General Sir John Kotelawala Defence University

The diagnosis and treatment of leptospirosis in high-burden, low-resource settings pose a challenge due to the limited availability of confirmatory diagnostics. Therefore, the initiation of treatment relies primarily on the clinical assessment of patients suspected of having leptospirosis in resource-poor settings. This study aimed to both early diagnostic indicators and predictors of disease severity. A total of 170 patients suspected of having leptospirosis admitted to selected hospitals in Western Province, Sri Lanka were enrolled. MAT, qPCR, and culture were used for confirmatory diagnosis. Patients with confirmed leptospirosis were grouped as severe and non severe based on presenting with at least one organ failure and/or dysfunction. Out of 170 leptospirosis suspected patients, 79 (46.47%) were confirmed by PCR (n = 49), MAT (n = 44) and/or culture (n = 2). Myalgia, oliguria, elevated neutrophils, serum creatinine, serum urea, SGOT, SGPT and CRP, decreased lymphocytes, haemoglobin and platelets had a significant association with confirmed leptospirosis. Of patients with confirmed leptospirosis, 51 were categorized as non severe and 28 were categorized as severe. Leptospirosis severity was correlated with decreased haemoglobin, lymphocyte and platelet counts, and elevated WBC, neutrophil, K+, SGOT, SGPT, serum urea, serum creatinine, total and direct bilirubin and CRP. A bacterial load between 1.21 × 102 to 1.26 × 106 (median 3,326) Leptospira/ml was reported with no significant association between severity of the disease and leptospiraemia. Clinical and basic laboratory findings play a crucial role in supporting the diagnosis of leptospirosis and predicting disease severity, particularly in tropical, resource-poor settings.

ABSTRACTPreventing pressure injuries among nursing home residents is a significant challenge that necessitates understanding the barriers and facilitators from the perspective of staff. This qualitative study aimed to describe these factors within Sri Lankan nursing homes. Semi‐structured interviews were conducted with 15 nursing home staff members from nine nursing homes in and near the Colombo district, Sri Lanka. The study was informed by the capability, opportunity, motivation, and behaviour model that guided both data collection and analysis. Data were analysed using content analysis. Using deductive coding based on capability, opportunity, and motivation, followed by inductive analysis, four primary categories emerged: focusing on skincare is foundational for pressure injury prevention, pressure injury knowledge is critical for prevention, pressure injury prevention is a low organisational priority, and overcoming challenges to enact pressure injury prevention. Key facilitators included access to skincare products, maintaining clean and dry skin, recognising risk factors, proactively managing risks, and understanding the broader implications of pressure injuries on residents and their families. Conversely, barriers encompassed limited training, varying staff support, inadequate resources, and the complexities of managing multiple tasks. This research highlights that enhancing knowledge and allocating resources effectively can improve the implementation of pressure injury prevention strategies in Sri Lankan nursing homes.

This study reports a novel approach to chronic woundtherapy byfabricating a dual antimicrobial electrospun wound dressing that simultaneouslydelivers neomycin (antibacterial) and clotrimazole (antifungal) ina poly­(vinyl alcohol) (PVA) and biocompatible chitosan (CS) PVA/CSmatrix. Compared to single-drug products in use today, this new dressingmitigates polymicrobial infections characteristic of chronic woundsthrough controlled dual-drug release kinetics, with initial rapidneomycin (NM) release to instantaneously control bacteria and slowdiffusion of clotrimazole (CZ) to provide extended antifungal coverage.Because they take longer to heal, chronic wounds with bacterial andfungal infections pose serious healthcare difficulties. The optimalpolymer combination of 3% (w/v) PVA and 3% (w/v) chitosan in a ratioof 4:1 (PVA/CS) was determined, with drug concentrations being 0.5%(w/v) neomycin and 1% (w/v) clotrimazole, and nanofibers with averagediameters of 60 ± 18 nm (control) and 87 ± 26 nm (drug-loadedfilms) were achieved. The dressings reported good mechanical properties(7.49 MPa tensile strength) and enhanced fluid absorption capacities(299% water absorption), suitable for application in wound healing.Kinetic patterns in drug release investigations revealed therapeuticactivity optimized uniquely. Neomycin displayed rapid initial release(40% within the first hour) following non-Fickian Weibull kinetics(R2 = 0.88), while clotrimazole showedsustained Higuchi-type diffusion (R2 =0.97). The wound dressing exhibited greater antimicrobial activityagainst Gram-positive and Gram-negative bacteria (zones of inhibition:22.5 ± 0.7 mm and 18.5 ± 0.7 mm, respectively) and excellentantifungal activity against Aspergillus niger and Lasiodiplodia theobromae (zonesof inhibition: 35.8 ± 7.4 mm and 27.0 ± 1.4 mm, respectively).The FTIR analysis confirmed successful drug incorporation within thepolymer matrix. This innovative multifunctional electrospun wounddressing is effectively fabricated with tailored dual antimicrobialrelease profiles, achieving an integrated approach to chronic woundtreatment. Subsequent studies should involve in vivo investigations and clinical trials for evidence of safety and efficacyin the future.

