Resource-limited Environments Research Articles

Hermetic microfluidic device for point-of-care viral nucleic acid testing

There is an unmet clinical and public health need for rapid and accurate point-of-care (POC) diagnosis and management of infectious pathogens, especially in resource-limited environments. In this work, we present a microfluidic deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) rapid test (μDART) device for POC detection of various viral pathogens. This platform hermetically integrates the modules of extraction-free sample lysis, loop-mediated isothermal amplification (LAMP) with lyophilized reagent beads, and real-time colorimetric signal sensing to realize "sample-in and result-out" in 15–30 min. Test results can be sent to a mobile phone for remote monitoring. Automated high-precision liquid handling is achieved by a combination of negative-pressure-driven microchambers and self-sealing valves, thus simplifying manual operations and eliminating the leakage of nucleic acid aerosols. The limit of detection (LOD) of the device is as low as ∼53 copies/mL or ∼2 copies/reaction for SARS-CoV-2, which is as sensitive as the gold standard of nucleic acid testing. To validate our device’s clinical applications, we tested both DNA and RNA viruses as representative pathogens including 537 clinical nasal swab samples for SARS-CoV-2, 74 cervical swab samples for human papillomavirus 16/18 (HPV16/18) and 82 pet swab samples for feline cupripoxvirus (FCV) and feline herpesvirus (FHV). Across these tests, the clinical sensitivity and specificity were 92.5% - 97.7% and 99.7%-100%, respectively. We demonstrate that the μDART is able to provide a quick and accurate result for POCT and self-testing, and can connect to health care wirelessly to achieve remote monitoring.

Resuscitative endovascular balloon occlusion of the aorta in trauma management: a comprehensive study of clinical indications and challenges

BackgroundThe application of resuscitative endovascular balloon occlusion of the aorta (REBOA) in trauma resuscitation, including for profound shock and cardiac arrest, has gained prominence. This study aimed to determine the...

Empowering Manets with Advanced Multimodal Biometric Authentication and Encryption

In a mobile ad hoc network (MANET), nodes communicate wirelessly, facing unique challenges. Traditional MANETs suffer from issues like erroneous transmission and vulnerability to unauthorized nodes joining the network, posing security risks. Authentication within MANETs is a significant security concern, prompting ongoing research for enhancements. Our solution integrates multimodal biometric authentication with RSA and AES encryption, providing robust security for user authentication and data protection in MANETs. This approach effectively addresses risks such as unauthorized access and data tampering, crucial for secure communication in dynamic, resource-limited MANET environments. Our proposed system utilizes a combination of face and fingerprint biometrics for encryption, enhancing network security. Through testing, our system demonstrates a high authentication rate of 92.42% with minimal processing times: 0.042 ms for key generation, 0.019 ms for encryption, and 0.032 ms for decryption, based on a 1024-bit key size. These practical results showcase the resilience and efficiency of our secure system.

Self-distillation framework for document-level relation extraction in low-resource environments.

The objective of document-level relation extraction is to retrieve the relations existing between entities within a document. Currently, deep learning methods have demonstrated superior performance in document-level relation extraction tasks. However, to enhance the model's performance, various methods directly introduce additional modules into the backbone model, which often increases the number of parameters in the overall model. Consequently, deploying these deep models in resource-limited environments presents a challenge. In this article, we introduce a self-distillation framework for document-level relational extraction. We partition the document-level relation extraction model into two distinct modules, namely, the entity embedding representation module and the entity pair embedding representation module. Subsequently, we apply separate distillation techniques to each module to reduce the model's size. In order to evaluate the proposed framework's performance, two benchmark datasets for document-level relation extraction, namely GDA and DocRED are used in this study. The results demonstrate that our model effectively enhances performance and significantly reduces the model's size.

