This paper reports a scalable approach to achieve spatially selective graphene functionalization using multiscale wrinkles. Graphene wrinkles were formed by relieving the strain in thermoplastic polystyrene substrates conformally coated with fluoropolymer and graphene skin layers. Chemical reactivity of a fluorination process could be tuned by changing the local curvature of the graphene nanostructures. Patterned areas of graphene nanowrinkles and crumples followed by a single-process plasma reaction resulted in substrates with regions having different fluorination levels. Notably, conductivity of the functionalized graphene nanostructures could be locally tuned as a function of feature size without affecting the mechanical properties.

Ultrasensitive detection, mapping, and monitoring of the activity of cancer cells is critical for treatment evaluation and patient care. Here, we demonstrate that a cancer cell's glycolysis-induced hyperactivity and enhanced electronegative membrane (from sialic acid) can sensitively modify the second-order overtone of in-plane phonon vibration energies (2D) of interfaced graphene via a hole-doping mechanism. By leveraging ultrathin graphene's high quantum capacitance and responsive phononics, we sensitively differentiated the activity of interfaced Glioblastoma Multiforme (GBM) cells, a malignant brain tumor, from that of human astrocytes at a single-cell resolution. GBM cell's high surface electronegativity (potential ∼310 mV) and hyperacidic-release induces hole-doping in graphene with a 3-fold higher 2D vibration energy shift of approximately 6 ± 0.5 cm than astrocytes. From molecular dipole-induced quantum coupling, we estimate that the sialic acid density on the cell membrane increases from one molecule per ∼17 nm to one molecule per ∼7 nm. Furthermore, graphene phononic response also identified enhanced acidity of cancer cell's growth medium. Graphene's phonon-sensitive platform to determine interfaced cell's activity/chemistry will potentially open avenues for studying activity of other cancer cell types, including metastatic tumors, and characterizing different grades of their malignancy.

†Indicates equal contribution Multiplexed analysis of single-cells enables accurate modeling of cellular behaviors, classification of new cell types, and characterization of their functional states. Here we present proximity-sequencing (Prox-seq), a method for simultaneous measurement of an individual cell's proteins, protein complexes and mRNA. Prox-seq utilizes deep sequencing and barcoded proximity assays to measure proteins and their complexes from all pairwise combinations of targeted proteins, in thousands of single-cells. The number of measured protein complexes scales quadratically with the number of targeted proteins, providing unparalleled multiplexing capacity. We developed a high-throughput experimental and computational pipeline and demonstrated the potential of Prox-Seq for multi-omic analysis with a panel of 13 barcoded proximity probes, enabling the

Amyotrophic lateral sclerosis (ALS) is the most common adult-onset motor neuron disease (MND) characterized by a rapid loss of upper and lower motor neurons resulting in patient death from respiratory failure within 3−5 years of initial symptom onset. Although at least 30 genes of major effect have been reported, the pathobiology of ALS is not well understood. Compounding this is the lack of a reliable laboratory test which can accurately diagnose this rapidly deteriorating disease. Herein, we report on the phonon vibration energies of graphene as a sensitive measure of the composite dipole moment of the interfaced cerebrospinal fluid (CSF) that includes a signature-composition specific to the patients with ALS disease. The second-order overtone of in-plane phonon vibration energy (2D peak) of graphene shifts by 3.2 ± 0.5 cm −1 for all ALS patients studied in this work. Further, the amount of ndoping-induced shift in the phonon energy of graphene, interfaced with CSF, is specific to the investigated neurodegenerative disease (ALS, multiple sclerosis, and MND). By removing a severe roadblock in disease detection, this technology can be applied to study diagnostic biomarkers for researchers developing therapeutics and clinicians initiating treatments for neurodegenerative diseases.

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