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Abstract Dynamic tracking of spinal instrumentation could facilitate real-time evaluation of hardware integrity and in so doing alert patients/clinicians of potential failure(s). Critically, no method yet exists to continually monitor the integrity of spinal hardware and by proxy the process of spinal arthrodesis; as such hardware failures are often not appreciated until clinical symptoms manifest. Accordingly, herein, we report on the development and engineering of a bio-adhesive metal detector array (BioMDA), a potential wearable solution for real-time, non-invasive positional analyses of osseous implants within the spine. The electromagnetic coupling mechanism and intimate interfacial adhesion enable the precise sensing of the metallic implants position without the use of radiation. The customized decoupling models developed facilitate the precise determination of the horizontal and vertical positions of the implants with incredible levels of accuracy (e.g.,

Abstract Ingestible electronics have the capacity to transform our ability to effectively diagnose and potentially treat a broad set of conditions. Current applications could be significantly enhanced by addressing poor electrode-tissue contact, lack of navigation, short dwell time, and limited battery life. Here we report the development of an ingestible, battery-free, and tissue-adhering robotic interface (IngRI) for non-invasive and chronic electrostimulation of the gut, which addresses challenges associated with contact, navigation, retention, and powering (C-N-R-P) faced by existing ingestibles. We show that near-field inductive coupling operating near 13.56 MHz was sufficient to power and modulate the IngRI to deliver therapeutically relevant electrostimulation, which can be further enhanced by a bio-inspired, hydrogel-enabled adhesive interface. In swine models, we demonstrated the electrical interaction of IngRI with the gastric mucosa by recording conductive signaling from the subcutaneous space. We further observed changes in plasma ghrelin levels, the “hunger hormone,” while IngRI was activated in vivo, demonstrating its clinical potential in regulating appetite and treating other endocrine conditions. The results of this study suggest that concepts inspired by soft and wireless skin-interfacing electronic devices can be applied to ingestible electronics with potential clinical applications for evaluating and treating gastrointestinal conditions.

Individuals with glaucoma are routinely prescribed and required to self-administer eye drop-based medication multiple times a day. Unfortunately, the process of self-administering eye drops requires a level of dexterity, strength, and visual acuity that the elderly population often do not possess, resulting in poor adherence and worsening condition. In this paper, we detail a prototyped eye drop assist device designed to safely and reliably deliver prescription medications. The ergonomic device safely anchors the eye drop bottle tip an optimal distance away from the face, aligns to the pupil, and provides feedback to the user when their head is at an appropriate tilt for a successful eye drop administration. We experimentally verify that the device improves hand steadiness, provides accurate head tilt feedback, precisely positions the bottle tip, and predictably delivers eye drops into the eye according to a parameterized model.

Abstract Point‐of‐care (POC) has the capacity to support low‐cost, accurate and real‐time actionable diagnostic data. Microneedle sensors have received considerable attention as an emerging technique to evolve blood‐based diagnostics owing to their direct and painless access to a rich source of biomarkers from interstitial fluid. This review systematically summarizes the recent innovations in microneedle sensors with a particular focus on their utility in POC diagnostics and personalized medicine. The integration of various sensing techniques, mostly electrochemical and optical sensing, has been established in diverse architectures of “lab‐on‐a‐microneedle” platforms. Microneedle sensors with tailored geometries, mechanical flexibility, and biocompatibility are constructed with a variety of materials and fabrication methods. Microneedles categorized into four types: metals, inorganics, polymers, and hydrogels, have been elaborated with state‐of‐the‐art bioengineering strategies for minimally invasive, continuous, and multiplexed sensing. Microneedle sensors have been employed to detect a wide range of biomarkers from electrolytes, metabolites, polysaccharides, nucleic acids, proteins to drugs. Insightful perspectives are outlined from biofluid, microneedles, biosensors, POC devices, and theragnostic instruments, which depict a bright future of the upcoming personalized and intelligent health management.

Abstract Modulation of autophagy, specifically its inhibition, stands to transform the capacity to effectively treat a broad range of cancers. However, the clinical efficacy of autophagy inhibitors has been inconsistent. To delineate clinical and epidemiological features associated with autophagy inhibition and a positive oncological clinical response, a retrospective analysis of patients is conducted treated with hydroxychloroquine, a known autophagy inhibitor. A direct correlation between smoking status and inhibition of autophagy with hydroxychloroquine is identified. Recognizing that smoking is associated with elevated circulating levels of carbon monoxide (CO), it is hypothesized that supplemental CO can amplify autophagy inhibition. A novel, gas‐entrapping material containing CO in a pre‐clinical model is applied and demonstrated that CO can dramatically increase the cytotoxicity of autophagy inhibitors and significantly inhibit the growth of tumors when used in combination. These data support the notion that safe, therapeutic levels of CO can markedly enhance the efficacy of autophagy inhibitors, opening a promising new frontier in the quest to improve cancer therapies.