Utilizing Point-Of-Care Ultrasound (POCUS) for Diagnosis in a Resource-Limited Setting: A Case Report of Pulmonary Embolism

Introduction: Acute pulmonary embolism (PE) is a common cause of cardiovascular-related deaths and poses diagnostic challenges due to its variable and non-specific symptoms. Computed tomography pulmonary angiography (CTPA) is the gold standard imaging method for PE diagnosis, but its availability is limited in resource-constrained settings. Point-of-care ultrasound (POCUS) has emerged as a valuable tool for emergency physicians, aiding accurate diagnoses, procedural guidance, and resuscitation efforts. Case Presentation: This case report presents a 76-year-old woman with non-specific symptoms diagnosed with PE using POCUS in the Emergency Department of the Korle Bu Teaching Hospital. The POCUS findings included an enlarged right ventricle with a flattened septum (D sign), poor cardiac contractility, thrombi in the right ventricle and a plethoric Inferior Vena Cava (IVC). Prompt diagnosis facilitated timely management, leading to improved patient outcomes. Conclusion: POCUS has proven to be indispensable in resource-constrained settings where confirmatory diagnostics are limited. Incorporating POCUS training into emergency medicine residency programs and establishing emergency ultrasound fellowships in under-resourced regions like Africa can enhance its utilization and empower clinicians in such environments. Equipping emergency room clinicians with POCUS skills enables timely diagnosis, early interventions, shorter Emergency Department stays, and improved patient outcomes. This approach can contribute to building an African faculty proficient in emergency ultrasound, facilitating the education and training of more clinicians in POCUS, and ultimately enhancing healthcare outcomes in resource-limited environments.

Rapid and sensitive point-of-care diagnosis of human cytomegalovirus infection using RPA-CRISPR technology

BackgroundHuman cytomegalovirus (HCMV) is a common herpesvirus that can cause a range of symptoms, from mild conditions such as fevers to severe illnesses like pneumonia. Early and accurate diagnosis of HCMV infection is crucial, particularly for vulnerable populations with limited medical care. However, current diagnostic methods are often expensive, time-consuming, and require skilled technicians. Materials and methodsWe developed an HCMV-RPA-CRISPR diagnosis platform for the rapid and cost-effective detection of HCMV infection. This method utilizes recombinase polymerase amplification (RPA) to amplify the HCMV target gene isothermally without the need for thermal cycling equipment. The platform integrates the CRISPR/Cas12a system, significantly enhancing specificity and sensitivity. A total of 13 clinical blood samples were tested to evaluate the platform's effectiveness and accuracy. Additionally, a lateral flow assay (LFA) and fluorescence detection were incorporated for straightforward and rapid visual interpretation of the results. ResultsThe assay effectively detected concentrations as low as a single copy of the positive control plasmid per microliter in under 1 h, without requiring specialized equipment or training. In clinical sample evaluations, both the fluorescence readout and LFA exhibited 100% sensitivity and specificity, identifying four HCMV-positive and nine HCMV-negative samples. ConclusionThe HCMV-RPA-CRISPR diagnosis platform is comparably effective to qPCR for HCMV diagnosis. Its applicability in common clinical laboratories, clinics, and point-of-care settings, particularly in resource-limited environments, makes it a valuable tool for widespread HCMV screening and diagnosis.

Automated and ultrasensitive point-of-care glycoprotein detection using boronate-affinity enhanced organic electrochemical transistor patch

Quantifying trace glycoproteins in biofluids requires ultrasensitive components, but feedback is not available in the current portable platforms of point-of-care (POC) diagnosis technologies. A compact and ultrasensitive bioelectrochemical patch was based on boronate-affinity amplified organic electrochemical transistors (BAAOECTs) for POC use was developed to overcome this dilemma. Benefit from the cascading signal enhancement deriving from boronate-affinity targeting multiple regions of glycoprotein and OECTs’ inherent signal amplification capability, the BAAOECTs achieved a detection limit of 300 aM within 25 min, displaying about 3 orders of magnitude improvement in sensitivity compared with the commercial electrochemical luminescence (ECL) kit. By using a microfluidic chip, a microcontroller module, and a wireless sensing system, the testing workflows of the above patch was automated, allowing for running the sample-to-answer pipeline even in a resource-limited environment. The reliability of such portable biosensing platform is well recognized in clinical diagnostic applications of heart failure. Overall, the remarkable enhanced sensitivity and automated workflow of BAAOECTs biosensing platform provide a prospective and generalized design policy for expanding the POC diagnosis capabilities of glycoproteins.

Enhanced recovery after surgery for oncological breast surgery reduces length of stay in a resource limited setting.

