PDE5 inhibitors: breaking new grounds in the treatment of COVID-19

INTRODUCTION

Despite the ever-increasing occurrences of the coronavirus disease (COVID-19) cases around the world, very few medications have been validated in the clinical trials to combat COVID-19. Although several vaccines have been developed in the past quarter, the time elapsed between deployment and administration remains a major impediment.

CONTENT

Repurposing of pre-approved drugs, such as phosphodiesterase 5 (PDE5) inhibitors, could be a game-changer while lessening the burden on the current healthcare system. Repurposing and developing phosphodiesterase 5 (PDE5) inhibitors could extrapolate their utility to combat the SARS-CoV-2 infection, and potentially aid in the management of the symptoms associated with its newer variants such as BF.7, BQ.1, BQ.1.1, XBB.1.5, and XBB.1.16.

SUMMARY

Administration of PDE5 inhibitors via the oral and intravenous route demonstrates other potential off-label benefits, including anti-apoptotic, anti-inflammatory, antioxidant, and immunomodulatory effects, by intercepting several pathways. These effects can not only be of clinical importance in mild-to-moderate, but also moderate-to-severe SARS-CoV-2 infections. This article explores the various mechanisms by which PDE5 inhibitors alleviates the symptoms associated with COVID-19 as well as well as highlights recent studies and findings.

OUTLOOK

These benefits of PDE5 inhibitors make it a potential drug in the physicians' armamentarium in alleviating symptoms associated with SARS-CoV-2 infection. However, adequate clinical studies must be instituted to eliminate any untoward adverse events.

Network pharmacology on mechanistic role of Thymus linearis Benth. against gastrointestinal and neurological diseases

BACKGROUND

Thymus linearis Benth. (TL) is native to the Himalayas and has been used traditionally to cure various diseases. Thymus is a well-known aromatic perennial herb commonly known as Van ajwain or Himalayan Thyme. The main components of the TL essential oil are thymol, terpinene, and p-cymene. There are many biological properties that TL has been reported to exhibit, including antioxidant, analgesic, anti-inflammatory, antipyretic, antibacterial, anticancerogenic, and neuroprotective effects.

PURPOSE

In this study, the network pharmacology and molecular docking were used to explore the potential compounds of TL and their interaction mechanism toward gastrointestinal complications and neurological diseases.

METHODS

Network pharmacology was used to analyze the active compounds and protein targets of TL on gastrointestinal and neurological related diseases. Protein-protein interaction and Kyoto Encyclopaedia of Genes and Genomes analysis were used to enrich and evaluate key pathways of target proteins. To ensure the reliability of the network pharmacology prediction estimates, molecular docking was used to confirm the relationships between the core components and targets of TL.

RESULT

77 physiologically active compounds and their 717 predicted protein targets with high association to the neuroactive ligand-receptor interaction pathway were derived from TL. Beta-citronellol, piperitol, p-cymen-8-ol, and alpha-humulene were found to have a role in gastrointestinal diseases associated with neurological diseases. These compounds showed significant levels of multitargeting cluster regulatory activity. The molecular docking results showed regulatory activity of highlighted multi-targeting compounds and the highest docking energy was reported in piperitol.

CONCLUSION

The study shows that Thymus linearis Benth., a medicinal plant with traditional use, possesses valuable biologically active compounds. It emphasizes the potential of Thymus in treating gastrointestinal and neurological diseases by regulating oxidative stress pathways. This research opens up possibilities for discovering antioxidant molecules for future drug development. It is an interesting study with promising implications for further research.

Multifunctional analysis and antimicrobial activity of Adhatoda vasica: a traditional medicinal plant

OBJECTIVES

Antibiotic resistance is rising, prompting innovative strategies for eradicating the epidemic. This study investigated the antibacterial properties of the leaves of a widely used medicinal plant, Adhatoda vasica.

METHODS

The plant's polar (water, methanol) and non-polar (hexane) extracts were tested against several different bacterial strains using the disc diffusion technique.

RESULTS

In a study, it was found that the water extract had the greatest inhibitory effect on Staphylococcus simulans and Staphylococcus aureus, with minimum inhibitory concentrations of 16.444 and 19.315 g/mL, respectively. Gram-negative strains were more susceptible to plant extracts than Gram-positive strains. The phytochemical analysis indicated the presence of secondary metabolites such as alkaloids, saponins, flavonoids, tannins, and steroids, where absorbance was recorded at 415 nm. The water extract had the highest amount of phenolics, with a total phenolic content of 53.92 0.47 mg and a total flavonoid content of 7.25 0.08 mg. Results suggest that the extract may have potential therapeutic applications for antimicrobial properties.

CONCLUSIONS

The study concluded that the extract's phenolic group of secondary metabolites were responsible for its antibacterial activity. The study highlights A. vasica as a promising source for discovering new and effective antibacterial compounds.

