From Hypertension to Beyond: Unraveling the Diverse Mechanisms of Olmesartan in Disease Modulation.

Olmesartan, originally known for its antihypertensive properties, exhibits promising potential in addressing inflammation-mediated diseases. As an angiotensin II receptor blocker (ARB), Olmesartan influences pivotal pathways, including reactive oxygen species, cytokines, NF-κB, TNF-α, and MAPK. This suggests a viable opportunity for repurposing the drug in conditions such as ulcerative colitis, neuropathy, nephropathy, and cancer, as supported by multiple preclinical studies. Ongoing clinical trials, particularly in cardiomyopathy and nephropathy, suggest a broader therapeutic scope for Olmesartan. Repurposing efforts would entail comprehensive investigations using disease-specific preclinical models and dedicated clinical studies. The drug's established safety profile, wide availability, and well-understood ARB mechanism of action offer distinct advantages that could facilitate a streamlined repurposing process. In summary, Olmesartan's versatile impact on inflammation-related pathways positions it as a promising candidate for repurposing across various diseases. Ongoing clinical trials and the drug's favorable attributes enhance its appeal for further exploration and potential application in diverse medical contexts.

MicroRNA-29b-3p degenerates terminally differentiated dopaminergic SH-SY5Y cells by perturbation of mitochondrial functions.

Mitochondrial dysfunction is the main cause of gradual deterioration of structure and function of neuronal cells, eventually resulting in neurodegeneration. Studies have revealed a complex interrelationship between neurotoxicant exposure, mitochondrial dysfunction, and neurodegenerative diseases. Alteration in the expression of microRNAs (miRNAs) has also been linked with disruption in mitochondrial homeostasis and bioenergetics. In our recent research (Cellular and Molecular Neurobiology (2023) https://doi.org/10.1007/s10571-023-01362-4), we have identified miR-29b-3p as one of the most significantly up-regulated miRNAs in the blood of Parkinson's patients. The findings of the present study revealed that neurotoxicants of two different natures, that is, arsenic or rotenone, dramatically increased miR-29b-3p expression (18.63-fold and 12.85-fold, respectively) in differentiated dopaminergic SH-SY5Y cells. This dysregulation of miR-29b-3p intricately modulated mitochondrial morphology, induced oxidative stress, and perturbed mitochondrial membrane potential, collectively contributing to the degeneration of dopaminergic cells. Additionally, using assays for mitochondrial bioenergetics in live and differentiated SH-SY5Y cells, a reduction in oxygen consumption rate (OCR), maximal respiration, basal respiration, and non-mitochondrial respiration was observed in cells transfected with mimics of miR-29b-3p. Inhibition of miR-29b-3p by transfecting inhibitor of miR-29b-3p prior to exposure to neurotoxicants significantly restored OCR and other respiration parameters. Furthermore, we observed that induction of miR-29b-3p activates neuronal apoptosis via sirtuin-1(SIRT-1)/YinYang-1(YY-1)/peroxisome proliferator-activated receptor-gamma coactivator-1alpha (PGC-1α)-regulated Bcl-2 interacting protein 3-like-dependent mechanism. Collectively, our studies have shown the role of miR-29b-3p in dysregulation of mitochondrial bioenergetics during degeneration of dopaminergic neurons via regulating SIRT-1/YY-1/PGC-1α axis.

Applications of some advanced sequencing, analytical, and computational approaches in medicinal plant research: a review.

