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The evolution of nature created delicate structures and organisms. With the advancement of technology, especially the rise of additive manufacturing, bionics has gradually become a popular research field. Recently, researchers have concentrated on soft robotics, which can mimic the complex movements of animals by allowing continuous and often responsive local deformations. These properties give soft robots advantages in terms of integration and control with human tissue. The rise of additive manufacturing technologies and soft matters makes the fabrication of soft robots with complex functions such as bending, twisting, intricate 3D motion, grasping, and stretching possible. In this paper, the advantages and disadvantages of the additive manufacturing process, including fused deposition modeling, direct ink writing, inkjet printing, stereolithography, and selective laser sintering, are discussed. The applications of 3D printed soft matter in bionics, soft robotics, flexible electronics, and biomedical engineering are reviewed.

With the huge demands of an aging society, it is urgent to develop a new generation of non-toxic titanium alloy to match the modulus of human bone. Here, we prepared bulk Ti2448 alloys by powder metallurgy technology, and focused on the influence of the sintering process on the porosity, phase composition, and mechanical properties of the initial sintered samples. Furthermore, we performed solution treatment on the samples under different sintering parameters to further adjust the microstructure and phase composition, so as to achieve strength enhancement and reduction of Young’s modulus. Solution treatment can effectively inhibit the continuous α phase precipitated along the grain boundaries of the β matrix, which is beneficial to the fracture resistance. Therefore, the water-quenched sample exhibits good mechanical properties due to the absence of acicular α-phase. Samples sintered at 1400 °C and subsequently water quenched have excellent comprehensive mechanical properties, which benefit from high porosity and the smaller feature size of microstructure. To be specific, the compressive yield stress is 1100 MPa, the strain at fracture is 17.5%, and the Young’s modulus is 44 GPa, which are more applicable to orthopedic implants. Finally, the relatively mature sintering and solution treatment process parameters were screened out for reference in actual production.

With the rapid development of transportation and aerospace, energy consumption and pollutant emissions have increased significantly, putting great pressure on environmental protection. In order to promote the sustainable development of industry, the realization of metal lightweight on the premise of ensuring the comprehensive performance of metal parts has a great role in improving energy efficiency and reducing the emission of pollutants. Lightweight high-entropy alloys (LWHEAs), with excellent mechanical properties, have a broad application prospect in the field of metal lightweight, and have the potential to replace aluminum alloys as the next generation of lightweight metal materials. The research status and preparation methods of LWHEAs in recent years, including metallurgical smelting, powder metallurgy (PM), and additive manufacturing (AM) technologies, were reviewed. The microstructures and mechanical properties of LWHEAs were analyzed. Meanwhile, LWHEAs design strategies were discussed, including thermodynamic criteria, calculation of phase diagrams (CALPHAD), and machine learning (ML). The future research focus of LWHEAs should include the synthesis of new alloy systems and the development of new preparation technologies. The potential applications of LWHEAs in oxidation resistance and corrosion resistance were also discussed. LWHEAs will meet a huge market demand in the field of engineered materials, but many challenges remain, such as the trade-off between high strength and great ductility. We believe that this combination of knowledge may shape the future of LWHEAs, which requires significant breakthroughs in structural design and performance optimization for LWHEAs.

Exposure to toxic metals (TMs) such as lead can cause lifelong neurodevelopmental impairment and other adverse outcomes. TMs enter drinking water from human activity, geogenic contamination, and corrosion of water system components. Several studies report TM contamination in piped systems and private wells in high-income countries (HICs). However, few robust studies report on TM contamination in low- and middle-income countries (LMICs). We characterized the occurrence and investigated sources of TM contamination in 261 rural water systems in three West African LMICs to inform prevention and management. Water samples were collected from 261 community water systems (handpumps and public taps) across rural Ghana, Mali, and Niger. Scrapings were collected from accessible components of a subset of these systems using a drill with acid-washed diamond-tipped bits. Samples were analyzed by inductively coupled plasma (ICP) mass spectrometry or ICP optical emission spectroscopy. Of the TMs studied, lead most frequently occurred at levels of concern in sampled water system components and water samples. Lead mass fractions exceeded International Plumbing Code (IPC) recommended limits (0.25% wt/wt) for components in 82% (107/130) of systems tested; brass components proved most problematic, with 72% (26/36) exceeding IPC limits. Presence of a brass component in a water system increased expected lead concentrations in drinking-water samples by 3.8 times. Overall, lead exceeded World Health Organization (WHO) guideline values in 9% (24/261) of drinking-water samples across countries; these results are broadly comparable to results observed in many HICs. Results did not vary significantly by geography or system type. Ensuring use of lead-free ( ) components in new water systems and progressively remediating existing systems could reduce drinking-water lead exposures and improve health outcomes for millions. However, reflexive decommissioning of existing systems may deprive users of sufficient water for health or drive them to riskier sources. Because supply chains for many water system components are global, TM monitoring, prevention, and management may be warranted in other LMICs beyond the study area as well. https://doi.org/10.1289/EHP7804.

