Technology-aided assessments of sensorimotor function: current use, barriers and future directions in the view of different stakeholders.

BACKGROUND: There is growing interest in the use of technology in neurorehabilitation, from robotic to sensor-based devices. These technologies are believed to be excellent tools for quantitative assessment of sensorimotor ability, addressing the shortcomings of traditional clinical assessments. However, clinical adoption of technology-based assessments is very limited. To understand this apparent contradiction, we sought to gather the points-of-view of different stakeholders in the development and use of technology-aided sensorimotor assessments. METHODS: A questionnaire regarding motivators, barriers, and the future of technology-aided assessments was prepared and disseminated online. To promote discussion, we present an initial analysis of the dataset; raw responses are provided to the community as Supplementary Material. Average responses within stakeholder groups were compared across groups. Additional questions about respondent's demographics and professional practice were used to obtain a view of the current landscape of sensorimotor assessments and interactions between different stakeholders. RESULTS: One hundred forty respondents from 23 countries completed the survey. Respondents were a mix of Clinicians (27%), Research Engineers (34%), Basic Scientists (15%), Medical Industry professionals (16%), Patients (2%) and Others (6%). Most respondents were experienced in rehabilitation within their professions (67% with > 5 years of experience), and had exposure to technology-aided assessments (97% of respondents). In general, stakeholders agreed on reasons for performing assessments, level of details required, current bottlenecks, and future directions. However, there were disagreements between and within stakeholders in aspects such as frequency of assessments, and important factors hindering adoption of technology-aided assessments, e.g., Clinicians' top factor was cost, while Research Engineers indicated device-dependent factors and lack of standardization. Overall, lack of time, cost, lack of standardization and poor understanding/lack of interpretability were the major factors hindering the adoption of technology-aided assessments in clinical practice. Reimbursement and standardization of technology-aided assessments were rated as the top two activities to pursue in the coming years to promote the field of technology-aided sensorimotor assessments. CONCLUSIONS: There is an urgent need for standardization in technology-aided assessments. These efforts should be accompanied by quality cross-disciplinary activities, education and alignment of scientific language, to more effectively promote the clinical use of assessment technologies. TRIAL REGISTRATION: NA; see Declarations section.

Red cell indexes made easy using an interactive animation: do students and their scores concur?

A good understanding of red cell indexes can aid medical students in a considerable manner, serving as a basis to unravel both concepts in red cell physiology and abnormalities associated with the same. In this study, we tried to assess whether an interactive animation was helpful in improving student comprehension and understanding of red cell indexes compared with conventional classroom teaching. Eighty-eight first-year MBBS students participated, of which 44 were assigned to group A and 44 were assigned to group B after randomization. After further creation of smaller groups, students were provided with 45 min to revise red cell indexes, after which they were required to complete a multimodal questionnaire. Group A subgroups used written material for revision, whereas group B subgroups had access to an interactive animation. After completion of the questionnaire, group A students also used the animation after which feedback was collected from all students. Efficacy of the animation to improve learning and retention was demonstrated, as group B students scored significantly higher than group A students on the questionnaire ( P = 0.0003). A clear majority of the students agreed/strongly agreed that the animation was easy to operate, conveyed important concepts efficiently, and improved their knowledge of related clinical aspects as well. From the results and feedback, we found that the animation was a simple, well-received model, which, by significantly improving student performance, corroborated our hypothesis that inclusion of interactive animation into student curriculum can advance their academic attainment, compared with didactic teaching alone.

On the assessment of coordination between upper extremities: towards a common language between rehabilitation engineers, clinicians and neuroscientists.

