Chimeric oncolytic adenovirus evades neutralizing antibodies from human patients and exhibits enhanced anti-glioma efficacy in immunized mice.

Oncolytic viruses are a promising treatment for patients with high-grade gliomas, but neutralizing antibodies can limit their efficacy in patients with prior virus exposure or upon repeated virus injections. Data from a previous clinical trial using the oncolytic adenovirus Delta-24-RGD showed that generation of anti-viral neutralizing antibodies may affect the long-term survival of glioma patients. Past studies have examined the effects of neutralizing antibodies during systemic virus injections, but largely overlooked their impact during local virus injections into the brain. We found that immunoglobulins colocalized with viral proteins upon local oncolytic virotherapy of brain tumors, warranting a strategy to prevent virus neutralization and maximize oncolysis. Thus, we generated a chimeric virus, Delta-24-RGD-H43m, by replacing the capsid protein HVRs from the serotype 5-based Delta-24-RGD with those from the rare serotype 43. Delta-24-RGD-H43m evaded neutralizing anti-Ad5 antibodies and conferred a higher rate of long-term survival than Delta-24-RGD in glioma-bearing mice. Importantly, Delta-24-RGD-H43m activity was significantly more resistant to neutralizing antibodies present in sera of glioma patients treated with Delta-24-RGD during a phase 1 clinical trial. These findings provide a framework for a novel treatment of glioma patients that have developed immunity against Delta-24-RGD.

Omadacycline pharmacokinetics/pharmacodynamics and efficacy against multidrug-resistant Mycobacterium tuberculosis in the hollow fiber system model.

Seventy-five years ago, first-generation tetracyclines demonstrated limited efficacy in the treatment of tuberculosis but were more toxic than efficacious. We performed a series of pharmacokinetic/pharmacodynamic (PK/PD) experiments with a potentially safer third-generation tetracycline, omadacycline, for the treatment of multidrug-resistant tuberculosis (MDR-TB). Mycobacterium tuberculosis (Mtb) H37Rv and an MDR-TB clinical strain (16D) were used in the minimum inhibitory concentration (MIC) and static concentration-response studies in test tubes, followed by a PK/PD study using the hollow fiber system model of TB (HFS-TB) that examined six human-like omadacycline doses. The inhibitory sigmoid maximal effect (Emax) model and Monte Carlo experiments (MCEs) were used for data analysis and clinical dose-finding, respectively. The omadacycline MIC for both Mtb H37Rv and MDR-TB clinical strain was 16 mg/L but dropped to 4 mg/L with daily drug supplementation to account for omadacycline degradation. The Mycobacteria Growth Indicator Tube MIC was 2 mg/L. In the test tubes, omadacycline killed 4.39 log10 CFU/mL in 7 days. On Day 28 of the HFS-TB study, the Emax was 4.64 log10 CFU/mL, while exposure mediating 50% of Emax (EC50) was an area under the concentration-time curve to MIC (AUC0-24/MIC) ratio of 22.86. This translates to PK/PD optimal exposure or EC80 as AUC0-24/MIC of 26.93. The target attainment probability of the 300-mg daily oral dose was 90% but fell at MIC ≧4 mg/L. Omadacycline demonstrated efficacy and potency against both drug-susceptible and MDR-TB. Further studies are needed to identify the omadacycline effect in combination therapy for the treatment of both drug-susceptible and MDR-TB.

Cholinergic signaling via the α7 nicotinic acetylcholine receptor regulates the migration of monocyte-derived macrophages during acute inflammation.

