In recent years, significant efforts have been focused into understanding metabolic reprogramming in cancer with the hope of discerning context-specific biology that is exploitable for either for diagnosis or treatment. While some generalized phenomena such as the ‘Warburg Effect’ have been identified, the metabolic landscape of cancer is highly heterogeneous, as tumors from the same sub-type can exhibit vastly different metabolic profiles, which can influence disease progression and response to treatments.

While there has been a recent emphasis in the field of chemistry education research on bridging the gap between research and practice, another important divide warrants attention: the growing gap between undergraduate academia and chemical industry. According to recent American Chemical Society data, approximately 70% of chemistry graduates enter industry directly after earning their bachelor’s degree. However, little is known about how these graduates transition into industry roles.

Spintronics are a class of electronics that utilize the intrinsic spin of electrons rather than the flow of charge through a circuit. As a result, they are more energy efficient and faster than conventional electronics and are critical in advancing quantum computing, information sciences, and wearable technologies. Current spintronic designs are composed of heterostructures of stacked thin films of ferromagnetic materials in combination with either antiferromagnetic or nonmagnetic materials.

Plastic plays an important role in modern life, but it also brings sustainability challenges due to its persistence in the environment and the lack of green end-of-life options. Researchers have been actively working on new strategies to mitigate these concerns and produce sustainable alternatives for specifically single-use applications. Cellulose acetate, a cellulose-derived monomer, has emerged as a promising alternative. It offers tunable properties through its degree of substitution, allowing a balance between durability and biodegradability.

Techniques for the detection of extremely high mass ions or the analysis of heterogenous samples in mass spectrometry are often limited by overlapping charge states and poor resolution.¹ The invention of electrospray ionization allowed for ionization of increasingly larger ions in mass spectrometry where multiple charging allows for the mass-to-charge ratio to be much lower than the molecular mass.² In traditional mass spectrometry, the mass-to-charge ratio is measured and then the charge of the ion is deduced from the spacing of isotope pe

Food packaging materials extensively utilize PFAS compounds for their exceptional grease and moisture resistance properties, yet their environmental persistence and potential health implications necessitate robust analytical methodologies.¹ The primary analytical challenges arise from PFAS structural diversity, ultra-trace concentrations, and complex matrix interference from packaging substrates.

Azulene, a 10-π-electron aromatic molecule, is widely used as a test system due to its bright S₂ singlet state, exhibiting anti-Kasha behavior. Despite extensive studies, its gas-phase time dynamics remain controversial. We revisited Azulene in a jet-cooled molecular beam to address these dynamics with a newly developed Ultrafast Resonance-Enhanced Multiphoton Ionization (REMPI) system. In addition, we obtained the first gas-phase REMPI spectrum of the Azulene dimer.

Neuronal calcium sensors (NCS), including neuronal calcium sensor 1 (NCS1) and downstream regulatory element antagonist modulator (DREAM), constitute a family of calcium-binding proteins involved in a wide range of physiological and pathological processes. These include neuronal development, exocytosis, learning and memory, pain perception, and the progression of disorders such as Alzheimer’s and Parkinson’s diseases, autism, and cancer.

De novo protein design has experienced a renaissance in recent years due to advances in generative diffusion-based approaches to develop high affinity, target-specific binders. However, the ability of these tools to generate “new-to-nature” proteins with unique backbones and amino acid sequences that target lipid/protein assemblies has not yet been explored. Here, we apply an end-to-end design pipeline using RFdiffusionAA, LigandMPNN, Chai-1, and Rosetta to develop lipid antigen/CD1-restricted T cell receptor (TCR) mimics.