Assessing the impact of frailty in elderly patients undergoing emergency laparotomies in Singapore.

Introduction: The global rise in ageing populations poses challenges for healthcare systems. By 2030, Singapore anticipates a quarter of its population to be aged 65 or older. This study addresses the dearth of research on frailty's impact on emergency laparotomy (EL) outcomes in this demographic, emphasising the growing significance of this surgical intervention. Method: Conducted at 2 tertiary centres in Singapore from January to December 2019, a retrospective cohort study examined EL outcomes in patients aged 65 or older. Frailty assessment, using the Clinical Frailty Scale (CFS), was integrated into demographic, diagnostic and procedural analyses. Patient data from Tan Tock Seng Hospital and Khoo Teck Puat Hospital provided a comprehensive view of frailty's role in EL. Results: Among 233 participants, 26% were frail, revealing a higher vulnerability in the geriatric population. Frail individuals exhibited elevated preoperative risk, prolonged ICU stays, and significantly higher 90-day mortality (21.3% versus 6.4%). The study illuminated a nuanced connection between frailty and adverse outcomes, underlining the critical need for robust predictive tools in this context. Conclusion: Frailty emerged as a pivotal factor influencing the postoperative trajectory of older adults undergoing EL in Singapore. The integration of frailty assessment, particularly when combined with established metrics like P-POSSUM, showcased enhanced predictive accuracy. This finding offers valuable insights for shared decision-making and acute surgical unit practices, emphasising the imperative of considering frailty in the management of older patients undergoing emergency laparotomy.

Correction: Lungu et al. Molecular Characterisation of Antimicrobial Resistance in E. coli Isolates from Piglets in the West Region of Romania. Antibiotics 2023, 12, 1544.

The authors Bianca Cornelia Lungu and Ioan Hutu did not state contributed equally [...].

Parameters Influencing the Photochemical Cyclodehydrochlorination (CDHC) Reaction.

The photochemical cyclodehydrochlorination (CDHC) reaction has recently been used to prepare a wide variety of polycyclic aromatic hydrocarbons and graphene nanoribbons (GNRs). However, the parameters affecting the efficiency of this reaction have been scarcely studied. In this work, we investigated how the reaction conditions influence the outcome of the reaction. The effect of functional groups on the different phenyl rings of the o-terphenyl scaffold was also studied. The reaction kinetics follow the same trend as Hammett's constant when electron-donating and electron-withdrawing groups are present on the ring bearing the chlorine. The CDHC reaction can be successfully performed using less energetic 365 nm light in the presence of a triplet sensitizer. Computational results provide insight on the reaction mechanism, notably by identifying its three intermediate structures as well as its limiting step.

Effects of in ovo injection of bacterial peptides and CpG-ODN on Salmonella enterica serovar Heidelberg infection in specific pathogen-free (SPF) chicks.

RESEARCH HIGHLIGHTS: Peptides + CpG-ODN reduced SH in caeca at the first week post-infection.Administered formulations did not reduce SH-faecal excretion.Levels of intestinal IgA were similar between all groups.CpG-ODN improved some parameters associated with chick intestinal health.

In-silico molecular modelling studies of some camphor imine based compounds as anti-influenza A (H1N1) pdm09 virus agents.

The advent of influenza A (H1N1) drug-resistant strains led to the search quest for more potent inhibitors of the influenza A virus, especially in this devastating COVID-19 pandemic era. Hence, the present research utilized some molecular modelling strategies to unveil new camphor imine-based compounds as anti-influenza A (H1N1) pdm09 agents. The 2D-QSAR results revealed GFA-MLR (R2train = 0.9158, Q2=0.8475) and GFA-ANN (R2train = 0.9264, Q2=0.9238) models for the anti-influenza A (H1N1) pdm09 activity prediction which have passed the QSAR model acceptability thresholds. The results from the 3D-QSAR studies also revealed CoMFA (R2train =0.977, Q2=0.509) and CoMSIA_S (R2train =0.976, Q2=0.527) models for activity predictions. Based on the notable information derived from the 2D-QSAR, 3D-QSAR, and docking analysis, ten (10) new camphor imine-based compounds (22a-22j) were designed using the most active compound 22 as the template. Furthermore, the high predicted activity and binding scores of compound 22j were further justified by the high reactive sites shown in the electrostatic potential maps and other quantum chemical calculations. The MD simulation of 22j in the active site of the influenza hemagglutinin (HA) receptor confirmed the dynamic stability of the complex. Moreover, the appraisals of drug-likeness and ADMET properties of the proposed compounds showed zero violation of Lipinski's criteria with good pharmacokinetic profiles. Hence, the outcomes in this work recommend further in-depth in vivo and in-vitro investigations to validate these theoretical findings.Communicated by Ramaswamy H. Sarma.