The potential active chemicals found in medicinal plants, which have long been employed as natural medicines, are abundant. Exploring the genes responsible for producing these compounds has given new insights into medicinal plant research. Previously, the authentication of medicinal plants was done via DNA marker sequencing. With the advancement of sequencing technology, several new techniques like next-generation sequencing, single molecule sequencing, and fourth-generation sequencing have emerged. These techniques enshrined the role of molecular approaches for medicinal plants because all the genes involved in the biosynthesis of medicinal compound(s) could be identified through RNA-seq analysis. In several research insights, transcriptome data have also been used for the identification of biosynthesis pathways. miRNAs in several medicinal plants and their role in the biosynthesis pathway as well as regulation of the disease-causing genes were also identified. In several research articles, an in silico study was also found to be effective in identifying the inhibitory effect of medicinal plant-based compounds against virus' gene(s). The use of advanced analytical methods like spectroscopy and chromatography in metabolite proofing of secondary metabolites has also been reported in several recent research findings. Furthermore, advancement in molecular and analytic methods will give new insight into studying the traditionally important medicinal plants that are still unexplored.

NMR spectroscopy-based analysis of gallstones of cancerous and benign gallbladders from different geographical regions of the Indian subcontinent.

Analysis of the chemical composition of gallstones is vital for the etiopathogenesis of gallstone diseases that can ultimately help in the prevention of its formation. In the present study, gallstones from seven different regions of India were analyzed to highlight the major difference in their composition. Also, gallstones of different pathological conditions i.e., benign (chronic cholecystitis, CC) and malignant gallbladder disease (gallbladder cancer GBC) were characterized. The type of polymorphs of cholesterol molecules was also studied to provide insight into the structure of gallstones. 1H solution state NMR spectroscopy 1D experiments were performed on a total of 94 gallstone (GS) samples collected from seven different geographical regions of India. Solid-State NMR spectroscopy 13C cross-polarization magic angle spinning (CPMAS) experiments were done on the 20 CC GS samples and 20 GBC GS samples of two regions. 1H NMR spectra from the solution state NMR of all the stones reveal that cholesterol was a major component of the maximum stones of the north India region while in south Indian regions, GS had very less cholesterol. 13C CPMAS experiments reveal that the quantity of cholesterol was significantly more in the GS of CC in the Lucknow region compared with GBC stones of Lucknow and Chandigarh. Our study also revealed that GS of the Lucknow region of both malignant and benign gallbladder diseases belong to the monohydrate crystalline form of cholesterol while GS of Chandigarh region of both malignant and benign gallbladder diseases exists in both monohydrate crystalline form with the amorphous type and anhydrous form. Gallstones have a complicated and poorly understood etiology. Therefore, it is important to understand the composition of gallstones, which can be found in various forms and clinical conditions. Variations in dietary practices, environmental conditions, and genetic factors may influence and contribute to the formation of GS. Prevention of gallstone formation may help in decreasing the cases of gallbladder cancer.

Clinical Manifestation of AGE-RAGE Axis in Neurodegenerative and Cognitive Impairment Disorders.

The receptor of Advanced Glycation Endproducts (RAGE) and Advanced Glycation Endproducts (AGE) have multiple functions in our body and their restraint are being observed in neurodegenerative and memory impairment disorders. The review of different pathways allows an understanding of the probable mechanism of neurodegeneration and memory impairment involving RAGE and AGE. Commonly we observe AGE accumulation in neural cells and tissues but the extent of accumulation increases with the presence of memory impairment disorder. The presence of AGEs can also be seen in morbid accumulation, pathological structures in the form of amyloid clots, and nervous fibrillary tangles in Alzheimer's Disease (AD) and memory impairment disease.Many neuropathological and biochemical aspects of AD are explained by AGEs, including widespread protein crosslinking, glial activation of oxidative stress, and neuronal cell death. Oxidative stress is due to different reasons and glycation end products set in motion and form or define various actions which are normally due to AGE changes in a pathogenic cascade. By regulating the transit of ß-amyloid in and out of the brain or altering inflammatory pathways, AGE and it's ensnare receptor such as soluble RAGE may function as blockage or shield AD development. RAGE activates the transcription-controlling factor Necrosis Factor (NF-κB) and increases the protraction of cytokines, like a higher number of Tumor Necrosis Factor (TNF-α) and Interleukin (IL-I) by inducing several signal transduction cascades. Furthermore, binding to RAGE can pro-activate reactive oxygen species (ROS), which is popularly known to cause neuronal death.