IntroductionClostridioides difficile infection (CDI) causes symptoms of varying severity and negatively impacts patients’ health-related quality of life (HRQL). Despite antibiotic treatment, recurrence of CDI (rCDI) is common and imposes clinical and economic burdens on patients. Fecal microbiota, live-jslm (REBYOTA [RBL]) is newly approved in the USA for prevention of rCDI following antibiotic treatments. We analyzed efficacy and HRQL impact of RBL vs. placebo in patients at first rCDI using data from the phase 3 randomized, double-blind placebo-controlled clinical trial, PUNCH CD3.MethodsThis post hoc analysis included patients at first rCDI fromPUNCH CD3. Treatment success (i.e., absence of diarrhea within 8 weeks post-treatment) was analyzed adjusting for baseline patient characteristics. HRQL was measured using the Clostridioides difficile Quality of Life Survey (Cdiff32); absolute scores and change from baseline in total and domain (physical, mental, and social) scores were summarized and compared between arms. Analyses were conducted for the trial’s blinded phase only.ResultsAmong 86 eligible patients (32.8% of the overall trial population, RBL 53 [61.6%], placebo 33 [38.4%]), RBL-treated patients had significantly lower odds of recurrence (i.e., greater probability of treatment success) at week 8 vs. placebo (odds ratio 0.35 [95% confidence interval 0.13, 0.98]). Probability of treatment success at week 8 was 81% for RBL and 60% for placebo, representing 21% absolute and 35% relative increases for RBL (crude proportions 79.2% vs. 60.6%; relative risk 0.53, p = 0.06). Additionally, RBL was associated with significantly higher Cdiff32 total (change score difference 13.5 [standard deviation 5.7], p < 0.05) and mental domain (16.2 [6.0], p < 0.01) scores vs. placebo from baseline to week 8.ConclusionCompared to placebo, RBL demonstrated a significantly higher treatment success in preventing further rCDI and enhanced HRQL among patients at first recurrence, establishing RBL as an effective treatment to prevent further recurrences in these patients.Trial RegistrationClinicalTrials.gov Identifier NCT03244644.

Introduction: Implementing patient- and family-centered communication strategies has proven challenging in primary care, particularly for persons with dementia. To address this, we designed SHARING Choices, a multicomponent intervention combining patient and family partnered agenda setting, electronic portal access, and supports for advance care planning (ACP). This qualitative descriptive study describes factors affecting SHARING Choices implementation within primary care. Methods: Semi-structured interviews or focus groups with patient/family dyads (family, friends, unpaid caregivers) and primary care stakeholders (clinicians, staff, administrators) elicited perceived barriers and facilitators of SHARING Choices implementation. Field notes and interview transcripts were coded using template analysis along the Consolidated Framework for Implementation Research (CFIR) constructs. Content analysis identified themes not readily categorized within CFIR. Results: About 22 dyads, including 14 with cognitive impairment, and 30 stakeholders participated in the study. Participants were receptive to the SHARING Choices components. Enablers of SHARING Choices included adaptability of the intervention, purposive engagement of family (particularly for patients with dementia), consistency with organizational priorities, and the relative advantage of SHARING Choices compared to current practices. Perceived barriers to implementation included intervention complexity, space constraints, workflow, and ACP hesitancy. The ACP facilitator was perceived as supportive in addressing individual and organizational implementation barriers including patient health and technology literacy and clinician time for ACP discussions. Conclusions: Patients, family, and primary care clinicians endorsed the objectives and individual components of SHARING Choices. Strategies to enhance adoption were to simplify materials, streamline processes, leverage existing workflows, and embed ACP facilitators within the primary care team.