BACKGROUND: The involvement of the autonomic nervous system in the regulation of inflammation is an emerging concept with significant potential for clinical applications. Recent studies demonstrate that stimulating the vagus nerve activates the cholinergic anti-inflammatory pathway that inhibits pro-inflammatory cytokines and controls inflammation. The α7 nicotinic acetylcholine receptor (α7nAChR) on macrophages plays a key role in mediating cholinergic anti-inflammatory effects through a downstream intracellular mechanism involving inhibition of NF-κB signaling, which results in suppression of pro-inflammatory cytokine production. However, the role of the α7nAChR in the regulation of other aspects of the immune response, including the recruitment of monocytes/macrophages to the site of inflammation remained poorly understood. RESULTS: We observed an increased mortality in α7nAChR-deficient mice (compared with wild-type controls) in mice with endotoxemia, which was paralleled with a significant reduction in the number of monocyte-derived macrophages in the lungs. Corroborating these results, fluorescently labeled α7nAChR-deficient monocytes adoptively transferred to WT mice showed significantly diminished recruitment to the inflamed tissue. α7nAChR deficiency did not affect monocyte 2D transmigration across an endothelial monolayer, but it significantly decreased the migration of macrophages in a 3D fibrin matrix. In vitro analysis of major adhesive receptors (L-selectin, ß1 and ß2 integrins) and chemokine receptors (CCR2 and CCR5) revealed reduced expression of integrin αM and αX on α7nAChR-deficient macrophages. Decreased expression of αMß2 was confirmed on fluorescently labeled, adoptively transferred α7nAChR-deficient macrophages in the lungs of endotoxemic mice, indicating a potential mechanism for α7nAChR-mediated migration. CONCLUSIONS: We demonstrate a novel role for the α7nAChR in mediating macrophage recruitment to inflamed tissue, which indicates an important new aspect of the cholinergic regulation of immune responses and inflammation.

Sarecycline pharmacokinetics/pharmacodynamics in the hollow-fibre model of Mycobacterium avium complex: so near and yet so far.

BACKGROUND: Poor sustained sputum culture conversion rates with the standard-of-care therapy highlight the need for better drugs to treat Mycobacterium avium complex pulmonary disease (MAC-PD). OBJECTIVE: To determine the pharmacokinetics/pharmacodynamics (PK/PD)-optimized exposure of sarecycline and its potential role in treating MAC-PD. METHODS: We performed MIC studies with MAC ATCC 700898 and 19 clinical isolates and test-tube static concentration-response studies. A dynamic hollow-fibre system model of intracellular MAC (HFS-MAC) study was performed mimicking six human-equivalent sarecycline dose concentration-time profiles to identify the PK/PD optimal exposure of sarecycline for MAC kill. The inhibitory sigmoid maximal effect (Emax) model was used for PK/PD analysis. RESULTS: The sarecycline MIC of MAC ATCC 700898 was 1 mg/L, while the MIC for the 19 clinical strains ranged between 32 and >256 mg/L. The concentration mediating 50% of Emax (EC50) was similar between intracellular and extracellular MAC. In the HFS-MAC, all six sarecycline doses killed intracellular MAC, with an Emax of 1.0 log10 cfu/mL below Day 0 burden (stasis). The sarecycline EC80 (optimal) exposure was identified as AUC0-24/MIC = 139.46. CONCLUSIONS: Sarecycline demonstrated anti-MAC Emax in the HFS-MAC model better than ethambutol but worse than omadacycline (>5 log10 cfu/mL below stasis) in HFS-MAC. However, since currently approved highest oral sarecycline dose achieves an AUC0-24 of 48.2 mg·h/L and MAC MICs are >32 mg/L, the target AUC0-24/MIC of 139.46 is unlikely to be achieved in patients.

Accelerating the discovery of antifungal peptides using deep temporal convolutional networks.

The application of machine intelligence in biological sciences has led to the development of several automated tools, thus enabling rapid drug discovery. Adding to this development is the ongoing COVID-19 pandemic, due to which researchers working in the field of artificial intelligence have acquired an active interest in finding machine learning-guided solutions for diseases like mucormycosis, which has emerged as an important post-COVID-19 fungal complication, especially in immunocompromised patients. On these lines, we have proposed a temporal convolutional network-based binary classification approach to discover new antifungal molecules in the proteome of plants and animals to accelerate the development of antifungal medications. Although these biomolecules, known as antifungal peptides (AFPs), are part of an organism's intrinsic host defense mechanism, their identification and discovery by traditional biochemical procedures is arduous. Also, the absence of a large dataset on AFPs is also a considerable impediment in building a robust automated classifier. To this end, we have employed the transfer learning technique to pre-train our model on antibacterial peptides. Subsequently, we have built a classifier that predicts AFPs with accuracy and precision of 94%. Our classifier outperforms several state-of-the-art models by a considerable margin. The results of its performance were proven as statistically significant using the Kruskal-Wallis H test, followed by a post hoc analysis performed using the Tukey honestly significant difference (HSD) test. Furthermore, we identified potent AFPs in representative animal (Histatin) and plant (Snakin) proteins using our model. We also built and deployed a web app that is freely available at https://tcn-afppred.anvil.app/ for the identification of AFPs in protein sequences.