Revisiting Licorice as a functional food in the management of neurological disorders: Bench to trend

Traditional and scientific evidence attribute numerous bioactivities of Licorice (Glycyrrhiza glabra Linn.) in aging-related disorders. In this state-of-art review, an extensive search in several databases was conducted to collect all relevant literature and comprehensively analyze Licorice's pharmacological attributes, neuroprotective properties, safety, and its mechanistic role in treating various neurological conditions. Network pharmacology was employed for the first time exploring the mechanistic role of Licorice in neurological disorders. Its neuroprotective role is attributed to phytoconstituents, including liquiritin, glycyrrhizic acid, liquiritigenin, glabridin, 18ß-glycyrrhetinic acid, quercetin, isoliquiritigenin, paratocarpin B, glycyglabrone, and hispaglabridin B, as evident from in vitro and in vivo studies. Network pharmacology analysis reveals that these compounds protect against long-term depression, aging-associated diseases, Alzheimer's disease, and other addictions through interactions with cholinergic, dopaminergic, and serotonergic proteins, validated in animal studies only. Future clinical trials are warranted as Licorice administration has a limiting factor of mild hypertension and hypokalemia. Hopefully, scientific updates on Licorice will propagate a paradigm shift in medicine, research propagation, and development of the central nervous system phytopharmaceuticals.

Anaerobic growth and drug susceptibility of versatile fungal pathogen Scedosporium apiospermum

Although severe cases of invasive mycoses of different hypoxic and anoxic body parts have been reported, growth and drug susceptibility of fungal pathogens under anaerobic conditions remains understudied. The current study evaluated anaerobic growth potential and drug susceptibility of environmental Scedosporium apiospermum isolates under aerobic and anaerobic conditions. All tested strains showed equivalent growth and higher sensitivity to tested antifungal drugs under anaerobic conditions with lower minimum inhibitory concentration (MIC) as compared to aerobic conditions. Antifungal azoles were effective against isolates under both aerobic and anaerobic conditions. Most strains were resistant to antifungal echinocandins and polyenes under aerobic conditions but exhibited sensitivity under anaerobic conditions. This study provides evidence that resistance of S. apiospermum to antifungal drugs varies with oxygen concentration and availability and suggests re-evaluating clinical breakpoints for antifungal compounds to treat invasive fungal infections more effectively.

Hyperon Polarization along the Beam Direction Relative to the Second and Third Harmonic Event Planes in Isobar Collisions at sqrt[s_{NN}]=200 GeV

The polarization of Λ and Λ[over ¯] hyperons along the beam direction has been measured relative to the second and third harmonic event planes in isobar Ru+Ru and Zr+Zr collisions at sqrt[s_{NN}]=200  GeV. This is the first experimental evidence of the hyperon polarization by the triangular flow originating from the initial density fluctuations. The amplitudes of the sine modulation for the second and third harmonic results are comparable in magnitude, increase from central to peripheral collisions, and show a mild p_{T} dependence. The azimuthal angle dependence of the polarization follows the vorticity pattern expected due to elliptic and triangular anisotropic flow, and qualitatively disagrees with most hydrodynamic model calculations based on thermal vorticity and shear induced contributions. The model results based on one of existing implementations of the shear contribution lead to a correct azimuthal angle dependence, but predict centrality and p_{T} dependence that still disagree with experimental measurements. Thus, our results provide stringent constraints on the thermal vorticity and shear-induced contributions to hyperon polarization. Comparison to previous measurements at RHIC and the LHC for the second-order harmonic results shows little dependence on the collision system size and collision energy.

Comparative performance analysis of binary variants of FOX optimization algorithm with half-quadratic ensemble ranking method for thyroid cancer detection

Thyroid cancer is a life-threatening condition that arises from the cells of the thyroid gland located in the neck's frontal region just below the adam's apple. While it is not as prevalent as other types of cancer, it ranks prominently among the commonly observed cancers affecting the endocrine system. Machine learning has emerged as a valuable medical diagnostics tool specifically for detecting thyroid abnormalities. Feature selection is of vital importance in the field of machine learning as it serves to decrease the data dimensionality and concentrate on the most pertinent features. This process improves model performance, reduces training time, and enhances interpretability. This study examined binary variants of FOX-optimization algorithms for feature selection. The study employed eight transfer functions (S and V shape) to convert the FOX-optimization algorithms into their binary versions. The vision transformer-based pre-trained models (DeiT and Swin Transformer) are used for feature extraction. The extracted features are transformed using locally linear embedding, and binary FOX-optimization algorithms are applied for feature selection in conjunction with the Naïve Bayes classifier. The study utilized two datasets (ultrasound and histopathological) related to thyroid cancer images. The benchmarking is performed using the half-quadratic theory-based ensemble ranking technique. Two TOPSIS-based methods (H-TOPSIS and A-TOPSIS) are employed for initial model ranking, followed by an ensemble technique for final ranking. The problem is treated as multi-objective optimization task with accuracy, F2-score, AUC-ROC and feature space size as optimization goals. The binary FOX-optimization algorithm based on the [Formula: see text] transfer function achieved superior performance compared to other variants using both datasets as well as feature extraction techniques. The proposed framework comprised a Swin transformer to extract features, a Fox optimization algorithm with a V1 transfer function for feature selection, and a Naïve Bayes classifier and obtained the best performance for both datasets. The best model achieved an accuracy of 94.75%, an AUC-ROC value of 0.9848, an F2-Score of 0.9365, an inference time of 0.0353 seconds, and selected 5 features for the ultrasound dataset. For the histopathological dataset, the diagnosis model achieved an overall accuracy of 89.71%, an AUC-ROC score of 0.9329, an F2-Score of 0.8760, an inference time of 0.05141 seconds, and selected 12 features. The proposed model achieved results comparable to existing research with small features space.

