Knowledge Connect @ SASTRA
Not a member yet
201 research outputs found
Sort by
Development of biodegradable Mg-1Zn-0.5Sc alloy & Surface treatment through Laser Shock Peening and Evaluation of Microstructure & Property correlation for Orthopedic Implants
No full textMagnesium (Mg) and its alloys are of much interest as promising third-generation bio-materials for bone implant applications; however, challenges remain for the alloy\u27s mechanical integrity and bio-corrosion behaviour. Therefore, appropriate alloying elements and surface-modification techniques are required to overcome these limitations. Zinc (Zn) and Scandium (Sc) elements were found to have good biocompatibility and biodegradability; hence, they were selected as suitable alloying elements for magnesium.
This research work aims to enhance the mechanical integrity and bio-corrosion resistance behaviour of a novel Mg-1wt% Zn-0.5wt% Sc cast alloy by laser shock peening surface treatment with multiple passes (LSP-2 Pass and LSP-3 Pass). Based on the characterization studies, LSP induced beneficial compressive residual stress around the surface and sub-surface region of Mg-1Zn-0.5Sc alloy due to severe plastic deformation, which led to grain refinement through the twinning mechanism of the Mg alloy.
Also, the dispersion of second-phase particles (β-ScZn) was observed while analysing the XRD profiles. Strain hardening and grain refinement have been attributed to the evolution of structure and texture, which enhanced the strength, ductility, and corrosion resistance of novel Mg-1Zn-0.5Sc alloy compared to the as-cast condition. From in vitro studies, a low rate of corrosion in simulated body fluid, uniform hydroxyapatite layer formation on the surface and less cytotoxic behaviour was observed for the LSP-3 pass Mg-1Zn-0.5Sc alloy, which is suitable for bone implant applications.
However, some limitations remain, and challenges need to be addressed. In the LSP-3 pass, Mg material had only a marginal strength and a corrosion rate of cortical bone properties for orthopaedic implant applications. To address these challenges, Mg-1Zn-0.5Sc alloy was developed through thermomechanical processing at various temperatures.
During extrusion at 250°C and 350°C, the microstructure and texture evolution of the hot extruded at 350°C alloy exhibited complete dynamic recrystallization, and texture evolved to strong basal plane orientation, influencing an increased strength of 152 MPa, reduced ductility of 10%, and improved corrosion resistance. Moreover, this hot extruded at 350°C processed Mg alloy underwent multipass laser shock peening surface treatment to synergistically enhance its strength and ductility properties via structural and textural evolution.
Hence, laser shock peening on this extruded alloy surface leads to further recrystallizations owing to the effect of developed compressive residual stress near the peened surface, resulting in large grain formation. Also, favourable texture evolution of basal and non-basal planes was observed due to this LSP-induced plastic strain, with significant improvement in strength and ductility to 230MPa and 16%, respectively.
Biocompatibility analysis shows that both extruded and LSP-treated alloys have uniform bio-friendly hydroxyapatite layer formation and exhibit good cell viability after 72h of incubation. It also shows a reduced corrosion rate compared to the as-cast alloy, which can also harmonize with tissue healing and implant degradation. The extruded Mg alloy was developed through the LSP technique and can be a candidate material for orthopaedic implant application
The Role of Biofilm Matrix on the Growth, Survival, and Diagnosis in Enterobacteriaceae
No full textBacteria in nature live together encased in a matrix creating community ecosystems called biofilms, this structured space protects them from hostile environments. This study aimed to understand the role of the biofilm matrix in the growth and survival of Enterobacteriaceae. Our hypothesis proposes that subgroups of individuals within a biofilm can specialize in the production of different matrix components.
Matrix expression is metabolically costly, despite its unicellular simplicity, microbes can coordinate complex behaviour like sharing of matrix between producers and non-producers as an adept evolutionary strategy. Their resilience to stress during biofilm formation was studied to assess their abilities to cooperate and produce biofilms.
Phenotypic and morphological characteristics of the colonies were typed using Congo red assay and the influence of matrix on the architecture of biofilms was visualized using scanning electron microscopy. Our results show that matrix aids in survival during stress and possible sharing of the matrix is occurring in co-culture, with one counterbalancing the inability of the other when confronted with stress.
By deeply studying the role of the matrix, we understood how important the matrix is in causing a chronic infection and how potential biomarker it is, for detection and thwarting an infection, so we decided to turn the pathogen’s weapon against them by targeting the matrix which further led to the other objectives of development of a matrix-based treatment and matrix-based diagnosis.
