Substance Use Disorder and COVID-19; Forensic Medicine and Pharmacology Perspectives: A Concise Narrative Review

Many investigations have confirmed the link between a substance use disorder (SUD) and the COVID-19 pandemic's increased risk of infection and consequences. This narrative review aims to understand these issues from a pharmacological standpoint, as well as the pandemic's impact on forensic medicine. Research and review articles included in this review were selected through an extensive search of databases such as PubMed and the use of appropriate keywords e.g. “substance use disorder” and “COVID-19”. Due to a weakened immune system and degeneration of the respiratory system's defense systems, SUDs have been shown to increase the risk of COVID-19 infection. Furthermore, some substances raise pro-inflammatory mediators, exposing the body to a cytokine storm. SUD frequently causes secondary comorbidities, such as the liver, lung and cardiovascular disease, complicating the treatment of COVID-19 infections. Some misused substances can compromise the treatment's effectiveness or safety. This study also looked at the effects of the pandemic on forensic medicine. It underlines the importance of developing safe forensic examination procedures and methodologies during pandemics. The use of narcotic substances was documented as one of the reasons for the increase in the frequency of COVID-19 and the severity of its repercussions.

Cyclic Vomiting Syndrome in Pediatric Patients: A Review of Therapeutics

Cyclic vomiting syndrome (CVS) is a functional gastrointestinal disorder that can present quite a challenge to clinicians caring for children with this complex disease. Different therapeutic interventions are recommended for prophylaxis and acute abortive therapy for a CVS attack. The aim of this review is to summarize therapeutic treatment recommendations from the 2008 North American Society for Pediatric Gastroenterology, Hepatology, and Nutrition (NASPGHN) Consensus Statement on the Diagnosis and Management of Cyclic Vomiting Syndrome and discuss studies contemporary to this expert recommendation. After an extensive search of medical databases, 8 studies that evaluated therapeutic treatments for CVS were identified. Amitriptyline and cyproheptadine remain the standard of care for prophylaxis. Nutritional supplements such as carnitine and coenzyme Q10 have shown efficacy in decreasing episodes and severity in small studies with high tolerability among patients. The combination of ondansetron and sumatriptan are recommended for abortion of an acute vomiting episode, but other agents such as aprepitant and sedative agents can be considered when vomiting is refractory to initial treatments.

Extremely Overdoped Superconducting Cuprates via High Pressure Oxygenation Methods

Within the cuprate constellation, one fixed star has been the superconducting dome in the quantum phase diagram of transition temperature vs. the excess charge on the Cu in the CuO2-planes, p, resulting from O-doping or cation substitution. However, a more extensive search of the literature shows that the loss of the superconductivity in favor of a normal Fermi liquid on the overdoped side should not be assumed. Many experimental results from cuprates prepared by high-pressure oxygenation show Tc converging to a fixed value or continuing to slowly increase past the upper limit of the dome of p = 0.26–0.27, up to the maximum amounts of excess oxygen corresponding to p values of 0.3 to > 0.6. These reports have been met with disinterest or disregard. Our review shows that dome-breaking trends for Tc are, in fact, the result of careful, accurate experimental work on a large number of compounds. This behavior most likely mandates a revision of the theoretical basis for high-temperature superconductivity. That excess O atoms located in specific, metastable sites in the crystal, attainable only with extreme O chemical activity under HPO conditions, cause such a radical extension of the superconductivity points to a much more substantial role for the lattice in terms of internal chemistry and bonding.

Licorice (Glycyrrhiza glabra) Extracts-Suitable Pharmacological Interventions for COVID-19? A Review

Even though vaccination has started against COVID-19, people should continue maintaining personal and social caution as it takes months or years to get everyone vaccinated, and we are not sure how long the vaccine remains efficacious. In order to contribute to the mitigation of COVID-19 symptoms, the pharmaceutical industry aims to develop antiviral drugs to inhibit the SARS-CoV-2 replication and produce anti-inflammatory medications that will inhibit the acute respiratory distress syndrome (ARDS), which is the primary cause of mortality among the COVID-19 patients. In reference to these tasks, this article considers the properties of a medicinal plant named licorice (Glycyrrhiza glabra), whose phytochemicals have shown both antiviral and anti-inflammatory tendencies through previous studies. All the literature was selected through extensive search in various databases such as google scholar, Scopus, the Web of Science, and PubMed. In addition to the antiviral and anti-inflammatory properties, one of the licorice components has an autophagy-enhancing mechanism that studies have suggested to be necessary for COVID-19 treatment. Based on reviewing relevant professional and historical literature regarding the medicinal properties of licorice, it is suggested that it may be worthwhile to conduct in vitro and in vivo studies, including clinical trials with glycyrrhizic and glycyrrhetinic acids together with other flavonoids found in licorice, as there is the potentiality to provide natural interventions against COVID-19 symptoms.

