercial Pt/C catalyst in the future.

Metal-Organic Framework-Derived Graphene Mesh: a Robust Scaffold for Highly Exposed Fe-N4 Active Sites toward an Excellent Oxygen Reduction Catalyst in Acid Media.

This study demonstrates a special ultrathin N-doped graphene nanomesh (NGM) as a robust scaffold for highly exposed Fe-N4 active sites. Significantly, the pore sizes of the NGM can be elaborately regulated by adjusting the thermal exfoliation conditions to simultaneously disperse and anchor Fe-N4 moieties, ultimately leading to highly loaded Fe single-atom catalysts (SA-Fe-NGM) and a highly exposed morphology. The SA-Fe-NGM is found to deliver a superior oxygen reduction reaction (ORR) activity in acidic media (half-wave potential = 0.83 V vs RHE) and a high power density of 634 mW cm-2 in the H2/O2 fuel cell test. First-principles calculations further elucidate the possible catalytic mechanism for ORR based on the identified Fe-N4 active sites and the pore size distribution analysis. This work provides a novel strategy for constructing highly exposed transition metals and nitrogen co-doped carbon materials (M-N-C) catalysts for extended electrocatalytic and energy storage applications.

Azobenzene-containing liquid crystalline composites for robust ultraviolet detectors based on conversion of illuminance-mechanical stress-electric signals.

Wearable ultraviolet (UV) detectors have attracted considerable interest in the military and civilian realms. However, semiconductor-based UV detectors are easily interfered by elongation due to the elastic modulus incompatibility between rigid semiconductors and polymer matrix. Polymer detectors containing UV responsive moieties seriously suffer from slow response time. Herein, a UV illuminance-mechanical stress-electric signal conversion has been proposed based on well-defined ionic liquid (IL)-containing liquid crystalline polymer (ILCP) and highly elastic polyurethane (TPU) composite fabrics, to achieve a robust UV monitoring and shielding device with a fast response time of 5 s. Due to the electrostatic interactions and hydrogen bonds between ILs and LC networks, the ILCP-based device can effectively prevent the exudation of ILs and maintain stable performance upon stretching, bending, washing and 1000 testing cycles upon 365 nm UV irradiation. This work provides a generalizable approach toward the development of full polymer-based wearable electronics and soft robots.