For treatment, we have selected bacteriophages which are specialist viruses targeting bacteria as a potential candidate for therapeutics in the treatment of biofilms related to gastrointestinal health. We studied the predator-prey population, and our results show that the isolated phages were not able to break the biofilm matrix. The matrix protects from viral predators leading to potential futuristic research questions on the evolution of phage and bacteria creating phage biofilm coexistence.
Further, our study led to the development of a biofilm-centric diagnostics modality to advance the landscape of clinical diagnostics using the electrochemical and colorimetric approaches for the detection of biofilm-based UTIs because of their high prevalence
Study of Anomalous Variations in Seismic and Non-Seismic Parameters Using Machine Learning Techniques to Develop the Earthquake Forecasting Model in The Himalayan Belt
No full textUnderstanding and forecasting earthquakes is not just about science it’s about saving lives, even as the dynamic and hidden nature of Earth\u27s tectonic processes makes this an intricate challenge. The Himalayan belt is one of the most seismically active regions globally due to the collision of the Indian and Eurasian tectonic plates. Investigating this region is essential for understanding highly complicated tectonic mechanisms and reducing substantial hazards posed to millions of people by persistent and intense seismic events. This study aims to enhance forecasting methodologies by applying machine learning techniques while dealing with the inherent challenges of geological complexity and data limitations.
Our research explores diverse parameters, such as solid earth tides (SET), outgoing longwave radiation (OLR), and Min-Light quakes, by studying their role as potential precursors to seismic activity. By integrating these precursory signatures, we develop an advanced earthquake forecasting model using machine learning techniques to improve forecasting accuracy and resilience. In this study, we utilize precursor datasets spanning the temporal extent from 1993 to 2024 based on the lunar phase. To analyze solid earth tide (SET) data, singular spectral analysis (SSA) has been applied to identify irregularities in the SET. Rolling window approach is implemented to handle periodic and noisy components in the decomposition to ensure robust analysis and pattern detection.
The study finds that irregularities in SET, particularly variations in the sixth EF component, may serve as reliable indicators for long-term earthquake forecasting. While the stress induced by Solid Earth Tides is significantly lower than that from tectonic plate motion, EF analysis of the SET time series remains a vital indicator of its inherent characteristics. Further, the possible vulnerable seismic nucleation zone and the possible depth and magnitude of triggering in mainshocks are identified through cluster analysis.
The OPTICS clustering algorithm was applied to Min-Light quake data, identifying distinct seismic clusters and vulnerable zones. These clusters align closely with the epicenters of major earthquakes, emphasizing their importance for seismic hazard assessment. The OLR observations give us insight into how atmospheric parameters are affected by seismic activity in an area. There was a correlation between the magnitude of the earthquake and the distinct features extracted from the analysis of Min-Light quakes and OLR.
An ensemble model has been developed by integrating spatio-temporal analysis of solid earth tides and Min-Light quakes with implications for earthquake forecasting. The models demonstrated near-perfect success in forecasting impending earthquake’s latitude (99%) but showed moderate success for “Earthquake_Occurrence” (60%) and longitude (50%). Forecasting the Depth of the impending earthquake is the most challenging one, with a low success rate of 40%, reflecting complexities in modelling subsurface processes. The findings emphasize the performance of ensemble models, especially in elucidating complex linkages and enhancing accuracy in forecasting for geophysical forecasting
A Geomatic Appraisal On Restoration Of Tank Cascade Systems In Ambuliyar Watershed, Tamilnadu
No full textTanks and earthen embankments used for water harvesting and storage have been a significant part of India\u27s irrigation system since the 2nd and 3rd centuries. In Tamil Nadu, around 39,202 tanks have storage capacities of around 178.94 million cubic feet. However, they have been impacted by natural and anthropogenic threats such as soil erosion, siltation, inadequate rainfall, and drought. This study aims to determine the current storage capacity of tanks, estimate the loss in storage capacity/volume of silt, estimate the rate of siltation and life of tanks, identify soil erosion-prone zones, and map deteriorating parameters along supply channels.
The study evaluates the degradation of tanks using qualitative and quantitative methods. The results show that most tanks significantly lost their capacity, with an average loss of 50.09%. The linear empirical equation-based model can effectively estimate tank storage capacity. The RUSLE model estimates erosion magnitude and spatial distribution, showing an overall increase in mean annual soil loss from 4084.40 t ha−1/yr (1996) to 4922.47 t ha−1/yr (2016). The model reveals the influence of land use modifications, mainly plantation and cropland areas, on the rate and pattern of soil erosion.
