Automated Quantification of Inflamed Lung Regions in Chest CT by UNet++ and SegCaps: A Comparative Analysis in COVID-19 Cases.

During the current COVID-19 pandemic, a high volume of lung imaging has been generated in the aid of the treating clinician. Importantly, lung inflammation severity, associated with the disease outcome, needs to be precisely quantified. Producing consistent and accurate reporting in high-demand scenarios can be a challenge that can compromise patient care with significant inter- or intra-observer variability in quantifying lung inflammation in a chest CT scan. In this backdrop, automated segmentation has recently been attempted using UNet++, a convolutional neural network (CNN), and results comparable to manual methods have been reported. In this paper, we hypothesize that the desired task can be performed with comparable efficiency using capsule networks with fewer parameters that make use of an advanced vector representation of information and dynamic routing. In this paper, we validate this hypothesis using SegCaps, a capsule network, by direct comparison, individual comparison with CT severity score, and comparing the relative effect on a ML(machine learning)-based prognosis model developed elsewhere. We further provide a scenario, where a combination of UNet++ and SegCaps achieves improved performance compared to individual models.

Antibacterial activity of medicinal plants against ESKAPE: An update.

Antibiotic resistance has emerged as a threat to global health, food security, and development today. Antibiotic resistance can occur naturally but mainly due to misuse or overuse of antibiotics, which results in recalcitrant infections and Antimicrobial Resistance (AMR) among bacterial pathogens. These mainly include the MDR strains (multi-drug resistant) of ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species). These bacterial pathogens have the potential to "escape" antibiotics and other traditional therapies. These bacterial pathogens are responsible for the major cases of Hospital-Acquired Infections (HAI) globally. ESKAPE Pathogens have been placed in the list of 12 bacteria by World Health Organisation (WHO), against which development of new antibiotics is vital. It not only results in prolonged hospital stays but also higher medical costs and higher mortality. Therefore, new antimicrobials need to be developed to battle the rapidly evolving pathogens. Plants are known to synthesize an array of secondary metabolites referred as phytochemicals that have disease prevention properties. Potential efficacy and minimum to no side effects are the key advantages of plant-derived products, making them suitable choices for medical treatments. Hence, this review attempts to highlight and discuss the application of plant-derived compounds and extracts against ESKAPE Pathogens.

Surface-plasmon-resonance-based fiber-optic refractive index sensor: sensitivity enhancement.

We have experimentally studied the surface plasmon resonance (SPR)-based fiber-optic refractive index sensor incorporating a high-index dielectric layer using the wavelength interrogation method. Silver and gold have been used as SPR active metals followed by a high-index dielectric layer of silicon. Experimental results predict a redshift in the resonance wavelength with the increase in the refractive index of the sensing layer for a given thickness of the silicon layer. Further, as the thickness of the silicon layer increases, the sensitivity of the sensor increases. The upper limit of the silicon film thickness for the enhancement of the sensitivity has been found to be around 10 nm. The experimental results obtained on sensitivity match qualitatively with the theoretical results obtained using the N-layer model and the ray approach. The increase in sensitivity is due to the increase in the electric field intensity at the silicon-sensing-region interface. In addition to an increase in sensitivity, the silicon layer can be used to tune the resonance wavelength and can protect the metal layer from oxidation and hence can improve the durability of the probe.

Apnoeic-hypopnoeic episodes during obstructive sleep apnoea are associated with histological nonalcoholic steatohepatitis.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) and obstructive sleep apnoea are associated with metabolic syndrome and atherosclerotic heart disease. This study evaluates the potential association between the NAFLD subtypes and a number of polysomnographical (PSG) parameters. METHODS: This study included patients undergoing bariatric surgery with extensive clinical and histological data for whom complete PSG data before surgery were also available. Excess alcohol intake and other causes of liver disease were excluded. Apnoea, hypopnoea and apnoea-hypopnoea index (AHI) were calculated as described previously. RESULTS: In this study, a total of 101 patients [77 nonalcoholic steatohepatitis (NASH) and 22 non-NASH controls] with PSG data were included (age 42.9 +/- 11.4 years, body mass index 51.6 +/- 9.5 kg/m(2), fasting serum glucose 117.4 +/- 53.4 mg/dl, fasting serum triglycerides 171.3 +/- 82.9 mg/dl, 58% hypertension and 33% diabetes mellitus). Subjects with histological NASH had significantly lower lowest desaturation (77 vs. 85%, P=0.006), lower mean nocturnal oxygen saturation (91 vs. 93%, P=0.05), higher AHI (35 vs. 22, P=0.03), higher respiratory disturbance index (46 vs. 21, P=0.02) and higher alanine aminotransferase/aspartate aminotransferase ratio (1.4 vs. 1.3, P=0.05) compared with non-NASH controls. In multivariate analysis, the lowest desaturation (P=0.04) was independently associated with histological NASH. Lowest desaturation and mean nocturnal oxygen saturation were significantly lower in subjects with fibrosis (76 vs. 85%, P=0.004 and 90.4 vs. 93.0%, P=0.02). CONCLUSIONS: Our results suggest that the frequent nocturnal hypoxic episodes in NAFLD patients may be a risk factor for developing NASH. Additional studies are needed to study the effect of optimizing sleep apnoea management on the outcomes of patients with NAFLD.