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BackgroundThe problem of medicine expiration presents a notable obstacle, resulting in considerable financial losses. Nevertheless, there is currently limited data indicating that certain medications do not experience a significant decrease in effectiveness after their expiration date. Therefore, the aim of the study was to assess the physico-chemical quality of expired fluoroquinolone antibiotics.MethodsThe expired samples of fluoroquinolone antibiotics were purposively collected from public hospitals in the Jimma zone of the Oromia regional state, Ethiopia. A World Health Organization quality evaluation sampling strategy was employed. Then, simple random sampling techniques were utilized for the selection of tablets for the laboratory quality control test. The assay, identification, and dissolution were performed in accordance with the United States Pharmacopeia (USP) guidelines, as well as failure mode and effect analysis (FMEA) techniques.ResultsThe finding revealed that about 100% (7/7) expired samples passed pharmacopeia quality specifications for identity and assay tests. However, of the seven expired brands, about 14.3% (1/7) of the sample (Code-002) was unable to release its API content within the USP criteria of 30 min. The risk-based quality evaluation revealed that assay was the most critical quality attributed to ciprofloxacin tablets (RPN = 189), followed by identity (RPN = 100). Assay was also the most critical quality attribute (RPN = 378), followed by identity (RPN = 100) for Norfloxacin tablets. The risk-based desirability function approach showed that 75% (3/4) of ciprofloxacin products were of good quality, and 25% (1) were found to be of acceptable quality, while the desirability function of norfloxacin tablets was found to be excellent 1 (33.3%), good 1 (33.3%), and acceptable 1 (33.3%).ConclusionThe study revealed that medications can maintain their quality beyond their labeled expiration date. By combining pharmacopeial standards with risk-based approaches like failure mode and effect analysis (FMEA), the study provides a comprehensive evaluation framework. This approach not only confirms the continued effectiveness of expired fluoroquinolone antibiotics but also underscores the potential waste reduction and cost-saving benefits. This could significantly contribute to addressing healthcare challenges in low-resource settings, promoting more efficient pharmaceutical resource utilization.

Ecological services in metropolitan areas are degrading more quickly due to changes in LULC brought about by urban expansion. To make a sustainable choice about the ideal location, however, merging the existing simulation approach with LULC optimization approaches involves several intricate procedures. Therefore, the goal of this study is to develop a unique technique that can forecast urban expansion over an extended period and to link with optimization of LULC techniques so as to make meaningful decisions on the impacts of urbanization on loss of biodiversity. In this study, three primary procedures were used: (1) an SVM-based supervised classification technique for LULC classification; (2) a Markov chain and cross-tabulation method for the examination of LULC trends in space and time, (3) utilizing the CA-Markov approach to forecast urban growth. By using Landsat imagery of 2008, 2015, and 2023, the study determined how urban cover changed over time, and what kind of LULC-to-urban transition occurred. The study revealed that uncontrolled and haphazard urban expansion was observed in the Sululta sub-city, which could have disastrous repercussions on physical, biological and urban ecosystem. The %age of urban area increased from 9.04% in 2008 to 13.07% in 2015. However, because of the internally displaced people from the Ethio-Somali Region, who have been resettled there since 2017, the ratio of urban areas grew from 13.7% in 2015 to 24.65% in 2023. Furthermore, by 2040, the sub-city will have grown by 27.69 %. The kappa coefficient statistics of the three classified images of the years 2008, 2015, and 2023 were 93.3 %, 97.5%, and 97.5 %, respectively. To identify the areas that would be covered by future city growth, it is advised that this innovative technique be integrated with optimizing land use strategies.

The diagnosis of tuberculosis (TB) is extremely important. Sputum smear microscopy is thought to be the best method available in terms of accessibility and ease of use in resource-constrained countries. In this paper, research was conducted to evaluate the effectiveness of tuberculosis diagnosis by examining, among other things, the underlying causes of sputum smear quality for Ethiopian states such as Tigray, Amahira, and Oromia. However, because it is done manually, it has its limitations. This study proposes a model for sputum smear quality inspection using an ensemble feature extraction approach. The dataset used was recorded and labeled by experts in a regional lab in Bahir Dar, near Felege Hiwot Hospital after being collected from Gabi Hospital, Felege Hiwot Hospital, Adit Clinic and Gondar Hospital, as well as Kidanemihret Clinic in Gondar. We used a controlled environment to reduce environmental influences and eliminate variation. All the data was collected using a smartphone (the standard 15) with a jpg file extension and a pixel resolution of 1,728 × 3,840. Prior to feature extraction, bicubic resizing, and ROI extraction using thresholding was performed. In addition, sequential Gaussian and Gabor filters were used for noise reduction, augmentation, and CLAHE was used for enhancement. For feature extraction, GLCM from the gray label and CNN from the color image were both chosen. Ultimately, when CNN, SVM, and KNN classifiers were used to test both CNN and GLCM features, KNN outperformed them all with scores of 87, 93, and 94% for GLCM, CNN, and a hybrid of CNN and GLCM, respectively. CNN with GLCM outperformed other methods by 0.7 and 0.1% for GLCM and CNN feature extractors using the same classifier, respectively. In addition, the KNN classifier with the combination of CNN and GLCM as feature extractors performed better than existing methods by 1.48%.

Background: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease that results in progressive weakness of skeletal muscles including respiratory muscles. Epidemiological and clinical aspects of ALS are derived from a few world regions with very little representation of low- and middle-income countries. We therefore set out to determine the epidemiological and clinical phenotype of individuals with ALS in Ethiopia. Methods: Multicenter retrospective analysis was conducted using clinical records from ALS patients seen in Ethiopia at Tikur Anbessa Specialized Hospital and Yehuleshet specialty clinic between January 2016 and August 2021. The data collected included clinical characteristics, disease-related symptoms, a revised ALS functional rating scale, and medications. Results: Patients in Ethiopia had a younger age of onset with a mean age of disease onset of 51.9 years. 2.9% of patients had juvenile ALS, and the male-to-female ratio was almost 2:1. 4.9% had a positive family history of the disease. 68% of patients had spinal region involvement at onset, while 32% had bulbar region involvement at onset. Riluzole was used by 31% of ALS patients. 20.6% of patients had some respiratory symptoms, but none received a standard respiratory function assessment. 33.3% of patients were wheelchair-bound. Conclusion: In this retrospective study spanning 5 years, we examined the clinical phenotype of ALS in Ethiopian patients. Our findings suggest that most patients had clinically definite ALS with spinal region involvement. Further research, including genetic and epigenetic information, is necessary to understand the early onset of the disease in Ethiopia.