Abstract Increasing the intensity of tumor treating fields (TTF) within a tumor bed improves clinical efficacy, but reaching sufficiently high field intensities to achieve growth arrest remains challenging due in part to the insulating nature of the cranium. Using MRI-derived finite element models (FEMs) and simulations, we optimized an exhaustive set of intracranial electrode locations to obtain maximum TTF intensities in three clinically challenging high-grade glioma (HGG) cases (i.e., thalamic, left temporal, brainstem). Electric field strengths were converted into therapeutic enhancement ratios (TER) to evaluate the predicted impact of stimulation on tumor growth. Concurrently, conventional transcranial configurations were simulated/optimized for comparison. Optimized intracranial TTF were able to achieve field strengths that have previously been shown capable of inducing complete growth arrest, in 98–100% of the tumor volumes using only 0.54–0.64 A current. The reconceptualization of TTF as a targeted, intracranial therapy has the potential to provide a meaningful survival benefit to patients with HGG and other brain tumors, including those in surgically challenging, deep, or anatomically eloquent locations which may preclude surgical resection. Accordingly, such an approach may ultimately represent a paradigm shift in the use of TTFs for the treatment of brain cancer.

Abstract Oral delivery of therapeutics is the preferred route of administration due to ease of administration which is associated with greater patient medication adherence. One major barrier to oral delivery and intestinal absorption is rapid clearance of the drug and the drug delivery system from the gastrointestinal (GI) tract. To address this issue, researchers have investigated using GI mucus to help maximize the pharmacokinetics of the therapeutic; while mucus can act as a barrier to effective oral delivery, it can also be used as an anchoring mechanism to improve intestinal residence. Nano-drug delivery systems that use materials which can interact with the mucus layers in the GI tract can enable longer residence time, improving the efficacy of oral drug delivery. This review examines the properties and function of mucus in the GI tract, as well as diseases that alter mucus. Three broad classes of mucus-interacting systems are discussed: mucoadhesive, mucus-penetrating, and mucolytic drug delivery systems. For each class of system, the basis for mucus interaction is presented, and examples of materials that inform the development of these systems are discussed and reviewed. Finally, a list of FDA-approved mucoadhesive, mucus-penetrating, and mucolytic drug delivery systems is reviewed. In summary, this review highlights the progress made in developing mucus-interacting systems, both at a research-scale and commercial-scale level, and describes the theoretical basis for each type of system.

Abstract Tumor hypoxia drives resistance to many cancer therapies, including radiotherapy and chemotherapy. Methods that increase tumor oxygen pressures, such as hyperbaric oxygen therapy and microbubble infusion, are utilized to improve the responses to current standard‐of‐care therapies. However, key obstacles remain, in particular delivery of oxygen at the appropriate dose and with optimal pharmacokinetics. Toward overcoming these hurdles, gas‐entrapping materials (GeMs) that are capable of tunable oxygen release are formulated. It is shown that injection or implantation of these materials into tumors can mitigate tumor hypoxia by delivering oxygen locally and that these GeMs enhance responsiveness to radiation and chemotherapy in multiple tumor types. This paper also demonstrates, by comparing an oxygen (O2)‐GeM to a sham GeM, that the former generates an antitumorigenic and immunogenic tumor microenvironment in malignant peripheral nerve sheath tumors. Collectively the results indicate that the use of O2‐GeMs is promising as an adjunctive strategy for the treatment of solid tumors.

