Dermal Delivery of Hypericum perforatum (L.)Loaded Nanogel: Formulation to Preclinical Psoriasis Assessment.

BACKGROUND: Nanophytosomes represent an effective choice for topical drug delivery systems thanks to their small size, general non-toxicity, ease of functionalization and high surface to volume ratio. The goal of the current study was to investigate the potential benefits of using Hypericum perforatum extract nanogel as a means of improving skin penetration and prolonging skin deposition in dermatitis similar to psoriasis. METHOD: Nanophytosomes (NPs) were developed, optimised and thoroughly characterised. The optimised NPs were then placed in a Carbopol gel base matrix and tested ex-vivo (skin penetration and dermatokinetic) and in-vivo (antipsoriatic activity in an Imiquimod-induced psoriatic rat model). RESULTS: The optimised NPs had a spherical form and entrapment efficiency of 69.68% with a nanosized and zeta potential of 168nm and -10.37mV, respectively. XRD spectra and transmission electron microscopy tests confirmed the plant botanical encapsulation in the NPs. Following 60 days of storage at 40 ± 2°C/75 ± 5% RH, the optimised formula remained relatively stable. As compared to extract gel, nano-gel showed a much-improved ex vivo permeability profile and considerable drug deposition in the viable epidermal-dermal layers. When developed nano-gel was applied topically to a rat model of psoriasis, it demonstrated distinct in vivo anti-psoriatic efficacy in terms of drug activity and reduction of epidermal thickness in comparison to other formulations and the control. ELISA and histopathologic studies also demonstrated that nano-organogel had improved skin integrity and downregulated inflammatory markers (IL-17, IL-6, IFN-γ and MCP-1). CONCLUSION: Findings suggest that a developed plant botanicals-based nanogel has a potential for the treatment of psoriasis-like dermatitis with better skin retention and effectiveness.

Analysis of structural, electronic and optical properties of Er-doped rock salt AlN using ab-initio calculations.

CONTEXT: This investigation includes the structural and optoelectronic characteristics of both pure and Er-doped rock salt aluminium nitride (AlN). Upon introducing Er doping into the AlN host, the calculations reveal a rise in the atomic parameter. Incorporating Er into the system leads to enhancements in the static dielectric coefficient ɛ1(0), static reflectivity R(0), as well as static refractive index n(0), at zero frequency. After doping, the peaks of imaginary dielectric tensor, extinction coefficient and absorption coefficient shift towards lower energy levels. Various exchange correlation potentials are incorporated to compare the results of electronic and optical characteristics. METHODS: We employed the full potential linearized augmented plane wave (FP-LAPW) approach with WIEN2k code in conjunction with the density functional theory (DFT). To explore the optoelectronic characteristics of both pure as well as doped systems, three distinct exchange correlation potentials are utilized: the Perdew-Burke-Ernzerhof Generalized Gradient Approximation (PBE-GGA), Modified Becke Johnson Generalized Gradient Approximations (mBJ + GGA) and Hubbard potential (GGA + U).

Combining platelet rich plasma with ablative laser for post acne scars: A review.

Background Acne scars are one of the most common sequelae of inflammatory acne. It commonly affects adolescents and young adults and hence is associated with significant psychological morbidity. It is historically resistant to oral as well as surgical modalities. In the last two decades, ablative lasers (fractional or otherwise) have proven to be effective in management of acne scars. Some studies have proven the efficacy of platelet rich plasma in reducing the adverse effects and improving the efficacy of lasers. Objective Review of the studies combining platelet rich plasma with ablative laser for post acne scars. Methods A literature review of the MEDLINE database for studies evaluating the combination of ablative lasers with platelet rich plasma was performed. Only studies with higher levels of evidence (randomised controlled trials and comparative studies) were included in this review. Results Adding intradermal platelet rich plasma to fractional ablative lasers in the management of post acne scars increases clinical efficacy, reduces downtime as well as frequency and duration of ablative lasers related adverse effects. The efficacy of topical platelet rich plasma is less as compared to intradermal platelet rich plasma. Limitations The studies analysed are heterogeneous in nature with varied protocols and duration of follow up. Conclusions It is recommended to combine the ablative lasers with intradermal platelet rich plasma for better clinical response and reduce adverse effects as well as downtime.