Deep-AFPpred: identifying novel antifungal peptides using pretrained embeddings from seq2vec with 1DCNN-BiLSTM.

Fungal infections or mycosis cause a wide range of diseases in humans and animals. The incidences of community acquired; nosocomial fungal infections have increased dramatically after the emergence of COVID-19 pandemic. The increase in number of patients with immunodeficiency / immunosuppression related diseases, resistance to existing antifungal compounds and availability of limited therapeutic options has triggered the search for alternative antifungal molecules. In this direction, antifungal peptides (AFPs) have received a lot of interest as an alternative to currently available antifungal drugs. Although the AFPs are produced by diverse population of living organisms, identifying effective AFPs from natural sources is time-consuming and expensive. Therefore, there is a need to develop a robust in silico model capable of identifying novel AFPs in protein sequences. In this paper, we propose Deep-AFPpred, a deep learning classifier that can identify AFPs in protein sequences. We developed Deep-AFPpred using the concept of transfer learning with 1DCNN-BiLSTM deep learning algorithm. The findings reveal that Deep-AFPpred beats other state-of-the-art AFP classifiers by a wide margin and achieved approximately 96% and 94% precision on validation and test data, respectively. Based on the proposed approach, an online prediction server is created and made publicly available at https://afppred.anvil.app/. Using this server, one can identify novel AFPs in protein sequences and the results are provided as a report that includes predicted peptides, their physicochemical properties and motifs. By utilizing this model, we identified AFPs in different proteins, which can be chemically synthesized in lab and experimentally validated for their antifungal activity.

StaBle-ABPpred: a stacked ensemble predictor based on biLSTM and attention mechanism for accelerated discovery of antibacterial peptides.

Due to the rapid emergence of multi-drug resistant (MDR) bacteria, existing antibiotics are becoming ineffective. So, researchers are looking for alternatives in the form of antibacterial peptides (ABPs) based medicines. The discovery of novel ABPs using wet-lab experiments is time-consuming and expensive. Many machine learning models have been proposed to search for new ABPs, but there is still scope to develop a robust model that has high accuracy and precision. In this work, we present StaBle-ABPpred, a stacked ensemble technique-based deep learning classifier that uses bidirectional long-short term memory (biLSTM) and attention mechanism at base-level and an ensemble of random forest, gradient boosting and logistic regression at meta-level to classify peptides as antibacterial or otherwise. The performance of our model has been compared with several state-of-the-art classifiers, and results were subjected to analysis of variance (ANOVA) test and its post hoc analysis, which proves that our model performs better than existing classifiers. Furthermore, a web app has been developed and deployed at https://stable-abppred.anvil.app to identify novel ABPs in protein sequences. Using this app, we identified novel ABPs in all the proteins of the Streptococcus phage T12 genome. These ABPs have shown amino acid similarities with experimentally tested antimicrobial peptides (AMPs) of other organisms. Hence, they could be chemically synthesized and experimentally validated for their activity against different bacteria. The model and app developed in this work can be further utilized to explore the protein diversity for identifying novel ABPs with broad-spectrum activity, especially against MDR bacterial pathogens.

BICAAC-Derived Covalent and Cationic Ir(I) Complexes: Application of Ir(BICAAC)Cl(COD) Complexes as Catalysts for Transfer Hydrogenation and Hydrosilylation Reactions.