Simultaneous microbial electrochemical degradation of methyl orange and bioelectricity generation using coculture as anode inoculum in a microbial fuel cell

Methyl Orange, an azo dye, is a widely used colouring agent in the textile industry. The study aimed to investigate the efficiency of bioremediating bacteria in degrading methyl orange. Escherichia coli (E. coli), a Methyl Orange-degrading bacterium, was isolated from cow dung and its biochemical properties were analysed using 16S rRNA sequencing, and MALDI-TOF MS. A pre-cultured strain of Pseudomonas aeruginosa was co-cultured with E. coli in 1:1 ration in a microbial fuel cell (MFC) for simultaneous electricity production and methyl orange degradation. The degradation was combined with biological wastewater treatment at varying Methyl Orange concentrations, and the electrochemical characteristics were analysed through polarisation study, cyclic voltammetry, and electrochemical impedance spectroscopy. The impact of parameters such as anolyte pH, dye concentration, incubation time, and substrate concentrations were also studied. This study confirmed E. coli as an effective methyl orange degrading bacteria with a maximum % degradation efficiency of 98% after 48 h incubation at pH 7.0. The co-culture of isolated microorganisms at 250 mg/L of methyl orange concentration showed a maximum power density 6.5 W/m3. Further, anode modification with Fe2O3 nanoparticles on the anode surface enhanced power production to 11.2 W/m3, an increase of 4.7 W/m3.

Chitosan-PEI passivated carbon dots for plasmid DNA and miRNA-153 delivery in cancer cells

These days carbon dots have been developed for multiple biomedical applications. In the current study, the transfection potential of synthesized carbon dots from single biopolymers such as chitosan, PEI-2kDa, and PEI-25kDa (CS-CDs, PEI2-CDs, and PEI25-CDs) and by combining two biopolymers (CP2-CDs and CP25-CDs) through a bottom-up approach have been investigated. The characterization studies revealed successful synthesis of fluorescent, positively charged carbon dots <20 nm in size. Synthesized carbon dots formed a stable complex with plasmid DNA (EGFP-N1) and miRNA-153 that protected DNA/miRNA from serum-induced degradation. In-vitro cytotoxicity analysis revealed minimal cytotoxicity in cancer cell lines (A549 and MDA-MB-231). In-vitro transfection of EGFP-N1 plasmid DNA with PEI2-CDs, PEI25-CDs and CP25-CDs demonstrated that these CDs could strongly transfect A549 and MDA-MB-231 cells. The highest EGFP-N1 plasmid transfection efficiency was observed with PEI2-CDs at a weight ratio of 32:1. PEI25-CDs polyplex showed maximum transfection at a weight ratio of 8:1 in A549 at a weight ratio of 16:1 in MDA-MB-231 cells. CP25-CDs exhibited the highest transfection at a weight ratio of 16:1 in both cell lines. The in-vitro transfection of target miRNA, i.e., miR-153 in A549 and MDA-MB-231 cells with PEI2-CDs, PEI25-CDs, and CP25-CDs suggested successful transfer of miR-153 into cells which induced significant cell death in both cell lines. Importantly, CS-CDs and CP2-CDs could be tolerated by cells up to 200 μg/mL concentration, while PEI2-CDs, PEI25-CDs, and CP25-CDs showed non-cytotoxic behavior at low concentrations (25 μg/mL). Together, these results suggest that a combination of carbon dots synthesized from chitosan and PEI (CP25-CDs) could be a novel vector for transfection nucleic acids that can be utilized in cancer therapy.

In silico designing of multiepitope-based-peptide (MBP) vaccine against MAPK protein express for Alzheimer's disease in Zebrafish

Understanding the role of the mitogen-activated protein kinases (MAPKs) signalling pathway is essential in advancing treatments for neurodegenerative disorders like Alzheimer's. In this study, we investigate in-silico techniques involving computer-based methods to extract the MAPK1 sequence. Our applied methods enable us to analyze the protein's structure, evaluate its properties, establish its evolutionary relationships, and assess its prevalence in populations. We also predict epitopes, assess their ability to trigger immune responses, and check for allergenicity using advanced computational tools to understand their immunological properties comprehensively. We apply virtual screening, docking, and structure modelling to identify promising drug candidates, analyze their interactions, and enhance drug design processes. We identified a total of 30 cell-targeting molecules against the MAPK1 protein, where we selected top 10 CTL epitopes (PAGGGPNPG, GGGPNPGSG, SAPAGGGPN, AVSAPAGGG, AGGGPNPGS, ATAAVSAPA, TAAVSAPAG, ENIIGINDI, INDIIRTPT, and NDIIRTPTI) for further evaluation to determine their potential efficacy, safety, and suitability for vaccine design based on strong binding potential. The potential to cover a large portion of the world's population with these vaccines is substantial-88.5 % for one type and 99.99 % for another. In exploring the molecular docking analyses, we examined a library of compounds from the ZINC database. Among them, we identified twelve compounds with the lowest binding energy. Critical residues in the MAPK1 protein, such as VAL48, LYS63, CYS175, ASP176, LYS160, ALA61, LEU165, TYR45, SER162, ARG33, PRO365, PHE363, ILE40, ASN163, and GLU42, are pivotal for interactions with these compounds. Our result suggests that these compounds could influence the protein's behaviour. Moreover, our docking analyses revealed that the predicted peptides have a strong affinity for the MAPK1 protein. These peptides form stable complexes, indicating their potential as potent inhibitors. This study contributes to the identification of new drug compounds and the screening of their desired properties. These compounds could potentially help reduce the excessive activity of MAPK1, which is linked to Alzheimer's disease.

