LNCT University

Ocular diseases like diabetic retinopathy, glaucoma, Age-related Macular Degeneration (AMD), cataracts, and hypertensive retinopathy can cause significant threats to vision loss if not detected at an early stage. This paper tackles the very important issue of accurate and timely diagnosis. This paper proposes Fundus-DeepNet, a highly efficient multi-label deep learning model that aims to automate the diagnosis of multiple ocular diseases simultaneously using fundus images. The main goal of this paper is to improve the scalability and accuracy of diagnosis by combining the latest advances in preprocessing methods like contrast enhancement, circular cropping, and noise removal with attention mechanisms like Convolutional Block Attention Module (CBAM) and Squeeze-and-Excitation (SE) blocks, and multi-branch feature fusion. When tested on the Ocular Imaging Alliance-Ocular Disease Intelligent Recognition (OIA-ODIR) dataset, Fundus-DeepNet demonstrated a precision of 88.75%, a recall of 94.37%, an F1-score of 91.37%, and an overall accuracy of 98.67%. The results clearly indicate its potential for practical use in facilitating efficient and high-throughput ophthalmic screening. Comparison with other state-of-the-art models revealed that Fundus-DeepNet performed better than other models on all key performance metrics, thereby validating its robustness and reliability.

Background: The postpartum period is associated with elevated stress levels that may adversely affect maternal well-being and lactation. Yoga, as a mind-body intervention, has shown promise in stress reduction; however, evidence regarding its effect on lactation outcomes remains limited. Aim: This study aimed to evaluate the effectiveness of a structured postpartum yoga intervention on perceived stress and milk volume among postpartum mothers. Methods: A randomized controlled trial with a pre-test and post-test parallel group design was conducted in the postnatal ward and outpatient department of [Hospital/Community Health Center],. Sixty-four postpartum mothers 6–8 weeks after delivery were selected through consecutive sampling and randomized into an experimental group (n=32) and a control group (n=32). The experimental group received standard postpartum care plus structured postpartum yoga for 45–60 minutes per session, five days per week for six weeks. The control group received standard postpartum care alone. Data were collected using a demographic proforma, the Perceived Stress Scale-10, and milk volume measurement by the test-weighing method. Data were analyzed using SPSS version 27.0 with paired and independent t-tests. Significance was set at p < 0.05.[City]Results: Both groups were comparable at baseline. The experimental group showed a significant reduction in perceived stress scores from 24.6 ± 3.8 to 15.2 ± 3.1 (p < 0.001), while the control group showed no significant change. Milk volume increased significantly in the experimental group from 412.5 ± 68.4 mL/day to 587.3 ± 74.2 mL/day (p < 0.001). Between-group comparisons revealed significantly greater improvement in both perceived stress (p < 0.001, d = 1.42) and milk volume (p < 0.001, d = 1.28) in the experimental group. Compliance with the intervention was 92.4%, with no adverse events reported. Conclusion: A six-week structured postpartum yoga intervention is effective in reducing perceived stress and improving milk volume among postpartum mothers. The intervention is safe, feasible, and clinically relevant. Integration of postpartum yoga into routine postnatal care is recommended to enhance maternal psychological well-being and lactation outcomes.

Baliospermum montanum (Family: Euphorbiaceae) is a medicinal plant traditionally used for antiinflammatory, antirheumatic, and hepatoprotective purposes. Despite its therapeutic potential, limited scientific evidence exists on the isolation and structural characterization of its bioactive constituents. This study employed Soxhlet extraction, TLC profiling, silica gel column chromatography, and multi-spectral analysis (UV–Vis, FTIR, ¹H NMR, and MS) to isolate and identify the primary triterpenoid constituent from ethanolic root extract. The extraction yielded 3.618% of crude extract from 300 g of plant material. TLC analysis using Toluene:Ethyl acetate:Methanol (8:1:1) confirmed similarity with standard Betulin (Rf = 0.40). Fraction F obtained from column chromatography showed strong UV absorption at 209 nm. FTIR analysis revealed characteristic –OH, C–H, C=C, and C–O functional groups. ¹H NMR signals supported the triterpenoid framework, while mass spectrometry confirmed the molecular ion peak at m/z 442.2822 corresponding to Betulin (C₃₀H₅₀O₂). Together, the chromatographic and spectroscopic findings verified the successful isolation of Betulin from B. montanum. This analytical framework provides a reproducible method for future phytochemical and pharmacological investigations.

This study describes the biological evaluation of a new series of naphthyloxy piperazine derivatives (6a–j) designed by conjugating naphthalene and piperazine scaffolds on monoamine oxidase (MAO). The compounds with potent antioxidant activity were screened for in vitro MAO inhibition assays employing DNPH spectrophotometry. The results demonstrated that short aliphatic substitutions (ethyl, butyl) on the piperazine ring enhanced both antioxidant potential and MAO inhibitory activity, whereas aromatic substituents reduced efficacy. Compounds 6e emerged as the most potent inhibitors, with IC50 values of 0.23 µM for MAO-A and 0.35 µM for MAO-B, respectively. These findings suggest that structural tethering of naphthalene and piperazine nuclei yields multifunctional molecules with dual antioxidant and MAO inhibitory properties, supporting their potential as lead candidates for antidepressant drug development.