Early recovery after surgery (ERAS) protocols in breast surgery optimizes resources and reduces healthcare costs by facilitating early discharges. These protocols are well established in tertiary centres, but not commonly adopted in regional centres. ERAS implementation potentially impacts smaller hospitals significantly, where resources are limited and persistent bed shortages with mounting waitlist pressures exist. Our study evaluates the feasibility of early discharge with the application of our ERAS protocol to mastectomies in a resource-constrained and rural setting. Breast cancer patients who underwent mastectomies with or without reconstruction between January 2017 and July 2023 were retrospectively reviewed. From January 2022, we implemented a standardized ERAS protocol for patients undergoing mastectomy. This incorporated a combination of pre-, intra- and post-operative elements to enhance patient readiness for discharge. Our study compared these patients (post-ERAS group) with the outcomes of mastectomies performed prior to January 2022 (pre-ERAS group). 104 patients were identified. In the post-ERAS group, 74.4% were discharged within 24 h compared to 23.1% in the pre-ERAS group. Length of stay was reduced from 2.26 to 1.42 days. There were no differences in unplanned clinician reviews or early representation to the emergency department between the two groups. Reducing the length of stay without increased complications can be achieved in a resource-limited environment with our protocolized ERAS principals. Our protocol has been instrumental in allowing safe discharges within 24 h. Other regional centres may benefit in adopting strategies implemented by us for their own ERAS protocols in breast cancer surgery.

Bioactive exometabolites drive maintenance competition in simple bacterial communities.

Free-living microbial populations often persist and engage in environments that offer few or inconsistently available resources. Thus, it is important to investigate microbial interactions in this common and ecologically relevant condition of non-growth. This work investigates the consequences of resource limitation for community metabolic output and for population interactions in simple synthetic bacterial communities. Despite non-growth, we observed active, exometabolite-mediated competition among the bacterial populations. Many of these interactions and produced exometabolites were dependent on the community composition but we also observed that one dominant competitor consistently produced interfering exometabolites regardless. These results are important for predicting and understanding microbial interactions in resource-limited environments.

Target Detection and Segmentation Technology for Zero-shot Learning

Zero-shot learning (ZSL) in the field of computer vision refers to enabling the model to recognize and understand categories that have not been encountered during the training phase. It is particularly critical for object detection and segmentation tasks, because these tasks require the model to have good generalization capabilities to unknown categories. Object detection requires the model to determine the location of the object, while segmentation further requires the precise demarcation of the object's boundaries. In ZSL research, knowledge representation and transfer are core issues. Researchers have tried to use semantic attributes as a knowledge bridge to connect categories seen during the training phase and categories not seen during the testing phase. These attributes may be color, shape, etc., but this method requires accurate attribute annotation, which is often not easy to achieve in practice. Therefore, researchers have begun to explore the use of non-visual information such as knowledge maps and text descriptions to enrich the recognition capabilities of models, but this also introduces the challenge of information integration and alignment. At present, ZSL has made certain progress in target detection and segmentation tasks, but there is still a significant gap compared with traditional supervised learning. This is mainly due to the limited ability of ZSL models to generalize to new categories. To this end, researchers have begun to explore combining ZSL with other technologies, such as generative adversarial networks (GANs) and reinforcement learning, to enhance the model's detection and segmentation capabilities for new categories. Future research needs to focus on several aspects. The first is how to design a more effective knowledge representation and transfer mechanism so that the model can better utilize existing knowledge. The second step is to develop new algorithms to improve the performance of ZSL in complex environments. In addition, research should focus on how to reduce the dependence on computing resources so that the ZSL method can run effectively in resource-limited environments. In summary, the research on target detection and segmentation technology of zero-shot learning is a cutting-edge topic in the field of computer vision. Despite the challenges, with the deepening of research, we expect these technologies to contribute to improving the generalization ability and intelligence level of computer vision systems.

Energy-efficient craters detection based on spiking neural network using digital elevation models

Craters are the primary topographic features on celestial bodies and play a vital role in deep space exploration missions. Recently, artificial neural networks (ANNs) have excelled in crater detection. However, when compared to ANNs, spike neural networks (SNNs) have the advantage of low power consumption, making them more suitable for resource-limited deep space environments. To the best of our knowledge, this is the first spiked-based crater detection model. Firstly, two conversion learning algorithms based on cluster neurons and vary-time windows neurons are proposed to address the non-differentiability problem of SNNs. Secondly, a calibration mechanism is introduced to correct the conversion loss between ANNs and SNNs. Thirdly, the experimental results demonstrate that the proposed scheme exhibits sufficient precision, while reducing the energy consumption cost by more than 10 times compared to the previous method. Additionally, this method is expected to offer new insights for segmentation tasks in resource-constrained environments.

