Gastroenterology Medical Center and Hospital

Purpose This study critically reviews the emerging literature on green digital finance, focusing on the interplay between digital technologies and sustainable financial transformation. This review examines four key domains (blockchain, artificial intelligence, big data and digital platforms) and analyses their potential contributions to green finance as well as associated risks. A conceptual framework is proposed to illustrate how digital innovations, supported by appropriate institutional contexts, can foster new quality productive forces. The study identifies major research gaps, particularly the lack of empirical assessments, the need for harmonised governance mechanisms and the limited engagement with behavioural dynamics. Policy and managerial implications are outlined, with strategic recommendations for regulators, financial institutions, platform providers and development agencies. The paper concludes by highlighting directions for future interdisciplinary research and practical frameworks to align green finance with technological transformation and sustainable productivity. Additionally, the work contributes to the ongoing debate on the emergence of new quality productive forces, analysing how green digital finance can act as a catalyst for sustainable economic transformation through technological innovation and institutional realignment. Design/methodology/approach The paper adopts a critical literature review methodology, systematically analysing peer-reviewed studies and policy documents on green digital finance across four technological domains. A conceptual framework is developed to structure the relationship between technological tools, institutional enablers and productive transformation. The review is complemented by a structured research agenda and a matrix of stakeholder-specific implications. Findings The review identifies four key technological drivers of green digital finance and highlights both their transformative potential and systemic risks. It finds that blockchain and AI can support traceability and automation, but face governance and bias concerns. Big data and platforms offer behavioural and analytical advantages, yet pose challenges in terms of privacy, data quality and accountability. The study concludes that green digital finance can catalyse new productive forces if supported by institutional innovation, inclusive design and standardised evaluation metrics. Originality/value This paper is among the first to systematically link green digital finance to the formation of new quality productive forces, providing both a conceptual framework and a policy-oriented synthesis of technological developments. Unlike prior reviews, it integrates critical reflections on governance, behavioural factors and empirical gaps, offering a structured research and policy agenda with relevance for China and other emerging economies.

Purpose: To develop a new domain generalization (DG) framework for diabetic retinopathy (DR) classification using Vision Transformers (VTs). Methods: A deep-learning-based prediction-softening mechanism has been used to allow self-distillation, whereby the knowledge extracted is transferred to intermediate layers. Intermediate representations are further improved with an adaptive convex combination of one-hot labels and internal predictions of the model, which helps regularize the network and counteract overfitting. Various publicly available DR datasets, such as APTOS and EYEPACS, in multi-source and single-source DG settings containing three VT backbones (DeiT, T2T-VT, and CvT) were used. Results: The proposed framework outperforms current DG methods, with better top-1 accuracy, strong calibration and predictive accuracy in unfamiliar domains. Conclusion: The Softening Predictions for Self-Distillation (SPSD)-VT framework is a robust, reliable, and generalizable framework that classifies DR and underscores the important role that domain generalization plays in medical imaging and sets a standard for future studies.

In the life of ancient Tamils, medicine was not merely a tool for curing diseases but existed as a way of life in harmony with nature. Siddha medicine, considered one of the oldest medical systems in the world, finds its foundational roots within Tamil literature. This research paper provides a comprehensive analysis of medical data embedded across a timeline ranging from the Tolkappiyam and Sangam literature to the Pathinen Keezhkanakku (Eighteen Lesser Texts) and Chola-era inscriptions. Specifically, the anatomical knowledge of ancient Tamils, battlefield surgical procedures, diagnostic techniques, and pharmacological classifications are analyzed from a scientific perspective. The paper presents detailed discussions on how the principle of 'Food as Medicine' and psychiatric treatment methods are recorded in literature. Through historical evidence such as the Thirumukkudal inscription, the hospital management systems and medical education methods of that era are investigated. Finally, the study concludes by highlighting how the medical wisdom of ancient Tamils aligns with modern medical discoveries and emphasizes its relevance for the future. பழந்தமிழர் வாழ்வியலில் மருத்துவம் என்பது வெறும் நோய் தீர்க்கும் கருவியாக அமையாமல், இயற்கையோடு இயைந்த ஒரு வாழ்வியல் நெறியாகவே திகழ்ந்தது. உலக அளவில் தொன்மையான மருத்துவ முறைகளில் ஒன்றாகக் கருதப்படும் சித்த மருத்துவம், தமிழர்களின் இலக்கியங்களிலேயே தனது வேர்களைக் கொண்டுள்ளது. இவ் ஆய்வேடு, தொல்காப்பியம் தொடங்கி, சங்க இலக்கியங்கள், பதினெண் கீழ்க்கணக்கு நூல்கள் மற்றும் சோழர் காலக் கல்வெட்டுகள் வரை பொதிந்துள்ள மருத்துவத் தரவுகளை விரிவாக ஆய்வு செய்கிறது. குறிப்பாக, பழந்தமிழரின் உடற்கூறியல் அறிவு, போர்க்கள அறுவை சிகிச்சை முறைகள், நோயறிதல் நுட்பங்கள் மற்றும் மருந்தியல் வகைப்பாடுகள் ஆகியவை அறிவியல் கண்ணோட்டத்தில் பகுப்பாய்வு செய்யப்படுகின்றன. 'உணவே மருந்து' என்ற கோட்பாடு மற்றும் மனநல மருத்துவ முறைகள் எவ்வாறு இலக்கியங்களில் பதிவாகியுள்ளன என்பது குறித்து விரிவான விவாதங்கள் முன்வைக்கப்படுகின்றன. திருமுக்கூடல் கல்வெட்டு போன்ற வரலாற்றுச் சான்றுகள் வழியாக, அன்றைய மருத்துவமனை மேலாண்மை மற்றும் மருத்துவக் கல்வி முறைகள் ஆராயப்படுகின்றன. முடிவாக, பழந்தமிழரின் மருத்துவ அறிவுத்திறன் தற்கால நவீன மருத்துவக் கண்டுபிடிப்புகளுடன் எவ்வாறு ஒத்துப் போகிறது என்பதும், அதன் எதிர்காலத் தேவை குறித்தும் இவ் ஆய்வு முடிவுகளை வழங்குகிறது.