Ab-initio study of strain-tunable g-GaN/BN nanoheterostructure for optoelectronic and photocatalytic applications.

CONTEXT: Two-dimensional (2D) nanoheterostructures of materials, integrating various phase or materials into a single nanosheet have stimulated large-scale research interest for designing novel two dimensional devices. In contemporary analysis present work, we examined the structural and electronic properties of the isolated 2D BN and GaN monolayers. We have investigated the structural stability and optoelectronic and photocatalytic response of the g-GaN/BN nanoheterostructure along with its response to strain. Nanoheterostructure g-GaN/BN is predicted to be a direct bandgap semiconductor with wide gap of 4.45 eV, whose value can be effectively modulated by applied strain ( ϵ ) , ranging from 4.55 ( ϵ = - 4%) to 3.58 eV ( ϵ = 8%). We also discovered that the tensile strain of 8% can substantially tune the direct bandgap of nanoheterostructure to indirect band gap nature. Even more important, the biaxial tensile strain engineering accentuates an enhancement of optical absorption in the UV region, broadening the light harvesting of the g-GaN/BN nanoheterostructure with the shifting of first absorption peak from 4.64 ( ϵ = - 4%) to 3.71 eV ( ϵ = 8%). Furthermore, strain-tuned band edge potentials arrangement perfectly fits the water reduction and oxidation redox potentials. Our findings portend that the g-GaN/BN nanoheterostructure has application in prospective nanoscale optoelectronic devices and photocatalytic hydrogen evolution system. METHODS: First principles calculations in this study are performed using density functional theory. Generalized gradient approximation within PBEsol functional employed to address the electron-electron exchange-correlation effects. For avoiding periodic interactions between the layers, we have inserted a vacuum region of thickness 10 Å in the z-direction. For ensuring the convergence accuracy of the computed results, convergence criteria of the iteration process is set to be 0.0001 eV. Local modified Becke-Johnson, a semi local functional, is applied for calculating electronic and optical properties for more accuracy of results. As in layered 2D nanoheterostructure, a factual depiction of the van der Waals interactions cannot be provided by conventional DFT techniques. Accordingly, in order to incorporate these interactions, we had employed the dispersion correction method of Grimme's.

Meta-GGA study of 2D AlN/BN planer heterostructure and performance enhancement via strain engineering.

CONTEXT: The 2D AlN/BN planer heterostructure is a promising wide band gap semiconductor, but systematic studies of its bandgap and optical characteristics under applied strain are scarce. Here, the engineering property of 2D AlN/BN comprising bandgap nature transition and optical absorption capability (from unstrained to strained) have been investigated using density functional theory calculations. The formation energy calculations confirm the stability of the simulated nanoheterostructure. The electronic band structure calculations demonstrate that nanoheterostructure is an indirect bandgap material with a large bandgap of 5.26 eV, which can be modified effectively by applying strain. According to the calculations, the transition from indirect to direct band gap behavior has been observed at +15% biaxial strain with 2.71 eV band gap energy. Meanwhile, calculations for optical absorption and dielectric function reveal that the system has significant absorption peaks in the ultraviolet region which are very sensitive to applied strain. As strain increases, the first absorption peaks are shifted towards a lower energy range from 5.73 eV (Ꜫ= 0 %) to 3.76 eV (Ꜫ = +15%), which features an enhancement of optical absorption for solar and solar-blind regions. Furthermore, we determined that the band edge positions in 2D AlN/BN straddled the water redox potential under strain, indicating its effectiveness as a proficient photocatalyst. These characteristics make 2D AlN/BN planer nanoheterostructure a promising candidate for applications in optoelectronics and photocatalytic water splitting performance. METHODS: First principles computations based on density functional theory were employed to carry out all the calculations with a self-consistent approach. For solving the Kohn-Sham equations, the first principles dependent full-potential linearized augmented plane wave scheme were adopted. For addressing the exchange-correlation effects, the generalized gradient approximation of PBEsol functional was used. To prevent interaction between the periodic images, we have inserted a vacuum region of 10 Šin the z-direction. Non-negligible weak dispersion corrections in nanoheterostructure were considered by using the DFT-D3 method of Grimme's. The locally modified Becke-Johnson (lmBJ) exchange potential has also been applied to compute electronic and optical properties in this research to obtain more accurate information.