We examined the effects of a communication intervention to engage family care partners on patient portal (MyChart) use, illness understanding, satisfaction with cancer care, and symptoms of anxiety in a single-blind randomized trial of patients in treatment for breast cancer. Patient-family dyads were recruited and randomly assigned a self-administered checklist to clarify the care partner role, establish a shared visit agenda, and facilitate MyChart access (n = 63) or usual care (n = 55). Interviews administered at baseline, 3, 9 (primary endpoint), and 12 months assessed anxiety (GAD-2), mean FAMCARE satisfaction, and complete illness understanding (4 of 4 items correct). Time-stamped electronic interactions measured MyChart use. By 9 months, more intervention than control care partners registered for MyChart (77.8 % vs 1.8%; p < 0.001) and logged into the patient’s account (61.2% vs 0% of those registered; p < 0.001), but few sent messages to clinicians (6.1% vs 0%; p = 0.247). More intervention than control patients viewed clinical notes (60.3% vs 32.7%; p = 0.003). No pre-post group differences in patient or care partner symptoms of anxiety, satisfaction, or complete illness understanding were found. Intervention patients whose care partners logged into MyChart were more likely to have complete illness understanding at 9 months (changed 70.0% to 80.0% vs 69.7% to 54.6%; p = 0.03); symptoms of anxiety were numerically lower (16.7% to 6.7% vs 15.2% to 15.2%; p = 0.24) and satisfaction numerically higher (15.8–16.2 vs 18.0–17.4; p = 0.25). A brief, scalable communication intervention led to greater care partner MyChart use and increased illness understanding among patients with more engaged care partners (NCT03283553).

Mapping protein sequence-function landscapes has either been limited to small steps (only few mutations) or to sequences similar to those already explored by evolution to maintain activity. Here, we overcome both limitations by applying deep-learning guided redesign to a natural protein tyrosine kinase to generate novel, functional sequences with highly combinatorial mutations. Using cell-free assays, we measure the activities and concentrations of 537 redesigned sequences, which differ from the wild-type by an average of 37 mutations while retaining activity in 85% of variants. These sequences sample 436 unique mutations at 76 different positions throughout the kinase domain. A simple regression model identifies key sequence determinants of function and predicts the function of unseen sequences. Our approach demonstrates how integrating deep-learning guided redesign, functional measurement at scale, and interpretable computational modelling enables functional exploration of highly combinatorial and sparse sequence-function landscapes at mutational scales not possible before.

Deep learning has greatly advanced design of highly stable static protein structures, but the controlled conformational dynamics that are hallmarks of natural switch-like signaling proteins have remained inaccessible to de novo design. In this dissertation, I review the fundamental principles and current advances in designing said conformational motions (Chapter 1) and then describe a general deep learning-guided approach for the de novo design of dynamic changes between intra-domain geometries of proteins, similar to switch mechanisms prevalent in nature, with atom-level precision (Chapter 2). In our study, we solved 4 structures validating the designed conformations, showed microsecond transitions between them, and demonstrated that the conformational landscape can be modulated by orthosteric ligands and allosteric mutations. Physics-based simulations were in remarkable agreement with deep learning predictions and experimental data, revealed distinct state-dependent residue interaction networks, and predicted mutations that tuned the designed conformational landscape. Our approach demonstrates that new modes of motion can now be realized through de novo design and provides a framework for constructing biology-inspired, tunable and controllable protein signaling behavior de novo. Finally, in Chapter 3, I discuss key areas where further multi-state tool development is needed and promising applications for de novo dynamics design in the near future.

Although regeneration through the reprogramming of one cell lineage to another occurs in fish and amphibians, it has not been observed in mammals. We discovered in the mouse that during wound healing, adipocytes regenerate from myofibroblasts, a cell type thought to be differentiated and nonadipogenic. Myofibroblast reprogramming required neogenic hair follicles, which triggered bone morphogenetic protein (BMP) signaling and then activation of adipocyte transcription factors expressed during development. Overexpression of the BMP antagonist Noggin in hair follicles or deletion of the BMP receptor in myofibroblasts prevented adipocyte formation. Adipocytes formed from human keloid fibroblasts either when treated with BMP or when placed with human hair follicles in vitro. Thus, we identify the myofibroblast as a plastic cell type that may be manipulated to treat scars in humans.