An overview of polymer surface coated synthetic quantum dots as therapeutics and sensors applications

Quantum dots (QDs) are a class of remarkable materials that have garnered significant attention since their initial discovery. It is noteworthy to mention that it took approximately a decade for these materials to be successfully implemented in practical applications. While QDs have demonstrated notable optical properties, it is important to note that these attributes alone have not rendered them a feasible substitute for traditional organic dyes. Furthermore, it is worth noting that the substance under investigation exhibited inherent toxicity and instability in its initial state, primarily due to the presence of a heavy metal core. In the initial stages of research, it was observed that the integration of nanocomposites had a positive impact on the properties of QDs. The discovery of these nanocomposites was motivated by the remarkable properties exhibited by biocomposites found in nature. Recent discoveries have shed light on the potential utilization of QDs as a viable strategy for drug delivery, offering a promising avenue to enhance the efficacy of current pharmaceuticals and pave the way for the creation of innovative therapeutic approaches. The primary objective of this review was to elucidate the distinctive characteristics that render QDs highly suitable for utilization as nanocarriers. In this study, we will delve into the multifaceted applications of QDs as sensing nanoprobes and their utilization in diverse drug delivery systems. The focus of our investigation was directed toward the utilization of QD/polymer composites in sensing applications, with particular emphasis on their potential as chemical sensors, biosensors, and physical sensors.

Application of nanomaterials as potential quorum quenchers for disease: Recent advances and challenges

Chemical signal molecules are used by bacteria to interact with one another. Small hormone-like molecules known as autoinducers are produced, released, detected, and responded to during chemical communication. Quorum Sensing (QS) is the word for this procedure; it allows bacterial populations to communicate and coordinate group behavior. Several research has been conducted on using inhibitors to prevent QS and minimize the detrimental consequences. Through the enzymatic breakdown of the autoinducer component, by preventing the formation of autoinducers, or by blocking their reception by adding some compounds (inhibitors) that can mimic the autoinducers, a technique known as "quorum quenching" (QQ) disrupts microbial communication. Numerous techniques, including colorimetry, electrochemistry, bioluminescence, chemiluminescence, fluorescence, chromatography-mass spectroscopy, and many more, can be used to test QS/QQ. They all permit quantitative and qualitative measurements of QS/QQ molecules. The mechanism of QS and QQ, as well as the use of QQ in the prevention of biofilms, are all elaborated upon in this writing, along with the fundamental study of nanoparticle (NP)in QQ. Q.

Design, synthesis and evaluation of 177Lu-labeled inverso and retro-inverso A9 peptide variants targeting HER2-overexpression

Several HER2-specific peptides are being continuously explored to find a candidate with suitable pharmacokinetic properties for development of effective radiopharmaceutical that can find applications for clinical screening of breast cancer patients. In the present work with an aim of preparing a radiopeptide with improved metabolic stability and in vivo pharmacokinetic performance we modified our previously reported [177Lu]DOTA-L-A9 peptide. Here we designed an 'inverso' peptide with all d-amino acids and a 'retro-inverso' peptide where sequence of d-amino acids was reversed. Higher secondary structure stabilization of retro- inverso A9 variant compared to inverso A9 peptide was evident by circular dichroism studies. The two radiopeptides [177Lu]DOTA-D-A9 and [177Lu]DOTA-rD-A9 exhibited significantly improved in vivo metabolic stability over the original l-peptide. The retro-inverso variant, [177Lu]DOTA-rD-A9 demonstrated better pharmacokinetic behavior with significantly higher tumor uptake than the inverso peptide, [177Lu]DOTA-D-A9 and the original peptide, [177Lu]DOTA-L-A9. In the present case of A9 peptide, reversal of the peptide sequence of d-amino acids boosted the uptake and retention of radioactivity in HER2-positive tumor. The present study can thus guide the design and development of newer and improved versions of peptides.

Measurement of the top quark mass using a profile likelihood approach with the lepton + jets final states in proton-proton collisions at s=13TeV

The mass of the top quark is measured in 36.3fb - 1 of LHC proton-proton collision data collected with the CMS detector at s = 13 Te V . The measurement uses a sample of top quark pair candidate events containing one isolated electron or muon and at least four jets in the final state. For each event, the mass is reconstructed from a kinematic fit of the decay products to a top quark pair hypothesis. A profile likelihood method is applied using up to four observables per event to extract the top quark mass. The top quark mass is measured to be 171.77 ± 0.37 Ge V . This approach significantly improves the precision over previous measurements.

Deep learning personalized recommendation-based construction method of hybrid blockchain model

This study aims to explore the construction of a personalized recommendation system (PRS) based on deep learning under the hybrid blockchain model to further improve the performance of the PRS. Blockchain technology is introduced and further improved to address security problems such as information leakage in PRS. A Delegated Proof of Stake-Byzantine Algorand-Directed Acyclic Graph consensus algorithm, namely PBDAG consensus algorithm, is designed for public chains. Finally, a personalized recommendation model based on the hybrid blockchain PBDAG consensus algorithm combined with an optimized back propagation algorithm is constructed. Through simulation, the performance of this model is compared with practical Byzantine Fault Tolerance, Byzantine Fault Tolerance, Hybrid Parallel Byzantine Fault Tolerance, Redundant Byzantine Fault Tolerance, and Delegated Byzantine Fault Tolerance. The results show that the model algorithm adopted here has a lower average delay time, a data message delivery rate that is stable at 80%, a data message leakage rate that is stable at about 10%, and a system classification prediction error that does not exceed 10%. Therefore, the constructed model not only ensures low delay performance but also has high network security performance, enabling more efficient and accurate interaction of information. This solution provides an experimental basis for the information security and development trend of different types of data PRSs in various fields.