Automated graded prognostic assessment for patients with hepatocellular carcinoma using machine learning.

BACKGROUND: Accurate mortality risk quantification is crucial for the management of hepatocellular carcinoma (HCC); however, most scoring systems are subjective. PURPOSE: To develop and independently validate a machine learning mortality risk quantification method for HCC patients using standard-of-care clinical data and liver radiomics on baseline magnetic resonance imaging (MRI). METHODS: This retrospective study included all patients with multiphasic contrast-enhanced MRI at the time of diagnosis treated at our institution. Patients were censored at their last date of follow-up, end-of-observation, or liver transplantation date. The data were randomly sampled into independent cohorts, with 85% for development and 15% for independent validation. An automated liver segmentation framework was adopted for radiomic feature extraction. A random survival forest combined clinical and radiomic variables to predict overall survival (OS), and performance was evaluated using Harrell's C-index. RESULTS: A total of 555 treatment-naïve HCC patients (mean age, 63.8 years ± 8.9 [standard deviation]; 118 females) with MRI at the time of diagnosis were included, of which 287 (51.7%) died after a median time of 14.40 (interquartile range, 22.23) months, and had median followed up of 32.47 (interquartile range, 61.5) months. The developed risk prediction framework required 1.11 min on average and yielded C-indices of 0.8503 and 0.8234 in the development and independent validation cohorts, respectively, outperforming conventional clinical staging systems. Predicted risk scores were significantly associated with OS (p < .00001 in both cohorts). CONCLUSIONS: Machine learning reliably, rapidly, and reproducibly predicts mortality risk in patients with hepatocellular carcinoma from data routinely acquired in clinical practice. CLINICAL RELEVANCE STATEMENT: Precision mortality risk prediction using routinely available standard-of-care clinical data and automated MRI radiomic features could enable personalized follow-up strategies, guide management decisions, and improve clinical workflow efficiency in tumor boards. KEY POINTS: • Machine learning enables hepatocellular carcinoma mortality risk prediction using standard-of-care clinical data and automated radiomic features from multiphasic contrast-enhanced MRI. • Automated mortality risk prediction achieved state-of-the-art performances for mortality risk quantification and outperformed conventional clinical staging systems. • Patients were stratified into low, intermediate, and high-risk groups with significantly different survival times, generalizable to an independent evaluation cohort.

Diabetes: a review of its pathophysiology, and advanced methods of mitigation.

Diabetes mellitus (DM) is a long-lasting metabolic non-communicable disease often characterized by an increase in the level of glucose in the blood or hyperglycemia. Approximately, 415 million people between the ages of 20 and 79 years had DM in 2015 and this figure will rise by 200 million by 2040. In a study conducted by CARRS, it's been found that in Delhi the prevalence of diabetes is around 27% and for prediabetic cases, it is more than 46%. The disease DM can be both short-term and long-term and is often associated with one or more diseases like cardiovascular disease, liver disorder, or kidney malfunction. Early identification of diabetes may help avoid catastrophic repercussions because untreated DM can result in serious complications. Diabetes' primary symptoms are persistently high blood glucose levels, frequent urination, increased thirst, and increased hunger. Therefore, DM is classified into four major categories, namely, Type 1, Type 2, Gestational diabetes, and secondary diabetes. There are various oral and injectable formulations available in the market like insulin, biguanides, sulphonylureas, etc. for the treatment of DM. Recent attention can be given to the various nano approaches undertaken for the treatment, diagnosis, and management of diabetes mellitus. Various nanoparticles like Gold Nanoparticles, carbon nanomaterials, and metallic nanoparticles are some of the approaches mentioned in this review. Besides nanotechnology, artificial intelligence (AI) has also found its application in diabetes care. AI can be used for screening the disease, helping in decision-making, predictive population-level risk stratification, and patient self-management tools. Early detection and diagnosis of diabetes also help the patient avoid expensive treatments later in their life with the help of IoT (internet of medical things) and machine learning models. These tools will help healthcare physicians to predict the disease early. Therefore, the Nano drug delivery system along with AI tools holds a very bright future in diabetes care.