Detection of IDH1 Mutation in cfDNA and Tissue of Adult Diffuse Glioma with Allele-Specific qPCR.

BACKGROUND: The World Health Organization (WHO) classification of central nervous system (CNS) tumors necessitates testing of isocitrate dehydrogenase (IDH) 1/2 gene mutation in patients with adult-type diffuse glioma (ADG) for better disease management. In clinical practice, the testing of IDH1 is primarily achieved using immunohistochemistry (IHC) specific to IDH1-R132, which carries a sensitivity of 80% and specificity of 100%. However, in some cases, non-specific background staining or regional heterogeneity in the protein expression of IDH1 may necessitate confirmatory genetic analysis. Robust and reliable assays are needed for IDH1/2 mutation testing. The aim of the current study was to detect IDH1 mutation in cfDNA and tissue of adult-type diffuse glioma with allele-specific qPCR. MATERIALS AND METHODS: In the current study, IDH1-R132H mutation was analyzed in tumor tissue with paired cell-free DNA (cfDNA) in patients with ADG (n = 45) using IHC and competitive allele-specific Taqman PCR (CAST-PCR). Genomic DNA was extracted from formalin-fixed paraffin-embedded (FFPE) tissue and matched serum for cfDNA using commercially available kits. CAST-PCR with IHC for the detection of IDH1-R132H mutation was also compared. RESULTS: The IDH1-R132H mutation was detected in 46.67% (21/45) cases and 57.78% (26/45) cases using IHC and allele-specific CAST-PCR. In cfDNA of matched IDH1-mutant FFPE tissue DNA, IDH1-R132H mutation was detected in 11.54% (3/26) using CAST-PCR. The concordance rate for IDH1-R132Hmutation between IHC and CAST-PCR was 80.77% (21/26). CONCLUSION: The CAST-PCR assay is more precise and sensitive for  IDH1-R132Hdetection than traditional IHC, and IDH1-R132H mutation detection using cfDNA may add to the current methods of glioma genomic characterization.

Repurposing of Drugs for Cardiometabolic Disorders: An Out and Out Cumulation.

Cardiometabolic disorders (CMD) is a constellation of metabolic predisposing factors for atherosclerosis such as insulin resistance (IR) or diabetes mellitus (DM), systemic hypertension, central obesity, and dyslipidemia. Cardiometabolic diseases (CMDs) continue to be the leading cause of mortality in both developed and developing nations, accounting for over 32% of all fatalities globally each year. Furthermore, dyslipidemia, angina, arrhythmia, heart failure, myocardial infarction (MI), and diabetes mellitus are the major causes of death, accounting for an estimated 19 million deaths in 2012. CVDs will kill more than 23 million individuals each year by 2030. Nonetheless, new drug development (NDD) in CMDs has been increasingly difficult in recent decades due to increased costs and a lower success rate. Drug repositioning in CMDs looks promising in this scenario for launching current medicines for new therapeutic indications. Repositioning is an ancient method that dates back to the 1960s and is mostly based on coincidental findings during medication trials. One significant advantage of repositioning is that the drug's safety profile is well known, lowering the odds of failure owing to undesirable toxic effects. Furthermore, repositioning takes less time and money than NDD. Given these facts, pharmaceutical corporations are becoming more interested in medication repositioning. In this follow-up, we discussed the notion of repositioning and provided some examples of repositioned medications in cardiometabolic disorders.

Dynamics of cell-free DNA in predicting response in adult diffuse glioma on chemoradiotherapy.

