An Investigation of Structure-Activity Relationships of Azolylacryloyl Derivatives Yielded Potent and Long-Acting Hemoglobin Modulators for Reversing Erythrocyte Sickling

Aromatic aldehydes that bind to sickle hemoglobin (HbS) to increase the protein oxygen affinity and/or directly inhibit HbS polymer formation to prevent the pathological hypoxia-induced HbS polymerization and the subsequent erythrocyte sickling have for several years been studied for the treatment of sickle cell disease (SCD). With the exception of Voxelotor, which was recently approved by the U.S. Food and Drug Administration (FDA) to treat the disease, several other promising antisickling aromatic aldehydes have not fared well in the clinic because of metabolic instability of the aldehyde moiety, which is critical for the pharmacologic activity of these compounds. Over the years, our group has rationally developed analogs of aromatic aldehydes that incorporate a stable Michael addition reactive center that we hypothesized would form covalent interactions with Hb to increase the protein affinity for oxygen and prevent erythrocyte sickling. Although, these compounds have proven to be metabolically stable, unfortunately they showed weak to no antisickling activity. In this study, through additional targeted modifications of our lead Michael addition compounds, we have discovered other novel antisickling agents. These compounds, designated MMA, bind to the α-globin and/or β-globin to increase Hb affinity for oxygen and concomitantly inhibit erythrocyte sickling with significantly enhanced and sustained pharmacologic activities in vitro

Antibiofilm Potential of Coelomic Fluid and Paste of Earthworm <i>Pheretima posthuma</i> (Clitellata, Megascolecidae) against Pathogenic Bacteria

Antibiotic drug resistance is a global public health issue that demands new and novel therapeutic molecules. To develop new agents, animal secretions or products are used as an alternative agent to overcome this problem. In this study, earthworm (Pheretima posthuma) coelomic fluid (PCF), and body paste (PBP) were used to analyze their effects as antibiofilm agents against four bacterial isolates MH1 (Pseudomonas aeruginosa MT448672), MH2 (Escherichia coli MT448673), MH3 (Staphylococcus aureus MT448675), and MH4 (Klebsiella pneumoniae MT448676). Coelomic fluid extraction and body paste formation were followed by minimum inhibitory concentrations (MICs), biofilm formation time kinetics, and an antibiofilm assay, using heat and cold shock, sunlight exposure auto-digestion, and test tube methods. The results showed that the MIC values of PCF and PBP against S. aureus, P. aeruginosa, K. pneumoniae, and E. coli bacterial isolates ranged from 50 to 100 μg/mL, while, the results related to biofilm formation for P. aeruginosa, S. aureus, and K. pneumoniae strains were observed to be highly significantly increased (p E. coli produced a significant (p p > 0.05) antibiofilm activity against all the selected strains (MH1-MH4). At 50 μg/mL concentration, both PCF and PBP showed significant (p p p < 0.001) biofilm inhibition at 150 and 200 μg/mL concentrations. Moreover, more than 90% biofilm inhibition was observed at 200 μg/mL of PCF, while in the case of the PBP, <96% biofilm reduction (i.e., 100%) was also observed by all selected strains at 200 μg/mL. In conclusion, earthworm body fluid and paste have biologically active components that inhibit biofilm formation by various pathogenic bacterial strains. For future investigations, there is a need for further study to explore the potential bioactive components and investigate in depth their molecular mechanisms from a pharmaceutical perspective for effective clinical utilization

Advances in fungal phenaloenones—natural metabolites with great promise: biosynthesis, bioactivities, and an in silico evaluation of their potential as human glucose transporter 1 inhibitors

Phenaloenones are structurally unique aromatic polyketides that have been reported in both microbial and plant sources. They possess a hydroxy perinaphthenone three-fused-ring system and exhibit diverse bioactivities, such as cytotoxic, antimicrobial, antioxidant, and anti-HIV properties, and tyrosinase, α-glucosidase, lipase, AchE (acetylcholinesterase), indoleamine 2,3-dioxygenase 1, angiotensin-I-converting enzyme, and tyrosine phosphatase inhibition. Moreover, they have a rich nucleophilic nucleus that has inspired many chemists and biologists to synthesize more of these related derivatives. The current review provides an overview of the reported phenalenones with a fungal origin, including their structures, sources, biosynthesis, and bioactivities. Moreover, more than 135 metabolites have been listed, and 71 references have been cited. SuperPred, an artificial intelligence (AI) webserver, was used to predict the potential targets for selected phenalenones. Among these targets, we chose human glucose transporter 1 (hGLUT1) for an extensive in silico study, as it shows high probability and model accuracy. Among them, aspergillussanones C (60) and G (60) possessed the highest negative docking scores of −15.082 and −14.829 kcal/mol, respectively, compared to the native inhibitor of 5RE (score: −11.206 kcal/mol). The MD (molecular dynamics) simulation revealed their stability in complexes with GLUT1 at 100 ns. The virtual screening study results open up a new therapeutic approach by using some phenalenones as hGLUT1 inhibitors, which might be a potential target for cancer therapy