Implementing biological and mechanical measures such as afforestation, promoting coconut and eucalyptus plantations, and so on can reduce erosion in the study area. The study investigates sedimentation rates and tank life estimations, highlighting the importance of tank conservation planning and management. Radionuclides, like 210Pb and 137Cs, estimate sediment deposition and accumulation rates in various environments. The Peravoorini tank\u27s sedimentation rate was calculated using a multichannel gamma-ray spectrometer, and the average sediment accumulation rate was 0.69 cm/y.
Under current sedimentation rates, the tank\u27s useful life is projected at 428.57 years. The study evaluates the storage efficiency of tanks after renovation using the SCS-CN method. The study reveals a correlation between runoff and the storage capacity of tanks in each microwatershed. The stored water can be efficiently used for agricultural and other needs throughout the year, improving the economy of the rural populous
Computational Studies On The Major Antioxidant Enzymes Of Wuchereria Bancrofti Towards The Development Of Anti Filarial Leads
No full textLymphatic filariasis (LF), or elephantiasis, is a mosquito-borne parasitic disease affecting the lymphatic system, primarily in tropical and subtropical regions. It is the second leading cause of long-term disability and a neglected tropical disease. According to WHO, LF threatens 882 million people in 44 countries, with over 9 billion treatments administered. The disease is caused by three nematodes: Wuchereria bancrofti (90% of cases worldwide, including India), Brugia malayi (10% in Southeast and Eastern Asia), and Brugia timori (found in Timor and nearby islands). Lymphatic filariasis (LF) is an ancient disease that continues to challenge scientists and physicians. Current treatments include diethylcarbamazine (DEC), albendazole (ALB), and ivermectin (IVM), but drug resistance is rising due to SNP mutations and lack of specificity with the filarial targets from repeated use. These drugs are ineffective at all stages of the parasite’s complex life cycle. There is an urgent need to identify new druggable targets and candidate molecules to combat LF effectively.
IDENTIFICATION OF PUTATIVE DRUG TARGETS OF W. BANCROFTI:
In this direction, we identified potential drug targets for W. bancrofti by analyzing its complete proteome, retrieved from NCBI and UniProt. After removing redundant sequences, BLASTp screening against the human proteome identified 8,350 non-homologous proteins, with 125 classified as essential through DEG analysis. Metabolic pathway screening revealed 12 key enzymes, including five major antioxidant enzymes: Cu/Zn superoxide dismutase (SOD1), glutathione peroxidase (GPx), peroxiredoxin 6 (Prx6), thioredoxin peroxidase 1 (Tpx1), and glutathione S-transferase (GST), critical for neutralizing reactive oxygen species (ROS) and maintaining cellular homeostasis. As these enzymes are vital for parasite survival, making them promising therapeutic targets for the development of antifilarial drugs.
MODELLING AND STRUCTURE-BASED DRUG DESIGN OF FILARIAL ANTIOXIDANT ENZYMES:
The three-dimensional structure of SOD1, GPx, Prx6 and Tpx1 was modelled and the dynamic stability from MD simulation showed that the antioxidant enzymes were found to be stable based on the trajectory profiles and the resultant structures were used for further studies. Structure-based drug design targeted filarial antioxidant enzymes using the ChemBridge database. To minimize failures, ADMET screening identified the top five non-toxic leads per enzyme with the highest docking scores. Comparative-docking against human antioxidant enzymes confirmed higher specificity for filarial targets due to differences in surface charge, cavity volume, and hydrogen bonding. The complex MD simulations confirmed the stable and intact binding of these leads in the enzyme pockets. Finally, the top three non-toxic leads per filarial antioxidant enzyme were procured for in vitro studies.
IN VITRO VALIDATION OF THE LEADS:
Antifilarial activity was tested using Setaria digitata, a homolog of W. bancrofti, authenticated at the Veterinary College, Orathanadu. The MTT-formazan assay evaluated the top three leads per target at concentrations ranging from 0.625 to 20.000 μM in triplicate, comparing their inhibition rates to ivermectin. We observed ten leads exhibit a lesser IC50 value, while the remaining five exhibit a higher IC50 value than the control drug ivermectin. The leads with lower IC50 than the control exhibited AAHR and AARR pharmacophore features, while the other leads had ADHR and AHRR, differing due to geometric variations.