BACKGROUND: Adult diffuse glioma (ADG) is a heterogeneous primary brain tumor with a variable prognosis and treatment response. Tissue biomarkers and molecular genetic profiling form an integral part of diagnosis and prognostication. However, obtaining tissue in inoperable locations and diagnosis of recurrence can be an issue. Cell-free DNA (cfDNA) may help to meet these challenges in the management of ADG. OBJECTIVES: The study aimed to serially quantify cfDNA in ADG on chemoradiation and to correlate mutational profiling of the cfDNA with biopsy. MATERIAL AND METHODS: The study group comprised of histopathological confirmed ADG (n = 50), including grade II, III and IV glioma, and controls (n = 25). Serum cfDNA was extracted using ChargeSwitch gDNA 1 mL Serum Kit (Invitrogen, USA) and quantified using SYBR based quantitative polymerase chain reaction (qPCR). Next-generation sequencing (NGS) was performed in 07 pre-operative and 05 post-operative cfDNA and tumor biopsy DNA on an Ion personal genome machine (IonPGM) with an in-house designed NGS panel (including TP53, ATRX, and IDH1 and IDH2). RESULTS: In patients with ADG, the pre-radiotherapy cfDNA level was significantly higher (Median; 113.46 ng/mL) than normal controls (Median; 74.37 ng/mL), (p = 0.048). Non-responders had significantly higher cfDNA levels (Median; 184.4 ng/mL), than responders (Median; 68.12 ng/mL), (p = 0.023). TP53 gene mutation was most common in both pre-operative and post-operative cfDNA samples. CONCLUSION: Pre-radiotherapy cfDNA levels are associated with clinical outcomes independent of other prognostic factors. Targeted NGS in pre-operative cfDNA matches the results of IHC analysis with high concordance, and it may be helpful in inoperable cases or ADG recurrence.

Effectual Endeavors of Silk Protein Sericin against Isoproterenol Induced Cardiac Toxicity and Hypertrophy in Wistar Rats.

The silkworm cocoon has been used in the treatment of various ailments in different Asian countries. This research was designed to evaluate the effect of sericin on myocardial necrosis and hypertrophy in isoproterenol-challenged rats. The rats were administered with sericin (500 and 1000 mg/kg, p.o.) for 28 days, followed by administration of isoprenaline (85 mg/kg, s.c.) on the 29th and 30th days. The cardioprotective activity was assessed by various physical, enzymatic, and histopathological parameters along with apoptotic marker expression. The cardioprotective effect showed that pre-treatment of rats with sericin significantly increased the non-enzymatic antioxidants marker in serum and heart tissue (glutathione, vitamin E, and vitamin C). The results were the same in enzymatic antioxidant marker, mitochondrial enzymes, and protein. The grading of heart, heart/body weight ratio, gross morphology, cardiac markers, oxidative stress markers in serum and heart tissue, glucose, serum lipid profiling and Lysosomal hydrolases, heart apoptotic markers such as MHC expression by western blot, apoptosis by flow cytometry, total myocardial collagen content, fibrosis estimation, myocyte size were significantly decreased when compared with isoproterenol (ISG) group however histopathological studies showed normal architecture of heart in both control and treated rats. The pharmacological study reflects that sericin on both doses i.e., 500 mg/kg and 1000 mg/kg have potent cardioprotective action against the experimental model which was confirmed by various physical, biochemical, and histopathological parameters evaluated further research is required to examine the molecular mechanism of cardioprotective effect of sericin.

An in-Depth Analysis of Ovarian Cancer: Pathogenesis and Clinical Manifestation.

Ovarian cancer is characterized by the establishment of tolerance, the recurrence of disease, as well as a poor prognosis. Gene signatures in ovarian cancer cells enable cancer medicine research, therapy, prevention, & management problematic. Notwithstanding advances in tumor puncture surgery, novel combinations regimens, and abdominal radiation, which can provide outstanding reaction times, the bulk of gynecological tumor patients suffer from side effects & relapse. As a consequence, more therapy alternatives for individuals with ovarian cancer must always be studied to minimize side effects and improve progression-free and total response rates. The development of cancer medications is presently undergoing a renaissance in the quest for descriptive and prognostic ovarian cancer biomarkers. Nevertheless, abnormalities in the BRCA2 or BRCA1 genes, a variety of hereditary predispositions, unexplained onset and progression, molecular tumor diversity, and illness staging can all compromise the responsiveness and accuracy of such indicators. As a result, current ovarian cancer treatments must be supplemented with broad-spectrum & customized targeted therapeutic approaches. The objective of this review is to highlight recent contributions to the knowledge of the interrelations between selected ovarian tumor markers, various perception signs, and biochemical and molecular signaling processes, as well as one's interpretation of much more targeted and effective treatment interventions.