Well-developed coordination of the upper extremities is critical for function in everyday life. Interlimb coordination is an intuitive, yet subjective concept that refers to spatio-temporal relationships between kinematic, kinetic and physiological variables of two or more limbs executing a motor task with a common goal. While both the clinical and neuroscience communities agree on the relevance of assessing and quantifying interlimb coordination, rehabilitation engineers struggle to translate the knowledge and needs of clinicians and neuroscientists into technological devices for the impaired. The use of ambiguous definitions in the scientific literature, and lack of common agreement on what should be measured, present large barriers to advancements in this area. Here, we present the different definitions and approaches to assess and quantify interlimb coordination in the clinic, in motor control studies, and by state-of-the-art robotic devices. We then propose a taxonomy of interlimb activities and give recommendations for future neuroscience-based robotic- and sensor-based assessments of upper limb function that are applicable to the everyday clinical practice. We believe this is the first step towards our long-term goal of unifying different fields and help the generation of more consistent and effective tools for neurorehabilitation.

On the analysis of movement smoothness.

Quantitative measures of smoothness play an important role in the assessment of sensorimotor impairment and motor learning. Traditionally, movement smoothness has been computed mainly for discrete movements, in particular arm, reaching and circle drawing, using kinematic data. There are currently very few studies investigating smoothness of rhythmic movements, and there is no systematic way of analysing the smoothness of such movements. There is also very little work on the smoothness of other movement related variables such as force, impedance etc. In this context, this paper presents the first step towards a unified framework for the analysis of smoothness of arbitrary movements and using various data. It starts with a systematic definition of movement smoothness and the different factors that influence smoothness, followed by a review of existing methods for quantifying the smoothness of discrete movements. A method is then introduced to analyse the smoothness of rhythmic movements by generalising the techniques developed for discrete movements. We finally propose recommendations for analysing smoothness of any general sensorimotor behaviour.

GMAC-A Simple Measure to Quantify Upper Limb Use From Wrist-Worn Accelerometers.

Various measures have been proposed to quantify upper-limb use through wrist-worn inertial measurement units. The two most popular traditional measures of upper-limb use - thresholded activity counts (TAC) and the gross movement (GM) score suffer from high sensitivity and low specificity, and vice versa. We previously proposed a hybrid version of these two measures - the GMAC - that showed better overall detection performance than TAC and GM. In this paper, we answer two critical questions to improve the GMAC measure's usefulness: (a) can it be implemented using only the accelerometer data? (b) what are its optimal parameter values? Here, we propose a modified GMAC using only the accelerometer data and optimize its parameters to develop: (a) a generic measure that is both limb- and subject-independent, and (b) limb-specific measures that were only subject-independent. The optimized GMAC showed better detection performance than the previous GMAC and surprisingly had comparable performance to the best-performing machine learning-based measure (random forest inter-subject model). In hemiparetic data, its performance was similar to the previous GMAC and the random forest inter-subject model; the limb-specific GMAC measure, however, had a better performance than the generic measure. The optimized limb-specific GMAC is a simple, interpretable alternative to a machine learning-based inter-subject model. The optimized GMAC can be a valuable measure for offline or real-time detection and feedback of upper limb use. The preliminary results of this study, based on a small dataset, need to be validated on a larger dataset to evaluate its generalizability.

Older individuals do not show task specific variations in EEG band power and finger force coordination.

OBJECTIVE: Controlling and coordinating finger force is crucial for performing everyday tasks and maintaining functional independence. Aging naturally weakens neural, muscular, and musculoskeletal systems, leading to compromised hand motor function. This decline reduces cortical activity, finger force control and coordination in older adults. OBJECTIVE: To investigate independently the EEG band power and finger force coordination in older individuals and compare the results with young healthy adults. METHODS: Twenty healthy young adults aged 20-30 (26.96±2.68) and fourteen older adults aged 58-72 (62.57±3.58) participated in this study. Participants held the instrumented handle gently for five seconds then lifted and held it for an additional five seconds in the two conditions: fixed (thumb platform secured) and free condition (thumb platform may slide on slider). RESULTS: In the older individuals there was no difference observed in the finger force synergy indices, and EEG beta band power between the two task conditions. However, in the young group synergy indices and EEG beta band power were less in free condition compared to fixed condition. Additionally, in the fixed condition, older adults showed a reduced synergy indices and reduced EEG beta band power than the young adults. CONCLUSION: Older participants exhibited consistent synergy indices and beta band power across conditions, while young adults adjusted strategies based on tasks. Task-dependent finger force synergy indices were observed in young adults, contrasting with older individuals Additionally, it is suggested that EEG band power and synergy indices may be related, indicating potential associations between EEG activity and finger force coordination.