CONCLUSION
Our computational results and in vitro studies identified potential leads for the five antioxidant enzymes that play a vital role in the first-line defence against free radicals and reactive oxygen species, in vitro assay revealed ten leads exhibit better antifilarial activity. Inhibiting these major antioxidant enzymes will likely reduce the pathogenicity and survival of W. bancrofti. The implication of the findings offers valuable insight. It opens up new avenues for developing novel inhibitors for further drug development and clinical trials to effectively combat lymphatic filariasis caused by W. bancrofti in India and globally. In addition, this study serves as a model pipeline for other Neglected Tropical Diseases (NTDs), to identify potential drug targets and candidate drug molecules
Detailed Modelling and Analysis of a Shake Table Comprising Hybrid Actuation and Load-Balancing Mechanism
No full textCatastrophic earthquakes endanger human lives by severely damaging critical infrastructure such as nuclear plants, bio-laboratories, and bridges. Developing earthquake-resistant structures is vital to mitigate these risks. Shake tables replicate recorded earthquake ground motions to assess structural performance. This research presents a novel three-legged, six degrees of freedom (6-DOF) hybrid shake table with a cost-effective design and decoupled motion control, offering a viable alternative to conventional six-legged models.
This architecture effectively decouples actuator motions by employing hydraulic actuators for 3-DOF spatial movement and electromechanical actuators for 3-DOF planar motion. Servo-hydraulic actuators support the static payload against gravity, while lightweight electromechanical actuators enable planar motion.
In the hybrid shake table, actuator assemblies and planar links cause inaccuracy while positioning the platform with a heavy payload due to the cantilever effect. While precise fabrication reduces inaccuracy, sustained loading weakens stiffness and necessitates an effective load-balancing mechanism. A passive load-balancing mechanism is preferred to eliminate actuator redundancy. However, its integration introduces complex coupled ordinary differential equations (ODEs), requiring system identification for precise motion control.
A fusion-based system identification approach was devised to select a suitable passive load-balancing mechanism from multiple alternatives using minimal experimental data. This approach integrates experimental data for identifying the shake table\u27s parameters with simulation data for characterising passive load-balancing mechanisms. A regression-based nonlinear least-squares (NLS) technique enhanced by the trust-region-reflective (TRR) algorithm is proposed for system identification.
Among the passive mechanisms analysed, the hydraulic damper demonstrated superior load-balancing performance. The use of a passive hydraulic damper to counteract the load-balancing effect is an innovative approach in parallel manipulator research, improving stiffness and damping characteristics. Additionally, its impact on motion control and overall system performance is analysed.
The electromechanical actuator assembly of the hybrid shake table consists of a servo motor, gearbox assembly, electric cylinder with a ball screw drive, and a recirculating ball linear motion guide block, requiring detailed modelling that accounts for frictional effects. Consequently, a state feedback controller is designed to ensure precise motion control
Design & Development of Efficient Biometric Authentication and Key Agreement Schemes for Wireless Body Area Network
No full textWireless Body Area Networks (WBANs) play a vital role in continuous health monitoring, where sensitive biometric and physiological data must be protected from privacy breaches and emerging quantum-based threats. Conventional security mechanisms are often inadequate due to resource constraints, scalability issues, and vulnerability to advanced attacks. To address these challenges, this research proposes a lightweight, scalable, and future-proof security framework tailored for WBAN applications, focusing on secure communication, privacy preservation, and quantum resilience.
An anonymous Certificate-Based Signcryption–Mutual Authentication and Key Agreement (CBS-MAKE) protocol is introduced to secure extra-body communications while ensuring patient anonymity. The protocol integrates Elliptic Curve Cryptography with anonymous certificates derived from the Quadratic Residuosity Problem to conceal user identities. Formal verification using BAN-Logic and validation through SPAN-AVISPA confirm the protocol’s resistance to known security attacks. The CBS-MAKE protocol supports both single and multi-user scenarios (PDA→AP and PDAi→AP), enabling scalable and secure group communication in WBAN environments.
The security of bio-hashed biometric templates within the CBS-MAKE framework is critically examined, revealing vulnerabilities to similarity and dictionary attacks when optimized using Particle Swarm Optimization and Covariance Matrix Adaptation–Evolution Strategy. These attacks exploit the similarity-preserving nature of biohashing, achieving only 64% resistance at a threshold of 0.8. To overcome these limitations, a Cancelable Biometric Template protection scheme based on Dynamic Degree-adjusted Chebyshev (D2CAP) chaotic maps is proposed, offering enhanced randomness and statistical robustness.