A deep neural network-based approach for prediction of mutagenicity of compounds.

We are exposed to various chemical compounds present in the environment, cosmetics, and drugs almost every day. Mutagenicity is a valuable property that plays a significant role in establishing a chemical compound's safety. Exposure and handling of mutagenic chemicals in the environment pose a high health risk; therefore, identification and screening of these chemicals are essential. Considering the time constraints and the pressure to avoid laboratory animals' use, the shift to alternative methodologies that can establish a rapid and cost-effective detection without undue over-conservation seems critical. In this regard, computational detection and identification of the mutagens in environmental samples like drugs, pesticides, dyes, reagents, wastewater, cosmetics, and other substances is vital. From the last two decades, there have been numerous efforts to develop the prediction models for mutagenicity, and by far, machine learning methods have demonstrated some noteworthy performance and reliability. However, the accuracy of such prediction models has always been one of the major concerns for the researchers working in this area. The mutagenicity prediction models were developed using deep neural network (DNN), support vector machine, k-nearest neighbor, and random forest. The developed classifiers were based on 3039 compounds and validated on 1014 compounds; each of them encoded with 1597 molecular feature vectors. DNN-based prediction model yielded highest prediction accuracy of 92.95% and 83.81% with the training and test data, respectively. The area under the receiver's operating curve and precision-recall curve values were found to be 0.894 and 0.838, respectively. The DNN-based classifier not only fits the data with better performance as compared to traditional machine learning algorithms, viz., support vector machine, k-nearest neighbor, and random forest (with and without feature reduction) but also yields better performance metrics. In current work, we propose a DNN-based model to predict mutagenicity of compounds.

Hydroxychloroquine in COVID-19: therapeutic promises, current status, and environmental implications.

The outbreak of novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected the entire world with its infectious spread and mortality rate. The severe cases of coronavirus disease 2019 (COVID-19) are characterized by hypoxia and acute respiratory distress syndrome. In the absence of any specific treatment, just the preventive and supportive care options are available. Therefore, much focus is given to assess the available therapeutic options not only to avoid acute respiratory failure and hypoxia but also to reduce the viral load to control the severity of the disease. The antimalarial drug hydroxychloroquine (HCQ) is among the much-discussed drugs for the treatment and management of COVID-19 patients. This article reviews the therapeutic potential of HCQ in the treatment of COVID-19 based on the available in vitro and clinical evidence, current status of registered HCQ-based clinical trials investigating therapeutic options for COVID-19, and environmental implications of HCQ.

Available Compounds With Therapeutic Potential Against COVID-19: Antimicrobial Therapies, Supportive Care, and Probable Vaccines.

The recent outbreak of the COVID-2019 (coronavirus disease 2019) due to the infectious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has realized the requirement of alternative therapeutics to mitigate and alleviate this lethal infection. These alternative therapies are effective when they are started at the initial stage of the infection. Some drugs that were used in previous other related infections SARS-CoV-2003 and Middle East respiratory syndrome coronavirus (MERS-CoV)-2012 could be potentially active against currently emerging SARS-CoV-2. This fact imparts some rationale of current interventions, in the absence of any specific therapeutics for SARS-CoV-2. It is imperative to focus on the available antimicrobial and adjunct therapies during the current emergency state and overcome the challenges associated with the absence of robust controlled studies. There is no established set of drugs to manage SARS-CoV-2 infected patients. However, closely following patients' conditions and responding with the dosage guidelines of available drugs may significantly impact our ability to slow down the infection. Of note, it depends upon the condition of the patients and associated comorbid; therefore, the health workers need to choose the drug combinations judiciously until COVID-19 specific drug or vaccine is developed with the collective scientific rigor. In this article, we reviewed the available antimicrobial drug, supportive therapies, and probable high importance vaccines for the COVID-19 treatment.