The ambiphilic bicyclic (alkyl)(amino)carbenes (Me/iPrBICAAC) upon reaction with [IrCl(COD)]2 smoothly afford mononuclear Ir(I) complexes that have been spectroscopically and structurally characterized. These complexes exhibit good catalytic activity for transfer hydrogenation (TH) of 4-chlorobenzaldehyde using isopropyl alcohol (iPrOH), with turnover frequency values ranging between 6269 and 8093 h-1. Choosing the covalent complex Ir(MeBICAAC)Cl(COD) as a catalyst, a wide array of carbonyls and imines functionalized with electron-withdrawing and electron-donating substituents have been surveyed and afforded their reduced products in moderate-to-good yields. No detachment of the BICAAC unit from the Ir center was observed upon prolonged heating of Ir(MeBICAAC)Cl(COD) in toluene-d8 or isopropyl alcohol-d8, which evidenced good thermal stability of the catalyst. Complex Ir(MeBICAAC)Cl(COD) was also found to be catalytically active for the hydrosilylation of a variety of aldehydes using triethylsilane (Et3SiH).

Peritoneal dialysis-associated peritonitis: A case first for Aquamicrobium.

Aquamicrobium is an aerobic gram-negative rod which until recently had only been isolated from wastewater and contaminated soil. In 2021, two cases of Aquamicrobium infection in humans were reported. Both were cases of endophthalmitis following cataract surgery. In this manuscript, we describe the presentation and treatment of a 56-year-old immunocompetent male who has peritoneal dialysis-associated peritonitis caused by Aquamicrobium lusatiense. To our knowledge, this is the third reported case of Aquamicrobium infection in humans and the first example of this agent causing peritonitis.

Kisspeptin stimulates oestradiol biosynthesis by upregulating steroidogenic transcripts and proliferation markers in the bubaline granulosa cells in vitro.

Kisspeptin (Kp), an upstream regulator of GnRH release, is essential for the development and function of reproductive axis. Previously, we demonstrated the localization of Kp and its receptor (Kiss1r) in the active follicle in the bubaline ovary. Present study aimed to determine the effect of Kp on granulosa cell (GCs) functions, especially oestradiol (E2 ) and progesterone (P4 ) production, and differential expression of genes regulating the proliferation, apoptosis and steroidogenesis in the buffalo. The ovaries with 6-10 mm size follicles obtained from the cyclic buffaloes after slaughtering were used for isolation of GCs for in vitro study. The primary GCs culture was treated with Kp (0, 10, 50 and 100 nM) and incubated for 48 h. Production of E2 and P4 was estimated in the culture supernatant by ELISA. The expression of gonadotropin receptors (FSHR and LHR), steroidogenic genes (STAR, 3ß-HSD, CYP19A1), proliferation marker (PCNA), apoptotic factors (CASP3 and BCL2) and Kp signalling molecule (extracellular signal-regulated kinase 1/2, ERK1/2 and p-ERK1/2) was studied in the GCs by qPCR. Significant E2 production was found in the Kp 50 and 100 nM groups (p < .05), whereas P4 production was reduced in Kp 100 nM group (p < .05). There was concomitant upregulation of FSHR, ERK1/2, STAR and CYP19A1 in the Kp 100 nM treated GCs. In addition, Kp at 100 nM stimulated the proliferation of GCs by upregulating the expression of BCL2 (5.0 fold) and PCNA (94.9 fold). Further, high immunoreactivity of p-ERK1/2 was observed in the Kp-treated GCs. It was concluded that Kp at 100 nM concentration stimulated E2 production by upregulating the steroidogenic pathway through ERK1/2, STAR and CYP19A1 and modulating PCNA and BCL2 expressions in the GCs. Further experiments are warranted using Kp antagonist in different combinations to establish the signalling pathway in Kp-mediated steroidogenesis in the GCs for developing strategies to control ovarian functions.

A Quality by Design Approach for Developing SNEDDS Loaded with Vemurafenib for Enhanced Oral Bioavailability.

