The blood−brain barrier (BBB) is a prime focus for clinicians to maintain the homeostatic function in health and deliver the theranostics in brain cancer and number of neurological diseases. The structural hierarchy and in situ biochemical signaling of BBB neurovascular unit have been primary targets to recapitulate into the in vitro modules. The microengineered perfusion systems and development in 3D cellular and organoid culture have given a major thrust to BBB research for neuropharmacology. In this review, we focus on revisiting the nanoparticles based bimolecular engineering to enable them to maneuver, control, target, and deliver the theranostic payloads across cellular BBB as nanorobots or nanobots. Subsequently we provide a brief outline of specific case studies addressing the payload delivery in brain tumor and neurological disorders (e.g., Alzheimer's disease, Parkinson's disease, multiple sclerosis, etc.). In addition, we also address the opportunities and challenges across the nanorobots' development and design. Finally, we address how computationally powered machine learning (ML) tools and artificial intelligence (AI) can be partnered with robotics to predict and design the next generation nanorobots to interact and deliver across the BBB without causing damage, toxicity, or malfunctions. The content of this review could be references to multidisciplinary science to clinicians, roboticists, chemists, and bioengineers involved in cutting-edge pharmaceutical design and BBB research.

Background: Tele-mentoring facilitates the transfer of surgical knowledge. The objective of this work is to develop a tele-mentoring framework that enables a specialist surgeon to mentor an operating surgeon by transferring information in a form of surgical instruments' motion required during a minimally invasive surgery. Method:A tele-mentoring framework is developed to transfer video stream of the surgical field, poses of the scope and port placement from the operating room to a remote location. From the remote location, the motion of virtual surgical instruments augmented onto the surgical field is sent to the operating room. Results:The proposed framework is suitable to be integrated with laparoscopic as well as robotic surgeries. It takes on average 1.56 s to send information from the operating room to the remote location and 0.089 s for vice versa over a local area network. Conclusions:The work demonstrates a tele-mentoring framework that enables a specialist surgeon to mentor an operating surgeon during a minimally invasive surgery. K E Y W O R D Saugmented reality, minimally invasive surgeries, tele-mentoring, telemedicine | INTRODUCTIONAs surgery has evolved from open to minimally invasive, the framework of tele-mentoring technologies has largely remained the same. [1][2][3] It still involves basic exchange of audio and annotated video messages, and lacks augmentation of information pertaining to surgical tool motion and tool-tissue interaction. 4,5 In an operating room setup of minimally invasive surgery (MIS), the surgeon operates on a patient using surgical instruments inserted through small incisions. These surgical instruments can either be manually operated (such as laparoscopic instruments) or robotically actuated.Along with instruments, a scope (camera) is also inserted inside the patient's body to visualise the interaction of surgical instruments' tooltips with the tissue. In the case of manual MIS, the surgeon This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Respiratory toxicology remains a major research area in the 21st century since current scenario of airborne viral infection transmission and pollutant inhalation is expected to raise the annual morbidity beyond 2 million. Clinical and epidemiological research connecting human exposure to air contaminants to understand adverse pulmonary health outcomes is, therefore, an immediate subject of human health assessment. Important observations in defining systemic effects of environmental contaminants on inhalation metabolic dysfunction, liver health, and gastrointestinal tract have been well explored with in vivo models. In this review, a framework is provided, a paradigm is established about inhalation toxicity testing in vitro, and a brief overview of breathing Lungs-on-Chip (LoC) as design concepts is given. The optimized bioengineering approaches and microfluidics with their fundamental pros, and cons are presented. There are different strategies that researchers apply to inhalation toxicity studies to assess a variety of inhalable substances and relevant LoC approaches. A case study from published literature and frame arguments about reproducibility as well as in vitro/in vivo correlations are discussed. Finally, the opportunities and challenges in soft robotics, systems inhalation toxicology approach integrating bioengineering, machine learning, and artificial intelligence to address a multitude model for future toxicology are discussed.

Increasing data on the infection indicate that maternal infections are severe. Under the realms of vaccine development, virus‐like particles (VLP)/nanoparticles (NPs) hold the promise of targeted control of therapeutics transfer across the placental barrier with the potential to trigger innate immune responses. Though the placenta is known to act as a barrier against exogenous materials, viruses exploit the transport systems and overcome the barrier properties. VLPs can be strategically designed to obtain the necessary mechanisms for navigation across the placenta and immune response. However, several knowledge gaps on the chemical, viral transmission strategies and the host defense response exist owing to the highly dynamic etiology of the placental barrier. This further complicates the toxicological analysis of the developed therapeutics. Herein, placental physiology and functions are discussed in significance with chemical toxicology, viral infections, and the host defense. Further, the promising applications of VLPs and perspective on their design to overcome the placental gatekeeper to gain the necessary immune response or therapy are provided. Finally, a holistic approach to various bioengineering models for studying chemical toxicants, viral infections, and effects of VLPs is provided to facilitate better translation of these VLPs to clinical applications.

Clinical imaging (e.g., magnetic resonance imaging and computed tomography) is a crucial adjunct for clinicians, aiding in the diagnosis of diseases and planning of appropriate interventions. This is especially true in malignant conditions such as hepatocellular carcinoma (HCC), where image segmentation (such as accurate delineation of liver and tumor) is the preliminary step taken by the clinicians to optimize diagnosis, staging, and treatment planning and intervention (e.g., transplantation, surgical resection, radiotherapy, PVE, embolization, etc). Thus, segmentation methods could potentially impact the diagnosis and treatment outcomes. This paper comprehensively reviews the literature (during the year 2012–2021) for relevant segmentation methods and proposes a broad categorization based on their clinical utility (i.e., surgical and radiological interventions) in HCC. The categorization is based on the parameters such as precision, accuracy, and automation.