Metabolomics: An emerging potential approach to decipher critical illnesses.

Critical illnesses contribute to the maximum morbidity and mortality of hospitalized patients. Acute respiratory distress syndrome (ARDS) and sepsis/septic shock are the two most common acute illnesses associated with intensive care unit (ICU) admission. Once triggered, both have an identical underlying mechanism, portrayed by inflammation and endothelial dysfunction. The diagnosis of ARDS is based on clinical findings, laboratory tests, and radiological imaging. Blood cultures remain the gold standard for the diagnosis of sepsis, with the limitation of time delay and low positive yield. A combination of biomarkers has been proposed to diagnose and prognosticate these acute disorders with strengths and limitations, but still, the gold standard has been elusive to clinicians. In this review article, we illustrate the potential of metabolomics to unravel biomarkers that can be clinically utilized as a rapid prognostic and diagnostic tool associated with specific patient populations (ARDS and sepsis/septic shock) based on the available scientific data.

Diligent profiling of preclinical safety of the silk protein sericin.

BACKGROUND: Sericin is a widely used protein in the pharmaceutical industry derived from the silkworm, Bombyx mori, and used for the treatment of various diseases and pathological conditions. It is the main ingredient of the Unani preparation khameera abresham. The study was conducted to evaluate the preclinical toxicity of the silk protein sericin in mice. METHODS: In the acute toxicity study, sericin was administered once orally to different groups of animals at doses of 500, 1000, and 2000 mg/kg. Animals were observed for 14 days. In the sub-acute toxicity study, sericin was administered in mice for 4 weeks in the toxic group at doses of 500, 1000, and 2000 mg/kg, while in the recovery group it was administered for 4 weeks at doses of 500 and 2000 mg/kg followed by 2 weeks of distilled water administration. RESULTS: In the acute toxicity study, the observed parameters showed no significant difference, and no mortality was reported. In the sub-acute toxicity study, there were no toxicological effects in any of the estimated parameters, while histopathological analysis showed inflammation in vital organs at the dose of 2000 mg/kg. CONCLUSIONS: Results of our acute toxicity study suggest that sericin is safe at all administered doses, while the sub-acute study suggests that the NOAEL (no-observed-adverse-effect level) of sericin is below 2000 mg/kg, at which it can be considered safe.

A conglomeration of preclinical models related to myocardial infarction

Cardiovascular diseases are the main source of death and morbidity in developed and developing nations. Animal models are required to propel our understanding of the pathogenesis, increase our knowledge, disease progress, and mechanism behind cardiovascular disorder, providing new approaches focused to improve the diagnostic and the treatment of these pathological conditions and additionally to test various therapeutic ways to deal with tissue regeneration and re-establish heart working following damage. A perfect model framework ought to be reasonable, effectively controlled, reproducible, and physiologically illustrative of human disease, show cardinal signs and pathology that resembles after the human ailment and ethically stable. The decision of selection of animal model should be considered precisely since it influences exploratory results and whether results of the research can be sensibly matched with the human. In this way, no specific technique splendidly reproduces the human disease, and relying upon the model, extra cost burden, resources, infrastructure and the necessity for technical hands, should also be kept under consideration. Here we have discussed and compiled various methods of inducing myocardial infarction in animals, basically by surgery, chemicals and through genetic modification, this may benefit the researchers in getting a complied data regarding various methods through which they can induce myocardial infarction in animals.

Post-periodontal surgery propounds early repair salivary biomarkers by 1H NMR based metabolomics.