Objectives Mask adherence continues to be a critical public health measure to prevent transmission of aerosol pathogens, such as SARS-CoV-2. We aimed to develop and deploy a computer vision algorithm to provide real-time feedback of mask wearing among staff in a hospital.Design Single-site, observational cohort study.Setting An urban, academic hospital in Boston, Massachusetts, USA.Participants We enrolled adult hospital staff entering the hospital at a key ingress point.Interventions Consenting participants entering the hospital were invited to experience the computer vision mask detection system. Key aspects of the detection algorithm and feedback were described to participants, who then completed a quantitative assessment to understand their perceptions and acceptance of interacting with the system to detect their mask adherence.Outcome measures Primary outcomes were willingness to interact with the mask system, and the degree of comfort participants felt in interacting with a public facing computer vision mask algorithm.Results One hundred and eleven participants with mean age 40 (SD15.5) were enrolled in the study. Males (47.7%) and females (52.3%) were equally represented, and the majority identified as white (N=54, 49%). Most participants (N=97, 87.3%) reported acceptance of the system and most participants (N=84, 75.7%) were accepting of deployment of the system to reinforce mask adherence in public places. One third of participants (N=36) felt that a public facing computer vision system would be an intrusion into personal privacy.Public-facing computer vision software to detect and provide feedback around mask adherence may be acceptable in the hospital setting. Similar systems may be considered for deployment in locations where mask adherence is important.

Abstract Maintaining an ample supply of personal protective equipment continues to be a challenge for the healthcare industry, especially during emergency situations and times of strain on the supply chain. Most critically, healthcare workers exposed to potential airborne hazards require sufficient respiratory protection. Respirators are the only type of personal protective equipment able to provide adequate respiratory protection. However, their ability to shield hazards depends on design, material, proper fit, and environmental conditions. As a result, not all respirators may be adequate for all scenarios. Additionally, factors including user comfort, ease of use, and cost contribute to respirator effectiveness. Therefore, a careful consideration of these parameters is essential for ensuring respiratory protection for those working in the healthcare industry. Here respirator design and material characteristics are reviewed, as well as properties of airborne hazards and potential filtration mechanisms, regulatory standards of governmental agencies, respirator efficacy in the clinical setting, attitude of healthcare personnel toward respiratory protection, and environmental and economic considerations of respirator manufacturing and distribution.

The trade-off between spatial and temporal resolution remains a fundamental challenge in machine vision. A captured image often contains a significant amount of redundant information, and only a small region of interest (ROI) is necessary for object detection and tracking. In this paper, we first systematically characterize the effects of ROI on camera capturing, data transmission, and image processing. We then present the closed-loop ROI algorithm capable of high spatial and temporal resolution as well as wide scanning field of view (FOV) in single and multi-object detection and tracking via real-time wireless video streaming. With the feedback from real-time object tracking, the wireless camera is able to capture and transmit only the ROI which in turn enhances both the spatial and temporal resolution in object tracking. In addition, the proposed approach can still maintain a large FOV by processing regions outside of the ROI at lower spatial and temporal resolutions. When applied to a high spatial resolution wireless stream (5 MegaPixels), the closed-loop ROI algorithm improves the temporal resolution by up to $10\times $ (from 2.4FPS to 22.5FPS). Specifically, camera processing is improved by up to $4.7\times $ , data transmission is improved by up to $160\times $ , and PC processing is improved by up to $2.5\times $ . In a person tracking experiment, the closed-loop ROI algorithm enables a wide-angle camera to outperform both a normal wide-angle camera–which suffers from poor temporal resolution and motion blur–and a pan & tilt camera–which cannot automatically refresh tracking after the tracking is lost.

The COVID-19 pandemic has accelerated methods to facilitate contactless evaluation of patients in hospital settings. By minimizing in-person contact with individuals who may have COVID-19, healthcare workers can prevent disease transmission and conserve personal protective equipment. Obtaining vital signs is a ubiquitous task that is commonly done in person by healthcare workers. To eliminate the need for in-person contact for vital sign measurement in the hospital setting, we developed Dr. Spot, a mobile quadruped robotic system. The system includes IR and RGB cameras for vital sign monitoring and a tablet computer for face-to-face medical interviewing. Dr. Spot is teleoperated by trained clinical staff to simultaneously measure the skin temperature, respiratory rate, and heart rate while maintaining social distancing from patients and without removing their mask. To enable accurate, contactless measurements on a mobile system without a static black body as reference, we propose novel methods for skin temperature compensation and respiratory rate measurement at various distances between the subject and the cameras, up to 5 m. Without compensation, the skin temperature MAE is 1.3°C. Using the proposed compensation method, the skin temperature MAE is reduced to 0.3°C. The respiratory rate method can provide continuous monitoring with a MAE of 1.6 BPM in 30 s or rapid screening with a MAE of 2.1 BPM in 10 s. For the heart rate estimation, our system is able to achieve a MAE less than 8 BPM in 10 s measured in arbitrary indoor light conditions at any distance below 2 m.