Molecular modelling studies of substituted indole derivatives as novel influenza a virus inhibitors.

The emergence of drug-resistant strains motivate researchers to find new innovative anti-IAV candidates with a different mode of action. In this work, molecular modelling strategies, such as 2D-QSAR, 3D-QSAR, molecular docking, molecular dynamics, FMOs, and ADMET were applied to some substituted indoles as IAV inhibitors. The best-developed 2D-QSAR models, MLR (Q2 = 0.7634, R2train = 0.8666) and ANN[4-3-1] (Q2 = 0.8699, R2train = 0.8705) revealed good statistical validation for the inhibitory response predictions. The 3D-QSAR models, CoMFA (Q2 = 0.504, R2train = 0.805) and CoMSIA/SEDHA (Q2 = 0.619, R2train = 0.813) are selected as the best 3D models following the global thresholds. In addition, the contour maps generated from the CoMFA and CoMSIA models illustrate the relationship between the molecular fields and the inhibitory effects of the studied molecules. The results of the studies led to the design of five new molecules (24a-e) with enhanced anti-IAV activities and binding potentials using the most active molecule (24) as the template scaffold. The conformational stability of the best-designed molecules with the NA protein showed hydrophobic and H-bonds with the key residues from the molecular dynamics simulations of 100 ns. Furthermore, the global reactivity indices from the DFT calculations portrayed the relevance of 24c in view of its smaller band gap as also justified by our QSAR and molecular simulation studies.Communicated by Ramaswamy H. Sarma.

Single Reference Treatment of Strongly Correlated H4 and H10 Isomers with Richardson-Gaudin States.

Richardson-Gaudin (RG) states are employed as a variational wave function ansatz for strongly correlated isomers of H4 and H10. In each case, a single RG state describes the seniority-zero sector quite well. Simple natural orbital functionals offer a cheap and reasonable approximation of the outstanding weak correlation in the seniority-zero sector, while systematic improvement is achieved by performing a configuration interaction in terms of RG states.

Molecular Characterisation of Antimicrobial Resistance in E. coli Isolates from Piglets in the West Region of Romania.

Antibiotics are widely used for prophylaxis and therapy, reducing morbidity and mortality produced by bacterial pathogensin pigs, including infections caused by Escherichia coli. The aim of this study was to characterise antibiotic resistance phenotypes and genotypes in E. coli isolates in pigs in West Romanian grower farms. Differential phenotypic susceptibility profiles and the contribution of resistance genes to phenotypic expression of susceptibility or resistance were evaluated. A total of 76 E. coli isolates were identified and confirmed by the MicroScan Walk Away System. The occurrence of four resistance genes, ampC, blaZ, blaTEM and tetK in strains resistant to 13 antibiotics was assessed. Of the E. coli isolates, 0% showed resistance to meropenem, 3.9% to tigecycline and 10.5% to piperacillin/tazobactam, whereas, in contrast, 100% were resistant to ampicillin and mezlocillin, 76.31% to piperacillin and 59.3% to tetracycline. The prevalence of resistance genes in resistant isolates detected by q-PCR analysis was 97.0% for ampC, 96% for blaZ, 32.9% for blaTEM and 58.8% for tetK. Penetrance (the proportion of individuals carrying a particular variant of a gene that also expresses an associated trait) was 50% for ampC (32% for amoxicillin/clavulanate, 62% for cefazolin, 32% for cefepime, 100% for cefotaxime, 56% for cefuroxime and 99% for ampicillin), 65% for blaZ (32% for amoxicillin/clavulanate and 99% for ampicillin), 51% for blaTEM (81% for piperacillin) and 44% for the tetK gene (83% for tetracycline). The result of phenotypic antibiotic resistance testing may indicate the presence of plasmid-borne resistance, with a diagnostic odds ratio of a positive phenotypic resistance for tetK being 4.52. As a management decision, the maximum penetrance admitted for using a specific antibiotic for E. coli infections in pigs is recommended to be less than 20%.