Vemurafenib (VMF) is a practically insoluble (< 0.1 µg/mL) and least bioavailable (1%) drug. To enhance its oral bioavailability and solubility, we formulated a reliable self-nano emulsifying drug delivery system (SNEDDS). A Quality by Design (QbD) approach was used to optimize the ratio of Capryol 90, Tween 80, and Transcutol HP. VMF-loaded SNEDDS was characterized for its size, polydispersity index (PDI), zeta potential, drug content, and transmittance. The in vitro release profile of the drug loaded in SNEDDS was compared to the free drug in two media, pH 6.8 and 1.2, and the data obtained were analyzed with different mathematical models. A reverse-phase ultra-pressure liquid chromatography (UPLC) technique with high sensitivity and selectivity was developed and validated for the quantification of VMF in analytical and bioanalytical samples. Dissolution efficiency for SNEDDS was estimated using different models, which proved that the developed novel SNEDDS formulation had a better in vitro dissolution profile than the free drug. A 2.13-fold enhanced oral bioavailability of VMF-loaded SNEDDS compared to the free drug demonstrates the superiority of the developed formulation. This work thus presents an overview of VMF-loaded SNEDDS as a promising alternative to improve the oral bioavailability of the drug.

Bistable Aryl Azopyrazolium Ionic Photoswitches in Water.

We report a new class of arylazopyrazolium-based ionic photoswitches (AAPIPs). These AAPIPs with different counter ions have been accessed through a modular synthetic approach in high yields. More importantly, the AAPIPs exhibit excellent reversible photoswitching and exceptional thermal stability in water. The effects of solvents, counter ions, substitutions, concentration, pH, and glutathione (GSH) have been evaluated using spectroscopic investigations. The results revealed that the bistability of studied AAPIPs is robust and near quantitative. The thermal half-life of Z isomers is extremely high in water (up to years), and it can be lowered electronically by the electron-withdrawing groups or highly basic pH.

AniAMPpred: artificial intelligence guided discovery of novel antimicrobial peptides in animal kingdom.

With advancements in genomics, there has been substantial reduction in the cost and time of genome sequencing and has resulted in lot of data in genome databases. Antimicrobial host defense proteins provide protection against invading microbes. But confirming the antimicrobial function of host proteins by wet-lab experiments is expensive and time consuming. Therefore, there is a need to develop an in silico tool to identify the antimicrobial function of proteins. In the current study, we developed a model AniAMPpred by considering all the available antimicrobial peptides (AMPs) of length $\in $[10 200] from the animal kingdom. The model utilizes a support vector machine algorithm with deep learning-based features and identifies probable antimicrobial proteins (PAPs) in the genome of animals. The results show that our proposed model outperforms other state-of-the-art classifiers, has very high confidence in its predictions, is not biased and can classify both AMPs and non-AMPs for a diverse peptide length with high accuracy. By utilizing AniAMPpred, we identified 436 PAPs in the genome of Helobdella robusta. To further confirm the functional activity of PAPs, we performed BLAST analysis against known AMPs. On detailed analysis of five selected PAPs, we could observe their similarity with antimicrobial proteins of several animal species. Thus, our proposed model can help the researchers identify PAPs in the genome of animals and provide insight into the functional identity of different proteins. An online prediction server is also developed based on the proposed approach, which is freely accessible at https://aniamppred.anvil.app/.

Deep-ABPpred: identifying antibacterial peptides in protein sequences using bidirectional LSTM with word2vec.

The overuse of antibiotics has led to emergence of antimicrobial resistance, and as a result, antibacterial peptides (ABPs) are receiving significant attention as an alternative. Identification of effective ABPs in lab from natural sources is a cost-intensive and time-consuming process. Therefore, there is a need for the development of in silico models, which can identify novel ABPs in protein sequences for chemical synthesis and testing. In this study, we propose a deep learning classifier named Deep-ABPpred that can identify ABPs in protein sequences. We developed Deep-ABPpred using bidirectional long short-term memory algorithm with amino acid level features from word2vec. The results show that Deep-ABPpred outperforms other state-of-the-art ABP classifiers on both test and independent datasets. Our proposed model achieved the precision of approximately 97 and 94% on test dataset and independent dataset, respectively. The high precision suggests applicability of Deep-ABPpred in proposing novel ABPs for synthesis and experimentation. By utilizing Deep-ABPpred, we identified ABPs in the tail protein sequences of Streptococcus bacteriophages, chemically synthesized identified peptides in lab and tested their activity in vitro. These ABPs showed potent antibacterial activity against selected Gram-positive and Gram-negative bacteria, which confirms the capability of Deep-ABPpred in identifying novel ABPs in protein sequences. Based on the proposed approach, an online prediction server is also developed, which is freely accessible at https://abppred.anvil.app/. This web server takes the protein sequence as input and provides ABPs with high probability (>0.95) as output.