Improving the Solubility and Oral Bioavailability of a Novel Aromatic Aldehyde Antisickling Agent (PP10) for the Treatment of Sickle Cell Disease

Background: Aromatic aldehydes, with their ability to increase the oxygen affinity of sickle hemoglobin, have become important therapeutic agents for sickle cell disease (SCD). One such compound, voxelotor, was recently approved for SCD treatment. Methyl 6-((2-formyl-3-hydroxyphenoxy)methyl) picolinate (PP10) is another promising aromatic aldehyde, recently reported by our group. Like voxelotor, PP10 exhibits O2-dependent antisickling activity, but, unlike voxelotor, PP10 shows unique O2-independent antisickling effect. PP10, however, has limited solubility. This study therefore aimed to develop oral and parenteral formulations to improve PP10 solubility and bioavailability. Methods: Oral drug tablets with 2-hydroxypropyl beta cyclodextrin (HP-β-CD), polyvinylpyrrolidone, or Eudragit L100-55 PP10-binary system, and an intravenous (IV) formulation with d-α-tocopherol polyethylene glycol 1000 succinate (TPGS) or HP-β-CD, were developed. The pharmacokinetic behavior of the formulations was studied in Sprague-Dawley rats. PP10, a methylester, and its acid metabolite were also studied in vitro with sickle whole blood to determine their effect on Hb modification, Hb oxygen affinity, and sickle red blood cell inhibition. Results: Aqueous solubility of PP10 was enhanced ~5 times with the HP-β-CD binary system, while the TPGS aqueous micelle formulation was superior, with a drug concentration of 0.502 ± 0.01 mg/mL and a particle size of 26 ± 3 nm. The oral tablets showed relative and absolute bioavailabilities of 173.4% and 106.34%, respectively. The acid form of PP10 appeared to dominate in vivo, although both PP10 forms demonstrated pharmacologic effect. Conclusion: Oral and IV formulations of PP10 were successfully developed using HP-β-CD binary system and TPGS aqueous micelles, respectively, resulting in significantly improved solubility and bioavailability

Investigating effect of water of hydration on active pharmaceutical ingredients in a water-sensitive dosage form

Abstract Background Preparation of mini buccal tablets incorporating either of the Alzheimer’s drugs, rivastigmine tartrate or donepezil hydrochloride, were developed for patients who have difficulty swallowing as a source of effervescence, by pairing the less commonly used malic acid with sodium bicarbonate in an experimentally determined (1:2) stochiometirc ratio. Methods To avoid premature reaction of the acid and the base during compounding, the tablet ingredients were mixed in the following order: acid, sweetener, binder, drug, preservative, base, and anti-adherent/lubricant. Results An accelerated thermal stability study at 40 °C and 25% relative humidity showed that the integrity of the effervescent tablets containing rivastigmine tartrate were superior to that of donepezil HCl tablets. FT-IR spectrometry confirmed the presence of water of hydrate in donepezil HCl crystals. This water was absent in the IR after one-month storage at accelerated thermal stability, but was present at room temperature. This behavior was not observed in the tablet made from rivastigmine tartrate powder. Differential scanning calorimetry of donepezil hydrochloride showed two thermal events: the first was associated with the loss of the water, and the second, at much higher temperature, was the melting of theanhydrous drug. Such behavior was not observed in the rivastigmine tartrate powder. Conclusions Hidden water which may function as catalyst to induce premature effervescence during storage

QUCoughScope: An Intelligent Application to Detect COVID-19 Patients Using Cough and Breath Sounds