The opportunity to create sustainable business models that take into account social, economic, and environmental factors is presented by the integration of artificial intelligence (AI) in smart cities. Intelligent transportation networks, waste management programs, and smart grids are some of the key uses. Cutting-edge frameworks for the circular economy, sharing economy platforms, and performance-based models improve recycling procedures, reduce waste, make resource sharing easier, and boost productivity. The useful advantages of AI in promoting urban sustainability are demonstrated by case studies of prosperous AI-driven sustainable business models in international smart cities. Nonetheless, issues including legal frameworks, significant upfront investment expenditures, and data privacy concerns must be resolved. Public-private collaborations, encouraging legislation, and the use of moral AI are some of the solutions. This chapter offers stakeholders a thorough manual for putting AI-enhanced sustainable solutions into practice in urban settings.

Autoimmune hepatitis (AIH) in children presents significant diagnostic and therapeutic challenges requiring a multidisciplinary and evidence-based approach. The Indian Society of Pediatric Gastroenterology, Hepatology, and Nutrition (ISPGHAN) convened a consensus meeting on February 23, 2025, bringing together national and international experts to address key clinical and research questions. The deliberations spanned epidemiology, clinical presentation, diagnosis including autoantibodies, immunoglobulin G (IgG), histology and diagnostic scores, therapeutic strategies, management of difficult-to-treat AIH, long-term monitoring, and special scenarios, such as seronegative AIH (SN-AIH), autoimmune sclerosing cholangitis/overlap syndromes and post-transplant complications like recurrence and de novo-AIH. Recommendations were formulated using standard GRADE system and finalized through structured consensus. These guidelines aim to standardize care, assist clinicians in decision-making, and improve outcomes in children with AIH across diverse healthcare settings.

Abstract Background Tumor necrosis factor (TNF) antagonists are central to the management of inflammatory bowel disease (IBD), but concerns regarding long-term safety, infection risk, and costs have prompted interest in treatment de-escalation. Whether discontinuing TNF therapy in patients with sustained remission is safe remains uncertain. Methods We performed a systematic review and meta-analysis of randomized controlled trials (RCTs) comparing TNF antagonist withdrawal with continuation in IBD patients in sustained remission. Databases including MEDLINE, Embase, CENTRAL, and ClinicalTrials.gov were searched through July 2025. Eligible trials enrolled adults with Crohn’s disease or ulcerative colitis in clinical remission. Primary outcomes were relapse risk and sustained remission. Data were pooled using a random-effects model. Results Four RCTs comprising 485 patients were included. TNF antagonist withdrawal was associated with a significantly higher risk of relapse compared with continuation (RR: 3.00, 95% CI: 1.47–6.11). Time to relapse was also shorter in the withdrawal group (HR: 5.34, 95% CI: 2.05–13.92). Sustained clinical remission did not differ significantly between groups (RR: 0.83, 95% CI: 0.55–1.27). Withdrawal reduced infection risk (RR: 0.47, 95% CI: 0.25–0.90), while rates of gastrointestinal and serious adverse events were comparable. Conclusions Discontinuation of TNF antagonists in IBD patients in remission substantially increases the risk and accelerates the timing of relapse, though it lowers infection risk. Careful patient selection and close monitoring are essential if withdrawal is considered.