Targeting the vivid facets of apolipoproteins as a cardiovascular risk factor in rheumatoid arthritis.

Mostly, cardiovascular diseases are blamed for casualties in rheumatoid arthritis (RA) patients. Customarily, dyslipidemia is probably the most prevalent underlying cause of untimely demise in people suffering from RA as it hastens the expansion of atherosclerosis. The engagement of inflammatory cytokines like tumor necrosis factor-α (TNF-α), interleukin-1 (IL-1), interleukin-6 (IL-6), etc., is crucial in the progression and proliferation of both RA and abnormal lipid parameters. Thus, lipid abnormalities should be monitored frequently in patients with both primary and advanced RA stages. An advanced lipid profile examination, i.e., direct role of apolipoproteins associated with various lipid molecules is a more dependable approach for better understanding of the disease and selecting suitable therapeutic targets. Therefore, studying their apolipoproteins is more relevant than assessing RA patients' altered lipid profile levels. Among the various apolipoprotein classes, Apo A1 and Apo B are primarily being focused. In addition, it also addresses how calculating Apo B:Apo A1 ratio can aid in analyzing the disease's risk. The marketed therapies available to control lipid abnormalities are associated with many other risk factors. Hence, directly targeting Apo A1 and Apo B would provide a better and safer option.

Automated MRI liver segmentation for anatomical segmentation, liver volumetry, and the extraction of radiomics.

OBJECTIVES: To develop and evaluate a deep convolutional neural network (DCNN) for automated liver segmentation, volumetry, and radiomic feature extraction on contrast-enhanced portal venous phase magnetic resonance imaging (MRI). MATERIALS AND METHODS: This retrospective study included hepatocellular carcinoma patients from an institutional database with portal venous MRI. After manual segmentation, the data was randomly split into independent training, validation, and internal testing sets. From a collaborating institution, de-identified scans were used for external testing. The public LiverHccSeg dataset was used for further external validation. A 3D DCNN was trained to automatically segment the liver. Segmentation accuracy was quantified by the Dice similarity coefficient (DSC) with respect to manual segmentation. A Mann-Whitney U test was used to compare the internal and external test sets. Agreement of volumetry and radiomic features was assessed using the intraclass correlation coefficient (ICC). RESULTS: In total, 470 patients met the inclusion criteria (63.9±8.2 years; 376 males) and 20 patients were used for external validation (41±12 years; 13 males). DSC segmentation accuracy of the DCNN was similarly high between the internal (0.97±0.01) and external (0.96±0.03) test sets (p=0.28) and demonstrated robust segmentation performance on public testing (0.93±0.03). Agreement of liver volumetry was satisfactory in the internal (ICC, 0.99), external (ICC, 0.97), and public (ICC, 0.85) test sets. Radiomic features demonstrated excellent agreement in the internal (mean ICC, 0.98±0.04), external (mean ICC, 0.94±0.10), and public (mean ICC, 0.91±0.09) datasets. CONCLUSION: Automated liver segmentation yields robust and generalizable segmentation performance on MRI data and can be used for volumetry and radiomic feature extraction. CLINICAL RELEVANCE STATEMENT: Liver volumetry, anatomic localization, and extraction of quantitative imaging biomarkers require accurate segmentation, but manual segmentation is time-consuming. A deep convolutional neural network demonstrates fast and accurate segmentation performance on T1-weighted portal venous MRI. KEY POINTS: • This deep convolutional neural network yields robust and generalizable liver segmentation performance on internal, external, and public testing data. • Automated liver volumetry demonstrated excellent agreement with manual volumetry. • Automated liver segmentations can be used for robust and reproducible radiomic feature extraction.

Current veterinary regulations and way ahead.

