Adult Opisthorchis viverrini Flukes in Humans, Takeo, Cambodia

(1). Sophisticated laboratory methods, although sensitive, are costly. The immunochromatographic strip test that uses recombinant K39 antigen (rK39), although satisfactory in India, is less sensitive in Africa, Latin America, and Mediterranean regions (2). Post–kala-azar dermal leishmaniasis (PKDL), a sequel to VL in India and Africa, is often confused with other skin diseases (3,4). Diagnosis of VL in dogs in Latin America and Mediterranean countries remains confusing because of rampant asymptomatic infections and elevated antibodies against Leishmania spp. (5)

Adaptive Method for Exploring Deep Learning Techniques for Subtyping and Prediction of Liver Disease

The term “Liver disease” refers to a broad category of disorders affecting the liver. There are a variety of common liver ailments, such as hepatitis, cirrhosis, and liver cancer. Accurate and early diagnosis is an emergent demand for the prediction and diagnosis of liver disease. Conventional diagnostic techniques, such as radiological, CT scan, and liver function tests, are often time-consuming and prone to inaccuracies in several cases. An application of machine learning (ML) and deep learning (DL) techniques is an efficient approach to diagnosing diseases in a wide range of medical fields. This type of machine-related learning can handle various tasks, such as image recognition, analysis, and classification, because it helps train large datasets and learns to identify patterns that might not be perceived by humans. This paper is presented here with an evaluation of the performance of various DL models on the estimation and subtyping of liver ailment and prognosis. In this manuscript, we propose a novel approach, termed CNN+LSTM, which is an integration of convolutional neural network (CNN) and long short-term memory (LSTM) networks. The results of the study prove that ML and DL can be used to improve the diagnosis and prognosis of liver disease. The CNN+LSTM model achieves a better accuracy of 98.73% compared to other models such as CNN, Recurrent Neural Network (RNN), and LSTM. The incorporation of the proposed CNN+LSTM model has better results in terms of accuracy (98.73%), precision (99%), recall (98%), F1 score (98%), and AUC (Area Under the Curve)-ROC (Receiver Operating Characteristic) (99%), respectively. The use of the CNN+LSTM model shows robustness in predicting the liver ailment with an accurate diagnosis and prognosis

Enhanced lesional foxp3 expression and peripheral anergic lymphocytes indicate a role for regulatory T cells in Indian post-kala-azar dermal leishmaniasis

Indian post-kala-azar dermal leishmaniasis (PKDL) is a low-frequency (5–10%) dermal sequela of visceral leishmaniasis (VL) caused by Leishmania donovani; importantly, affected individuals are speculated to be parasite reservoirs. Insight into its immunopathogenesis could translate into rational immunomodulatory therapeutic approaches against leishmaniases. In patients with PKDL (n=21), peripheral lymphocytes were analyzed for surface markers, intracellular cytokines, and lymphoproliferative responses using flow cytometry. In lesional tissue biopsies (n=12), expression of counter-regulatory cytokines (IFN-γ and IL-10) and the T-regulatory transcription factor forkhead box protein 3 (Foxp3) was analyzed using reverse transcriptase-PCR, along with immunohistochemical detection (n=8) of CD3 and Foxp3 positivity. In patients with PKDL, circulating CD8+CD28- and antigen-induced IL-10+CD3+ lymphocytes were increased and receded with treatment. CD8+ lymphocytes showed impaired proliferative responses to L. donovani antigen (LDA) and phytohemagglutinin, which were reinstated after treatment. At presentation, the upregulated lesional IFN-γ and IL-10 messenger RNA (mRNA), Foxp3 mRNA, and protein were curtailed after treatment. In Indian patients with PKDL, increased frequency of the CD8+CD28- phenotype, enhanced antigen-specific IL-10 production, and accompanying anergy of circulating lymphocytes suggest their regulatory nature. Furthermore, the concomitantly elevated lesional expression of Foxp3 suggests their possible recruitment into the lesional site, which would sustain disease pathology

Genomic Characterization of Nipah Virus, West Bengal, India

An intrafamilial outbreak in West Bengal, India, involving 5 deaths and person-to-person transmission was attributed to Nipah virus. Full-genome sequence of Nipah virus (18,252 nt) amplified from lung tissue showed 99.2% nt and 99.8% aa identity with the Bangladesh-2004 isolate, suggesting a common source of the virus