M, Kveton A, Ayala E, Carrera Jarrin E, Abdelalim AA, Salama E, Abdullah Al-Mashad M, Mahmoud MA, Bhowmik S, Dewanjee RK, Ehataht K, Kadastik M, Lange T, Nandan S, Nielsen C, Pata J, Raidal M, Tani L, Veelken C, Eerola P, Kirschenmann H, Osterberg K, Voutilainen M, Bharthuar S, Brücken E, Garcia F, Havukainen J, Kim MS, Kinnunen R, Lampén T, Lassila-Perini K, Lehti S, Lindén T, Lotti M, Martikainen L, Myllymäki M, Rantanen MM, Siikonen H, Tuominen E, Tuominiemi J, Luukka P, Petrow H, Tuuva T, Amendola C, Besancon M, Couderc F, Dejardin M, Denegri D, Faure JL, Ferri F, Ganjour S, Gras P, Hamel de Monchenault G, Lohezic V, Malcles J, Rander J, Rosowsky A, Sahin M, Savoy-Navarro A, Simkina P, Titov M, Baldenegro Barrera C, Beaudette F, Buchot Perraguin A, Busson P, Cappati A, Charlot C, Damas F, Davignon O, Diab B, Falmagne G, Fontana Santos Alves BA, Ghosh S, Granier de Cassagnac R, Hakimi A, Harikrishnan B, Liu G, Motta J, Nguyen M, Ochando C, Portales L, Salerno R, Sarkar U, Sauvan JB, Sirois Y, Tarabini A, Vernazza E, Zabi A, Zghiche A, Agram JL, Andrea J, Apparu D, Bloch D, Bourgatte G, Brom JM, Chabert EC, Collard C, Darej D, Goerlach U, Grimault C, Le Bihan AC, Van Hove P, Beauceron S, Blancon B, Boudoul G, Carle A, Chanon N, Choi J, Contardo D, Depasse P, Dozen C, El Mamouni H, Fay J, Gascon S, Gouzevitch M, Grenier G, Ille B, Laktineh IB, Lethuillier M, Mirabito L, Perries S, Torterotot L, Vander Donckt M, Verdier P, Viret S, Lomidze D, Lomidze I, Tsamalaidze Z, Botta V, Feld L, Klein K, Lipinski M, Meuser D, Pauls A, Röwert N, Teroerde M, Diekmann S, Dodonova A, Eich N, Eliseev D, Erdmann M, Fackeldey P, Fasanella D, Fischer B, Hebbeker T, Hoepfner K, Ivone F, Lee MY, Mastrolorenzo L, Merschmeyer M, Meyer A, Mondal S, Mukherjee S, Noll D, Novak A, Nowotny F, Pozdnyakov A, Rath Y, Redjeb W, Rehm F, Reithler H, Schmidt A, Schuler SC, Sharma A, Stein A, Torres Da Silva De Araujo F, Vigilante L, Wiedenbeck S, Zaleski S, Dziwok C, Flügge G, Haj Ahmad W, Hlushchenko O, Kress T, Nowack A, Pooth O, Stahl A, Ziemons T, Zotz A, Petersen HA, Martin MA, Alimena J, Asmuss P, Baxter S, Bayatmakou M, Becerril Gonzalez H, Behnke O, Bhattacharya S, Blekman F, Borras K, Brunner D, Campbell A, Cardini A, Cheng C, Colombina F, Consuegra Rodríguez S, Silva GC, De Silva M, Eckerlin G, Eckstein D, Estevez Banos LI, Filatov O, Gallo E, Geiser A, Giraldi A, Greau G, Grohsjean A, Guglielmi V, Guthoff M, Jafari A, Jomhari NZ, Kaech B, Kasemann M, Kaveh H, Kleinwort C, Kogler R, Komm M, Krücker D, Lange W, Leyva Pernia D, Lipka K, Lohmann W, Mankel R, Melzer-Pellmann IA, Mendizabal Morentin M, Metwally J, Meyer AB, Milella G, Mormile M, Mussgiller A, Nürnberg A, Otarid Y, Pérez Adán D, Ranken E, Raspereza A, Ribeiro Lopes B, Rübenach J, Saggio A, Savitskyi M, Scham M, Scheurer V, Schnake S, Schütze P, Schwanenberger C, Shchedrolosiev M, Sosa Ricardo RE, Stafford D, Tonon N, Van De Klundert M, Vazzoler F, Ventura Barroso A, Walsh R, Walter D, Wang Q, Wen Y, Wichmann K, Wiens L, Wissing C, Wuchterl S, Yang Y, Zimermmane Castro Santos A, Albrecht A, Albrecht S, Antonello M, Bein S, Benato L, Bonanomi M, Connor P, De Leo K, Eich M, El Morabit K, Feindt F, Fröhlich A, Garbers C, Garutti E, Hajheidari M, Haller J, Hinzmann A, Jabusch HR, Kasieczka G, Keicher P, Klanner R, Korcari W, Kramer T, Kutzner V, Labe F, Lange J, Lobanov A, Matthies C, Mehta A, Moureaux L, Mrowietz M, Nigamova A, Nissan Y, Paasch A, Pena Rodriguez KJ, Quadfasel T, Rieger M, Savoiu D, Schindler J, Schleper P, Schröder M, Schwandt J, Sommerhalder M, Stadie H, Steinbrück G, Tews A, Wolf M, Brommer S, Burkart M, Butz E, Chwalek T, Dierlamm A, Droll A, Faltermann N, Giffels M, Gosewisch JO, Gottmann A, Hartmann F, Horzela M, Husemann U, Klute M, Koppenhöfer R, Link M, Lintuluoto A, Maier S, Mitra S, Müller T, Neukum M, Oh M, Quast G, Rabbertz K, Shvetsov I, Simonis H, Trevisani N, Ulrich R, van der Linden J, Von Cube RF, Wassmer M, Wieland S, Wolf R, Wozniewski S, Wunsch S, Zuo X, Anagnostou G, Assiouras P, Daskalakis G, Kyriakis A, Loukas D, Stakia A, Diamantopoulou M, Karasavvas D, Kontaxakis P, Manousakis-Katsikakis A, Panagiotou A, Papavergou I, Saoulidou N, Theofilatos K, Tziaferi E, Vellidis K, Zisopoulos I, Bakas G, Chatzistavrou T, Karapostoli G, Kousouris K, Papakrivopoulos I, Tsipolitis G, Zacharopoulou A, Adamidis K, Bestintzanos I, Evangelou I, Foudas C, Gianneios P, Kamtsikis C, Katsoulis P, Kokkas P, Kosmoglou Kioseoglou PG, Manthos N, Papadopoulos I, Strologas J, Csanád M, Farkas K, Gadallah MMA, Major P, Mandal K, Pásztor G, Rádl AJ, Surányi O, Veres GI, Bartók M, Bencze G, Hajdu C, Horvath D, Sikler F, Veszpremi V, Beni N, Czellar S, Karancsi J, Molnar J, Szillasi Z, Teyssier D, Raics P, Ujvari B, Zilizi G, Csorgo T, Nemes F, Novak T, Babbar J, Bansal S, Beri SB, Bhatnagar V, Chaudhary G, Chauhan S, Dhingra N, Gupta R, Kaur A, Kaur A, Kaur H, Kaur M, Kumar S, Kumari P, Meena M, Sandeep K, Sheokand T, Singh JB, Singla A, Ahmed A, Bhardwaj A, 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A search for decays of the Higgs boson to invisible particles in events with a top-antitop quark pair or a vector boson in proton-proton collisions at s=13TeV

