Liposomal drug delivery to the lungs: a post covid-19 scenario.

High local delivery of anti-infectives to the lungs is required for activity against infections of the lungs. The present pandemic has highlighted the potential of pulmonary delivery of anti-infective agents as a viable option for infections like Covid-19, which specifically causes lung infections and mortality. To prevent infections of such type and scale in the future, target-specific delivery of drugs to the pulmonary region is a high-priority area in the field of drug delivery. The suboptimal effect of oral delivery of anti-infective drugs to the lungs due to the poor biopharmaceutical property of the drugs makes this delivery route very promising for respiratory infections. Liposomes have been used as an effective delivery system for drugs due to their biocompatible and biodegradable nature, which can be used effectively for target-specific drug delivery to the lungs. In the present review, we focus on the use of liposomal drug delivery of anti-infectives for the acute management of respiratory infections in the wake of Covid-19 infection.

Tetrahydrobiopterin and Its Multiple Roles in Neuropsychological Disorders.

Tetrahydrobiopterin (BH4) is a multifunctional co-factor of various enzymes and a substantial amount of studies have shown BH4 as a key regulator in the synthesis of neurotransmitters such as serotonin, nor-epinephrine as well as dopamine. The imbalance of BH4 may affect neurotransmitter production which can lead to many abnormalities in CNS. This article reviews the role of BH4 in neurodegenerative and neurodevelopmental disorders. We focus on the therapeutic potential of BH4 in various brain diseases that involves neurotransmitters and attempt to address how the modulation of BH4 may provide a novel strategy in various neuropsychological conditions.

Comparative Evaluation of the Removal of Gutta Percha From the Root Canal Using Various Retreatment File Systems With and Without Magnification: An In Vitro Study.

AIM AND OBJECTIVE: The main goal was to compare the efficacy of gutta percha (GP) removal from the root canal using the Neo Endo Retreatment file system, Solite RS3, and ProTaper Universal Retreatment (PTUR) files with and without magnification under a direct operative microscope using stereomicroscopic evaluation. MATERIALS AND METHODS: Sixty single-rooted teeth were randomly assigned to one of three groups after obturation till F2 mastercone with resin sealer: Group 1 (n=20): Neo Endo Retreatment Files, Group 2 (n=20): Solite RS3, Group 3 (n=20): PTUR files. Each group was further separated into two subgroups: Subgroup 1: without magnification (no direct operative microscope) and Subgroup 2: with magnification under a direct operative microscope at 12× magnification. After retreatment, the roots were grooved buccolingually and split into two halves using a diamond disc with the help of a chisel. The samples were examined under a stereomicroscope. Images were captured in a digital camera and analyzed using image analyzing software Image Pro v10 (Media Cybernetics). RESULTS: The Neo Endo retreatment file system had a significantly greater percentage of remaining obturating material than the Solite RS3 Retreatment and PTUR file systems (p<0.05) in both groups with and without magnification. In the group without magnification, Solite RS3 showed a significant difference compared to ProTaper (p<0.05). In the group with magnification, there was no significant difference between the ProTaper Universal retreatment file system and Solite RS3 (p=0.589). Retreatment performed without magnification had more remnant GP when compared to the retreatment procedure performed under magnification of the direct operative microscope. CONCLUSION: Under stereomicroscopic evaluation, the remnant GP was higher in the Neo Endo File System both with and without magnification than in the Solite Retreatment and PTUR file systems. ProTaper showed moderate significance in removing the obturation than Solite RS3 in the magnification group. The Solite RS3 file system performed as efficiently as the PTUR file system.

Griffiths-like behavior and magnetocaloric properties of rare-earth silicide Tb2Co0.8Si3.2.

Novel rare-earth silicide, Tb2Co0.8Si3.2compound, crystallizes in Lu2CoGa3structure, a distorted substitution variant of theAlB2structure. The compound exhibits a complex magnetic state, with a ferromagnetic transition at 58 K, followed by successive antiferromagnetic transitions at 24 K and 8 K, respectively. Isothermal and magnetic hysteresis studies indicate the prominence of competing antiferro and ferromagnetic interactions in the compound. However, this does not lead to the formation of spin glass behavior, as confirmed by AC magnetic susceptibility and heat capacity studies. In the paramagnetic state, the short-range ferromagnetic ordering of cobalt creates a Griffiths-like anomaly that is suppressed at higher magnetic fields. Investigation of magnetocaloric and magnetoresistance properties identifies the compound as a conventional second-order magnetocaloric material with negative magnetoresistance. Furthermore, the determination of Landau coefficients and subsequent analysis indicate that the isothermal entropy change of the compound can be calculated from these coefficients.

Diffuse pleural metastasis from atypical meningioma.

Meningioma is the most common benign primary brain tumour and does not usually metastasise. We report the case of a 69-year-old male patient with a history of meningioma who presented respiratory symptoms. He was found to have diffuse pleural metastasis from meningioma, which occurred 10 years after surgical management of recurrent meningioma. This case study provides insights into the clinical profile, workup and management of metastatic meningioma.

Treatment outcome of coronal pulpotomy and indirect pulp capping in mature permanent molars with symptoms of moderate pulpitis: A randomized clinical trial.

