Anti-fibrotic agents could be the game-changer for post-COVID-19 pulmonary fibrosis treatment

More than 220 countries and territories are globally affected by the recent pandemic COVID-19 which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). There is possibility of third wave of this pandemic as per epidemiological and public health experts. Besides that post-COVID-19 complications are alarming matter to look upon. Post-COVID-19 complications include several symptoms like as persistent fever; cough; fatigue; headache; attention disorder; dyspnea; anosmia; ageusia; chest pain discomfort; various respiratory illness; acute respiratory distress syndrome (ARDS) etc., and here the things to worry about is the development of pulmonary fibrosis after COVID-19. In some COVID-19 patients, hyper-inflammation in the form of ‘cytokine storm’ along with dysregulated immune response, alveolar epithelial tissue injury and wound repair collectively cause this secondary pulmonary fibrosis. Therefore, using anti-fibrotic agents e.g. pirfenidone, nintedanib and other natural compounds could be meaningful in these circumstances although their efficacy in treating COVID-19 is subject to more detailed laboratory research works. In this review article, we have discussed the progression of pulmonary fibrosis development which is triggered by COVID-19; probable solutions with anti-fibrotic agents including anti-fibrotic drugs, some well-known natural compounds, combined anti-fibrotic therapies; and the current challenges of this field. DOI: http://dx.doi.org/10.5281/zenodo.581312

Carboxylated acyclonucleosides: synthesis and RNase A inhibition

Strategically designed carboxylated acyclonucleosides have been probed as a new class of RNase A inhibitors. Several experimental and theoretical studies have been performed to compile relevant qualitative and quantitative information regarding the nature and extent of inhibition. The inhibition constant (Ki) values were determined using a UV-based kinetics experiment. The changes in the secondary structure of the enzyme upon binding with the inhibitors were obtained from circular dichroism studies. The binding constants for enzyme-inhibitor interactions were determined with the help of fluorescence spectroscopy. Docking studies were performed to reveal the possible binding sites of the inhibitors within the enzyme. The cytosine analogues were found to possess better inhibitory properties in comparison to the corresponding uracil derivatives. An increment in the number of carboxylic acid groups (-COOH) in the inhibitor backbone was found to result in better inhibition

Sensitivity to CP Discovery in the Presence of Lorentz Invariance Violating Potential at T2HK/T2HKK

Investigation of conservation/violation of CP symmetry in the leptonic sector is very essential in understanding the evolution of the universe. Lorentz invariance and CPT are fundamental symmetries of nature. The violation of Lorentz invariance can also lead to CPT violations. The standard three flavour neutrino oscillation framework presents a scenario to observe the signature of Lorentz invariance and CP violations. This work focuses on the effect of Lorentz invariance violating (LIV) parameters on the sensitivity to CP violation. We investigate the sensitivity in two proposed configurations of the upcoming T2HK experiment: (i) one detector each placed at 295 km and 1100 km, and (ii) two identical detectors at 295 km. This study probes the effect of CPT violating parameters $a_{e\mu},a_{e\tau},a_{\mu\tau}$.Comment: 10 pages, 11 figure

Correlated disorder in entropic crystals

We report computational evidence of a new type of disordered phase in crystals resulting from entropy driven self-assembly of hard convex polyhedra. The disorder was reflected in the orientations of the anisotropic particles and not in the positions of the centers of geometry. Despite the lack of order, particle orientations were not random and exhibited strong correlations. The correlations were manifested in terms of ``quantized'' rotational motions in a fixed number of absolute orientations, while maintaining equal populations and specific measure of pairwise angular differences among the discrete values. This gave rise to a discretely mobile phase in the low density solid and a quenched disordered state at high pressure. This finding can be interpreted as the simplest example of correlated disorder in crystalline materials.Comment: 15 pages, 4 figures in the main text, 11 figures in the supporting informatio

Detecting and Mitigating System-Level Anomalies of Vision-Based Controllers

Autonomous systems, such as self-driving cars and drones, have made significant strides in recent years by leveraging visual inputs and machine learning for decision-making and control. Despite their impressive performance, these vision-based controllers can make erroneous predictions when faced with novel or out-of-distribution inputs. Such errors can cascade to catastrophic system failures and compromise system safety. In this work, we introduce a run-time anomaly monitor to detect and mitigate such closed-loop, system-level failures. Specifically, we leverage a reachability-based framework to stress-test the vision-based controller offline and mine its system-level failures. This data is then used to train a classifier that is leveraged online to flag inputs that might cause system breakdowns. The anomaly detector highlights issues that transcend individual modules and pertain to the safety of the overall system. We also design a fallback controller that robustly handles these detected anomalies to preserve system safety. We validate the proposed approach on an autonomous aircraft taxiing system that uses a vision-based controller for taxiing. Our results show the efficacy of the proposed approach in identifying and handling system-level anomalies, outperforming methods such as prediction error-based detection, and ensembling, thereby enhancing the overall safety and robustness of autonomous systems