A search for decays to invisible particles of Higgs bosons produced in association with a top-antitop quark pair or a vector boson, which both decay to a fully hadronic final state, has been performed using proton-proton collision data collected at s = 13 Te V by the CMS experiment at the LHC, corresponding to an integrated luminosity of 138fb - 1 . The 95% confidence level upper limit set on the branching fraction of the 125Ge V Higgs boson to invisible particles, B ( H → inv ) , is 0.54 (0.39 expected), assuming standard model production cross sections. The results of this analysis are combined with previous B ( H → inv ) searches carried out at s = 7 , 8, and 13Te V in complementary production modes. The combined upper limit at 95% confidence level on B ( H → inv ) is 0.15 (0.08 expected).

Advancement in precision diagnosis and therapeutic for triple-negative breast cancer: Harnessing diagnostic potential of CRISPR-cas & engineered CAR T-cells mediated therapeutics

Cancer is characterized by uncontrolled cell growth, disrupted regulatory pathways, and the accumulation of genetic mutations. These mutations across different types of cancer lead to disruptions in signaling pathways and alterations in protein expression related to cellular growth and proliferation. This review highlights the AKT signaling cascade and the retinoblastoma protein (pRb) regulating cascade as promising for novel nanotheranostic interventions. Through synergizing state-of-the-art gene editing tools like the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas system with nanomaterials and targeting AKT, there is potential to enhance cancer diagnostics significantly. Furthermore, the integration of modified CAR-T cells into multifunctional nanodelivery systems offers a promising approach for targeted cancer inhibition, including the eradication of cancer stem cells (CSCs). Within the context of highly aggressive and metastatic Triple-negative Breast Cancer (TNBC), this review specifically focuses on devising innovative nanotheranostics. For both pre-clinical and post-clinical TNBC detection, the utilization of the CRISPR-Cas system, guided by RNA (gRNA) and coupled with a fluorescent reporter specifically designed to detect TNBC's mutated sequence, could be promising. Additionally, a cutting-edge approach involving the engineering of TNBC-specific iCAR and syn-Notch CAR T-cells, combined with the co-delivery of a hybrid polymeric nano-liposome encapsulating a conditionally replicative adenoviral vector (CRAdV) against CSCs, could present an intriguing intervention strategy. This review thus paves the way for exciting advancements in the field of nanotheranostics for the treatment of TNBC and beyond.

Observation of τ Lepton Pair Production in Ultraperipheral Pb-Pb Collisions at sqrt[s_{NN}]=5.02 TeV

We present an observation of photon-photon production of τ lepton pairs in ultraperipheral lead-lead collisions. The measurement is based on a data sample with an integrated luminosity of 404  μb^{-1} collected by the CMS experiment at a center-of-mass energy per nucleon pair of sqrt[s_{NN}]=5.02  TeV. The γγ→τ^{+}τ^{-} process is observed for τ^{+}τ^{-} events with a muon and three charged hadrons in the final state. The measured fiducial cross section is σ(γγ→τ^{+}τ^{-})=4.8±0.6(stat)±0.5(syst)  μb, where the second (third) term corresponds to the statistical (systematic) uncertainty in σ(γγ→τ^{+}τ^{-}) in agreement with leading-order QED predictions. Using σ(γγ→τ^{+}τ^{-}), we estimate a model-dependent value of the anomalous magnetic moment of the τ lepton of a_{τ}=0.001_{-0.089}^{+0.055}.