Retraction notice to "In-silico modelling studies of 5-benzyl-4-thiazolinone derivatives as influenza neuraminidase inhibitors via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions" [Heliyon 8, 2022 Article e10101].

[This retracts the article DOI: 10.1016/j.heliyon.2022.e10101.].

Combining docking, molecular dynamics simulations, AD-MET pharmacokinetics properties, and MMGBSA calculations to create specialized protocols for running effective virtual screening campaigns on the autoimmune disorder and SARS-CoV-2 main protease.

The development of novel medicines to treat autoimmune diseases and SARS-CoV-2 main protease (Mpro), a virus that can cause both acute and chronic illnesses, is an ongoing necessity for the global community. The primary objective of this research is to use CoMFA methods to evaluate the quantitative structure-activity relationship (QSAR) of a select group of chemicals concerning autoimmune illnesses. By performing a molecular docking analysis, we may verify previously observed tendencies and gain insight into how receptors and ligands interact. The results of the 3D QSAR models are quite satisfactory and give significant statistical results: Q_loo∧2 = 0.5548, Q_lto∧2 = 0.5278, R∧2 = 0.9990, F-test = 3,101.141, SDEC = 0.017 for the CoMFA FFDSEL, and Q_loo∧2 = 0.7033, Q_lto∧2 = 0.6827, Q_lmo∧2 = 0.6305, R∧2 = 0.9984, F-test = 1994.0374, SDEC = 0.0216 for CoMFA UVEPLS. The success of these two models in exceeding the external validation criteria used and adhering to the Tropsha and Glorbaikh criteria's upper and lower bounds can be noted. We report the docking simulation of the compounds as an inhibitor of the SARS-CoV-2 Mpro and an autoimmune disorder in this context. For a few chosen autoimmune disorder receptors (protein tyrosine phosphatase, nonreceptor type 22 (lymphoid) isoform 1 (PTPN22), type 1 diabetes, rheumatoid arthritis, and SARS-CoV-2 Mpro, the optimal binding characteristics of the compounds were described. According to their potential for effectiveness, the studied compounds were ranked, and those that demonstrated higher molecular docking scores than the reference drugs were suggested as potential new drug candidates for the treatment of autoimmune disease and SARS-CoV-2 Mpro. Additionally, the results of analyses of drug similarity, ADME (Absorption, Distribution, Metabolism, and Excretion), and toxicity were used to screen the best-docked compounds in which compound 4 scaled through. Finally, molecular dynamics (MD) simulation was used to verify compound 4's stability in the complex with the chosen autoimmune diseases and SARS-CoV-2 Mpro protein. This compound showed a steady trajectory and molecular characteristics with a predictable pattern of interactions. These findings suggest that compound 4 may hold potential as a therapy for autoimmune diseases and SARS-CoV-2 Mpro.

Structure-based drug design, molecular dynamics simulation, ADMET, and quantum chemical studies of some thiazolinones targeting influenza neuraminidase.

The genetic mutability of the influenza virus leads to the existence of drug-resistant strains which is dangerous, particularly with the lingering coronavirus disease (COVID-19). This necessitated the need for the search and discovery of more potential anti-influenza agents to avert future outbreaks. In furtherance of our previous in-silico studies on 5-benzyl-4-thiazolinones as anti-influenza neuraminidase (NA) inhibitors, molecule 11 was selected as the template scaffold for the structure-based drug design due to its good binding, pharmacokinetic profiling, and better NA inhibitory activity. As such, eighteen (18) new molecules (11a-r) were designed with better MolDock scores as compared with the template scaffold and the zanamivir reference drug. However, the dynamic stability of molecule 11a in the binding cavity of the NA target (3TI5) showed water-mediated hydrogen and hydrophobic bondings with the active residues such as Arg118, Ile149, Arg152, Ile222, Trp403, and Ile427 after the MD simulation for 100 ns. The drug-likeness and ADMET assessment of all designed molecules predicted non-violation of the stipulated thresholds of Lipinski's rule and good pharmacokinetic properties respectively. In addition, the quantum chemical calculations also suggested the significant chemical reactivity of molecules with their smaller band energy gap, high electrophilicity, high softness, and low hardness. The results obtained in this study proposed a reliable in-silico viewpoint for anti-influenza drug discovery and development.Communicated by Ramaswamy H. Sarma.

