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Oral extranodal non Hodgkin's lymphoma: series of forty two cases in Malaysia

Ramanathan A, Mahmoud HA, Hui LP, Mei NY, Valliappan V, Zain RB

Asian Pac J Cancer Prev, 2014;15(4):1633-7.
PMID: 24641380

BACKGROUND: Lymphoma is a malignant neoplasm of lymphoid tissue classified into Hodgkin's and non-Hodgkin's types. It mostly affects lymph nodes although a considerable proportion of Non-Hodgkin's cases occur in extranodal sites.
MATERIALS AND METHODS: Selected cases diagnosed as non-Hodgkin's lymphoma (NHL) during the period of 1980 to 2012 were retrieved from the archives of the Oral Pathology Diagnostic Laboratory, Faculty of Dentistry, University of Malaya. The sections from the formalin-fixed paraffin embedded tissue blocks were stained with H and E as well as with LCA, CD20, and CD3.
RESULTS: The mean age was 41.6 years with a male: female ratio of 1.3:1. Out of the forty two cases, nineteen were Malays, eighteen were Chinese, followed by Indians (3) and Indonesians (2). The most common site of involvement was the mandible (22.2%), followed by the maxilla and palate (19.4% each). Most of the lesions presented as a painless progressive swelling. Only thirty six cases were further subdivided into B or T cell types. The majority were B-cell type (26 cases), of these 6 cases were Burkitt's lymphomas. Only ten cases were T-cell lymphoma, with three cases of NK/T-cell lymphoma.
CONCLUSIONS: In this series of 42 patients diagnosed as extranodal non-Hodgkin's lymphoma, the lesions appeared as painless swellings, mostly in men with the mandible as the most frequent site of involvement. Majority were B-cell lymphomas with Malays and Chinese being equally affected whereas lymphomas were rare in the Indian ethnicity. T-cell lymphomas were found to be common in the Chinese ethnic group.
Fulltext Revolutionizing proton exchange membrane fuel cell modeling through hybrid aquila optimizer and arithmetic algorithm optimization

Singla MK, Muhammed Ali SA, Kumar R, Jangir P, Khishe M, Gulothungan G, et al.

Sci Rep, 2025 Feb 11;15(1):5122.
PMID: 39934364 DOI: 10.1038/s41598-025-89631-8

Parameter identification in a Proton Exchange Membrane Fuel Cell (PEMFC) entails the application of optimization algorithms to ascertain the optimal unknown variables essential for crafting an accurate model that predicts fuel-cell performance. These parameters are typically not included in the manufacturer's datasheet and must be identified to ensure precise modeling and forecasting of fuel cell behavior. This paper introduces a recently developed hybrid algorithm (Aquila Optimizer Arithmetic Algorithm Optimization (AOAAO)) that enhances the AO and AAO algorithm's efficiency through a novel mutation strategy, aimed at determining seven unknown parameters of a PEMFC during the optimization process. These parameters function as decision variables, and the objective function aimed for minimization is the sum square error (SSE) between the predicted and actual measured cell voltages. AOAAO demonstrated superior performance across various metrics, achieving an SSE minimum in comparison to other compared algorithm. AOAAO's robustness was validated through extensive testing with six commercially available PEMFCs, including BCS 500 W-PEM, 500 W SR-12PEM, Nedstack PS6 PEM, H-12 PEM, HORIZON 500 W PEM, and a 250 W-stack, across twelve case studies derived from various operational conditions detailed in manufacturers' datasheets. For each datasheet, both Current-Voltage (I/V) and Power-Voltage (P/V) characteristics of the PEMFCs scenarios closely aligned with those observed in experimental data, affirming AOAAO's superior accuracy, robustness, and time efficiency for real-time fuel cell modeling. In terms of computational efficiency, AOAAO runtime is significantly faster than all compared algorithms, demonstrating an efficiency improvement of approximately 98%.

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