Highly Electrophilic Mononuclear Cationic Aluminium Alkoxide Complexes: Syntheses, Reactivity and Catalytic Applications.

Herein, we report the synthesis of ß-diketiminate-supported aluminium complexes bearing terminal alkoxide and mono-thiol functional groups: LAlOMe(Et) (2), LAlOtBu(Et) (3), and LAlSH(Et) (4), (L=[HC{C(Me)N-(2,6-iPr2 C6 H3 )}2 ]). Complexes 2 and 3 are further used as synthons to generate the fascinating cationic aluminium alkoxide complexes, [LAlOMe(µ-OMe)-Al(Et)L][EtB(C6 F5 )3 ] (5), [LAlOMe(OEt2 )][EtB(C6 F5 )3 ] (6), and [LAlOtBu(OEt2 )][EtB(C6 F5 )3 ] (8). These electrophilic cationic species are well characterized by spectroscopic and crystallographic techniques. The assessment of Lewis acidity by the Gutmann-Beckett method revealed superior Lewis acidity of the cations substituted with electron-demanding alkoxy groups in comparison to the known methyl analogue [LAlMe][B(C6 F5 )4 ]. This has been further endorsed by computational calculations to determine the NBO charges and hydride ion affinity for complexes 6 and 8. These complexes are also capable of activating triethylsilane in stoichiometric reactions. The applicability of these complexes has been realized in the hydrosilylation of ethers, carbonyls, and olefines. Additionally, the solid-state structure of a new THF stabilized aluminium halide cation [LAlCl(THF)][B(C6 F5 )4 ] (11) has also been reported.

Brønsted-Acid-Catalyzed One-Pot Synthesis of ß,ß-Diaryl Esters: Direct Regioselective Approach to Diverse Arrays of 3-Aryl-1-indanone Cores.

A three-component, solvent-dependent, Brønsted-acid-catalyzed reaction of benzaldehydes, silyl enolates and arene nucleophiles has been developed for the synthesis of potential drug candidate 3-aryl-1-indanones. This reaction features the formation of three C-C bonds, high regioselectivity in a one-pot strategy, broad substrate generality, facile scalability (1.04g), high functional group tolerance and viable substrates. The ß-O-silyl ethers generated in-situ from the Mukaiyama aldol reaction were subjected to acid-catalyzed benzylic arylation with strong as well as weak nucleophiles, and the resultant ß,ß-diaryl esters can undergo a third C-C bond formation with excellent regioselectivity through intramolecular cyclization to afford the indanone products in the same pot. Detailed mechanistic insight leads to a feasible reaction pathway. This transformation opens up a practical and adaptable approach to producing a variety of synthetically valuable transformations and enable the synthesis of medicinally valuable (R)-tolterodine and (+)-indatraline.

Cooperative Friedel-Crafts Alkylation of Electron-Deficient Arenes via Catalyst Activation with Hexafluoroisopropanol.

A Friedel-Crafts alkylation of electron-deficient arenes with aldehydes through ''catalyst activation'' is presented. Through hydrogen bonding interactions, the solvent 1,1,1,3,3,3, -hexafluoroisopropanol (HFIP) interacted with the added Brønsted acid catalyst pTSA•H2 O, increasing its acidity. This activated catalyst enabled the Friedel-Crafts alkylation of electron-neutral as well as electron-deficient arenes. Strongly electron withdrawing arenes including arenes with multiple halogen atoms, NO2 , CHO, CO2 R, and CN, groups acted as efficient nucleophiles in this reaction. DFT studies reveal multiple roles of solvent HFIP viz; increasing the Brønsted acidity of the catalyst pTSA•H2 O, and stabilization of the transition states through a concerted pathway enabling the challenging reaction.