IL-1ß stimulates a novel, IKKα -dependent, NIK -independent activation of non-canonical NFκB signalling.

In this study, we examined the activation of non-canonical nuclear factor Kappa B (NFκB) signalling in U2OS cells, a cellular metastatic bone cancer model. Whilst Lymphotoxin α1ß2 (LTα1ß2) stimulated the expected slow, delayed, sustained activation of serine 866/870 p100 phosphorylation and increased cellular expression of p52 NFκB, we found that canonical agonists, Interleukin-1ß (IL-1ß) and also Tumour necrosis factor-α (TNFα) generated a rapid transient increase in pp100, which was maximal by 15-30 min. This rapid phosphorylation was also observed in other cells types, such as DU145 and HCAECs suggesting the phenomenon is universal. IKKα deletion using CRISPR/Cas9 revealed an IKKα-dependent mechanism for serine 866/870 and additionally serine 872 p100 phosphorylation for both IL-1ß and LTα1ß2. In contrast, knockdown of IKKß using siRNA or pharmacological inhibition of IKKß activity was without effect on p100 phosphorylation. Pre-incubation of cells with the NFκB inducing-kinase (NIK) inhibitor, CW15337, had no effect on IL-1ß induced phosphorylation of p100 however, the response to LTα1ß2 was virtually abolished. Surprisingly IL-1ß also stimulated p52 nuclear translocation as early as 60 min, this response and the concomitant p65 translocation was partially reduced by IKKα deletion. Furthermore, p52 nuclear translocation was unaffected by CW15337. In contrast, the response to LTα1ß2 was essentially abolished by both IKKα deletion and CW15337. Taken together, these finding reveal novel forms of NFκB non-canonical signalling stimulated by ligands that activate the canonical NFκB pathway strongly such as IL-1ß.

Genomic analyses of hair from Ludwig van Beethoven.

Ludwig van Beethoven (1770-1827) remains among the most influential and popular classical music composers. Health problems significantly impacted his career as a composer and pianist, including progressive hearing loss, recurring gastrointestinal complaints, and liver disease. In 1802, Beethoven requested that following his death, his disease be described and made public. Medical biographers have since proposed numerous hypotheses, including many substantially heritable conditions. Here we attempt a genomic analysis of Beethoven in order to elucidate potential underlying genetic and infectious causes of his illnesses. We incorporated improvements in ancient DNA methods into existing protocols for ancient hair samples, enabling the sequencing of high-coverage genomes from small quantities of historical hair. We analyzed eight independently sourced locks of hair attributed to Beethoven, five of which originated from a single European male. We deemed these matching samples to be almost certainly authentic and sequenced Beethoven's genome to 24-fold genomic coverage. Although we could not identify a genetic explanation for Beethoven's hearing disorder or gastrointestinal problems, we found that Beethoven had a genetic predisposition for liver disease. Metagenomic analyses revealed furthermore that Beethoven had a hepatitis B infection during at least the months prior to his death. Together with the genetic predisposition and his broadly accepted alcohol consumption, these present plausible explanations for Beethoven's severe liver disease, which culminated in his death. Unexpectedly, an analysis of Y chromosomes sequenced from five living members of the Van Beethoven patrilineage revealed the occurrence of an extra-pair paternity event in Ludwig van Beethoven's patrilineal ancestry.

Stressor-response functions as a generalizable model for context dependence.

Defining the context dependence of ecological states or processes is a fundamental goal of ecology. Stressor-response functions are the quantitative representation of context dependence, where the context (environmental contingency) is defined by location on the stressor (x) axis, and represents a unifying concept in biological science.

Defining the HIV Capsid Binding Site of Nucleoporin 153.