The Sympatric Coexistence Mechanism: A Case Study of Two Penahia Species in the Beibu Gulf, South China Sea.

The study of trophic relationships among closely related species plays an important role in deepening our understanding of the resource utilization characteristics, differentiation patterns, and population dynamics of co-occurring species in the same habitat. This research uses two congeneric fish species, Pennahia pawak and Pennahia anea, as examples. Based on a stomach content analysis and a carbon-nitrogen stable isotope analysis, a comparative analysis of their feeding habits and trophic niches is conducted. Additionally, a spatial niche analysis is employed to explore the coexistence and competitive mechanisms between these two closely related fish species. The results show that specialized feeding habits mitigate intraspecific competition as the population densities increase. The carbon and nitrogen stable isotope analysis reveals variations in the feeding habits and trophic levels with body length, indicating adaptive shifts in prey selection. Despite similar food resources, niche differentiation arises due to differences in dominant prey, facilitating coexistence. Differences in spatial niche further contribute to niche separation and coexistence. In resource-limited environments, species such as Pennahia utilize trophic and spatial niche differentiation to collectively exploit resources and achieve coexistence, with implications for fishery management favoring Pennahia resource occupancy capabilities.

Design and Usability of an Open-Source, Low-Cost Flexible Laryngoscope for Resource-Limited Settings

Endoscopes are paramount to the practice of otolaryngology. To provide physicians in low-middle-income countries with adequate tools to treat otolaryngologic problems, it is necessary to create a low-cost sustainable option. To describe the design and usability of an open-source, low-cost flexible laryngoscope that addresses the lack of affordable and accessible methods for otolaryngologic visualization in resource-limited settings. This quality improvement study used a mixed-methods approach, including a technical description of device design as well as quantitative and qualitative survey evaluation of device usability. Engineering involved device design, sourcing or manufacturing individual components, fabricating a prototype, and iterative testing. Key assumptions and needs for the device were identified in collaboration with otolaryngologists in Zimbabwe, and designed and simulated by biomedical engineers in a US university laboratory. Board-certified otolaryngologists at a single US university hospital trialed a completed prototype on simulated airways between May 2023 and June 2023. Technical details on the design of the device are provided. Otolaryngologist gave feedback on device characteristics, maneuverability, and visualization using the System Usability Scale, a customized Likert-scale questionnaire (5-point scale), and semistructured interviews. A functional prototype meeting requirements was completed consisting of a distal-chip camera, spring bending tip, handle housing the control mechanism and electronics, and flexible polyether block amide-coated silicone sheath housing the camera and control wires; an external monitor provided real-time visualization and ability to store data. A total of 14 otolaryngologists participated in the device review. The mean (SD) System Usability Scale score was 88.93 (10.08), suggesting excellent usability. The device was rated highly for ease of set up, physical attributes, image quality, and functionality. This quality improvement study described the design of a novel open-source low-cost flexible laryngoscope that external review with otolaryngologists suggests was usable and feasible in various resource-limited environments. Future work is needed to translate the model into a clinical setting.