Abstract Continuous monitoring in the intensive care setting has transformed the capacity to rapidly respond with interventions for patients in extremis. Noninvasive monitoring has generally been limited to transdermal or intravascular systems coupled to transducers including oxygen saturation or pressure. Here it is hypothesized that gastric fluid (GF) and gases, accessible through nasogastric (NG) tubes, commonly found in intensive care settings, can provide continuous access to a broad range of biomarkers. A broad characterization of biomarkers in swine GF coupled to time‐matched serum is conducted . The relationship and kinetics of GF‐derived analyte level dynamics is established by correlating these to serum levels in an acute renal failure and an inducible stress model performed in swine. The ability to monitor ketone levels and an inhaled anaesthetic agent (isoflurane) in vivo is demonstrated with novel NG‐compatible sensor systems in swine. Gastric access remains a main stay in the care of the critically ill patient, and here the potential is established to harness this establishes route for analyte evaluation for clinical management.

Objectives To compare the impact of respirator extended use and reuse strategies with regard to cost and sustainability during the COVID-19 pandemic.Design Cost analysis.Setting USA.Participants All healthcare workers within the USA.Interventions Not applicable.Main outcome measures A model was developed to estimate usage, costs and waste incurred by several respirator usage strategies over the first 6 months of the pandemic in the USA. This model assumed universal masking of all healthcare workers. Estimates were taken from the literature, government databases and commercially available data from approved vendors.Results A new N95 respirator per patient encounter would require 7.41 billion respirators, cost $6.38 billion and generate 84.0 million kg of waste in the USA over 6 months. One respirator per day per healthcare worker would require 3.29 billion respirators, cost $2.83 billion and generate 37.22 million kg of waste. Decontamination by ultraviolet germicidal irradiation would require 1.64 billion respirators, cost $1.41 billion and accumulate 18.61 million kg of waste. H2O2 vapour decontamination would require 1.15 billion respirators, cost $1.65 billion and produce 13.03 million kg of waste. One reusable respirator with daily disposable filters would require 18 million respirators, cost $1.24 billion and generate 15.73 million kg of waste. Pairing a reusable respirator with H2O2 vapour-decontaminated filters would reduce cost to $831 million and generate 1.58 million kg of waste. The use of one surgical mask per healthcare worker per day would require 3.29 billion masks, cost $460 million and generate 27.92 million kg of waste.Conclusions Decontamination and reusable respirator-based strategies decreased the number of respirators used, costs and waste generated compared with single-use or daily extended-use of disposable respirators. Future development of low-cost,simple technologies to enable respirator and/or filter decontamination is needed to further minimise the economic and environmental costs of masks.

High swelling ratio, speed and long term robustness tend not coexist in hydrogels which limits their use in devices. Here, the authors introduce a pufferfish-inspired hydrogel device ingested as a standard-sized pill, swells rapidly and maintains robustness under repeated mechanical loads in the stomach.

Abstract Cancer patients undergoing therapeutic radiation routinely develop injury of the adjacent gastrointestinal (GI) tract mucosa due to treatment. To reduce radiation dose to critical GI structures including the rectum and oral mucosa, 3D‐printed GI radioprotective devices composed of high‐Z materials are generated from patient CT scans. In a radiation proctitis rat model, a significant reduction in crypt injury is demonstrated with the device compared to without (p

Objective To develop and test a new reusable, sterilisable N95 filtering facepiece respirator (FFR)-comparable face mask, known as the Injection Molded Autoclavable, Scalable, Conformable (iMASC) system, given the dire need for personal protective equipment within healthcare settings during the COVID-19 pandemic.Design Single-arm feasibility study.Setting Emergency department and outpatient oncology clinic.Participants Healthcare workers who have previously undergone N95 fit testing.Interventions Fit testing of new iMASC system.Primary and secondary outcome measures Primary outcome is success of fit testing using an Occupational Safety and Health Administration (OSHA)-approved testing method, and secondary outcomes are user experience with fit, breathability and filter replacement.Results Twenty-four subjects were recruited to undergo fit testing, and the average age of subjects was 41 years (range of 21–65 years) with an average body mass index of 26.5 kg/m2. The breakdown of participants by profession was 46% nurses (n=11), 21% attending physicians (n=5), 21% resident physicians (n=5) and 12% technicians (n=3). Of these participants, four did not perform the fit testing due to the inability to detect saccharin solution on premask placement sensitivity test, lack of time and inability to place mask over hair. All participants (n=20) who performed the fit test were successfully fitted for the iMASC system using an OSHA-approved testing method. User experience with the iMASC system, as evaluated using a Likert scale with a score of 1 indicating excellent and a score of 5 indicating very poor, demonstrated an average fit score of 1.75, breathability of 1.6, and ease of replacing the filter on the mask was scored on average as 2.05.Conclusions The iMASC system was shown to successfully fit multiple different face sizes and shapes using an OSHA-approved testing method. These data support further certification testing needed for use in the healthcare setting.