Problem-Since the outbreak of the COVID-19 pandemic, mass testing has become essential to reduce the spread of the virus. Several recent studies suggest that a significant number of COVID-19 patients display no physical symptoms whatsoever. Therefore, it is unlikely that these patients will undergo COVID-19 testing, which increases their chances of unintentionally spreading the virus. Currently, the primary diagnostic tool to detect COVID-19 is a reverse-transcription polymerase chain reaction (RT-PCR) test from the respiratory specimens of the suspected patient, which is invasive and a resource-dependent technique. It is evident from recent researches that asymptomatic COVID-19 patients cough and breathe in a different way than healthy people. Aim-This paper aims to use a novel machine learning approach to detect COVID-19 (symptomatic and asymptomatic) patients from the convenience of their homes so that they do not overburden the healthcare system and also do not spread the virus unknowingly by continuously monitoring themselves. Method-A Cambridge University research group shared such a dataset of cough and breath sound samples from 582 healthy and 141 COVID-19 patients. Among the COVID-19 patients, 87 were asymptomatic while 54 were symptomatic (had a dry or wet cough). In addition to the available dataset, the proposed work deployed a real-time deep learning-based backend server with a web application to crowdsource cough and breath datasets and also screen for COVID-19 infection from the comfort of the user's home. The collected dataset includes data from 245 healthy individuals and 78 asymptomatic and 18 symptomatic COVID-19 patients. Users can simply use the application from any web browser without installation and enter their symptoms, record audio clips of their cough and breath sounds, and upload the data anonymously. Two different pipelines for screening were developed based on the symptoms reported by the users: asymptomatic and symptomatic. An innovative and novel stacking CNN model was developed using three base learners from of eight state-of-the-art deep learning CNN algorithms. The stacking CNN model is based on a logistic regression classifier meta-learner that uses the spectrograms generated from the breath and cough sounds of symptomatic and asymptomatic patients as input using the combined (Cambridge and collected) dataset. Results-The stacking model outperformed the other eight CNN networks with the best classification performance for binary classification using cough sound spectrogram images. The accuracy, sensitivity, and specificity for symptomatic and asymptomatic patients were 96.5%, 96.42%, and 95.47% and 98.85%, 97.01%, and 99.6%, respectively. For breath sound spectrogram images, the metrics for binary classification of symptomatic and asymptomatic patients were 91.03%, 88.9%, and 91.5% and 80.01%, 72.04%, and 82.67%, respectively. Conclusion-The web-application QUCoughScope records coughing and breathing sounds, converts them to a spectrogram, and applies the best-performing machine learning model to classify the COVID-19 patients and healthy subjects. The result is then reported back to the test user in the application interface. Therefore, this novel system can be used by patients in their premises as a pre-screening method to aid COVID-19 diagnosis by prioritizing the patients for RT-PCR testing and thereby reducing the risk of spreading of the disease.Funding: This work was supported by the Qatar National Research Grant: UREP28-144-3-046. The statements made herein are solely the responsibility of the authors.Scopu

ViSHWaS: Violence Study of Healthcare Workers and Systems—a global survey

Objective To provide insights into the nature, risk factors, impact and existing measures for reporting and preventing violence in the healthcare system. The under-reporting of violence against healthcare workers (HCWs) globally highlights the need for increased public awareness and education.Methods The Violence Study of Healthcare Workers and Systems study used a survey questionnaire created using Research Electronic Data Capture (REDCap) forms and distributed from 6 June to 9 August 2022. Logistic regression analysis evaluated violence predictors, including gender, age, years of experience, institution type, respondent profession and night shift frequency. A χ2 test was performed to determine the association between gender and different violence forms.Results A total of 5405 responses from 79 countries were analysed. India, the USA and Venezuela were the top three contributors. Female respondents comprised 53%. The majority (45%) fell within the 26–35 age group. Medical students (21%), consultants (20%), residents/fellows (15%) and nurses (10%) constituted highest responders. Nearly 55% HCWs reported firsthand violence experience, and 16% reported violence against their colleagues. Perpetrators were identified as patients or family members in over 50% of cases, while supervisor-incited violence accounted for 16%. Around 80% stated that violence incidence either remained constant or increased during the COVID-19 pandemic. Among HCWs who experienced violence, 55% felt less motivated or more dissatisfied with their jobs afterward, and 25% expressed willingness to quit. Univariate analysis revealed that HCWs aged 26–65 years, nurses, physicians, ancillary staff, those working in public settings, with &gt;1 year of experience, and frequent night shift workers were at significantly higher risk of experiencing violence. These results remained significant in multivariate analysis, except for the 55–65 age group, which lost statistical significance.Conclusion This global cross-sectional study highlights that a majority of HCWs have experienced violence, and the incidence either increased or remained the same during the COVID-19 pandemic. This has resulted in decreased job satisfaction