INTRODUCTION: Oral microflora is a well-orchestrated and acts as a sequential defense mechanism for any infection related to oral disease. Chronic periodontitis is a disease of a microbial challenge to symbiosis and homeostasis. Periodontal surgery is the most promising cure with repair process during periodontal regeneration. It has an encouraging outcome in terms of early recovery biomarkers. OBJECTIVE: Saliva of periodontal surgery subjects with the chronic periodontitis have been evaluated by 1H NMR spectroscopy in search of possible early metabolic differences that could be obtained in order to see the eradication of disease which favours the symbiotic condition. METHOD: The study employed 1H NMR spectroscopy on 176 human saliva samples in search of distinctive differences and their spectral data were further subjected to multivariate and quantitative analysis. RESULT: The 1H NMR study of periodontal surgery samples shows clear demarcation and profound metabolic differences when compared with the diseased condition. Several metabolites such as lactate, ethanol, succinate, and glutamate were found to be of higher significance in periodontal surgery in contrast to chronic periodontitis subjects. The PLS-DA model of the studied group resulted in R2 of 0.83 and Q2 of 0.70. CONCLUSION: Significant metabolites could be considered as early repair markers for chronic periodontitis disease as they are being restored to achieve symbiosis. The study, therefore, concluded the early recovery process of the diseased subjects with the restoration of possible metabolomic profile similar to the healthy controls.

In vitro studies on oxidative stress-independent, Ag nanoparticles-induced cell toxicity of Candida albicans, an opportunistic pathogen.

Silver nanoparticles (AgNps) have attracted maximal attention among all metal nanoparticles, and the study of their biological properties has gained impetus for further medical adoption. This study evaluated the cellular and molecular mechanisms associated with the action of AgNps against an opportunistic pathogen, Candida albicans. Spherical, stable AgNp (average size 21.6 nm) prepared by a chemical reduction method showed minimum inhibitory concentration (required to inhibit the growth of 90% of organisms) at 40 µg/mL. AgNps have been reported to induce oxidative stress-mediated programmed cell death through the accumulation of intracellular reactive oxygen species (ROS). However, this study demonstrated that intracellular levels of AgNp-induced ROS could be reversed by using antioxidant ascorbic acid, but the sensitivity of AgNp-treated Candida cells could not be completely reversed. Moreover, in addition to the generation of ROS, the AgNps were found to affect other cellular targets resulting in altered membrane fluidity, membrane microenvironment, ergosterol content, cellular morphology, and ultrastructure. Thus, the generation of ROS does not seem to be the sole major cause of AgNp-mediated cell toxicity in Candida. Rather, the multitargeted action of AgNps, generation of ROS, alterations in ergosterol content, and membrane fluidity together seem to have potentiated anti-Candida action. Thus, this "nano-based drug therapy" is likely to favor broad-spectrum activity, multiple cellular targets, and minimum host toxicity. AgNps, therefore, appear to have the potential to address the challenges in multidrug resistance and fungal therapeutics.

Prediction of Drug-Plasma Protein Binding Using Artificial Intelligence Based Algorithms.

AIM AND OBJECTIVE: Plasma protein binding (PPB) has vital importance in the characterization of drug distribution in the systemic circulation. Unfavorable PPB can pose a negative effect on clinical development of promising drug candidates. The drug distribution properties should be considered at the initial phases of the drug design and development. Therefore, PPB prediction models are receiving an increased attention. MATERIALS AND METHODS: In the current study, we present a systematic approach using Support vector machine, Artificial neural network, k- nearest neighbor, Probabilistic neural network, Partial least square and Linear discriminant analysis to relate various in vitro and in silico molecular descriptors to a diverse dataset of 736 drugs/drug-like compounds. RESULTS: The overall accuracy of Support vector machine with Radial basis function kernel came out to be comparatively better than the rest of the applied algorithms. The training set accuracy, validation set accuracy, precision, sensitivity, specificity and F1 score for the Suprort vector machine was found to be 89.73%, 89.97%, 92.56%, 87.26%, 91.97% and 0.898, respectively. CONCLUSION: This model can potentially be useful in screening of relevant drug candidates at the preliminary stages of drug design and development.