Increasing the Motivation to Train Through Haptic Social Interaction - Pilot study.

Motivation is crucial in stroke rehabilitation, as it enhances patient engagement, adherence, and recovery. Robots can be employed to improve motivation through multiplayer rehabilitation games, which allow patients to collaborate and interact in a virtual environment through multimodal sensory cues. This social interaction can provide social support and increase motivation, resulting in better therapy engagement. A hand rehabilitation robot (PLUTO) was used to investigate the potential of social interaction to implement haptic multiplayer games. Twelve unimpaired participants (6 dyads) played in solo, collaborative, and competitive game modes. Surprisingly, no difference was found in self-reported engagement, tension, or competence between solo and multiplayer games. However, the IMI scale indicated that engagement for multiplayer games was rated higher than for solo games. The collaborative game was preferred by 10 out of 12 participants, highlighting its potential for promoting behavioural involvement and engagement. This study indicates that using PLUTO with multiplayer game modes can enhance therapy engagement. This can potentially improve rehabilitation outcomes if translated to the patient population.

A systematic investigation of detectors for low signal-to-noise ratio EMG signals.

Background: Active participation of stroke survivors during robot-assisted movement therapy is essential for sensorimotor recovery. Robot-assisted therapy contingent on movement intention is an effective way to encourage patients' active engagement. For severely impaired stroke patients with no residual movements, a surface electromyogram (EMG) has been shown to be a viable option for detecting movement intention. Although numerous algorithms for EMG detection exist, the detector with the highest accuracy and lowest latency for low signal-to-noise ratio (SNR) remains unknown. Methods: This study, therefore, investigates the performance of 13 existing EMG detection algorithms on simulated low SNR (0dB and -3dB) EMG signals generated using three different EMG signal models: Gaussian, Laplacian, and biophysical model. The detector performance was quantified using the false positive rate (FPR), false negative rate (FNR), and detection latency. Any detector that consistently showed FPR and FNR of no more than 20%, and latency of no more than 50ms, was considered an appropriate detector for use in robot-assisted therapy. Results: The results indicate that the Modified Hodges detector - a simplified version of the threshold-based Hodges detector introduced in the current study - was the most consistent detector across the different signal models and SNRs. It consistently performed for ~90% and ~40% of the tested trials for 0dB and -3dB SNR, respectively. The two statistical detectors (Gaussian and Laplacian Approximate Generalized Likelihood Ratio) and the Fuzzy Entropy detectors have a slightly lower performance than Modified Hodges. Conclusions: Overall, the Modified Hodges, Gaussian and Laplacian Approximate Generalized Likelihood Ratio, and the Fuzzy Entropy detectors were identified as the potential candidates that warrant further investigation with real surface EMG data since they had consistent detection performance on low SNR EMG data.

Collagen Functionalization of Polymeric Electrospun Scaffolds to Improve Integration into Full-Thickness Wounds.

BACKGROUND: Electrospun fibers are widely studied in regenerative medicine for their ability to mimic the extracellular matrix (ECM) and provide mechanical support. In vitro studies indicated that cell adhesion and migration is superior on smooth poly(L-lactic acid) (PLLA) electrospun scaffolds and porous scaffolds once biofunctionalized with collagen. METHODS: The in vivo performance of PLLA scaffolds with modified topology and collagen biofunctionalization in full-thickness mouse wounds was assessed by cellular infiltration, wound closure and re-epithelialization and ECM deposition. RESULTS: Early indications suggested unmodified, smooth PLLA scaffolds perform poorly, with limited cellular infiltration and matrix deposition around the scaffold, the largest wound area, a significantly larger panniculus gape, and lowest re-epithelialization; however, by day 14, no significant differences were observed. Collagen biofunctionalization may improve healing, as collagen-functionalized smooth scaffolds were smallest overall, and collagen-functionalized porous scaffolds were smaller than non-functionalized porous scaffolds; the highest re-epithelialization was observed in wounds treated with collagen-functionalized scaffolds. CONCLUSION: Our results suggest that limited incorporation of smooth PLLA scaffolds into the healing wound occurs, and that altering surface topology, particularly by utilizing collagen biofunctionalization, may improve healing. The differing performance of the unmodified scaffolds in the in vitro versus in vivo studies demonstrates the importance of preclinical testing.

