Mixed Solvency Concept to Replace Harmful Organic Solvent: Recent Trends and Future Challenges in Formulation Development.

Organic solvents are hazardous and should be replaced with less harmful alternatives. When developing a new formulation for a medicine with low aqueous solubility, improving its solubility might be a significant difficulty. According to the mixed solvency concept, a novel concept of solubilization, the solubility of poorly soluble drugs can be increased by dissolving them in a concentrated solution comprising various substances. Methods commonly used to improve solubility include complexation, pH modification, salt formation, hydrotropy, cosolvency, and micelle solubilization. By reducing the concentration of specific solubilizers, this method can be used to reduce the toxicity of solubilizers in various formulations of poorly soluble medicines. This review aims to provide scientists with a fresh concept for enhancing medication solubility. The benefits and drawbacks of currently available green solvents have been analyzed as potential replacements for traditional solvents. Some examples of these solvents are bio-based solvents like ethanol, methanol, and cyrene; d-limonene; deep eutectic solvents such as ionic liquids and natural deep eutectic solvents; supercritical fluids; subcritical water; surfactant-based solutions like hydrotopes and supramolecular solvents; and deep eutectic solvents like cyrene.

Traditional Herbal Medications Utilized in the Indian Medical System for the Management of Diabetes: An Updated Review and Clinical Implications.

Phytomedicine, also called botanical medicine, is the practice of using plants to treat disease. Diabetes, for example, has been treated and prevented with herbal medication for a lot longer than Western medicine. Worldwide, diabetes has become a major health concern. The management of diabetes and hyperglycemia, two of the most common public health threats, is far from ideal. When hyperglycemia persists or is not under control, diabetes-related complications, like blindness, lower limb amputations, renal disease, and cardiovascular disease, play a significant role in the morbidity and mortality of the disease. Although chemicals and biochemical agents can assist in managing diabetes, there is currently no complete cure for the disease. Herbal remedies are one of many methods that can be used to treat and prevent diabetes and its subsequent problems. Numerous traditional treatments have been discovered for diabetes as a result of extensive research efforts. However, there are many factors to consider when deciding which herbs to use, such as the patient's financial status, the presence or absence of co-morbidities, and the accessibility, cost-effectiveness, and safety profile of the herbs. This article focuses on the use of herbal and natural remedies in the treatment and prevention of diabetes, the mechanisms by which these remedies lower blood glucose levels, and the specific herbal items now utilized in the management of diabetes.

Cubosomes: An Emerging and Promising Drug Delivery System for Enhancing Cancer Therapy.

Cancer and other diseases can be treated with cubosomes, which are lyotropic nonlamellar liquid crystalline nanoparticles (LCNs). These cubosomes can potentially be a highly versatile carrier with theranostic efficacy, as they can be ingested, applied topically, or injected intravenously. Recent years have seen substantial progress in the synthesis, characterization, regulation of drug release patterns, and target selectivity of loaded anticancer bioactive compounds. However, its use in clinical settings has been slow and necessitates additional proof. Recent progress and roadblocks in using cubosomes as a nanotechnological intervention against various cancers are highlighted. In the last few decades, advances in biomedical nanotechnology have allowed for the development of "smart" drug delivery devices that can adapt to external stimuli. By improving therapeutic targeting efficacy and lowering the negative effects of payloads, these well-defined nanoplatforms can potentially promote patient compliance in response to specific stimuli. Liposomes and niosomes, two other well-known vesicular systems, share a lipid basis with cubosomes. Possible applications include a novel medication delivery system for hydrophilic, lipophilic, and amphiphilic drugs. We evaluate the literature on cubosomes, emphasizing their potential use in tumor-targeted drug delivery applications and critiquing existing explanations for cubosome self-assembly, composition, and production. As cubosome dispersion has bioadhesive and compatible features, numerous drug delivery applications, including oral, ocular, and transdermal, are also discussed in this review.

Automation of Drug Discovery through Cutting-edge In-silico Research in Pharmaceuticals: Challenges and Future Scope.