This article aims to perform a comparative systematic review of regulations in veterinary medicine between the years 2016 to 2023. It explores the complex web of veterinary medicine regulations in various agencies and the nations, including USA (United States of America), EU (European Union), UK (United Kingdom), Japan, Australia, and India. Current article provides the comparative study on the veterinary regulations of different countries, including acts, directives, and drug approval processes. Such as, the specific legislation is needed to address zoonotic diseases. The strategic and regulated stockpiling of the veterinary drugs especially in chronic veterinary disease outbreak. It is essential to develop the dedicated Veterinary Pharmacopoeia for the regulated standardization of the raw materials as well as the formulations. Veterinary medical device is a field which is highly unregulated. There is a need to have regulations for the same. It is important to have dedicated veterinary pharmacovigilance centers which help in improving quality of medications to the livestock farms. After comparing the regulations of different countries. We observed that there is the absence of the zoonotic diseases and pharma stockpiling in every country. There is also an absence of the dedicated veterinary pharmacopoeia in every country. USA and Australia have the veterinary medical device regulation which is not there in other countries. Around the globe only Australia has the dedicated pharmacovigilance center. Including these recommendations into regulatory framework enhances the quality and safety of veterinary medicine. The current article adds a valuable resource for policymakers, veterinarians, and stakeholders in the field of animal health care.

LiverHccSeg: A publicly available multiphasic MRI dataset with liver and HCC tumor segmentations and inter-rater agreement analysis.

Accurate segmentation of liver and tumor regions in medical imaging is crucial for the diagnosis, treatment, and monitoring of hepatocellular carcinoma (HCC) patients. However, manual segmentation is time-consuming and subject to inter- and intra-rater variability. Therefore, automated methods are necessary but require rigorous validation of high-quality segmentations based on a consensus of raters. To address the need for reliable and comprehensive data in this domain, we present LiverHccSeg, a dataset that provides liver and tumor segmentations on multiphasic contrast-enhanced magnetic resonance imaging from two board-approved abdominal radiologists, along with an analysis of inter-rater agreement. LiverHccSeg provides a curated resource for liver and HCC tumor segmentation tasks. The dataset includes a scientific reading and co-registered contrast-enhanced multiphasic magnetic resonance imaging (MRI) scans with corresponding manual segmentations by two board-approved abdominal radiologists and relevant metadata and offers researchers a comprehensive foundation for external validation, and benchmarking of liver and tumor segmentation algorithms. The dataset also provides an analysis of the agreement between the two sets of liver and tumor segmentations. Through the calculation of appropriate segmentation metrics, we provide insights into the consistency and variability in liver and tumor segmentations among the radiologists. A total of 17 cases were included for liver segmentation and 14 cases for HCC tumor segmentation. Liver segmentations demonstrates high segmentation agreement (mean Dice, 0.95 ± 0.01 [standard deviation]) and HCC tumor segmentations showed higher variation (mean Dice, 0.85 ± 0.16 [standard deviation]). The applications of LiverHccSeg can be manifold, ranging from testing machine learning algorithms on public external data to radiomic feature analyses. Leveraging the inter-rater agreement analysis within the dataset, researchers can investigate the impact of variability on segmentation performance and explore methods to enhance the accuracy and robustness of liver and tumor segmentation algorithms in HCC patients. By making this dataset publicly available, LiverHccSeg aims to foster collaborations, facilitate innovative solutions, and ultimately improve patient outcomes in the diagnosis and treatment of HCC.

Understanding the role of radiologists in complex treatment decisions for patients with hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common primary malignant tumor of the liver and represents a significant global health burden. Management of HCC can be challenging due to multiple factors, including variable expectations for treatment outcomes. Several treatment options are available, each with specific eligibility and ineligibility criteria, and are provided by a multidisciplinary team of specialists. Radiologists should be aware of the types of treatment options available, as well as the criteria guiding the development of individualized treatment plans. This awareness enables radiologists to contribute effectively to patient-centered multidisciplinary tumor boards for HCC and play a central role in reassessing care plans when the treatment response is deemed inadequate. This comprehensive review aims to equip radiologists with an overview of HCC staging systems, treatment options, and eligibility criteria. The review also discusses the significance of imaging in HCC diagnosis, treatment planning, and monitoring treatment response. Furthermore, we highlight the crucial branch points in the treatment decision-making process that depend on radiological interpretation.