Nanomaterials-based Drug Delivery Approaches for Wound Healing.

Wound healing is a complex and dynamic process that requires intricate synchronization between multiple cell types within appropriate extracellular microenvironment. Wound healing process involves four overlapping phases in a precisely regulated manner, consisting of hemostasis, inflammation, proliferation, and maturation. For an effective wound healing, all four phases must follow in a sequential pattern within a time frame. Several factors might interfere with one or more of these phases in healing process, thus causing improper or impaired wound healing resulting in non-healing chronic wounds. The complications associated with chronic non-healing wounds, along with the limitations of existing wound therapies, have led to the development and emergence of novel and innovative therapeutic interventions. Nanotechnology presents unique and alternative approaches to accelerate the healing of chronic wounds by the interaction of nanomaterials during different phases of wound healing. This review focuses on recent innovative nanotechnology-based strategies for wound healing and tissue regeneration based on nanomaterials, including nanoparticles, nanocomposites and scaffolds. The efficacy of the intrinsic therapeutic potential of nanomaterials (including silver, gold, zinc oxide, copper, cerium oxide, etc.) and the ability of nanomaterials as carriers (liposomes, hydrogels, polymeric nanomaterials, nanofibers) and therapeutic agents associated with wound-healing applications have also been addressed. The significance of these nanomaterial-based therapeutic interventions for wound healing needs to be highlighted to engage researchers and clinicians towards this new and exciting area of bio-nanoscience. We believe that these recent developments will offer researchers an updated source for the use of nanomaterials as an advanced approach to improve wound healing.

Experiences of patients who had a stroke and rehabilitation professionals with upper limb rehabilitation robots: a qualitative systematic review protocol.

INTRODUCTION: Emerging evidence suggests that robotic devices for upper limb rehabilitation after a stroke may improve upper limb function. For robotic upper limb rehabilitation in stroke to be successful, patients' experiences and those of the rehabilitation professionals must be considered. Therefore, this review aims to synthesise the available evidence on experiences of patients after a stroke with rehabilitation robots for upper limb rehabilitation and the experiences of rehabilitation professionals with rehabilitation robots for upper limb stroke rehabilitation. METHODS AND ANALYSIS: Database search will include MEDLINE (Ovid), EMBASE (Elsevier), Cochrane CENTRAL, PsycINFO, Scopus, Web of Science, IEEE and CINAHL (EBSCOhost). Grey literature from Open Grey, PsyArXiv, bioRxiv, medRxiv and Google Scholar will also be searched. Qualitative studies or results from mixed-method studies that include adult patients after a stroke who use upper limb rehabilitation robots, either supervised by rehabilitation professionals or by patients themselves, at any stage of their rehabilitation and/or stroke professionals who use upper limb rehabilitation robots will be included. Robotic upper limb rehabilitation provided by students, healthcare assistants, technicians, non-professional caregivers, family caregivers, volunteer caregivers or other informal caregivers will be excluded. Articles published in English will be considered regardless of date of publication. Studies will be screened and critically appraised for methodological quality by two independent reviewers. A standardised tool from JBI System for the Unified Management, Assessment and Review of Information for data extraction, the meta-aggregation approach for data synthesis and the ConQual approach for confidence evaluation will be followed. ETHICS AND DISSEMINATION: As this systematic review is based on previously published research, no informed consent or ethical approval is required. It is anticipated that this systematic review will highlight the experiences of patients after a stroke and perceived facilitators and barriers for rehabilitation professionals on this topic, which will be disseminated through peer-reviewed publications and national and international conferences. PROSPERO REGISTRATION NUMBER: CRD42022321402.