Summary: Inactive ingredients and generally recognized as safe compounds are regarded by the US Food and Drug Administration (FDA) as benign for human consumption within specified dose ranges, but a growing body of research has revealed that many inactive ingredients might have unknown biological effects at these concentrations and might alter treatment outcomes. To speed up such discoveries, we apply state-of-the-art machine learning to delineate currently unknown biological effects of inactive ingredients—focusing on P-glycoprotein (P-gp) and uridine diphosphate-glucuronosyltransferase-2B7 (UGT2B7), two proteins that impact the pharmacokinetics of approximately 20% of FDA-approved drugs. Our platform identifies vitamin A palmitate and abietic acid as inhibitors of P-gp and UGT2B7, respectively; in silico, in vitro, ex vivo, and in vivo validations support these interactions. Our predictive framework can elucidate biological effects of commonly consumed chemical matter with implications on food- and excipient-drug interactions and functional drug formulation development. : Reker et al. use machine learning to identify biological activities of food and drug additives. Validation confirms vitamin A palmitate as an inhibitor of P-glycoprotein transport and abietic acid as an inhibitor of UGT2b7 metabolism. Such associations have important implications as food- or excipient-drug interactions. Keywords: machine learning, pharmacology, virtual screening, excipient-drug interactions, food-drug interactions, pharmacokinetics, data science, inactive ingredients, drug delivery

Poor adherence to daily antiretrovirals can significantly affect treatment efficacy, but oral long-acting antiretrovirals are currently lacking. Here, the authors develop a once-weekly oral dosage form for anti-HIV drugs, assess its pharmacokinetics in pigs, and model its impact on viral resistance and disease epidemics.

The use of drug delivery systems for the gastrointestinal tract has been faced with a number of drawbacks related to their prolonged use. Here, the authors develop a drug-loaded hydrogel with high strength to withstand long-term gastrointestinal motility and can be triggered to dissolve on demand.

Abstract Submucosal elevation, the process of instilling material in the submucosal space for separation of the surface mucosa and deeper muscularis layer, is a significant aspect of the endoscopic mucosal resection of large lesions performed to facilitate lesion removal and maximize safety. Submucosal injection, when applied, has historically been performed with normal saline, though this is limited by its rapid dissipation; solutions ideally need to be easily injectable, biocompatible, and provide a long‐lasting submucosal cushion with a desirable height. Here, reported is a new set of materials, endoscopically injectable shear‐thinning hydrogels, meeting these requirements because of their biocompatible components and ability to form a solid hydrogel upon injection. These findings are supported by evaluation in a large animal model and ultimately demonstrate the potential of these shear‐thinning hydrogels to serve as efficient submucosal injection fluids for cushion development. Given these unique characteristics, their broad application in mucosal resection techniques is anticipated.

Best practices in Biomedical Engineering education seek to connect classroom knowledge to practical applications. MIT's Medical Device Design course is comprised of in-class didactics, individual laboratory assignments, and a semester-long, team- based design and prototyping challenge, based in real unmet biomedical need. Students in the course represent a broad set of undergraduate and graduate students, from diverse educational backgrounds, with different levels of training and expertise. This year, as a precursor to the semester-long project, we designed, piloted, and evaluated a new experiential learning lab based around a syringe pump, selected because of its prevalence in the clinical setting, exemplification of core, multidisciplinary biomedical engineering concepts, and suitability for a team-based learning exercise. Students individually calculated patient dosing requirements and translated desired volume and flow rate into stepper motor commands. Then, during a single in-class session, teams worked from a custom-designed and fabricated kit to assemble a syringe pump, breadboard electronics, implement software controls, and finally close the design loop by evaluating their pumps' dispensing performance. A post-lab survey of the student cohort indicated that this pilot lab provided a sound biomedical learning and teamwork opportunity that improved technical literacy. The survey also identified key opportunities for improvement -- students wanted more time and instructor-guided learning to increase their understanding of the mechanical engineering, electrical engineering, and software subtopics. Consequently, next year we will expand the lab into a multi-class exercise, with enhanced lectures and supplementary materials. Overall, we share this problem-based learning exercise, designed to exemplify key concepts, improve teamwork, and foster hands-on tinkering skills, with other biomedical engineering instructors.