The rapidity and high-throughput nature of in silico technologies make them advantageous for predicting the properties of a large array of substances. In silico approaches can be used for compounds intended for synthesis at the beginning of drug development when there is either no or very little compound available. In silico approaches can be used for impurities or degradation products. Quantifying drugs and related substances (RS) with pharmaceutical drug analysis (PDA) can also improve drug discovery (DD) by providing additional avenues to pursue. Potential future applications of PDA include combining it with other methods to make insilico predictions about drugs and RS. One possible outcome of this is a determination of the drug potential of nontoxic RS. ADME estimation, QSAR research, molecular docking, bioactivity prediction, and toxicity testing all involve impurity profiling. Before committing to DD, RS with minimal toxicity can be utilised in silico. The efficacy of molecular docking in getting a medication to market is still debated despite its refinement and improvement. Biomedical labs and pharmaceutical companies were hesitant to adopt molecular docking algorithms for drug screening despite their decades of development and improvement. Despite the widespread use of "force fields" to represent the energy exerted within and between molecules, it has been impossible to reliably predict or compute the binding affinities between proteins and potential binding medications.

Tribological Performance Evaluation of Greases on a Four-Ball Tester with Graphene Oxide Nanoparticles.

Conventional greases have an exceptional place in the field of lubrication. They are unique in the sense of their areas of application and are very difficult to replace with other lubricating substances for the same reason. The advancements in the field of nanoparticles and the results they provide as an additive in greases have great scientific interest as they improve the tribological properties of greases to a great extent. The current work's aim is to synthesize a nanogripe using graphene oxide (GO) nanoparticles to lithium grease (Li grease), which will increase the tribological properties of the plain Li grease. Steps were taken to investigate the impact of variation of load on the frictional and wear characteristics of nanogrease. Synthesis of nanogrease and tribological evaluation were performed with a magnetic stirrer with a hot plate and a four-ball tester. Results indicated that nanogrease exhibits better tribological properties. It is also found that the antiwear and frictional properties of grease are not proportional to the wt % of GO nanoparticles. It is also detected that with the increase in load, the tribological properties of nanogrease increase.

Recent Progress and Challenges in the Development of Edible Vaccines Produced by Genetically Modified Plants.

Biotechnologists have pioneered the idea of an edible vaccination in recent years. Subunit vaccines, such as those used to create edible vaccines, involve the introduction of certain genes into transgenic plants, which are subsequently coaxed into producing the corresponding protein. Bananas, potatoes, legumes, lettuce, soybeans, corn, and rice are all examples of foods that fall under this category. They have a low unit cost, can be stored conveniently, and are simple to administer to patients of varying ages. There is great hope that the use of edible vaccinations, particularly in underdeveloped countries, could drastically reduce the prevalence of diseases, including measles, cholera, hepatitis B, and diarrhea. The development of effective and widely applicable edible vaccination, however, faces a number of technological and regulatory hurdles. When compared to traditional immunizations, edible vaccines offer significant cost savings, increased productivity, and reduced risk. It raises the possibility of a more efficient approach to illness prevention. This article includes important uses, production, host plants, benefits, drawbacks, mechanism of action, and many regulatory difficulties related to edible vaccines. In this article, we have discussed the most recent developments and successes with edible and intradermal vaccines in terms of the system used for immunogen production, the molecular properties of these vaccines, and their ability to generate a protective systemic and mucosal response.

Unsupervised machine learning framework for discriminating major variants of concern during COVID-19.

Due to the high mutation rate of the virus, the COVID-19 pandemic evolved rapidly. Certain variants of the virus, such as Delta and Omicron emerged with altered viral properties leading to severe transmission and death rates. These variants burdened the medical systems worldwide with a major impact to travel, productivity, and the world economy. Unsupervised machine learning methods have the ability to compress, characterize, and visualize unlabelled data. This paper presents a framework that utilizes unsupervised machine learning methods to discriminate and visualize the associations between major COVID-19 variants based on their genome sequences. These methods comprise a combination of selected dimensionality reduction and clustering techniques. The framework processes the RNA sequences by performing a k-mer analysis on the data and further visualises and compares the results using selected dimensionality reduction methods that include principal component analysis (PCA), t-distributed stochastic neighbour embedding (t-SNE), and uniform manifold approximation projection (UMAP). Our framework also employs agglomerative hierarchical clustering to visualize the mutational differences among major variants of concern and country-wise mutational differences for selected variants (Delta and Omicron) using dendrograms. We also provide country-wise mutational differences for selected variants via dendrograms. We find that the proposed framework can effectively distinguish between the major variants and has the potential to identify emerging variants in the future.

