Chitosan Versus Dapagliflozin in a Diabetic Cardiomyopathy Mouse Model.

Diabetes mellitus is a metabolic disorder with global economic implications that can lead to complications such as diabetic cardiomyopathy. The aim of this study was to compare the effects of chitosan versus dapagliflozin in mouse diabetic cardiomyopathy. We used 32 C57Bl/6 male mice aged between 8 and 10 weeks, which were randomly divided into Control-without diabetes mellitus (DM), type 1 DM (T1DM), T1DM + Chitosan, and T1DM + Dapapgliflozin groups. We induced diabetes with streptozotocin and treated the animals for 12 weeks. The analysis showed a reduction in intramyocardial fibrosis in the T1DM + Dapapgliflozin compared to T1DM animals. In T1DM + CHIT, a reduction in intramyocardial fibrosis was observed although, accordingly, there was also no significant decrease in blood glucose. The level of oxidative stress was reduced in the groups of treated animals compared to T1DM. All these observed changes in the structure and function of hearts were highlighted in the echocardiographic examination. In the treated groups, there was delayed appearance of left ventricular (LV) hypertrophy, a slight decrease in the ejection fraction of the LV, and an improved diastolic profile. The results demonstrate that chitosan has promising effects on diabetic cardiomyopathy that are comparable to the beneficial effects of dapagliflozin.

COVID-19 and Artificial Intelligence: An Approach to Forecast the Severity of Diagnosis.

(1) Background: The new SARS-COV-2 pandemic overwhelmed intensive care units, clinicians, and radiologists, so the development of methods to forecast the diagnosis' severity became a necessity and a helpful tool. (2) Methods: In this paper, we proposed an artificial intelligence-based multimodal approach to forecast the future diagnosis' severity of patients with laboratory-confirmed cases of SARS-CoV-2 infection. At hospital admission, we collected 46 clinical and biological variables with chest X-ray scans from 475 COVID-19 positively tested patients. An ensemble of machine learning algorithms (AI-Score) was developed to predict the future severity score as mild, moderate, and severe for COVID-19-infected patients. Additionally, a deep learning module (CXR-Score) was developed to automatically classify the chest X-ray images and integrate them into AI-Score. (3) Results: The AI-Score predicted the COVID-19 diagnosis' severity on the testing/control dataset (95 patients) with an average accuracy of 98.59%, average specificity of 98.97%, and average sensitivity of 97.93%. The CXR-Score module graded the severity of chest X-ray images with an average accuracy of 99.08% on the testing/control dataset (95 chest X-ray images). (4) Conclusions: Our study demonstrated that the deep learning methods based on the integration of clinical and biological data with chest X-ray images accurately predicted the COVID-19 severity score of positive-tested patients.

Prevalence and Antimicrobial Resistance of Klebsiella Strains Isolated from a County Hospital in Romania.

The study evaluated the evolution of the incidence of infections with Klebsiella in the County Clinical Emergency Hospital of Craiova (SCJUC), Romania. Also, we monitored antibiotic resistance over more than two years and detected changes in resistance to various antimicrobial agents. Our study included 2062 patients (823 women and 1239 men) hospitalised in SCJUC during the period 1st of September 2017 to 30 June 2019. In 458 patients (22.21%) from the 2062 total patients, the collected samples (1116) were positive and from those, we isolated 251 strains of Klebsiella spp. We conducted a longitudinal analysis of the prevalence of Klebsiella spp. over calendar months, which showed a prevalence in surgical wards that ranged between 5.25% and 19.49% in June 2018, while in medical wards the variation was much wider, between 5.15% and 17.36% in April 2018. Klebsiella spp. strains showed significant resistance to Amoxicillin/Clavulanate, Aztreonam and Cephalosporins such as Ceftriaxone, Ceftazidime and Cefepime. We examined the possible link with the consumption of antibiotics in the same month by performing a multiple linear regression analysis. The evolution of antibiotic resistance in Klebsiella was correlated with the variation of resistance in other bacteria, which suggests common resistance mechanisms in the hospital environment. By performing the regression for dependency between antibiotic resistance and antibiotic consumption, we observed some correlations between antibiotic consumption and the development of antibiotic resistance after 1, 2 and even 3 months (e.g., resistance to meropenem was influenced by the consumption in the hospital ward of imipenem 1 month and two months before, but only 1 month before by the consumption of meropenem). The clustering of strains showed filiation between multiresistant Klebsiella spp. strains isolated from specific patients from the ICU. The evolution of prevalence and antibiotic resistance in Klebsiella correlated with the resistance in other bacteria, which suggest common resistance mechanisms in the hospital environment, and also with the consumption of antibiotics.

The Study of Clinical and Biochemical Parameters in Assessing the Response to the Antiviral Therapy in the Chronic Viral Hepatitis B.

Background and Objectives: Hepatitis B virus infection remains a major public health concern. The interaction between hepatitis B virus (HBV) hepatitis B virus and the host inflammatory response is an important contributing factor driving liver damage and diseases outcomes. The management of chronic hepatitis B virus infection is an area of massive unmet clinical need worldwide. Our primary aim for this study was to evaluate biological response rates and sustained virological response in patients with chronic hepatitis B treated with Peg-IFN α-2a/b. The second aim of the study was the identification of metabolic changes and insulin resistance. Materials and Methods: We enrolled in this study 166 patients who fulfilled all inclusion and exclusion criteria. These treatment-naive patients with chronic HBV were treated with Pegylated Interferon α-2a/b. HBV infection was defined by the presence of HBV serological markers (HBsAg, anti-HBsAb, anti-HBcAb, HBeAg, anti HBeAb) by Enzyme-Linked Immuno Sorbent Assay (ELISA) and serum HBV-DNA levels were estimated by a commercially available quantitative polymerase chain reaction (PCR) assay. Results: Patients' recovery progress has been evaluated by determining the following: age, gender; biochemical tests; alanine aminotransferase, aspartate aminotransferase; serological assays for HBV serological markers (HBsAg, anti-HBsAc/Ab, anti-HBcAc/Ab, HBeAg, anti HBeAc/Ab); molecular tests to detect viral particles, testing for HBV DNA (PCR) to confirm the diagnosis and quantify the number of viral copies in the blood (viremia); liver ultrasound-performed through epigastric and intercostal approach (transversal and longitudinal sections). Conclusions: Our results indicated that only HOMA index values, that of fasting insulin, together with baseline HBV DNA, alanine aminotransferase values, mean blood glucose at the beginning of treatment may be predictive of the early viral response in chronic hepatitis B.