Aim: This clinical trial aimed to compare the clinical success of coronal pulpotomy and indirect pulp capping (IPC) in managing symptomatic deep proximal caries in molars with moderate pulpitis over a 12-month period. Materials and Methods: A total of 108 vital mature permanent molars with moderate pulpitis were randomly allocated to the IPC (n = 54) or coronal pulpotomy group (n = 54). Dycal and Biodentine were used as pulp-capping materials, followed by composite restoration. The absence of periapical infection and asymptomatic teeth that positively responded to the cold pulp sensitivity test (only in IPC) was considered posttreatment success at 12 months. Data from the study were analyzed using the Chi-square test and Kaplan-Meier survival analysis. Results: There was a statistically significant difference between preoperative symptoms and the cold pulp sensibility test response (P = 0.000), indicating an association between symptoms and pulp sensibility. The average remaining dentine thickness (RDT) value was 0.48 ± 0.5 mm, with no statistically significant difference found between the location of caries and RDT (P = 0.084, P > 0.05). Compared to the IPC group, the pulpotomy group had a greater number of patients at 12 months after treatment that required no intervention. The Kaplan-Meier survival analysis revealed that the mean survival duration for pulpotomy was 48 weeks, and for IPC, it was 42.3 ± 2.35 weeks. Conclusion: Coronal pulpotomy with Biodentine proved more effective in reducing symptoms, achieving radiographic success, and ensuring tooth survival compared to IPC with calcium hydroxide.

Microbial Interactions in Oral Biofilm: Evaluating Therapeutic Interventions and the Emergence of Resistance: A Narrative Review.

The oral cavity comprises numerous anatomical surfaces that are inhabited by a diverse array of bacteria, collectively forming a bacterial biofilm. Within this complex microbial community, certain bacterial species are etiologically linked to the development of common oral pathologies, such as dental caries and periodontitis, which stand as prominent instances of bacterial infections frequently encountered in clinical settings. Most biofilms are believed to be multispecies consortia. While single-species biofilms have been well-researched, mixed-species biofilms and their interactions amongst themselves have not drawn interest. The aim of the current review was to assess the various interactions of dual-species microorganisms in oral biofilm formation. Farnesol given exogenously for the treatment of biofilm can enhance or inhibit the growth of certain organisms, as seen in Candida albicans. In the age of antibiotic resistance, it is imperative to develop and uncover drugs capable of simultaneously targeting multiple species in order to mitigate antimicrobial resistance.

Deep learning based detection of monkeypox virus using skin lesion images.

As we set into the second half of 2022, the world is still recovering from the two-year COVID-19 pandemic. However, over the past three months, the outbreak of the Monkeypox Virus (MPV) has led to fifty-two thousand confirmed cases and over one hundred deaths. This caused the World Health Organisation to declare the outbreak a Public Health Emergency of International Concern (PHEIC). If this outbreak worsens, we could be looking at the Monkeypox virus causing the next global pandemic. As Monkeypox affects the human skin, the symptoms can be captured with regular imaging. Large samples of these images can be used as a training dataset for machine learning-based detection tools. Using a regular camera to capture the skin image of the infected person and running it against computer vision models is beneficial. In this research, we use deep learning to diagnose monkeypox from skin lesion images. Using a publicly available dataset, we tested the dataset on five pre-trained deep neural networks: GoogLeNet, Places365-GoogLeNet, SqueezeNet, AlexNet and ResNet-18. Hyperparameter was done to choose the best parameters. Performance metrics such as accuracy, precision, recall, f1-score and AUC were considered. Among the above models, ResNet18 was able to obtain the highest accuracy of 99.49%. The modified models obtained validation accuracies above 95%. The results prove that deep learning models such as the proposed model based on ResNet-18 can be deployed and can be crucial in battling the monkeypox virus. Since the used networks are optimized for efficiency, they can be used on performance limited devices such as smartphones with cameras. The addition of explainable artificial intelligence techniques LIME and GradCAM enables visual interpretation of the prediction made, helping health professionals using the model.

A decision support system for osteoporosis risk prediction using machine learning and explainable artificial intelligence.

Osteoporosis is a metabolic bone condition that occurs when bone mineral density and mass decrease. This makes the bones weak and brittle. The disorder is often undiagnosed and untreated due to its asymptomatic nature until the manifestation of a fracture. Machine Learning (ML) is extensively used in diverse healthcare domains to analyze precise outcomes, provide timely risk scores, and allocate resources. Hence, we have designed multiple heterogeneous machine-learning frameworks to predict the risk of Osteoporosis. An open-source dataset of 1493 patients containing bone density, blood, and physical tests is utilized. Thirteen distinct feature selection techniques were leveraged to extract the most salient parameters. The best-performing pipeline consisted of a Forward Feature Selection algorithm followed by a custom multi-level ensemble learning-based stack, which achieved an accuracy of 89 %. Deploying a layer of explainable artificial intelligence using tools such as SHAP (SHapley Additive Values), LIME (Local Interpretable Model Explainer), ELI5, Qlattice, and feature importance provided interpretability and rationale behind classifier prediction. With this study, we aim to provide the holistic risk prediction of Osteoporosis and concurrently present a system for automated screening to assist physicians in making diagnostic decisions.