The D2CAP-based template protection scheme demonstrates superior statistical performance compared to standard Chebyshev maps, satisfying all NIST 800-22 randomness requirements. Extensive evaluation across multiple biometric modalities—including iris, fingerprint, palm vein, ear, face images, and real-time video sequences—shows strong security characteristics, with entropy above 7.95%, NPCR exceeding 99.5%, UACI around 33%, and a low Equal Error Rate of approximately 0.12±0.05%. While effective against classical cryptographic and similarity attacks, the scheme remains susceptible to quantum-enhanced plaintext attacks.
To achieve quantum-resistant biometric security, the framework is extended using binary lattice-based cryptography and Hyperelliptic Curve Cryptography (HECC). Two quantum-secure schemes, AEGIIS and G2CAPS, are developed to reinforce cancelable biometric templates against both classical and quantum adversaries. These methods achieve high recognition accuracy of up to 99.7% while offering improved storage and computational efficiency. Notably, the proposed hyperelliptic curve was standardized by ITU-T Study Group 17 in 2024, reinforcing its credibility as a robust and future-ready cryptographic solution
Assessment of Risk Factor Prediction using Machine Learning Techniques and Hybrid Approach based on Soft Sets
No full textCardiovascular diseases (CVDs) are the leading cause of mortality worldwide, and India reports a significantly high death rate due to its large population base and the increasing prevalence of non-communicable diseases. National statistics indicate that 20–27% of deaths in India are attributed to CVDs, with the proportion steadily rising over the years. Recognizing the urgency of early detection and risk prevention, the World Health Organization (WHO) introduced “The Global Action Plan for the Prevention and Control of Non-Communicable Diseases (2013–2020),” emphasizing early identification, risk reduction, and timely treatment. In this context, decision-making applications have gained importance across domains especially healthcare where effective and timely decisions can prevent premature deaths.
This research focuses on developing a decision-making algorithm for identifying significant risk factors associated with CVDs using a hybrid approach combining soft sets and machine learning. A soft-set-based parameter reduction algorithm is proposed to identify essential parameters influencing cardiovascular risk. The algorithm represents patient data as soft sets, constructs a map matrix, and performs parameter reduction with a computational complexity of O(nf + 2^f). Real-world data consisting of nine clinical features collected from diagnostic laboratories in Kumbakonam, Tamil Nadu, are processed using this approach, with triglycerides emerging as a key factor across all reductions.
Subsequently, various machine learning classifiers including SVM, KNN, LDA, Decision Tree, Random Forest, Naïve Bayes, CART, and Logistic Regression are applied to develop predictive models. Among these, Random Forest achieves the highest accuracy of 69.23%. Clustering techniques such as k-means, PAM, hierarchical clustering, and fuzzy clustering are also used to analyze patient risk groups, supported by validation methods including Hopkins statistic, Dunn’s index, silhouette analysis, PCA, and model-based clustering.
A hybrid integration of soft-set-based reductions with machine learning further improves prediction accuracy, with Random Forest achieving 88.46%. Ensemble learning methods bagging, boosting, and stacking identify an efficient parameter subset consisting of Gender, SugarPP, Creatinine, Total Cholesterol, HDL, and LDL, yielding 93% accuracy. Across all evaluations, Total Cholesterol and LDL consistently emerge as predominant risk factors. The proposed framework demonstrates strong potential for enhancing early diagnosis and supporting clinical decision-making in cardiovascular healthcare
Comparative Analysis of Copyright in Electronic Games and Its Impact on Personality Rights
No full textIn India and globally, the electronic gaming business is a rapidly growing and evolving sector both in terms of revenue as well as technological creativity. Over the last 20 years, the video game business has seen significant change. It has transcended borders and is no longer limited to a single or a few players played within a room. Modern video games, unlike their predecessors, include many distinctive visuals and other components are and closely compared to motion pictures.
Electronic games and their complexities present unique challenges to copyright law. In this research, the researcher explores and examines issues in the existing copyright jurisprudence in relation to these games. Electronic games provide a number of legal concerns and challenges for copyright, mostly because of their intricacy and segmentation. Copyright protection may be applied to the various components found in these games. Copyright covers all original creative elements like literary work, artistic work, musical work, sound recording and cinematograph film.
When it comes to electronic games, on one hand, there is the computer program (literary work) that serves as the game\u27s foundation and on the other hand, there is the other creative aspects like the graphics (artistic work), music , sound and some games even have story line which projects like a film that show up on the screen as the game is being played, giving it a distinctive and original appearance. The copyrightability of electronic games and the protection that copyright laws may provide to these games and the stakeholders involved are examined in this research.