Single-Session Fractional CO2 Laser following Urea Occlusion in Management of Onychomycosis: A Pilot Study.

Introduction: Onychomycosis is a common nail disorders. Antifungal resistance, interactions, and side effects limit treatment options. Fractional CO2 (FCO2) laser along with topical antifungal is effective in multiple monthly sessions. A modification reducing repeated visits and hence better compliance is preferable. Single-session FCO2 laser following urea occlusion is reported to be effective. Thus, we conducted a study to determine the efficacy of single-session FCO2 laser with 1% terbinafine cream with and without "urea cream occlusion" in managing onychomycosis. Methods: A prospective, randomized, parallel-group study was conducted at a tertiary centre. Onychomycosis was confirmed by positive fungal mount and culture. Patients were randomized into 2 groups and administered single-session FCO2 laser. Group A was treated after overnight urea cream occlusion and group B without occlusion. Both groups applied 1% terbinafine cream twice daily for 3 months. Response was assessed by improvement in Onychomycosis Severity Index (OSI) at 6 months. Results: Group A had 10 patients, 14 nails. Clinical improvement was seen in 12/14 (85.7%) nails. Average reduction in OSI was 10.78. Group B had 10 patients, 11 nails. Clinical improvement was seen in 5/11 (45.5%) nails. Average reduction in OSI was 1.73. "Reduction in OSI" was statistically significant (p < 0.05) only in group A. Conclusion: Single-session FCO2 laser following overnight urea cream occlusion, followed by 1% terbinafine cream, is effective for management of onychomycosis.

Pulmonary Fibrosis: Unveiling the Pathogenesis, Exploring Therapeutic Targets, and Advancements in Drug Delivery Strategies.

Idiopathic pulmonary fibrosis (IPF) is an ailment with no cure and a very high rate of progression that ultimately leads to death. The exact reason for this disease is still not acknowledged. Many underlying mechanisms of wound healing and various types of stimuli that trigger the pathogenesis of IPF continue to be intensively explored. The exact therapy for the reversal of this disease is not yet known and is constantly in progress. Existing treatments only slow down the process or mitigate the symptoms to enhance the patient's healthcare system. The only two Food and Drug Administration-approved oral medications include pirfenidone and nintedanib whose high dose and systemic circulation can have side effects to a greater extent. Further research on restorative and extra-curative therapies for IPF is necessary due to the absence of viable therapeutic choices. To assure minimum off-targeted site delivery and longer duration of action, techniques that offer a sustainable release of the drug, better bioavailability, and patient compliance can be used.The work is an overview of the main therapeutic targets and pertinent developing therapies for the management of IPF. This study is an attempt to focus on various drug delivery systems that are responsible for showing effectiveness in defense mechanisms against IPF.

Medical Aesthetics - Current Trends and a Review of Its Applications.

Medical aesthetics is the use of a procedure or product for a therapeutic indication which is conventionally used for aesthetics. Several medical conditions are now being treated with products, procedures or equipment that are conventionally used for aesthetic indications. This has widened the scope of treatment modalities available for dermatologists to treat various indications that fall outside the purview of aesthetic dermatology. The authors present aesthetic treatment modalities and procedures which can be used for medical aesthetics, their present-day status and usefulness in field of therapeutics with a review of published literature from "Medline" (via "PubMed"), "Cochrane," the Virtual Health Library, and Google Scholar.

MRI of Benign Prostatic Hyperplasia: Important Pre- and Posttherapeutic Considerations.

