METHODS: Antibiotics susceptibility testing, detection of OXAs genes and the biofilm-producing capacity were performed using the Kirby Bauer method, polymerase chain reaction (PCR) and adherence quantitative assays, respectively.
RESULTS: A total of 80 A. baumannii isolates were mainly obtained from sputum and most of them were resistant to antibiotics. All A. baumannii carried blaOXA-51 gene, yet no blaOXA-24 and blaOXA-58 genes were detected. Fourteen (82.4%) of the 17 meropenem resistant isolates carried blaOXA-23 gene, but it was not found in meropenem sensitive isolates. In addition, sixty (75.0%) of 80 isolates were biofilm producers with 2 (2.5%), 16 (20.0%), and 42 (52.5%) isolates were identified as strong, moderate and weak biofilm producers, respectively.
CONCLUSION: Most of A. baumannii isolates had a high level of antibiotic resistance and had a capacity to produce biofilm.
PURPOSE: The present study investigated the effects of oral treatment with M. pumilum var. alata (MPA) extracts on the estrogen receptor, metabolic characteristics and insulin signaling pathway in pancreas and liver of ovariectomised nicotidamide streptozotocin-induced diabetes in female rats.
MATERIALS AND METHODS: Ovariectomised diabetic (OVXS) Sprague-Dawley rats were orally administered with either aqueous leaf extract and ethanol (50%) stem-root extract of MPA (50 or 100 mg/kg) respectively for 28 days. Metabolic parameters were evaluated by measuring fasting blood glucose, serum insulin, oral glucose and insulin tolerance test. Distribution and expression level of insulin, oxidative stress and inflammatory marker in the pancreatic islets and liver were evaluated by immunohistochemistry and western blot, respectively.
RESULTS: Oral treatment with aqueous leaf and ethanol (50%) stem-root extracts of MPA (100 mg/kg) significantly reversed the elevated fasting blood glucose, impaired glucose and insulin tolerance. The protein expression of insulin, glucose transporter (GLUT-2 and GLUT-4) increased in the pancreatic islets and liver. Furthermore, marked improvement in the tissue morphology following treatment with MPA was observed. Similarly, the western blots analysis denotes improved insulin signaling in the liver and decreased reactive oxygen species producing enzymes, inflammatory and pro-apoptotic molecules with MPA treatment.
CONCLUSIONS: Taken together, this work demonstrate that 100 mg/kg of aqueous leaf extract and ethanol (50%) stem-root extract of MPA improves β-cell function and insulin signaling in postmenopausal diabetes through attenuation of oxidative stress and partially mediated by oestrogen receptor stimulation.
METHODS: Patients initiating cART between 2006 and 2013 were included. TI was defined as stopping cART for >1 day. Treatment failure was defined as confirmed virological, immunological or clinical failure. Time to treatment failure during cART was analysed using Cox regression, not including periods off treatment. Covariables with P < 0.10 in univariable analyses were included in multivariable analyses, where P < 0.05 was considered statistically significant.
RESULTS: Of 4549 patients from 13 countries in Asia, 3176 (69.8%) were male and the median age was 34 years. A total of 111 (2.4%) had TIs due to AEs and 135 (3.0%) had TIs for other reasons. Median interruption times were 22 days for AE and 148 days for non-AE TIs. In multivariable analyses, interruptions >30 days were associated with failure (31-180 days HR = 2.66, 95%CI (1.70-4.16); 181-365 days HR = 6.22, 95%CI (3.26-11.86); and >365 days HR = 9.10, 95% CI (4.27-19.38), all P < 0.001, compared to 0-14 days). Reasons for previous TI were not statistically significant (P = 0.158).
CONCLUSIONS: Duration of interruptions of more than 30 days was the key factor associated with large increases in subsequent risk of treatment failure. If TI is unavoidable, its duration should be minimised to reduce the risk of failure after treatment resumption.
STUDY DESIGN: This was an open-label, randomized clinical trial conducted at 14 public hospitals across Malaysia from February to June 2021 among 500 symptomatic, RT-PCR confirmed COVID-19 patients, aged ≥50 years with ≥1 co-morbidity, and hospitalized within first 7 days of illness. Patients were randomized on 1:1 ratio to favipiravir plus standard care or standard care alone. Favipiravir was administered at 1800mg twice-daily on day 1 followed by 800mg twice-daily until day 5. The primary endpoint was rate of clinical progression from non-hypoxia to hypoxia. Secondary outcomes included rates of mechanical ventilation, intensive care unit (ICU) admission, and in-hospital mortality.
RESULTS: Among 500 patients were randomized (mean age, 62.5 [SD 8.0] years; 258 women [51.6%]; and 251 [50.2%] had COVID-19 pneumonia), 487 (97.4%) patients completed the trial. Clinical progression to hypoxia occurred in 46 (18.4%) patients on favipiravir plus standard care and 37 (14.8%) on standard care alone (OR 1.30; 95%CI, 0.81-2.09; P=.28). All three pre-specified secondary end points were similar between both groups. Mechanical ventilation occurred in 6 (2.4%) vs 5 (2.0%) (OR 1.20; 95%CI, 0.36-4.23; P=.76), ICU admission in 13 (5.2%) vs 12 (4.8%) (OR 1.09; 95%CI, 0.48-2.47; P=.84), and in-hospital mortality in 5 (2.0%) vs 0 (OR 12.54; 95%CI, 0.76- 207.84; P=.08).
CONCLUSIONS: Among COVID-19 patients at high risk of disease progression, early treatment with oral favipiravir did not prevent their disease progression from non-hypoxia to hypoxia.
INTRODUCTION: Artificial intelligence (AI) is a relatively new technology that has widespread use in dentistry. The AI technologies have primarily been used in dentistry to diagnose dental diseases, plan treatment, make clinical decisions, and predict the prognosis. AI models like convolutional neural networks (CNN) and artificial neural networks (ANN) have been used in endodontics to study root canal system anatomy, determine working length measurements, detect periapical lesions and root fractures, predict the success of retreatment procedures, and predict the viability of dental pulp stem cells. Methodology. The literature was searched in electronic databases such as Google Scholar, Medline, PubMed, Embase, Web of Science, and Scopus, published over the last four decades (January 1980 to September 15, 2021) by using keywords such as artificial intelligence, machine learning, deep learning, application, endodontics, and dentistry.
RESULTS: The preliminary search yielded 2560 articles relevant enough to the paper's purpose. A total of 88 articles met the eligibility criteria. The majority of research on AI application in endodontics has concentrated on tracing apical foramen, verifying the working length, projection of periapical pathologies, root morphologies, and retreatment predictions and discovering the vertical root fractures.
CONCLUSION: In endodontics, AI displayed accuracy in terms of diagnostic and prognostic evaluations. The use of AI can help enhance the treatment plan, which in turn can lead to an increase in the success rate of endodontic treatment outcomes. The AI is used extensively in endodontics and could help in clinical applications, such as detecting root fractures, periapical pathologies, determining working length, tracing apical foramen, the morphology of root, and disease prediction.