110 Effects of sire selection on puberty and reproduction of offspring selected as replacement heifers

Abstract Sire selection is important to maintain the desired genetic capability of any cattle herd; therefore, selection of economic production traits affect profitability by increasing pre- and post-weaning gain and carcass quality potential. Using heifers developed from sires selected for growth and milk traits may have long-term impact on sustainability of the cowherd by influencing mature cow size and milk production. Our objective was to determine the impacts of sires selected for high and moderate growth and high and low milk traits on growth and reproductive performance of replacement heifers. Therefore, we selected replacement heifers sired by bulls within the upper 5th and 50th percentiles of the Angus breed for yearling weight (YW) EPD as high growth (HG) moderate growth (MG), the upper 15th percentile of the Angus breed for milk EPD as high milk (HM), and the lower 15th percentile for low milk (LM) in a 2×2 factorial design resulting in 4 treatments: HG/HM, HG/LM, MG/HM, and MG/LM. Heifers (n = 46) from appropriate AI sires that were born and developed at Oklahoma State University – Range Cow Research Center – South Range Unit were selected as replacements. They were raised on a base diet of dry, dormant tall grass prairie and moderate quality grass hay following weaning and 2 kg/d of 16% crude protein concentrate supplement. Body weights and biometrics were recorded at weaning and approximately at 1-yr of age, and blood was collected at 11 and 0 d before synchronization for progesterone analysis to determine pubertal status pre-breeding. Estrus was synchronized using the 14-d CIDR-PG with timed AI method followed by a 45-d natural service breeding period. Pregnancy checks were conducted by serum collection 35-d following AI and via rectal palpation by an experienced veterinarian 112 d after removal of the bulls. Statistical analyses were performed using the mixed procedure of SAS (SAS 9.4, SAS INC., Carey, NC). Heifers from high growth sires were 28 kg heavier at weaning (P < 0.01) and 26 kg heavier as yearlings (P < 0.01) than those sired by moderate growth sires, while sire milk EPD affected neither (P ≥ 0.55). High growth and high milk sired heifers had greater hip heights, frame scores and thus greater (P ≤ 0.05) estimated mature body weight (EMBW). Despite this, sire selection had no impact on percentage of heifers pubertal before breeding, AI pregnancy, or the total pregnancy rates (P > 0.24) Based on these data, selection of sires for HG and HM leads to increased productivity of the offspring but gives rise to larger mature cows, which may pressure grazing resources in limited resource environments impacting the long-term sustainability of the cow-calf enterprise.

Living with voracious roommates: Factors that explain isotopic niche variation in a mixed colony of insectivorous bats.

Theory predicts that in resource-limited environments, coexisting species may overlap their niche dimensions but must differ in at least one to avoid competitive exclusion. Specifically, it has been suggested that the coexistence of competing species within a guild, could be sustained with mechanisms of resource partitioning, such as segregation along a trophic dimension. Among the most gregarious mammals are bats, which present diversification in their diet based on habitat choice and body size. Despite differences that could explain specialization in prey selection, there are insufficient studies that explore food overlap in mixed bat colonies and the factors that determine the selection of prey, both at intra- and inter-specific levels. To fill this gap, we analyzed the isotope signal (δ13C and δ15N) in feces collected in a mixed colony of Tadarida brasiliensis and Myotis chiloensis. To understand how several factors could influence these isotopic signals, intrinsic explanatory variables were analyzed, including body mass, body length, age, and sex. Also, extrinsic variables were analyzed, including monthly temporality and moonlight intensity. Our findings support age-dependent specialization in M. chiloensis, with a significant role of moonlight intensity and sex on δ15N. In T. brasiliensis, we identified a significant effect of size, sex, and ear length on δ15N. Our analysis indicates that both species of bats experience diverse degrees of overlap through austral summer months, affected by several factors that explain the variability in their fecal isotopic signals.

Enhancing Sustainability in Resource-Limited Environments: Government, Culture, and AI

Enhancing Sustainability in Resource-Limited Environments: Government, Culture, and AI

Determining the cost and cost-effectiveness of childhood cancer treatment in Haiti.

Haiti is a low-income country with one of the lowest human development index rankings in the world. Its childhood cancer services are provided by a single hospital with the only dedicated paediatric oncology department in the country. Our objective was to assess the cost and cost-effectiveness of all types of childhood cancer in Haiti to help prioritise investments and to support national cancer control planning. All costing data were collected from the year 2017 or 2018 hospital records. Costs were classified into 11 cost categories, and the proportion of the overall budget represented by each was calculated and converted from Haitian Gourde to United States dollars. The 5-year survival rate was retrieved from hospital records and used to calculate the cost-effectiveness of disability-adjusted life year (DALY) averted, using a healthcare costing perspective. Additional sensitivity analyses were conducted accounting for late-effect morbidity and early mortality and discounting rates of 0%, 3% and 6%. The annual cost of operating a paediatric oncology unit in Haiti treating 74 patients with newly diagnosed cancer was $803,184 overall or $10,854 per patient. The largest cost category was pharmacy, constituting 25% of the overall budget, followed by medical personnel (20%) and administration (12%). The cost per DALY averted in the base-case scenario was $1,128, which is 76% of the gross domestic product per capita, demonstrating that treating children with cancer in Haiti is very cost-effective according to the World Health Organisation Choosing Interventions that are Cost-Effective (WHO-CHOICE) threshold. In the most conservative scenario, the cost per DALY averted was cost-effective by WHO-CHOICE criteria. Our data will add to the growing body of literature illustrating a positive return on investment associated with diagnosing and treating children with cancer in even the most resource-limited environments. We anticipate that these data will aid local stakeholders and policymakers when identifying cancer control priorities and making budgetary decisions.