Encoder-Controlled Functional Electrical Stimulator for Bilateral Wrist Activities-Design and Evaluation.

Upper limb impairment following stroke is often characterized by limited voluntary control in the affected arm. In addition, significant motor coordination problems occur on the unaffected arm due to avoidance of performing bilateral symmetrical activities. Rehabilitation strategies should, therefore, not only aim at improving voluntary control on the affected arm, but also contribute to synchronizing activity from both upper limbs. The encoder-controlled functional electrical stimulator, described in this paper, implements precise contralateral control of wrist flexion and extension with electrical stimulation. The stimulator is calibrated for each individual to obtain a table of stimulation parameters versus wrist angle. This table is used to set stimulation parameters dynamically, based on the difference in wrist angle between the set and stimulated side, which is continuously monitored. This allows the wrist on the stimulated side to follow flexion and extension patterns on the set side, thereby mirroring wrist movements of the normal side. This device also gives real-time graphical feedback on how the stimulated wrist is performing in comparison to the normal side. A study was performed on 25 normal volunteers to determine how closely wrist movements on the set side were being followed on the stimulated side. Graphical results show that there were minor differences, which were quantified by considering the peak angles of flexion and extension on the set and stimulated side for each participant. The mean difference in peak flexion and extension range of movement was 2.3 degrees and 1.9 degrees, respectively, with a mean time lag of 1 s between the set and the stimulated angle graphs.

Comparing algorithms for assessing upper limb use with inertial measurement units.

The various existing measures to quantify upper limb use from wrist-worn inertial measurement units can be grouped into three categories: 1) Thresholded activity counting, 2) Gross movement score and 3) machine learning. However, there is currently no direct comparison of all these measures on a single dataset. While machine learning is a promising approach to detecting upper limb use, there is currently no knowledge of the information used by machine learning measures and the data-related factors that influence their performance. The current study conducted a direct comparison of the 1) thresholded activity counting measures, 2) gross movement score,3) a hybrid activity counting and gross movement score measure (introduced in this study), and 4) machine learning measures for detecting upper-limb use, using previously collected data. Two additional analyses were also performed to understand the nature of the information used by machine learning measures and the influence of data on the performance of machine learning measures. The intra-subject random forest machine learning measure detected upper limb use more accurately than all other measures, confirming previous observations in the literature. Among the non-machine learning (or traditional) algorithms, the hybrid activity counting and gross movement score measure performed better than the other measures. Further analysis of the random forest measure revealed that this measure used information about the forearm's orientation and amount of movement to detect upper limb use. The performance of machine learning measures was influenced by the types of movements and the proportion of functional data in the training/testing datasets. The study outcomes show that machine learning measures perform better than traditional measures and shed some light on how these methods detect upper-limb use. However, in the absence of annotated data for training machine learning measures, the hybrid activity counting and gross movement score measure presents a reasonable alternative. We believe this paper presents a step towards understanding and optimizing measures for upper limb use assessment using wearable sensors.

A self-aligning end-effector robot for individual joint training of the human arm.

AIM: Intense training of arm movements using robotic devices can help reduce impairments in stroke. Recent evidence indicates that independent training of individual joints of the arm with robots can be as effective as coordinated multi-joint arm training. This makes a case for designing and developing robots made for training individual joints, which can be simpler and more compact than the ones for coordinate multi-joint arm training. The design of such a robot is the aim of the work presented in this paper. METHODS: An end-effector robot kinematic design was developed and the optimal robot link lengths were estimated using an optimization procedure. A simple algorithm for automatically detecting human limb parameters is proposed and its performance was evaluated through a simulation study. RESULTS: A six-degrees-of-freedom end-effector robot with three actuated degrees-of-freedom and three non-actuated self-aligning degrees-of-freedom for safe assisted training of the individual joints (shoulder or elbow) of the human arm was conceived. The proposed robot has relaxed constraints on the relative positioning of the human limb with respect to the robot. The optimized link lengths chosen for the robot allow it to cover about 80% of the human limb's workspace, and possess good overall manipulability. The simple estimation procedure was demonstrated to estimate human limb parameters with low bias and variance. DISCUSSION: The proposed robot with three actuated and three non-actuated degrees-of-freedom has a compact structure suitable for both the left and right arms without any change to its structure. The proposed automatic estimation procedure allows the robot to safely apply forces and impose movements to the human limb, without the need for any manual measurements. Such compact robots have the highest potential for clinical translation.