HFpEF accounts for 12-25% of heart failure cases in South Asia, primarily driven by hypertension, diabetes, and obesity. Late diagnosis and healthcare disparities worsen outcomes. This expert consensus aims to provide region-specific guidelines for the diagnosis, management, and prevention of HFpEF. A modified Delphi process with experts from five South Asian countries was conducted, informed by a literature review (2018-2024) and adapted international guidelines. Recommendations include the use of an adjusted H2FPEF score (BMI > 25 kg/m²), essential echocardiographic criteria (E/e' > 9, LAVi > 34 mL/m²) for diagnosis, and SGLT2 inhibitors as first-line pharmacotherapy, with finerenone for cardio-renal protection. Emphasis on lifestyle modification, patient education, and aggressive management of comorbidities is highlighted to reduce hospitalizations. HFpEF presents earlier and is associated with higher comorbidity in South Asia. Adaptations such as lower BMI thresholds and region-specific screening are critical. Cost and accessibility challenges persist in the use of SGLT2 inhibitors and finerenone. Public health measures and infrastructure strengthening are necessary to improve outcomes. Early diagnosis, multidisciplinary management, and tailored treatment strategies can enhance outcomes in HFpEF in South Asia. This consensus serves as a call for regionally focused implementation to reduce the burden of HFpEF.

The exponential advancement of quantum computing poses an unprecedented threat to blockchain technology and emerging Sixth Generation (6G) networks, necessitating an urgent transition to post-quantum cryptographic solutions. This comprehensive review proposed post-quantum Cryptography (PQC) integration within Blockchain Enabled 6G (BE6G) architectures, highlighting vulnerabilities by Shor’s and Grover’s algorithms according to existing cryptographic standards, including Rivest-Shamir-Adleman (RSA), Elliptic Curve Digital Signature Algorithm (ECDSA), and Elliptic-Curve Cryptography (ECC). The paper addresses quantum computing fundamentals and blockchain security implications, exploring quantum-resistant cryptographic schemes including lattice-based, hash-based, code-based, and multivariate approaches. Through systematic examination of post-quantum threats, this review shows vulnerabilities affecting nearly 25% of existing cryptocurrency assets, presenting how quantum computers can break public-key systems in polynomial time. The study proposes solutions for implementing quantum-resistant blockchain architectures throughout 6G components, including Radio Access Network (RAN), edge computing, and core transport networks, while meeting ultra-low latency and scalability requirements. Key findings elaborate that hybrid cryptographic approaches combining classical and quantum-resistant algorithms provide promising directions. Lattice-based algorithms, particularly CRYSTALS-kyber and CRYSTALS-dilithium, are identified as primary deployment candidates. The review concludes that successful Quantum-Resistant Security deployment for BE6G Networks requires unprecedented coordination among telecommunication operators, blockchain developers, equipment manufacturers, and regulatory bodies. The ”harvest now, decrypt later” threat model creates sudden implementation, valuable for long-term digital infrastructure security.

The long-debated philosophical dilemmas such as ethics, consciousness, and free-will have become of considerable interest among the philosophers and scientists alike who work on artificial intelligence (AI). This study investigates how the Tiantai Buddhist concept of Buddha-nature can be incorporated into the ethics pertaining to "artificial animals" or bots, as "ethically charged machines." The major research problem addressed here is whether the thoughts of Tiantai Buddhist School on Buddha-nature can contribute to the improvement of AI-based technologies. This analysis uses certain philosophical developments in the school of New Materialism that rethinks the nature of matter, agency, and subjectivity by transcending old-fashioned dualisms for instance mind/body, human/nonhuman, and subject/object while emphasizing on the active, dynamic qualities of matter and the interconnectedness of all entities; blurring demarcations between human and nonhuman. The ideas of Jingxi Zhanran (711–782) from the Tiantai school, which assert that Buddha-nature exists not only in sentient beings but also in insentient things, will form a major premise of this argument. The study has used comparative analysis and hermeneutics as the research methodologies with academic interpretation and comparative analysis. The objective of the study is exploring the Tiantai concept of Buddha-nature in AI Ethics connecting with philosophical discourse found in the school of New Materialism. In conclusion, compassion and wisdom towards insentient beings that was neglected by the Western paradigms of ethics will throw a new light on AI ethics.

Small and Medium-sized Enterprises (SMEs) in Sri Lanka are increasingly turning to social media to gain insights into consumer preferences; however, they frequently lack sophisticated analytical tools to derive actionable insights. This research introduces a hybrid deep learning framework aimed at sentiment and emotion analysis specifically for the Sri Lankan cake sector. Customer reviews and social media comments were gathered and processed through various methods including text cleaning, emoji translation, stopword elimination, tokenization, and sequence padding. Several deep learning models— Convolutional Neural Networks (CNN), Bidirectional Long Short-Term Memory (BiLSTM), and Gated Recurrent Units (GRU) were assessed, along with hybrid models that combined CNN and BiLSTM with GPT-2 embeddings. The CNN+GPT-2 model achieved the highest accuracy in sentiment classification at 96.14%, while BiLSTM performed best in emotion classification with an accuracy of 91.57%. In terms of trend forecasting, Long Short-Term Memory (LSTM) outshone both SARIMA and Prophet, yielding the lowest error metrics and the most reliable sentiment predictions. These results underscore the potential of hybrid deep learning and transformer-based models to effectively capture complex consumer sentiments and provide SMEs with practical, AI-driven insights. This study is among the first to implement such hybrid NLP models within a localized Sri Lankan context, presenting a scalable approach for business intelligence and informed decision-making.