Novel Synergistic Approach: Tazarotene-Calcipotriol-Loaded-PVA/PVP-Nanofibers Incorporated in Hydrogel Film for Management and Treatment of Psoriasis.

Psoriasis is an autoimmune skin disease that generally affects 1%-3% of the total population globally. Effective treatment of psoriasis is limited because of numerous factors, such as ineffective drug delivery and efficacy following conventional pharmaceutical treatments. Nanofibers are widely being used as nanocarriers for effective treatment because of their multifunctional and distinctive properties, including a greater surface area, higher volume ratio, increased elasticity and improved stiffness and resistance to traction, favorable biodegradability, high permeability, and sufficient oxygen supply, which help maintain the moisture content of the skin and improve the bioavailability of the drugs. Similar to the extracellular matrix, nanofibers have a regeneration capacity, promoting cell growth, adhesion, and proliferation, and also have a more controlled release pattern compared with that of other conventional therapies at the psoriatic site. To ensure improved drug targeting and better antipsoriatic efficacy, this study formulated and evaluated a tazarotene (TZT)-calcipotriol (CPT)-loaded nanofiber and carbopol-based hydrogel film. The nanofiber was prepared using electrospinning with a polyvinyl alcohol/polyvinylpyrrolidone (PVA/PVP) K-90 polymeric blend that was later incorporated into a carbopol base to form hydrogel films. The prepared nanofibers were biochemically evaluated and in vitro and in vivo characterized. The mean diameters of the optimized formulation, i.e., TZT-loaded polyvinyl alcohol/polyvinylpyrrolidone nanofiber (TZT-PVA/PVP-NF) and TZT-CPT-loaded polyvinyl alcohol/polyvinylpyrrolidone nanofiber (TZT-CPT-PVA/PVP-NF) were 244.67 ± 58.11 and 252.31 ± 35.50 nm, respectively, as determined by scanning electron microscopy, and their tensile strength ranged from 14.02 ± 0.54 to 22.50 ± 0.03 MPa. X-ray diffraction revealed an increase in the amorphous nature of the nanofibers. The biodegradability studies of prepared nanofiber formulations, irrespective of their composition, showed that these completely biodegraded within 2 weeks of their application. The TZT-CPT-PVA/PVP-NF nanofibers exhibited 95.68% ± 0.03% drug release at the end of 72 h, indicating a controlled release pattern and following Higuchi release kinetics as a best-fit model. MTT assay, antioxidant and lipid profile tests, splenomegaly assessment, and weight fluctuation were all performed in the in vitro as well as in vivo studies. We found that the TZT-CPT-PVA/PVP-NF-based hydrogel film has high potential for antipsoriatic activity in imiquimod-induced Wistar rats in comparison with that of TT-PVA/PVP-NF nanofibers.

Enantioselective Distal Functionalization of 3-Cyano-4-methylcoumarins through Direct Vinylogous Conjugate Addition to Maleimides.

An unprecedented organocatalyzed asymmetric vinylogous Michael reaction between 3-cyano-4-methylcoumarins and maleimides with an excellent enantiomeric ratio (up to 99.5:0.5) and yield (up to 95%) is reported. This remarkable selectivity is attributed to the hydrogen bonding ability of l-tert-leucine-derived amine thiourea catalyst. The versatility, practical applicability, and scalability are demonstrated by the generation of γ-functionalized coumarin derivatives.

Brønsted Acid-Mediated Multicomponent One-Pot Approach to Direct Construction of 4-Aryl-hydrocoumarin Derivatives.

The facile and efficient synthesis of a unique class of 4-aryl-hydrocoumarins having enormous applications in medicinal chemistry and natural products is presented. We have for the first time developed a Brønsted acid-catalyzed, multicomponent, one-pot approach for producing various 4-aryl-coumarin derivatives. The feedstock availability of these precursors allowed access to a wide range of 2-chromanone derivatives in good to excellent yields under mild conditions. The practicality of this protocol was justified by the synthesis of bioactive compounds, late-stage functionalization of natural products, and gram-scale synthesis.