New minimally invasive techniques that reduce morbidity while improving lower urinary tract symptoms (LUTS) due to benign prostatic hypertrophy (BPH) have become attractive alternatives for patients, in comparison to traditional techniques such as transurethral resection of the prostate (TURP) and simple prostatectomy. Pre- and postprocedural MRI is not routinely performed for LUTS due to BPH treatments. However, because of the combination of rapidly evolving treatments available for LUTS due to BPH and increasing demand for prebiopsy prostate MRI for detection of clinically significant prostate cancer (PCa), an understanding of procedural techniques and expected changes are important for accurate interpretation of prostate MRI performed after treatment of BPH. The authors discuss the imaging evaluation of LUTS due to BPH and emerging predictors of treatment success. The posttreatment appearance and underlying anatomic changes in the prostate after medical, surgical, and minimally invasive treatments including TURP, simple prostatectomy, laser enucleations and ablations, prostatic urethral lift, water vapor thermal therapy, and prostate artery embolization are detailed. Most procedures reduce prostate volume, notably in the periurethral prostatic tissue. Ablations create areas of necrosis and can distort the normal zonal anatomy between the transition zone and the peripheral zone, and prostate artery embolization creates infarcts in the transition zone. Mechanical prostatic urethral lift devices open the anterior channel at the bladder base but create susceptibility artifacts that can obscure and prevent detection of a lesion in the transition zone. Also discussed are the detection of clinically significant prostate cancer in the postprocedural prostate and imaging of BPH procedure complications such as urethral strictures, abscesses, and hematuria. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material. See the invited commentary by Purysko in this issue.

The Current Landscape of Bioactive Molecules against DENV: A Systematic Review.

With a 30-fold increase in incidence over the previous 50 years, dengue fever is now the most widespread viral disease transmitted by mosquitoes in the world. The intricate interaction of the human defense system, hereditary predisposition, and specific bitterness elements is more likely to be the pathogenesis of dengue. There are presently no viable treatments for dengue. Synthetic drugs which are used against this ailment also show major side effects. There must be a deeper understanding of the underlying mechanism generating severe symptoms to develop auguring markers, cutting-edge diagnostics, and treatments and finally a well-rounded and secure antiserum. Hence, the aim is to search for safer and more potent drugs derived from plants. Plants or herbs are mainly targeting replication or its enzyme or specific stereotypes, though an exact mechanism of phytoconstituents interfering with the viral replication is still undiscovered. The present attempt provided the update with the objective to bringing up forward pathophysiological eventualities involved in dengue virus along with the naturally derived treatment relevant to provide the impregnable therapy by evading the noxious symptoms for dengue fever. Governor's plum, Cryptocarya chartacea, magnolia berry, and Chinese ginger are such plants exhibiting many effective phytoconstituents against DENV and can be further explored for novel drug discovery by medicinal scientists.

Fractional CO2 laser with topical 1% terbinafine cream versus oral itraconazole in the management of onychomycosis: A randomized controlled trial.

Background Onychomycosis accounts for 20-40% of all nail disorders. It is difficult to cure with resistance to anti-fungal drugs, their side effects and drug interactions limiting treatment options. Itraconazole is a widely accepted oral medication used for onychomycosis while fractional CO2 laser along with a topical anti-fungal has shown promising results for nail plate clearance in onychomycosis. Aim To compare the efficacy of fractional CO2 laser with 1% terbinafine cream versus itraconazole in the management of onychomycosis. Methods A prospective, randomised, single-centre, two-arm, parallel-group interventional study was conducted at Command Hospital Air Force, Bangalore. Onychomycosis cases confirmed by KOH mount/culture-positive were included. Patients were randomly divided into two groups. Group A received 4 sessions of fractional CO2 laser every fourth week with twice-daily application of 1% terbinafine cream; Group B received one-week pulse therapy with capsule itraconazole once every four-week for three pulses. The response was assessed by Onychomycosis Severity Index, a validated onychomycosis assessment scale, at baseline and at six months. Results Group A had 50 patients with a total of 98 nails. Clinical improvement was seen in 83/98 (84.7%) nails. The average reduction in Onychomycosis Severity Index was 8.65 (P < 0.05). Group B had 50 patients with a total of 136 nails. Clinical improvement was seen in 104/136 (76.5%) nails. The average reduction in Onychomycosis Severity Index was 7.37 (P < 0.05). Both groups showed statistically significant improvement measured by 'Reduction in Onychomycosis Severity Index' at six months; however, there was no significant difference between the two arms. Limitations The main limitations of the study are the small sample size and lack of long-term follow-up to assess recurrence of infection. Conclusion Fractional CO2 laser with 1% terbinafine cream is an effective and safe method for inducing nail clearance in onychomycosis and has efficacy similar to itraconazole pulse therapy.