Protective Effects Of Isothiocyanates Against Alzheimer's Disease

Background: The extensive search for a novel therapeutic agent against Alzheimer's Disease (AD) in medical and pharmaceutical research still continues. Despite a lot being explored about its therapeutics, there is still much more to learn in order to achieve promising therapeutic agents against ADAlzheimer's. Phytochemicals, especially secondary metabolites, are the major focus of the investigators for AD treatment. Objective: To describe major therapeutics targets of AD and the role of isothiocyanates (ITCs) in modulating these targets. Methods: Scientific databases, including Elsevier, Science Direct, Pub med, were explored. The explored literature was mainly journal publications on pathogenesis and targets of AD, and the effect of various ITCs in the modulation of these targets. Results: The major targets of AD include the Nrf-2/ARE signaling pathway, MAPKs pathway, GSK-3 signaling, and Ubiquitin-Protease system. ITCs, such as Sulforaphane, Allyl isothiocyanates, Moringin, 6-(methylsulfinyl) hexyl ITC, Phenethyl isothiocyanates, and Erucin, were reported to exert a protective effect against AD via modulating one of the several above mentioned targets. Conclusion: This article gives a detailed description of the therapeutic targets of AD and sheds light that phytochemicals, such as ITCs, can exert a protective effect against AD by targeting those pathways. However, properly designed research and clinical trials are required to include ITCs as a mainstream agent against AD.

Analysis of Loop Programs Using Generalization

<p>This thesis describes a symbolic execution system, PAN, that is able to symbolically execute loops. PAN achieves this by generalizing the effect of a few loop iterations to predict the effect of an unknown number of iterations. PAN operates on relatively unstructured loops that include 'go to' type constructs, allowing multiple exits from a loop. PAN uses a two stage generalization approach using techniques developed in Artificial Intelligence systems. The first stage uses models of expected loop effects and requires only limited search to generalize the effect of simple loops The second stage uses a less constrained approach that can generalize the effects of more complex loops by using extensive search. Fundamental to PAN's generalization method is the sequence. These are identified using models and used in both stages of the generalization process.</p>

Analysis of Loop Programs Using Generalization

<p>This thesis describes a symbolic execution system, PAN, that is able to symbolically execute loops. PAN achieves this by generalizing the effect of a few loop iterations to predict the effect of an unknown number of iterations. PAN operates on relatively unstructured loops that include 'go to' type constructs, allowing multiple exits from a loop. PAN uses a two stage generalization approach using techniques developed in Artificial Intelligence systems. The first stage uses models of expected loop effects and requires only limited search to generalize the effect of simple loops The second stage uses a less constrained approach that can generalize the effects of more complex loops by using extensive search. Fundamental to PAN's generalization method is the sequence. These are identified using models and used in both stages of the generalization process.</p>

Kaptive 2.0: updated capsule and LPS locus typing for the Klebsiella pneumoniae species complex

The outer polysaccharide capsule and lipopolysaccharide antigens are key targets for novel control strategies targeting Klebsiella pneumoniae and related taxa from the K. pneumoniae species complex (KpSC), including vaccines, phage and monoclonal antibody therapies. Given the importance and growing interest in these highly diverse surface antigens, we had previously developed Kaptive, a tool for rapidly identifying and typing capsule (K) and outer lipopolysaccharide (O) loci from whole genome sequence data. Here, we report two significant updates, now freely available in Kaptive 2.0 (github.com/katholt/kaptive); i) the addition of 16 novel K locus sequences to the K locus reference database following an extensive search of >17,000 KpSC genomes; and ii) enhanced O locus typing to enable prediction of the clinically relevant O2 antigen (sub)types, for which the genetic determinants have been recently described. We applied Kaptive 2.0 to a curated dataset of >12,000 public KpSC genomes to explore for the first time the distribution of predicted O (sub)types across species, sampling niches and clones, which highlighted key differences in the distributions that warrant further investigation. As the uptake of genomic surveillance approaches continues to expand globally, the application of Kaptive 2.0 will generate novel insights essential for the design of effective KpSC control strategies.

Analysis of Loop Programs Using Generalization

<p>This thesis describes a symbolic execution system, PAN, that is able to symbolically execute loops. PAN achieves this by generalizing the effect of a few loop iterations to predict the effect of an unknown number of iterations. PAN operates on relatively unstructured loops that include 'go to' type constructs, allowing multiple exits from a loop. PAN uses a two stage generalization approach using techniques developed in Artificial Intelligence systems. The first stage uses models of expected loop effects and requires only limited search to generalize the effect of simple loops The second stage uses a less constrained approach that can generalize the effects of more complex loops by using extensive search. Fundamental to PAN's generalization method is the sequence. These are identified using models and used in both stages of the generalization process.</p>

Analysis of Loop Programs Using Generalization

<p>This thesis describes a symbolic execution system, PAN, that is able to symbolically execute loops. PAN achieves this by generalizing the effect of a few loop iterations to predict the effect of an unknown number of iterations. PAN operates on relatively unstructured loops that include 'go to' type constructs, allowing multiple exits from a loop. PAN uses a two stage generalization approach using techniques developed in Artificial Intelligence systems. The first stage uses models of expected loop effects and requires only limited search to generalize the effect of simple loops The second stage uses a less constrained approach that can generalize the effects of more complex loops by using extensive search. Fundamental to PAN's generalization method is the sequence. These are identified using models and used in both stages of the generalization process.</p>