Murine sterile fecal filtrate is a potent pharmacological agent that exerts age-independent immunomodulatory effects in RAW264.7 macrophages

BACKGROUND

Sterile fecal filtrate (SFF) is being considered a safer alternative to fecal microbiota transplantation (FMT) therapy; however, its bioactive potency is very little understood. The present study thus assessed the age-dependent immunostimulatory and immunomodulatory attributes of murine SFF in vitro.

METHODS

SFF from young (Y-SFF) and old (O-SFF) Swiss albino mice were prepared. Immunostimulatory and immunomodulatory effects of SFF were evaluated in resting and lipopolysaccharide (LPS) stimulated macrophage cells by measuring intracellular reactive oxygen species (ROS), nitric oxide (NO) production, inflammatory cytokines profile, as well as gene expression of oxidative and inflammatory transcription factors. SFF were also evaluated for native antioxidant capacity by measuring DPPH and ABTS free radical scavenging activity. Bioactive components present in SFF were also determined by GC/MS analysis.

RESULTS

Both Y-SFF and O-SFF induced potent immunostimulatory effects characterized by changes in cell morphology, a significant increase in NO production, ROS levels, and an increased ratio of pro-inflammatory (IL-6, TNF-α, IL-1β) to anti-inflammatory (IL-10) secretory proteins although no significant aggravation in the transcription of NF-κB and Nrf-2 could be observed. Application of LPS to cells significantly augmented a pro-oxidative and pro-inflammatory response which was much higher in comparison to Y-SFF or O-SFF application alone and mediated by strong suppression of Nrf-2 gene expression. Pre-treatment of macrophages with both Y-SFF and O-SFF robustly attenuated cellular hyperresponsiveness to LPS characterized by significantly decreased levels of NO, ROS, and inflammatory cytokines while a concomitant increase in anti-inflammatory protein (IL-10) was observed. Further, both Y-SFF and O-SFF strongly resisted LPS-induced downregulation of Nrf-2 expression although O-SFF appeared to protect cells slightly better from the overall LPS threat. Neat SFF samples exhibited moderate antioxidant capacity and GC/MS analysis of SFF revealed diverse volatile organic compounds characterized by alkanes, organosulphur compounds, furans, amides, amino acids, and antimicrobial elements.

CONCLUSION

Our results indicate that SFF is a potent stimulant of macrophages and confers strong anti-inflammatory effects regardless of donor age thereby suggesting its therapeutic efficacy in lieu of FMT therapy.

A drug design strategy based on molecular docking and molecular dynamics simulations applied to development of inhibitor against triple-negative breast cancer by Scutellarein derivatives

Triple-negative breast cancer (TNBC), accounting for 10-15% of all breast malignancies, is more prevalent in women under 40, particularly in those of African descent or carrying the BRCA1 mutation. TNBC is characterized by the absence of estrogen and progesterone receptors (ER, PR) and low or elevated HER2 expression. It represents a particularly aggressive form of breast cancer with limited therapeutic options and a poorer prognosis. In our study, we utilized the protein of TNBC collected from the Protein Data Bank (PDB) with the most stable configuration. We selected Scutellarein, a bioactive molecule renowned for its anti-cancer properties, and used its derivatives to design potential anti-cancer drugs employing computational tools. We applied and modified structural activity relationship methods to these derivatives and evaluated the probability of active (Pa) and inactive (Pi) outcomes using pass prediction scores. Furthermore, we employed in-silico approaches such as the assessment of absorption, distribution, metabolism, excretion, and toxicity (ADMET) parameters, and quantum calculations through density functional theory (DFT). Within the DFT calculations, we analyzed Frontier Molecular Orbitals, specifically the Highest Occupied Molecular Orbital (HOMO) and Lowest Unoccupied Molecular Orbital (LUMO). We then conducted molecular docking and dynamics against TNBC to ascertain binding affinity and stability. Our findings indicated that Scutellarein derivatives, specifically DM03 with a binding energy of -10.7 kcal/mol and DM04 with -11.0 kcal/mol, exhibited the maximum binding tendency against Human CK2 alpha kinase (PDB ID 7L1X). Molecular dynamic simulations were performed for 100 ns, and stability was assessed using root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF) parameters, suggesting significant stability for our chosen compounds. Furthermore, these molecules met the pharmacokinetics requirements for potential therapeutic candidates, displaying non-carcinogenicity, minimal aquatic and non-aquatic toxicity, and greater aqueous solubility. Collectively, our computational data suggest that Scutellarein derivatives may serve as potential therapeutic agents for TNBC. However, further experimental investigations are needed to validate these findings.