The study, which uses the doctrinal methodology of research, is restricted to the protection of video games under the copyright laws and employs a comparative analysis with nations like the USA, Canada, China, South Africa, Japan, Germany and Singapore. The study examines India\u27s legal framework on personality rights and how they are likely to be violated in electronic games.
Personality rights, which are sometimes seen as the core of an individual\u27s identity, and they are also known as publicity rights which provides an individual the authority to govern the commercial use of one\u27s own personal identity / attributes, as the Delhi High Court noted in the historic Titan Industries Case1. These attributes of an individual are likely to be utilised in certain electronic games.
This is the point of contention since the use of some elements of the individual\u27s personal identity may impact and violate personality rights, including those related to privacy and publicity. The researcher evaluates whether personality rights in electronic games are attributed only to celebrities or can it also extend to any individual whose likeness is monetized without their consent. The research highlights the evolving nature of electronic games and the scope of personality rights in these games due to the fact that in today’s modern digital world, with the use of social media, any individual can attain fame
Facile Fabrication Of Protein-Polysaccharide Conjugate Multifilament Nerve Guidance Conduit For Peripheral Nerve Regeneration
Get PDFLong segmental defects in peripheral nerves impair sensory and motor function by disrupting neural impulse transmission. End-to-end autologous grafting with proper fascicular complementation has demonstrated functional recovery per the Medical Research Council Classification (MRCC). However, obtaining donor nerve tissue exceeding 30 mm remains a significant challenge. Artificial hollow conduits serve as an alternative but are limited to defects smaller than 30 mm due to inadequate innervation across the lumen.
Multichannel nerve guidance conduits (mNGCs) have emerged as a promising solution by enhancing fascicular complementation similar to autografts. This study presents a two-step approach for fabricating nerve conduits with precise fascicular organization. A customized 3D-printed multifilament extrusion system enables the rapid creation of perineurium-like structures, encapsulated within a biomimetic epineurial sheath via dip-coating. Pectin-based multifilament conduits, designed with tunable filament numbers (4, 6, 8, and 10), were fabricated using a 3D wet writing process to closely mimic native nerve fascicles.
To address the limited structural integrity of ionically crosslinked pectin, methacrylate groups were introduced to the hydroxyl functionalities of pectin via aldehyde-mediated chemistry, enabling covalent network formation through photo-induced crosslinking. This chemical modification significantly enhances the mechanical stability and durability of the resulting conduits. However, native pectin lacks intrinsic bioactive cues necessary for effective cellular adhesion.
To overcome this limitation, keratin extracted from human hair was covalently conjugated to the methylene functional groups of the methacrylated pectin (PecMA) via thiol-ene click chemistry. The keratin conjugated pectin methacrylate (Keratin-PecMA) provides biologically active motifs for cellular attachment while ensuring its stable integration into the polymer backbone, thereby preventing leaching during fabrication or physiological implantation.
The bio-ink’s dual crosslinkable properties and template-free fabrication allowed the rapid formation of structurally stable, cell-laden conduits. Scanning electron microscopy (SEM) and micro-Computed Tomography (Micro-CT) reconstructions confirmed that the acellular multifilament conduits closely resembled native rat and goat sciatic nerves, replicating epi-, peri-, and endoneurial features.
In vitro studies demonstrated that the cellular multifilament conduits supported cytocompatibility and enhanced Neurofilament Heavy chain (NF200) expression in PC12 cells and S100 expression in RSC96 cells. Ex vivo micro-CT imaging of anastomosed decellularized goat sciatic nerve with an 8-filament conduit using Vetbond® revealed precise fascicular alignment. In vivo, Keratin-PecMA multifilament conduits remained non-irritant for 8 weeks in a rat subcutaneous pouch model, confirming biocompatibility. In a rat sciatic nerve defect model, the conduits improved sciatic function index (SFI) and reduced foot slips 8 weeks post-implantation.
Proper fascicular alignment facilitated greater nerve fibre orientation, with Keratin-PecMA conduits supporting larger fibre diameters than PecMA conduits, emphasising keratin’s role in nerve regeneration. Immunohistochemical analysis further revealed enhanced neuronal and Schwann cell marker expression in Keratin-PecMA conduits. Additionally, the comparable muscle mass ratio between Keratin-PecMA and autograft groups indicated effective end-organ innervation. These findings suggest that customizable Keratin-PecMA multifilament conduits could serve as a viable alternative to autografts