An Enigmatic Case of Jaundice and Photosensitivity in an Adolescent.

Erythropoietic protoporphyria (EPP) presents with nonblistering photosensitivity. Hepatobiliary manifestations are seen in around 5% cases and include cholelithiasis, elevations in liver enzymes, progressive jaundice, and end-stage liver disease. The diagnosis is suspected based on clinical features and elevated erythrocyte metal-free protoporphyrin and confirmed by genetic analysis showing loss-of-function mutations in the ferrochelatase (FECH) gene. We present an adolescent boy who presented with jaundice and photosensitivity with the liver biopsy showing deposition of brown pigments within the canaliculi and hepatocytes. This pigment showed Maltese cross birefringence on polarizing microscopy and Medusa-head appearance on electron microscopy. Genetic analysis revealed loss-of-function mutations in FECH. Introduction of EPP is an inborn error of heme biosynthesis caused by mutations in FECH with a prevalence of 1:75,000 to 1:200,000. We present a case of a 16-year-old adolescent boy with photosensitivity, abdominal pain, and jaundice with protoporphyrin deposition in the liver who was ultimately diagnosed with EPP based on genetic analysis.

Qualitative comparison of elemental concentration in soils and other geomaterials using FP-XRF.

Field portable X-ray fluorescence (FP-XRF) has tremendous potential in geoenvironmental engineering as a qualitative assessment tool. Identification of the elevated concentrations of the selected elements (Cr, Cu, Mn, Ni, Pb, and Zn) in various geomaterials like soil-like-material (SLM), incinerated bottom ash (IBA), construction and demolition waste (CDW), zinc tailings (ZT) and fly ash (FA) was performed by FP-XRF and compared with the local soil-Delhi silt. Comparably higher concentrations (mg/kg) of Cr (401.0), Cu (499.0), Pb (532.0), Zn (608.0) in SLM, Cr (195.0), Cu (419.0), Ni (93.0), Pb (931.0), Zn (771.0) in IBA and Cr (195.0), Cu (4000.0), Pb (671.0), Zn (7122.0) in ZT were observed. CDW and FA showed similar concentrations range as in local soils. FP-XRF was also used in-situ on local soil at 11 sites to examine its ability to identify the elements with significant variations in concentrations. The results showed high variability in Cl and S concentration values across the 11 sites attributed to the changing moisture content and dissolved salts. The concentration range for the remaining elements were similar at all sites. The verification of the detected elements through visual inspection of the spectrum was also carried out.

Severe Acute Respiratory Infection Surveillance during the Initial Phase of the COVID-19 Outbreak in North India: A Comparison of COVID-19 to Other SARI Causes.

INTRODUCTION: World Health Organization proposes severe acute respiratory infection (SARI) case definition for coronavirus disease 2019 (COVID-19) surveillance; however, early differentiation between SARI etiologies remains challenging. We aimed to investigate the spectrum and outcome of SARI and compare COVID-19 to non-COVID-19 causes. PATIENTS AND METHODS: A prospective cohort study was conducted between March 15, 2020, to August 15, 2020, at an adult medical emergency in North India. SARI was diagnosed using a "modified" case definition-febrile respiratory symptoms or radiographic evidence of pneumonia or acute respiratory distress syndrome of ≤14 days duration, along with a need for hospitalization and in the absence of an alternative etiology that fully explains the illness. COVID-19 was diagnosed with reverse transcription-polymerase chain reaction testing. RESULTS: In total, 95/212 (44.8%) cases had COVID-19. Community-acquired pneumonia (n = 57), exacerbation of chronic lung disease (n = 11), heart failure (n = 11), tropical febrile illnesses (n = 10), and influenza A (n = 5) were common non-COVID-19 causes. No between-group differences were apparent in age ≥60 years, comorbidities, oxygenation, leukocytosis, lymphopenia, acute physiology and chronic health evaluation (APACHE)-II score, CURB-65 score, and ventilator requirement at 24-hour. Bilateral lung distribution and middle-lower zones involvement in radiography predicted COVID-19. The median hospital stay was longer with COVID-19 (12 versus 5 days, p = 0.000); however, mortality was similar (31.6% versus 28.2%, p = 0.593). Independent mortality predictors were higher mean APACHE II in COVID-19 and early ventilator requirement in non-COVID-19 cases. CONCLUSIONS: COVID-19 has similar severity and mortality as non-COVID-19 SARI but requires an extended hospital stay. Including radiography in the SARI definition might improve COVID-19 surveillance. HOW TO CITE THIS ARTICLE: Pannu AK, Kumar M, Singh P, Shaji A, Ghosh A, Behera A, et al. Severe Acute Respiratory Infection Surveillance during the Initial Phase of the COVID-19 Outbreak in North India: A Comparison of COVID-19 to Other SARI Causes. Indian J Crit Care Med 2021;25(7):761-767.

