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Abstract Background Myasthenia gravis (MG) is an auto-immune disease, and the mainstay of therapy is immunomodulation. Such patients are at high risk of acquiring any infections. Hence, we sought to determine the impact of the current global pandemic COVID-19 infection in MG patients. Methods For our study, we used Cerner Real-World DataTM that was provided through Cerner’s HealtheDataLab research tool. We ran a database query from January 2019 to July 2020 in our study and identified myasthenia patients with and without COVID-19 infection. To extract these patients’ data, we used ICD 9-CM, ICD-10, and SNOMED-CT codes. We reported the data using means, range, and prevalence rates, and the p-values were calculated using the two-sample t-test and Pearson’s chi-squared test. Results In the COVID-19 data set, a total of twenty-seven myasthenia patients were identified with a positive COVID-19 infection, and four were diagnosed with an exacerbation. The male to female ratio was equal and one unknown gender (3.7%) with a mean (± SD) age of 64.33 ± 18.42 years. This study group was compared with a non-COVID-19 data set in which a total of sixty-four myasthenia patients were identified, and twenty-three had an exacerbation. Among the 13 hospitalized patients in the two groups, the mean length of hospitalization for the myasthenia patients in the COVID-19 data set was 8.28 days (n = 7), and the non-COVID-19 set was 4.33 days (n = 6), and it was statistically significant (p-value= 0.007). Conclusions The mean length of hospital stay is prolonged in myasthenia patients who tested positive for COVID-19.

Smokeless tobacco (SLT) products like gutka and paan masala are a growing public health crisis in India. Despite enacting a ban-the highest form of regulation-little is known about implementation progress. The purpose of this study was to look at how enforcement of gutka ban is covered in Indian news media and if media is a reliable source of data. We conducted a content analysis of online news reports (n = 192) from 2011 to 2019. News characteristics such as name and type of publication, language, location, slant and beat coverage, visuals, and administrative focus were quantified. Similarly, news contents were inductively coded to examine dominant themes and the implementation landscape. We found that coverage was initially low but increased after 2016. Overall, news reports were in favor of the ban. Five leading English newspapers covered the majority of the ban enforcement reports. Prominent themes like consumption, health hazards, tobacco control responses, impact on livelihoods, and illicit trade were drawn from the textual analysis as the main arguments in relation to the ban. Gutka is largely seen as an issue of crime reflected by the contents, sources, and frequent use of pictures depicting law enforcement. The interconnected distribution channels of the gutka industry hindered enforcement, highlighting the need to study the complexities of regional and local SLT supply chains.

Abstract Nasal continuous positive airway pressure (nCPAP) is the standard non-invasive respiratory support for newborns with respiratory distress. Nasal injury is a common problem with the interfaces used. To compare the incidence and severity of nasal injury in neonates with respiratory distress and supported on nCPAP with Hudson prong or RAM cannula with Cannulaide, a semipermeable membrane. This is an open-label, parallel-arm, gestational age-stratified, bi-centric, randomized control trial including neonates between 28 and 34 weeks gestational age and birth weight > 1000 g needing nCPAP. The size of the interface was chosen as per the manufacturer’s recommendation. Of the 229 neonates enrolled, 112 were randomized to RAM cannula with Cannulaide and 117 to Hudson prong. The baseline characteristics were similar. Any nasal injury at CPAP removal was significantly lower in the RAM cannula with Cannulaide group [6 (5.4%) vs. 31 (26.4%); risk ratio—0.77 (95% CI 0.69–0.87); p = 0.0001]. The incidence of moderate to severe nasal injury, need for mechanical ventilation within 72 h of age, duration of oxygen, and requirement of nCPAP for > 3 days were similar. For preterm infants on nCPAP, RAM cannula with Cannulaide, compared to Hudson prongs, decreases nasal injury without increasing the need for mechanical ventilation. Trail registration: CTRI/2019/03/018333, http://www.ctri.nic.in .

The SARS-CoV-2 Delta variant is emerging as a globally dominant strain. Its rapid spread and high infection rate are attributed to a mutation in the spike protein of SARS-CoV-2 allowing for the virus to invade human cells much faster and with an increased efficiency. In particular, an especially dangerous mutation P681R close to the furin cleavage site has been identified as responsible for increasing the infection rate. Together with the earlier reported mutation D614G in the same domain, it offers an excellent instance to investigate the nature of mutations and how they affect the interatomic interactions in the spike protein. Here, using ultra large-scale ab initio computational modeling, we study the P681R and D614G mutations in the SD2-FP domain, including the effect of double mutation, and compare the results with the wild type. We have recently developed a method of calculating the amino-acid–amino-acid bond pairs (AABP) to quantitatively characterize the details of the interatomic interactions, enabling us to explain the nature of mutation at the atomic resolution. Our most significant finding is that the mutations reduce the AABP value, implying a reduced bonding cohesion between interacting residues and increasing the flexibility of these amino acids to cause the damage. The possibility of using this unique mutation quantifiers in a machine learning protocol could lead to the prediction of emerging mutations.