In silico and in vitro study of bioactive compounds of Nigella sativa for targeting neuropilins in breast cancer

Introduction: Breast cancer poses a significant global challenge, prompting researchers to explore novel approaches for potential treatments. Material and Methods: For in vitro study we used thin layer chromatography (TAC) for phytochemical screening, total antioxidant capacity (TLC) assay for antioxidant capacity, and hemolytic activity test for toxicity of Neuropilins (NRPs). We performed bioinformatic analyses to predict protein structures, molecular docking, pharmacophore modeling, and virtual screening to reveal interactions with oncogenes. We conducted 200 ns Molecular Dynamics (MD) simulations and MMGBSA calculations to assess the complex dynamics and stability. Results: We identified phytochemical constituents in Nigella sativa leaves, including tannins, saponins, steroids, and cardiac glycosides, while phlobatannins and terpenoids were absent. The leaves contained 9.4% ± 0.04% alkaloids and 1.9% ± 0.05% saponins. Methanol extract exhibited the highest yield and antioxidant capacity, with Total Flavonoid Content at 127.51 ± 0.76 mg/100 g and Total Phenolic Content at 134.39 ± 0.589 mg GAE/100 g. Hemolysis testing showed varying degrees of hemolysis for different extracts. In-silico analysis indicated stable Neuropilin complexes with key signaling pathways relevant for anti-cancer therapy. Molecular docking scores at different possesses (0, C-50, C -80, C-120,C -150, C -200 ns) revealed strong hydrogen bonding in the complexes and showed -12.9, -11.6, and -11.2 binding Affinities (kcal/mol) to support their stability. Our MD simulations analysis at 200ns confirmed the stability of Neuropilin complexes with the signaling pathways protein PI3K. The calculated binding free energies using MMGBSA provided valuable quantitative information on ligand potency on different time steps. These findings highlight the potential health benefits of N. sativa leaves and their possible role in anti-cancer treatments targeting angiogenesis. Conclusion: Nigella sativa leaves have shown significant medical potential due to their bioactive compounds, which exhibit strong properties in supporting organogenic processes related to cancer. Furthermore, studies have highlighted the promising role of neuropilins in anticancer treatment, demonstrating stable interactions and potential as targeted therapy specifically for breast cancer.

Cytomorphology of mesenchymal lesions in a tertiary care centre and its correlation with histopathology

Objectives

Fine needle aspiration cytology (FNAC) is a minimally invasive method for sampling a heterogenous lesion. It is one of the first-line investigations in the evaluation of soft tissue tumours. However, the heterogeneity of mesenchymal lesions pose a challenge to the cytological diagnosis. The present study aims at evaluation of the cytomorphological findings of mesenchymal lesions on FNAC along with their histopathological correlation.

Material and Methods

This was a retrospective study conducted over a period of 1 year from January 2021 to January 2022. All the patients of cytologically diagnosed mesenchymal lesions on their FNA aspirates were included in the study. Cytomorphology of the May Grunwald Giemsa and Papanicolaou stained slides were examined and correlated with clinical and histopathological details wherever available.

Results

Out of the 90 patients, 69 (76.7%) were males and 21 (23.3%) were females. Maximum number of cases were in 4-5th decade of life. The lower limb was found to be the most common site (57.8%) for the mesenchymal lesions. Majority of the cases on FNA in our study were found to be benign - 79 (87.8%), while only 11 cases were malignant (12.2%). On cytological examination, spindle cell lesions were most common followed by adipocytic lesions. Based on the cyto-histological correlation, sensitivity, specificity, negative predictive value, positive predictive value and diagnostic accuracy of FNAC in diagnosis of mesenchymal lesion was 78.6%, 100%, 92.5%, 100% and 94.1% respectively.

Conclusion

FNAC is a simple and minimally invasive tool that plays an important role in triaging patients with good specificity and sensitivity.

Gold nanoparticle assisted colorimetric biosensors for rapid polyethylene terephthalate (PET) sensing for sustainable environment to monitor microplastics

The extremely widespread and ubiquitous nature of plastics, estimated to boost its global production by 26 billion tons till 2050. The large chunks of plastic waste that decomposed down to micro- or nano plastics (MNPs) leads to various ill effects on biological entities. The conventional PET detection methods lack rapid detection of microplastics due to variances in microplastic features, long-drawn-out sample pre-processing procedures and complex instrumentation. Therefore, an instantaneous colorimetric evaluation of microplastic will ensures the simplicity of conducting assays on field. Several nanoparticle-based biosensors that detects proteins, nucleic acids, metabolites operate on either cluster or disperse state of nanoparticle. However, gold nanoparticle (AuNPs) emerges an ideal scaffold for sensory element in lateral flow biosensors due to their simple surface functionalization, unique optoelectronic properties and varied colour spectrum depending on morphologies and aggregation state. In this paper an effort has been made in the form of a hypothesis using in silico tools as a basis to detect polyethylene terephthalate (PET) - most abundant type of microplastic using gold nanoparticle based lateral flow biosensor. We retrieved sequences of PET-binding synthetic peptides and modelled their 3-D structure using I-Tasser server. The best protein model for each peptide sequences are docked with PET monomers - BHET, MHET and other PET polymeric ligands, to evaluate their binding affinities. The synthetic peptide SP 1 (WPAWKTHPILRM) docked with BHET and (MHET)4 exhibits 1.5-fold increases in binding affinity as compared to reference PET anchor peptide Dermaseptin SI (DSI). The GROMACS molecular dynamics simulation studies of synthetic peptide SP 1 - BHET & - (MHET)4 complexes for 50 ns further confirmed the stable binding. RMSF, RMSD, hydrogen bonds, Rg and SASA analysis provides useful structural insights of the SP 1 complexes as compared to reference DSI. Furthermore, SP 1 functionalized AuNP-based colorimetric device was described in detail for detection of PET.