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Polymer–protein hybrids are intriguing materials that can bolster protein stability in non‐native environments, thereby enhancing their utility in diverse medicinal, commercial, and industrial applications. One stabilization strategy involves designing synthetic random copolymers with compositions attuned to the protein surface, but rational design is complicated by the vast chemical and composition space. Here, a strategy is reported to design protein‐stabilizing copolymers based on active machine learning, facilitated by automated material synthesis and characterization platforms. The versatility and robustness of the approach is demonstrated by the successful identification of copolymers that preserve, or even enhance, the activity of three chemically distinct enzymes following exposure to thermal denaturing conditions. Although systematic screening results in mixed success, active learning appropriately identifies unique and effective copolymer chemistries for the stabilization of each enzyme. Overall, this work broadens the capabilities to design fit‐for‐purpose synthetic copolymers that promote or otherwise manipulate protein activity, with extensions toward the design of robust polymer–protein hybrid materials.

In this work, we present, evaluate, and analyze strategies for representing polymer chemistry to machine learning models for the advancement of data-driven sequence or composition design of macromolecules.

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Among the many molecules that contribute to glial scarring, chondroitin sulfate proteoglycans (CSPGs) are known to be potent inhibitors of neuronal regeneration. Chondroitinase ABC (ChABC), a bacterial lyase, degrades the glycosaminoglycan (GAG) side chains of CSPGs and promotes tissue regeneration. However, ChABC is thermally unstable and loses all activity within a few hours at 37 °C under dilute conditions. To overcome this limitation, the discovery of a diverse set of tailor-made random copolymers that complex and stabilize ChABC at physiological temperature is reported. The copolymer designs, which are based on chain length and composition of the copolymers, are identified using an active machine learning paradigm, which involves iterative copolymer synthesis, testing for ChABC thermostability upon copolymer complexation, Gaussian process regression modeling, and Bayesian optimization. Copolymers are synthesized by automated PET-RAFT and thermostability of ChABC is assessed by retained enzyme activity (REA) after 24 h at 37 °C. Significant improvements in REA in three iterations of active learning are demonstrated while identifying exceptionally high-performing copolymers. Most remarkably, one designed copolymer promotes residual ChABC activity near 30%, even after one week and notably outperforms other common stabilization methods for ChABC. Together, these results highlight a promising pathway toward sustained tissue regeneration.

The activity-stability conundrum has long been the Achilles' heel in the design of catalysts, in particular, for electrochemical reactions such as water splitting. Here, we use ab-initio thermodynamics to delineate...

Atopic dermatitis, commonly known as eczema, is a common chronic, relapsing skin disease characterized by pruritus, disrupted epidermal barrier function, and immunoglobulin E-mediated sensitization to food and environmental allergens. Atopic dermatitis is a complex disease that arises from interactions between genes and the environment. Loci on several chromosomes have been identified, including a family of epithelium-related genes called the epidermal differentiation complex on chromosome 1q21. Mutations in filaggrin, a key protein in epidermal differentiation, have also been identified in early-onset and severe atopic dermatitis. There are 3 classical stages of eczema: infantile, childhood, and adulthood. The spectrum of eczema presentation varies widely from a variant that only affect the hand to major forms where a patient presents with erythroderma. The acute and subacute lesions of atopic dermatitis are often characterized by intensely pruritic, erythematous papules and vesicles with excoriations and a serous exudate. Chronic atopic dermatitis is exemplified by lichenified plaques and papules with excoriations. Atopic dermatitis patients are also at higher risk for skin infections, including bacterial and viral superinfections. Conventional therapy includes avoidance of irritants and potential allergens, as well as continued hydration of the skin with thick emollients. Topical corticosteroids and topical immunomodulators are often used primarily. Other therapies including phototherapy, antimicrobials, antihistamines, and systemic immunosuppressives are also options in certain situations.

Difficulty in accessing a new arteriovenous fistula (AVF) is a common technical issue in hemodialysis patients, which often leads to interventional radiology and/or vascular surgery referral. As a consequence, the patient who needs dialysis may require a temporary dialysis catheter with its known potential complications. We present a case where bedside ultrasonography facilitated successful cannulation of a difficult AVF. Ultrasonography (US) training in this procedure may allow early cannulation of new AVFs when the venous diameter is large enough (>0.6 cm) but the fistula is too deep (>0.6 cm). Real-time, US-guided AVF cannulation may also decrease the number of failed venous punctures per hemodialysis (HD) session minimizing vessel wall damage and subsequent potential hematoma and aneurysm formation.