While there exist a plethora of datasets on the Internet related to Food, Energy, and Water (FEW), there is a real lack of reliable methods and tools that can consume these resources. This hinders the development of novel decision-making applications utilizing knowledge graphs. In this paper, we introduce a novel software tool, called FoodKG, that enriches FEW knowledge graphs using advanced machine learning techniques. Our overarching goal is to improve decision-making and knowledge discovery as well as to provide improved search results for data scientists in the FEW domains. Given an input knowledge graph (constructed on raw FEW datasets), FoodKG enriches it with semantically related triples, relations, and images based on the original dataset terms and classes. FoodKG employs an existing graph embedding technique trained on a controlled vocabulary called AGROVOC, which is published by the Food and Agriculture Organization of the United Nations. AGROVOC includes terms and classes in the agriculture and food domains. As a result, FoodKG can enhance knowledge graphs with semantic similarity scores and relations between different classes, classify the existing entities, and allow FEW experts and researchers to use scientific terms for describing FEW concepts. The resulting model obtained after training on AGROVOC was evaluated against the state-of-the-art word embedding and knowledge graph embedding models that were trained on the same dataset. We observed that this model outperformed its competitors based on the Spearman Correlation Coefficient score.

ABSTRACT Invasive fungal infections remain difficult to treat and require novel targeting strategies. The 12-kDa FK506-binding protein (FKBP12) is a ubiquitously expressed peptidyl-prolyl isomerase with considerable homology between fungal pathogens and is thus a prime candidate for future targeting efforts to generate a panfungal strategy. Despite decades of research on FKBPs, their substrates and mechanisms of action remain unclear. Here we describe structural, biochemical, and in vivo analyses of FKBP12s from the pathogenic fungi Candida albicans, Candida glabrata, and Aspergillus fumigatus. Strikingly, multiple apo A. fumigatus and C. albicans FKBP12 crystal structures revealed a symmetric, intermolecular interaction involving the deep insertion of an active-site loop proline into the active-site pocket of an adjacent subunit. Such interactions have not been observed in previous FKBP structures. This finding indicates the possibility that this is a self-substrate interaction unique to the A. fumigatus and C. albicans fungal proteins that contain this central proline. Structures obtained with the proline in the cis and trans states provide more data in support of self-catalysis. Moreover, cysteine cross-linking experiments captured the interacting dimer, supporting the idea that it forms in solution. Finally, genetic studies exploring the impact of mutations altering the central proline and an adjacent residue provide evidence that any dimeric state formed in vivo, where FKBP12 concentrations are low, is transient. Taken together, these findings suggest a unique mechanism of self-substrate regulation by fungal FKBP12s, lending further novel understanding of this protein for future drug-targeting efforts. IMPORTANCE FKBP12 is a cis-trans peptidyl-prolyl isomerase that plays key roles in cellular protein homeostasis. FKBP12s also bind the immunosuppressive drug FK506 to inhibit the phosphatase calcineurin (CaN). CaN is required for virulence of A. fumigatus, C. albicans, C. glabrata, and other deadly fungal pathogens, marking FKBP12 and CaN as potential broad-spectrum drug targets. Here we describe structures of fungal FKBP12s. Multiple apo A. fumigatus and C. albicans FKBP12 structures reveal the insertion of a proline, conspicuously conserved in these proteins, into the active sites of adjacent molecules. This suggests that these proteins might serve as their own substrates. Cysteine disulfide trapping experiments provide support for this self-interaction and hence possible intermolecular catalysis by these enzymes.

Calcineurin is a key protein phosphatase required for hyphal growth and virulence in Aspergillus fumigatus, making it an attractive antifungal target. However, currently available calcineurin inhibitors, FK506 and cyclosporine A, are immunosuppressive, limiting usage in the treatment of patients with invasive aspergillosis. Therefore, the identification of endogenous inhibitors of calcineurin belonging to the calcipressin family is an important parallel strategy. We previously identified the gene cbpA as the A. fumigatus calcipressin member and showed its involvement in hyphal growth and calcium homeostasis. However, the mechanism of its activation/inhibition through phosphorylation and its interaction with calcineurin remains unknown. Here we show that A. fumigatus CbpA is phosphorylated at three distinct domains, including the conserved SP repeat motif (phosphorylated domain-I; PD-I), a filamentous fungal-specific domain (PD-II), and the C-terminal CIC motif (Calcipressin Inhibitor of Calcineurin; PD-III). While mutation of three phosphorylated residues (Ser208, Ser217, Ser223) in the PD-II did not affect CbpA function in vivo, mutation of the two phosphorylated serines (Ser156, Ser160) in the SP repeat motif caused reduced hyphal growth and sensitivity to oxidative stress. Mutational analysis in the key domains in calcineurin A (CnaA) and proteomic interaction studies confirmed the requirement of PxIxIT motif-binding residues (352-NIR-354) and the calcineurin B (CnaB)-binding helix residue (V371) for the binding of CbpA to CnaA. Additionally, while the calmodulin-binding residues (442-RVF-444) did not affect CbpA binding to CnaA, three mutations (T359P, H361L, and L365S) clustered between the CnaA catalytic and the CnaB-binding helix were also required for CbpA binding. This is the first study to analyze the phosphorylation status of calcipressin in filamentous fungi and identify the domains required for binding to calcineurin.