Two Birds with one Stone: Dual-mode immunoassay constructed using a novel emitter ethylene glycol-induced perylene diimide and a multifunctional ANS probe

Perylene diimide (PDI) is a readily reducible electron-deficient dye that exhibits strong photoluminescent properties, providing new opportunities for synthesizing novel electrochemiluminescence (ECL) emitters. In this study, ethylene glycol (EG) was used to induce the self-assembly of PDI supramolecules for the preparation of ultrathin EG-PDI nanosheets characterized by low crystallinity and weak stacking interaction. Notably, EG-PDI integrates luminescent and catalytic functions into one device, accelerating the interfacial electron transfer and the faster charge transfer kinetics of EG-PDI with K2S2O8. Furthermore, the narrow band gap of EG-PDI facilitates its excitation at an ultra-low potential (−0.3 V). To improve the efficiency of tumor marker analysis, multifunctional Au nanostars (ANS) was introduced both as an energy acceptor of the ECL system and a probe for the photothermal system. Dual-mode immunoassay have demonstrated superior analytical performance in detecting alpha-fetoprotein (AFP), meeting the requirements of modern clinical diagnostics in resource-limited environments.

DWS-YOLO: A Lightweight Detector for Blood Cell Detection

ABSTRACT Peripheral blood cell detection is an essential component of medical practice and is used to diagnose and treat diseases, as well as to monitor the progress of therapies. Our objective is to construct an efficient deep learning model for peripheral blood cell analysis that achieves an optimized balance between inference speed, computational complexity, and detection accuracy. In this article, we propose the DWS-YOLO blood detector, which is a lightweight blood detector. Our model includes several improved modules, including the lightweight C3 module, the increased combined attention mechanism, the Scylla-IoU loss function, and the improved soft non-maximum suppression. Improved attention, loss function, and suppression enhance detection accuracy, while lightweight C3 module reduces computation time. The experiment results demonstrate that our proposed modules can enhance a detector’s detection performance, and obtain new state-of-the-art (SOTA) results and excellent robustness performance on the BCCD dataset. On the white blood cell detection dataset (Raabin-WBC), the proposed detector’s generalization performance was confirmed to be satisfactory. Our proposed blood detector achieves high detection accuracy while requiring few computational resources and is very suitable for resource-limited but efficient medical device environments, providing a reliable and advanced solution for blood detection that greatly improves the efficiency and effectiveness of peripheral blood cell analysis in clinical practice.

Regional Anesthesia in the Austere Environment: Lessons Learned from Current Out-of-Hospital Practice.

Pain management for trauma in the extreme environment is vital for both casualty comfort and aiding safe extrication. However, adequate pain management in a resource-limited environment can be challenging and is often limited. We conducted a scoping review of the use of regional anesthesia in the prehospital environment, evaluating which regional anesthetic procedure was performed for various indications, their efficacy, and the type of healthcare provider delivering the anesthetic. A PRISMA-guided systematic literature review was conducted of Medline, Embase, and Cochrane databases for studies reporting the use of regional anesthesia in the prehospital environment published before June 30, 2022. Thirty studies met the criteria and were included in the review. The most common types of regional anesthesia were fascia-iliaca compartment block (n = 317, from 12 studies) and femoral nerve block (n = 210, from 8 studies), along with various other blocks for a range of indications. These blocks had good efficacy and a low-risk profile and could be delivered by a wide range of healthcare providers. Regional anesthesia is an effective and non-resource-heavy pain management tool in prehospital environments, which may be applicable to austere settings. It can cover a wide range of injuries and can avoid systemic complications for casualties that may already be challenging to manage in out-of-hospital settings. Additionally, regional anesthesia can be effectively delivered by a wide range of providers. This review provides a holistic summary of pain management using regional anesthesia in the prehospital environment, with a discussion on its potential use in more extreme settings.