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Microbial Biotechnology
Published in Nwadiuto (Diuto) Esiobu, James Chukwuma Ogbonna, Charles Oluwaseun Adetunji, Olawole O. Obembe, Ifeoma Maureen Ezeonu, Abdulrazak B. Ibrahim, Benjamin Ewa Ubi, Microbiomes and Emerging Applications, 2022
Olawole O. Obembe, Nwadiuto (Diuto) Esiobu, O. S. Aworunse, Nneka R. Agbakoba
The SLE, also simply called “Lupus,” is a heterogeneous autoimmune disease with a wide range of clinical and serological manifestations. It can affect the brain, joints, skin, blood cells, kidneys, heart, and lungs. The disease may be mild or severe and marked by relapses and remissions. The condition affects more women than men often. The pathogenesis of SLE is poorly understood and may involve hormonal factors, genetic and environmental factors like infection, and drugs (Zhang et al., 2014). Like in other autoimmune diseases, the gut microbiota has been suspected of playing a contributory role as etiologic agents in the pathogenesis of SLE. Reports of many studies show that dysbiosis of the intestinal microbiota is suspected to affect the genesis and development of SLE.
Hematopoietic Stem Cell Transplantation for Systemic Lupus Erythematosus
Published in Richard K. Burt, Alberto M. Marmont, Stem Cell Therapy for Autoimmune Disease, 2019
Ann E. Traynor, Richard K. Burt, Alberto Marmont
A long-term complete remission (CR) should probably be considered as an equivalent of “cure”. It is a well established axiom that the absence of minimal residual disease after allogeneic HSCT is the best demonstration of a cure. In analogy to oncohematology, CR in lupus has been defined as a long-term and treatment-free complete remission with restoration of normal blood counts and a normal immune system.74 The already reported patient who underwent allogeneic HSCT and is (still) in CR 15 years after allo-HSCT, with no treatment and only a residual ANA (1:40) trace, would seem to fit in this definition. Since probably no patient would meet these stringent requirements, in the EBMT/ EULAR study CR, which was utilized for calculating the disease-free survival (DFS), was defined as a SLEDAI index <3. However, for a disease such as SLE, it is more practical for a patient to utilize the concept of sustained remission from clinical disease activity and no residual, irreversible damage, without therapy. There is a growing consensus that a CR should (or might) be defined as no clinical evidence of active disease and on no immune suppressive medications. Small (<10 mg) doses of prednisone are accepted in this context, but it is uncertain whether they are useful because of prolonged hypocorticism (in which case ACTH would be more indicated) or to control minimal residual autoimmune disease.
Microbiological drinking water parameters
Published in Frank R. Spellman, The Drinking Water Handbook, 2017
Watery diarrhea, abdominal cramping, low-grade fever, and decreased appetite are common features of the illness. The illness also is marked by periods of remission and relapse that may continue for up to several weeks. Microscopic examination of stool specimens from 11 infected people showed many spherical bodies 8 to 10 μm in diameter that were identified as a Cyclospora species. The only other outbreaks associated with Cyclospora in the literature have been seasonal outbreaks in Nepal. One outbreak in Nepal was associated with chlorinated drinking water.
Computer-assisted grading of follicular lymphoma: a classification based on SVM, machine learning, and transfer learning approaches
Published in The Imaging Science Journal, 2022
Classification accuracies of other pre-trained deep learning approaches like classical ResNet-50 modified ResNet-50 are tested on raw images of FL tissue samples. This Classic ResNet-50 architecture will be able to achieve 90.32% of accuracy. In another experiment, classic ResNet-50 architecture is modified by adding extra layers in classic ResNet-50 architecture. A pair of batch norm layers are added to reduce training time. A couple of dropout layers are added to prevent overfitting while training, and a pair of SoftMax layers to generalize outcomes into three histological grades. This new design significantly reduces the training time by 40 min, and classification accuracy increases from 90.32–93.48. This modified ResNet-50 architecture is so far showing the most promising results in comparison to all the previous research [15,32,33,41,42] and all models we have deployed (Classic ResNet-50, Multi-class SVM, AlexNet, and VGG-16). Then we moved to transfer learning approaches. AlexNet and VGG-16 pre-trained networks are implemented. After 100 epochs, accuracies for AlexNet and VGG-16 are 90.78% and 91.38%, respectively, for classifying the images into respective classes. AlexNet & VGG-16 reduces the computation time compared to the modified ResNet-50 architecture, but modified ResNet-50 is much better in terms of accuracy. Experimental results provide the promising performance of computer-assisted grading for H&E-Stained FL histology, which can supplement decision-making policies to improve current agreement among different readers. Eventually, increase patients’ chance of remission and prolongs their lives. The current research results are based on the premises of WHO 2008 classification of Follicular Lymphoma (FL). In our future work, WHO 2016 FL i.e. progression from In SITU follicular neoplasia to follicular lymphoma will be considered.
New method for prediction of future order statistics
Published in Quality Technology & Quantitative Management, 2021
Haroon M. Barakat, Osama M. Khaled, Hadeer A. Ghonem
Remission means that the signs and symptoms of cancer are reduced. Cancer remission does not mean the cancer is cured, but it is an important milestone. In some cases, cancer may never come back. In others, it may recur. In any clinical trial, and in general, for the cancer patients, the prediction of the duration of remission achieved by any remedy is an extremely important issue in facing this disease, it marks a major turn in patient care and long-term health. The result of Example 1 (Table 10) shows that the application of CP2 provides an accurate way to predict the duration of remission of cancer. Example 2. The data set given inTable 11, which we analyze in this example, was handled by Lawless (1982) and analyzed also by Valiollahi et al. (2017). This data was taken from accelerator life test of 59 conductors. Valiollahi et al. (2017) used this data to compare the four methods: MLP, BUP, CMP, and BP. We use the data set to compare the preceding methods with the new method CP2. This data set is represented inTable 11as 59 observed order statistics. The generalized exponential distributionis appropriate model for this data with parameters (andand the K – S, with p-value = 0.532. We assume that we have observed the first 20 observations and we want to predict the next observations for different values ofsay (1,3,5,8). Becauseis random in (2), we repeat the process 10,000 times and compute the average to obtain suggested point D-prediction (see Remarks 2 and 4).Remark 4. The only reason that calls us for repeating the simulation process a large number, namely 10,000 times, and compute the average to obtain suggested point prediction is to diminish the resulted error from the simulation process. However (as we have checked) if we repeated the simulation process 1000 and 500 times rather than 10,000 times, the values of the resulted point predictions would be randomly changed by a very bit amount.We compare our result concerning the CP2 method with the result of Valiollahi et al. (2017) concerning the method MLP, BUP, CMP, and BP. This comparison is presented inTable 12. InTable 12, the MSE pertaining to each of the methods MLP, BUP, CMP, BP, and CP2 is computed over the 4 predictions. The result presented inTable 12asserts that the CP2 method is better than all other methods.