IIT@MIT

Cytokines dimerize two receptor chains to activate Janus kinases and STAT transcription factors that regulate immune cells but have therapeutic liabilities. We engineered “Trikines” to compel cis formation of three-chain cytokine receptor complexes at the cell surface that induce bespoke STAT transcriptional signaling programs optimized for therapeutic efficacy. Designed Trikines co-activated pSTAT5 and pSTAT3 signatures distinct from any natural cytokines, by assembling trimeric combinations of Interleukin-2 (IL-2), Interleukin-10 (IL-10), and Interleukin-21 (IL-21) receptors. An IL-2-based-Trikine restrained terminal differentiation of T cells, promoted stemness, and enhanced durability of tumor control without toxicity. Unexpectedly, an IL-10-based Trikine induced immune infiltration into poorly immunogenic tumors, showing striking efficacy in small cell lung cancer and pancreatic cancer models. Trikines obviate the need for cell engineering to customize STAT signatures for immunotherapy.

Past research has widely explored the design and fabrication of resistive matrix-based tactile sensors for creating touch-sensitive devices. However, real-world deployment of resistive tactile sensing systems remains difficult for individuals with limited prior experience in embedded sensing due to challenges of portability, adaptivity, and efficiency. We introduce the WiReSens Toolkit, an accessible, open-source platform to bridge this gap. Central to our approach is adaptive hardware for interfacing with resistive sensors and a web-based GUI that streamlines access to advanced features for building scalable tactile sensing systems, including multi-device programming and wireless visualization across three communication protocols, autocalibration for adaptive sensitivity, and intermittent data transmission for low-power use. We validated the toolkit’s usability through a user study with 11 novice participants, who, on average, configured a tactile sensor with over 95% accuracy in under five minutes, calibrated sensors 10× faster than baseline methods, and showed improved sense-making of tactile data.

This studio explores rapid prototyping of shape-morphing fabrics as tangible interfaces by combining parametric modeling tools with accessible 3D printing techniques. Participants will experiment with two textile-based fabrication methods: (1) 3D printing on pre-stretched textiles for programmable morphing, and (2) printing TPU-based modular mesh structures with varying parameters to explore material properties. Through hands-on exercises, participants will investigate how material parameters—such as pattern, scale, thickness, and density—define fundamental rules for shape morphing and enable the creation of responsive, expressive, and multi-stable tangible artifacts. Emphasizing thinking-through-design for desired material behaviors, the studio invites HCI researchers and designers to collaboratively explore and critically reflect on the benefits, limitations, and future integration of shape-morphing interfaces.

Color-changing materials, such as photochromic pigments, allow objects to have reprogrammable multicolor surface images. Existing systems that reprogram these images are based on projectors and LEDs, each with advantages and limitations in device portability and image resolution. In this paper, we present ChromoLCD, a surface reprogrammer that uses a liquid crystal display (LCD) to achieve a compact handheld device without sacrificing image resolution. ChromoLCD consists of an LCD panel with a custom backlight containing R,G,B and UV LEDs, forming high-resolution light patterns with the required wavelengths. The compact form factor of ChromoLCD enables on-the-fly reprogramming of everyday surfaces. Our technical evaluation shows that ChromoLCD achieves a resolution of 25 ppi, which is 8 times better than the prior work. We demonstrate ChromoLCD with three applications, including the stamping of reprogrammable AR markers on a kitchen counter, on-the-fly designs on personal accessories, and reference pictures on a whiteboard.

Mouse CD8 T cell differentiation has been studied extensively in models of infections and cancer, yet no unified framework spans the full spectrum of immunological contexts. We present the CD8 immgenT framework, integrating >200,000 single-cell transcriptomes and 128-plex surface proteomes from 734 samples spanning multiple perturbations, tissues, and timepoints. Unbiased analysis identifies 21 states encompassing naive, effector, circulating memory, tissue-resident memory, progenitor-exhausted, and terminally-exhausted compartments, among others. These states re-emerge with striking molecular convergence across acute/chronic infections, cancer, autoimmunity, aging, and homeostasis, showing that near-identical transcriptional programs support protective or dysfunctional outcomes depending on developmental history and microenvironment. Classic archetypes map to discrete clusters but exhibit unappreciated heterogeneity and overlap, cautioning against rigid nomenclature. We provide validated combinatorial markers, flow cytometry gating strategies, and immgenT reference-based integration for reproducible annotation of new datasets. This universal coordinate system harmonizes fragmented CD8 T cell literature and clarifies relationships across diverse immune challenges.

Abstract Grain growth, governed by the mobility and migration mechanisms of grain boundaries, is a fundamental process shaping the microstructure and properties of polycrystalline materials. This article explores the critical interplay between solute adsorption, disconnections, and complexion transitions in determining grain-boundary behavior. Traditional models based on curvature-driven motion are insufficient, as experimental and computational studies reveal complex mechanisms, including disconnection-mediated migration and transitions in structure or interface excess concentration. Solute atoms not only exert classical drag effects, but can also catalyze or suppress mobility by altering activation energies for disconnection formation or modifying boundary structures. The concept of grain-boundary complexions provides a thermodynamic framework for understanding structural and chemical transitions at interfaces, with direct implications for mobility. Special attention is given to ionic systems, where charge effects and electric fields further influence migration. Collectively, these insights highlight new strategies for tailoring grain growth to engineer advanced materials. Graphical abstract

Upon hearing objects collide, humans can estimate physical attributes such as material and mass. Although the physics of sound generation is well established, the inverse problem that listeners solve - of inferring physical parameters from sound - remains poorly understood. Classical accounts posit the use of acoustic cues that correlate with physical variables, but do not explain how humans might distinguish multiple concurrent physical causes. To study this problem, we built a probabilistic generative model of impact sounds, combining theoretical acoustics with statistics of object resonances measured from hundreds of everyday objects, and used it to synthesize and manipulate experimental stimuli. Humans accurately judged object properties from collision sounds. However, when both of the colliding objects varied, performance was impaired if the distribution of object resonances deviated from those measured in real-world objects. The results suggest that listeners use internal physical models to separate the acoustic contributions of objects in the world.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and long COVID are debilitating multisystem illnesses with overlapping symptoms and poorly understood mechanisms. Female sex is a major risk factor, and preliminary evidence links sex hormones and other fluctuating endocrine hormones, including cortisol, aldosterone, and DHEA, to these conditions. However, existing studies have not comprehensively captured diurnal, infradian, and circadian biorhythms, leaving critical gaps in understanding. The MELLOW study (ME/CFS + Long COVID Longitudinal Omics and Women’s Health) is a prospective, chronobiology-based study of reproductive-aged women with ME/CFS, long COVID, and healthy controls. It integrates menstrual-phase and diurnal sampling with multi-omics profiling (genomics, proteomics, metabolomics, lipidomics, steroidomics), physiological monitoring, and symptom tracking. By accounting for natural and disrupted biorhythms, MELLOW will map temporal links between hormonal, molecular, physiological, and symptom dynamics, improving biomarker reproducibility and clarifying endocrine network disruption underlying ME/CFS, long COVID, and women’s health more broadly.