Epidemiological Aspects and Antibiotics Susceptibility Patterns of Streptococcus pyogenes Isolated from Subjects with Tonsillitis, Sudan

Background: Globally, Streptococcus pharyngitis is a major public health challenge. The current study investigates the prevalence of Streptococcal pyogenes among children under 17 years old in ENT Kosti Teaching Hospital and examines the susceptibility of isolated S. pyogenes strains to commonly used antibiotics.Methods: A total of 384 throat swabs were obtained from children under the age of 17 who attended the Kosti Teaching Hospital between 2019 and 2021. Streptococcus pyogenes was isolated by conventional microbiology procedures. Each S. pyogenes strain was subjected to antibiotic susceptibility testing according to the CLSI guidelines.Results: Most participants of this study were females 219 (57%) and aged between 5 and 10 years 259 (67.4%). Out of the 384 participants, 134 (34.9%) and 255 (66.4%) suffered from lymphadenopathy and tonsil hyperplasia, respectively. Interestingly, lymphadenopathy and tonsil hyperplasia were more (P 0.05) in the 5–10 age group than those aged 11–16 years. Moreover, 41.4% of the participants were infected by a GAS sore throat. GAS sore throat is significantly associated with lymphadenopathy (AOR: 2.375, 95% CI: 1.479–3.815, P 0.000) and tonsil hyperplasia (AOR: 3.374, 95% CI: 1.939–5.874, P 0.000). Notably, males (AOR: 0.853, 95% CI: 0.549–1.325, P 0.479) and individuals aged 5–10 years (AOR: 0.867, 95% CI: 0.464–1.618, P 0.654) were less likely to have a GAS sore throat. In our study, all isolated strains were sensitive to penicillin. Clindamycin, azithromycin, and erythromycin resistance were observed in 7 (4.4%), 44 (27.7%), and 47 (29.6%) isolates, respectively.Conclusion: The study displayed the current situation of GAS sore throat in the White Nile state. Penicillin was found to be the effective drug to cure S. tonsillitis but a high rate of resistance to macrolides was noticed which is an alarming sign

A Deep Batch Normalized Convolution Approach for Improving COVID-19 Detection from Chest X-ray Images

Pre-trained machine learning models have recently been widely used to detect COVID-19 automatically from X-ray images. Although these models can selectively retrain their layers for the desired task, the output remains biased due to the massive number of pre-trained weights and parameters. This paper proposes a novel batch normalized convolutional neural network (BNCNN) model to identify COVID-19 cases from chest X-ray images in binary and multi-class frameworks with a dual aim to extract salient features that improve model performance over pre-trained image analysis networks while reducing computational complexity. The BNCNN model has three phases: Data pre-processing to normalize and resize X-ray images, Feature extraction to generate feature maps, and Classification to predict labels based on the feature maps. Feature extraction uses four repetitions of a block comprising a convolution layer to learn suitable kernel weights for the features map, a batch normalization layer to solve the internal covariance shift of feature maps, and a max-pooling layer to find the highest-level patterns by increasing the convolution span. The classifier section uses two repetitions of a block comprising a dense layer to learn complex feature maps, a batch normalization layer to standardize internal feature maps, and a dropout layer to avoid overfitting while aiding the model generalization. Comparative analysis shows that when applied to an open-access dataset, the proposed BNCNN model performs better than four other comparative pre-trained models for three-way and two-way class datasets. Moreover, the BNCNN requires fewer parameters than the pre-trained models, suggesting better deployment suitability on low-resource devices

Epidemiological Aspects and Antibiotics Susceptibility Patterns of Streptococcus pyogenes Isolated from Subjects with Tonsillitis, Sudan

Abstract Background: Globally, Streptococcus pharyngitis is a major public health challenge. The current study investigates the prevalence of Streptococcal pyogenes among children under 17 years old in ENT Kosti Teaching Hospital and examines the susceptibility of isolated S. pyogenes strains to commonly used antibiotics. Methods: A total of 384 throat swabs were obtained from children under the age of 17 who attended the Kosti Teaching Hospital between 2019 and 2021. Streptococcus pyogenes was isolated by conventional microbiology procedures. Each S. pyogenes strain was subjected to antibiotic susceptibility testing according to the CLSI guidelines. Results: Most participants of this study were females 219 (57%) and aged between 5 and 10 years 259 (67.4%). Out of the 384 participants, 134 (34.9%) and 255 (66.4%) suffered from lymphadenopathy and tonsil hyperplasia, respectively. Interestingly, lymphadenopathy and tonsil hyperplasia were more (P ˂ 0.05) in the 5–10 age group than those aged 11–16 years. Moreover, 41.4% of the participants were infected by a GAS sore throat. GAS sore throat is significantly associated with lymphadenopathy (AOR: 2.375, 95% CI: 1.479–3.815, P ˂ 0.000) and tonsil hyperplasia (AOR: 3.374, 95% CI: 1.939–5.874, P ˂ 0.000). Notably, males (AOR: 0.853, 95% CI: 0.549–1.325, P 0.479) and individuals aged 5–10 years (AOR: 0.867, 95% CI: 0.464–1.618, P 0.654) were less likely to have a GAS sore throat. In our study, all isolated strains were sensitive to penicillin. Clindamycin, azithromycin, and erythromycin resistance were observed in 7 (4.4%), 44 (27.7%), and 47 (29.6%) isolates, respectively. Conclusion: The study displayed the current situation of GAS sore throat in the White Nile state. Penicillin was found to be the effective drug to cure S. tonsillitis but a high rate of resistance to macrolides was noticed which is an alarming sign

Adsorptive Removal of Boron by DIAION™ CRB05: Characterization, Kinetics, Isotherm, and Optimization by Response Surface Methodology

A significant issue for the ecosystem is the presence of boron in water resources, particularly in produced water. Batch and dynamic experiments were used in this research to extract boron in the form of boric acid from aqueous solutions using boron selective resins, DIAION CRB05. DIAION™ CRB05 is an adsorbent that is effective in extracting boron from aqueous solutions due to its high binding capacity and selectivity for boron ions, and it is also regenerable, making it cost-effective and sustainable. Field Emission Scanning Electron Microscopy (FESEM), X-ray diffraction (XRD), and FTIR analysis for DIAION CRB05 characterization. To increase the adsorption capacity and find the ideal values for predictor variables such as pH, adsorbent dose, time, and boric acid concentration, the Box–Behnken response surface method (RSM) was applied. The dosage was reported to be 2000 mg/L at pH 2 and boron initial concentration of 1115 mg/L with 255 min for the highest removal anticipated from RSM. According to the outcomes of this research, the DIAION CRB05 material enhanced boron removal capability and has superior performance to several currently available adsorbents, which makes it suitable for use as an adsorbent for removing boric acid from aqueous solutions. The outcomes of isotherm and kinetic experiments were fitted using linear methods. The Temkin isotherm and the pseudo-first-order model were found to have good fits after comparison with R2 of 0.998, and 0.997, respectively. The results of the study demonstrate the effectiveness of DIAION™ CRB05 in removing boron from aqueous solutions and provide insight into the optimal conditions for the adsorption process. Thus, the DIAION CRB05 resin was chosen as the ideal choice for recovering boron from an aqueous solution because of its higher sorption capacity and percentage of boron absorbed