A model for real time, in situ estimation of cesium coverage on metal substrate using infrared imaging under vacuum.

The present work is to develop an infra-red (IR) camera based in situ diagnostic tool for the determination of cesium (Cs) coverage suitable for ion source applications. Cs seeding is done to reduce the surface work function that enhances the surface assisted negative hydrogen ion production. The temporal Cs deposition on a metal surface (for, e.g., tungsten or molybdenum) follows Langmuir adsorption isotherm (LAI) kind of behavior. The surface temperature varies while the Cs deposition is reflected in the IR camera temperature measurements for a constant surface emissivity value. In this paper, a model on the relationship between Cs coverage in correlation with surface emissivity and temperature variation based on the theory of LAI is presented. A surface ionization probe (SIP) in the form of a cathode-anode assembly together with an IR camera viewing arrangement is designed to measure the Cs flux and the surface temperature simultaneously to test our model. In the present experiment, the Cs flux measurement using SIP is validated with a standard quartz crystal microbalance (QCM). The proposed model would be useful to correlate Cs coverage on plasma grid-like surface conditions under negative ion source relevant vacuum conditions.

Computational study to investigate effect of tonometer geometry and patient-specific variability on radial artery tonometry.

Tonometry-based devices are valuable method for vascular function assessment and for measurement of blood pressure. However current design and calibration methods rely on simple models, neglecting key geometrical features, and anthropometric and property variability among patients. Understanding impact of these influences on tonometer measurement is thus essential for improving outcomes of current devices, and for proposing improved design. Towards this goal, we present a realistic computational model for tissue-device interaction using complete wrist section with hyperelastic material and frictional contact. Three different tonometry geometries were considered including a new design, and patient-specific influences incorporated via anthropometric and age-dependent tissue stiffness variations. The results indicated that the new design showed stable surface contact stress with minimum influence of the parameters analyzed. The computational predictions were validated with experimental data from a prototype based on the new design. Finally, we showed that the underlying mechanics of vascular unloading in tonometry to be fundamentally different from that of oscillatory method. Due to directional loading in tonometry, pulse amplitude maxima was observed to occur at a significantly lower compression level (around 31%) than previously reported, which can impact blood pressure calibration approaches based on maximum pulse pressure recordings.

Molecular methods for serovar determination of Salmonella.

Salmonella is a diverse foodborne pathogen, which has more than 2600 recognized serovars. Classification of Salmonella isolates into serovars is essential for surveillance and epidemiological investigations; however, determination of Salmonella serovars, by traditional serotyping, has some important limitations (e.g. labor intensive, time consuming). To overcome these limitations, multiple methods have been investigated to develop molecular serotyping schemes. Currently, molecular methods to predict Salmonella serovars include (i) molecular subtyping methods (e.g. PFGE, MLST), (ii) classification using serovar-specific genomic markers and (iii) direct methods, which identify genes encoding antigens or biosynthesis of antigens used for serotyping. Here, we reviewed reported methodologies for Salmonella molecular serotyping and determined the "serovar-prediction accuracy", as the percentage of isolates for which the serovar was correctly classified by a given method. Serovar-prediction accuracy ranged from 0 to 100%, 51 to 100% and 33 to 100% for molecular subtyping, serovar-specific genomic markers and direct methods, respectively. Major limitations of available schemes are errors in predicting closely related serovars (e.g. Typhimurium and 4,5,12:i:-), and polyphyletic serovars (e.g. Newport, Saintpaul). The high diversity of Salmonella serovars represents a considerable challenge for molecular serotyping approaches. With the recent improvement in sequencing technologies, full genome sequencing could be developed into a promising molecular approach to serotype Salmonella.