Invasive aspergillosis (IA) is a life-threatening infection due to Aspergillus fumigatus and other Aspergillus spp. Drugs targeting the fungal cell membrane (triazoles, amphotericin B) or cell wall (echinocandins) are currently the sole therapeutic options against IA. Their limited efficacy and the emergence of resistance warrant the identification of new antifungal targets. Histone deacetylases (HDACs) are enzymes responsible of the deacetylation of lysine residues of core histones, thus controlling chromatin remodeling and transcriptional activation. HDACs also control the acetylation and activation status of multiple non-histone proteins, including the heat shock protein 90 (Hsp90), an essential molecular chaperone for fungal virulence and antifungal resistance. This review provides an overview of the different HDACs in Aspergillus spp. as well as their respective contribution to total HDAC activity, fungal growth, stress responses, and virulence. The potential of HDAC inhibitors, currently under development for cancer therapy, as novel alternative antifungal agents against IA is discussed.

Abstract A young woman with terminal respiratory failure due to idiopathic pulmonary hypertension underwent bilateral lung transplantation. The postoperative course was complicated by herniation of the heart through over the cut pericardial edge on left side leading to left-sided graft infarction requiring pneumonectomy. Unable to wean off mechanical ventilation, patient required lobar transplantation on the left side.

One of the crucial problems for taxi drivers is to efficiently locate passengers in order to increase profits. The rapid advancement and ubiquitous penetration of Internet of Things (IoT) technology into transportation industries enables us to provide taxi drivers with locations that have more potential passengers (more profitable areas) by analyzing and querying taxi trip data. In this paper, we propose a query processing system, called Distributed Profitable-Area Query (DISPAQ) which efficiently identifies profitable areas by exploiting the Apache Software Foundation’s Spark framework and a MongoDB database. DISPAQ first maintains a profitable-area query index (PQ-index) by extracting area summaries and route summaries from raw taxi trip data. It then identifies candidate profitable areas by searching the PQ-index during query processing. Then, it exploits a Z-Skyline algorithm, which is an extension of skyline processing with a Z-order space filling curve, to quickly refine the candidate profitable areas. To improve the performance of distributed query processing, we also propose local Z-Skyline optimization, which reduces the number of dominant tests by distributing killer profitable areas to each cluster node. Through extensive evaluation with real datasets, we demonstrate that our DISPAQ system provides a scalable and efficient solution for processing profitable-area queries from huge amounts of big taxi trip data.

The escalation of traffic congestion in urban cities has urged many countries to use intelligent transportation system (ITS) centers to collect historical traffic sensor data from multiple heterogeneous sources. By analyzing historical traffic data, we can obtain valuable insights into traffic behavior. Many existing applications have been proposed with limited analysis results because of the inability to cope with several types of analytical queries. In this paper, we propose the QET (querying and extracting timeline information) system—a novel analytical query processing method based on a timeline model for road traffic sensor data. To address query performance, we build a TQ-index (timeline query-index) that exploits spatio-temporal features of timeline modeling. We also propose an intuitive timeline visualization method to display congestion events obtained from specified query parameters. In addition, we demonstrate the benefit of our system through a performance evaluation using a Busan ITS dataset and a Seattle freeway dataset.

Purpose. NSAIDs constitute an important class of drugs with therapeutic applications that have spanned several centuries. Treatment of inflammatory conditions such as rheumatoid arthritis (RA) and osteoarthritis (OA) starting from the classic drug aspirin to the recent rise and fall of selective COX-2 inhibitors has provided an enthralling evolution. Efforts to discover an ultimate magic bullet to treat inflammation continues to be an important drug design challenge. This review traces the origins of NSAIDs, their mechanism of action at the molecular level such as cyclooxygenase (COX) inhibition, development of selective COX-2 inhibitors, their adverse cardiovascular effects, and some recent developments targeted to the design of effective anti-inflammatory agents with reduced side effects. Methods. Literature data is presented describing important discoveries pertaining to the sequential development of classical NSAIDs and then selective COX-2 inhibitors, their mechanism of action, the structural basis for COX inhibition, and recent discoveries. Results. A brief history of the development of NSAIDs and the market withdrawal of selective COX-2 inhibitors is explained, followed by the description of prostaglandin biosynthesis, COX isoforms, structure and function. The structural basis for COX-1 and COX-2 inhibition is described along with methods used to evaluate COX-1/COX-2 inhibition. This is followed by a section that encompasses the major chemical classes of selective COX-2 inhibitors. The final section describes briefly some of the recent advances toward developing effective anti-inflammatory agents such as nitric oxide donor NO-NSAIDs, dual COX/LOX inhibitors and anti-TNF therapy. Conclusions. A great deal of progress has been made toward developing novel anti-inflammatory agents. In spite of the tremendous advances in the last decade, the design and development of a safe, effective and economical therapy for treating inflammatory conditions still presents a major challenge.