A Framework for Sensor-Based Assessment of Upper-Limb Functioning in Hemiparesis.

The ultimate goal of any upper-limb neurorehabilitation procedure is to improve upper-limb functioning in daily life. While clinic-based assessments provide an assessment of what a patient can do, they do not completely reflect what a patient does in his/her daily life. The use of compensatory strategies such as the use of the less affected upper-limb or excessive use of trunk in daily life is a common behavioral pattern seen in patients with hemiparesis. To this end, there has been an increasing interest in the use of wearable sensors to objectively assess upper-limb functioning. This paper presents a framework for assessing upper-limb functioning using sensors by providing: (a) a set of definitions of important constructs associated with upper-limb functioning; (b) different visualization methods for evaluating upper-limb functioning; and (c) two new measures for quantifying how much an upper-limb is used and the relative bias in their use. The demonstration of some of these components is presented using data collected from inertial measurement units from a previous study. The proposed framework can help guide the future technical and clinical work in this area to realize valid, objective, and robust tools for assessing upper-limb functioning. This will in turn drive the refinement and standardization of the assessment of upper-limb functioning.

Quantification of the relative arm use in patients with hemiparesis using inertial measurement units.

INTRODUCTION: Accelerometry-based activity counting for measuring arm use is prone to overestimation due to non-functional movements. In this paper, we used an inertial measurement unit (IMU)-based gross movement (GM) score to quantify arm use. METHODS: In this two-part study, we first characterized the GM by comparing it to annotated video recordings of 5 hemiparetic patients and 10 control subjects performing a set of activities. In the second part, we tracked the arm use of 5 patients and 5 controls using two wrist-worn IMUs for 7 and 3 days, respectively. The IMU data was used to develop quantitative measures (total and relative arm use) and a visualization method for arm use. RESULTS: From the characterization study, we found that GM detects functional activities with 50-60% accuracy and eliminates non-functional activities with >90% accuracy. Continuous monitoring of arm use showed that the arm use was biased towards the dominant limb and less paretic limb for controls and patients, respectively. CONCLUSIONS: The gross movement score has good specificity but low sensitivity in identifying functional activity. The at-home study showed that it is feasible to use two IMU-watches to monitor relative arm use and provided design considerations for improving the assessment method.Clinical trial registry number: CTRI/2018/09/015648.

Robot-assisted rehabilitation of hand function.

PURPOSE OF REVIEW: Initial work on robot-assisted neurorehabilitation for the upper extremity aimed primarily at training, reaching movements with the proximal sections of the upper extremity. However, recent years have seen a surge in devices dedicated to hand function. This review describes the state of the art and the promises of this novel therapeutic approach. RECENT FINDINGS: Numerous robotic devices for hand function with various levels of complexity and functionality have been developed over the last 10 years. These devices range from simple mechanisms that support single joint movements to mechanisms with as many as 18 degrees-of-freedom (DOF) that can support multijoint movements at the wrist and fingers. The results from clinical studies carried out with eight out of 30 reported devices indicate that robot-assisted hand rehabilitation reduces motor impairments of the affected hand and the arm, and improves the functional use of the affected hand. SUMMARY: The current evidence in support of the robot-assisted hand rehabilitation is preliminary but very promising, and provides a strong rationale for more systematic investigations in the future.

Estimating Movement Smoothness From Inertial Measurement Units.

Inertial measurement units (IMUs) are increasingly used to estimate movement quality and quantity to the infer the nature of motor behavior. The current literature contains several attempts to estimate movement smoothness using data from IMUs, many of which assume that the translational and rotational kinematics measured by IMUs can be directly used with the smoothness measures spectral arc length (SPARC) and log dimensionless jerk (LDLJ-V). However, there has been no investigation of the validity of these approaches. In this paper, we systematically evaluate the use of these measures on the kinematics measured by IMUs. We show that: (a) SPARC and LDLJ-V are valid measures of smoothness only when used with velocity; (b) SPARC and LDLJ-V applied on translational velocity reconstructed from IMU is highly error prone due to drift caused by integration of reconstruction errors; (c) SPARC can be applied directly on rotational velocities measured by a gyroscope, but LDLJ-V can be error prone. For discrete translational movements, we propose a modified version of the LDLJ-V measure, which can be applied to acceleration data (LDLJ-A). We evaluate the performance of these measures using simulated and experimental data. We demonstrate that the accuracy of LDLJ-A depends on the time profile of IMU orientation reconstruction error. Finally, we provide recommendations for how to appropriately apply these measures in practice under different scenarios, and highlight various factors to be aware of when performing smoothness analysis using IMU data.

Collagen-functionalized electrospun smooth and porous polymeric scaffolds for the development of human skin-equivalent.

Electrospun polymer fibers have garnered substantial importance in regenerative medicine owing to their intrinsic 3D topography, extracellular matrix microenvironment, biochemical flexibility, and mechanical support. In particular, a material's nano-topography can have a significant effect on cellular responses, including adhesion, proliferation, differentiation, and migration. In this study, poly(l-lactic acid) (PLLA), a biodegradable polymer with excellent biocompatibility was electrospun into fibers with either smooth or porous topologies. The scaffolds were further modified and biofunctionalized with 0.01% and 0.1% collagen to enhance bioactivity and improve cellular interactions. Human keratinocytes (HaCaTs) and fibroblasts (human foreskin fibroblasts-HFF) were cultured on the scaffolds using a modified co-culture technique, where keratinocytes were grown on the dorsal plane for 5 days, followed by flipping, seeding with fibroblasts on the ventral plane and culturing for a further 5 days. Following this, cellular adhesion of the skin cells on both the unmodified and collagen-modified scaffolds (smooth and porous) was performed using scanning electron microscopy (SEM) and immunofluorescence. Distinct outcomes were observed with the unmodified smooth scaffolds showing superior cell adhesion than the porous scaffolds. Modification of the porous and smooth scaffolds with 0.1% collagen enhanced the adhesion and migration of both keratinocytes and fibroblasts to these scaffolds. Further, the collagen-modified scaffolds (both porous and smooth) produced confluent and uniform epidermal sheets of keratinocytes on one plane with healthy fibroblasts populated within the scaffolds. Thus, presenting a vast potential to serve as a self-organized skin substitute this may be a promising biomaterial for development as a dressing for patients suffering from wounds.

Heat Shock Protein 90 (Hsp90)-Inhibitor-Luminespib-Loaded-Protein-Based Nanoformulation for Cancer Therapy.

Drugs targeting heat shock protein 90 (Hsp90) have been extensively explored for their anticancer potential in advanced clinical trials. Nanoformulations have been an important drug delivery platform for the anticancer molecules like Hsp90 inhibitors. It has been reported that bovine serum albumin (BSA) nanoparticles (NPs) serve as carriers for anticancer drugs, which have been extensively explored for their therapeutic efficacy against cancers. Luminespib (also known as NVP-AUY922) is a new generation Hsp90 inhibitor that was introduced recently. It is one of the most studied Hsp90 inhibitors for a variety of cancers in Phase I and II clinical trials and is similar to its predecessors such as the ansamycin class of molecules. To our knowledge, nanoformulations for luminespib remain unexplored for their anticancer potential. In the present study, we developed aqueous dispensable BSA NPs for controlled delivery of luminespib. The luminespib-loaded BSA NPs were characterized by SEM, TEM, FTIR, XPS, UV-visible spectroscopy and fluorescence spectroscopy. The results suggest that luminespib interacts by non-covalent reversible interactions with BSA to form drug-loaded BSA NPs (DNPs). Our in vitro evaluations suggest that DNP-based aqueous nanoformulations can be used in both pancreatic (MIA PaCa-2) and breast (MCF-7) cancer therapy.