The interaction between the HIV-1 capsid and human nucleoporin 153 (NUP153) is vital for delivering the HIV-1 preintegration complex into the nucleus via the nuclear pore complex. The interaction with the capsid requires a phenylalanine/glycine-containing motif in the C-terminus of NUP153 (NUP153C). This study used molecular modeling and biochemical assays to comprehensively determine the amino acids in NUP153 that are important for capsid interaction. Molecular dynamics, FoldX, and PyRosetta simulations delineated the minimal capsid binding motif of NUP153 based on the known structure of NUP153 bound to the HIV-1 capsid hexamer. Computational predictions were experimentally validated by testing the interaction of NUP153 with capsid using an in vitro binding assay and a cell-based TRIM-NUP153C restriction assay. This work identified eight amino acids from P1411 to G1418 that stably engage with capsid, with significant correlations between the interactions predicted by molecular models and empirical experiments. This validated the usefulness of this multidisciplinary approach to rapidly characterize the interaction between human proteins and the HIV-1 capsid. IMPORTANCE The human immunodeficiency virus (HIV) can infect nondividing cells by interacting with the host nuclear pore complex. The host nuclear pore protein NUP153 directly interacts with the HIV capsid to promote viral nuclear entry. This study used a multidisciplinary approach combining computational and experimental techniques to comprehensively map the effect of mutating the amino acids of NUP153 on HIV capsid interaction. This work showed a significant correlation between computational and empirical data sets, revealing that the HIV capsid interacted specifically with only six amino acids of NUP153. The simplicity of the interaction motif suggested other FG-containing motifs could also interact with the HIV-1 capsid. Furthermore, it was predicted that naturally occurring polymorphisms in human and nonhuman primates would disrupt NUP153 interaction with capsid, potentially protecting certain populations from HIV-1 infection.

Computational modelling studies of some 1,3-thiazine derivatives as anti-influenza inhibitors targeting H1N1 neuraminidase via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions.

Background: Influenza virus disease remains one of the most contagious diseases that aided the deaths of many patients, especially in this COVID-19 pandemic era. Recent discoveries have shown that the high prevalence of influenza and SARS-CoV-2 coinfection can rapidly increase the death rate of patients. Hence, it became necessary to search for more potent inhibitors for influenza disease therapy. The present study utilized some computational modeling concepts such as 2D-QSAR, 3D-QSAR, molecular docking simulation, and ADMET predictions of some 1,3-thiazine derivatives as inhibitors of influenza neuraminidase (NA). Results: The 2D-QSAR modeling results showed GFA-MLR ( R train 2 = 0.9192, Q 2 = 0.8767, R 2 adj = 0.8991, RMSE = 0.0959, R test 2 = 0.8943, R pred 2 = 0.7745) and GFA-ANN ( R train 2 = 0.9227, Q 2 = 0.9212, RMSE = 0.0940, R test 2 = 0.8831, R pred 2 = 0.7763) models with the computed descriptors as ATS7s, SpMax5_Bhv, nHBint6, and TDB9m for predicting the NA inhibitory activities of compounds which have passed the global criteria of accepting QSAR model. The 3D-QSAR modeling was carried out based on the comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA). The CoMFA_ES ( R train 2 = 0.9620, Q 2 = 0.643) and CoMSIA_SED ( R train 2 = 0.8770, Q 2 = 0.702) models were found to also have good and reliable predicting ability. The compounds were also virtually screened based on their binding scores via molecular docking simulations with the active site of the NA (H1N1) target receptor which also confirms their resilient potency. Four potential lead compounds (4, 7, 14, and 15) with the relatively high inhibitory rate (> 50%) and docking (> - 6.3 kcal/mol) scores were identified as the possible lead candidates for in silico exploration of improved anti-influenza agents. Conclusion: The drug-likeness and ADMET predictions of the lead compounds revealed non-violation of Lipinski's rule and good pharmacokinetic profiles as important guidelines for rational drug design. Hence, the outcome of this research set a course for the in silico design and exploration of novel NA inhibitors with improved potency.

In-silico modelling studies of 5-benzyl-4-thiazolinone derivatives as influenza neuraminidase inhibitors via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions.

Influenza virus disease is one of the most infectious diseases responsible for many human deaths, and the high mutability of the virus causes drug resistance effects in recent times. As such, it became necessary to explore more inhibitors that could avert future influenza pandemics. The present research utilized some in-silico modelling concepts such as 2D-QSAR, 3D-QSAR, molecular docking simulation, and ADMET predictions on some 5-benzyl-4-thiazolinone derivatives as influenza neuraminidase (NA) inhibitors. The 2D-QSAR modelling results revealed GFA-MLR ( R train 2 =0.8414, Q2 = 0.7680) and GFA-ANN ( R train â€‹ 2 =0.8754, Q2 = 0.8753) models with the most relevant descriptors (MATS3i, SpMax5_Bhe, minsOH and VE3_D) for predicting the inhibitory activities of the molecules which has passed the global criteria of accepting QSAR models. The results of the 3D-QSAR modelling results showed that CoMFA_ES ( R train â€‹ 2 =0.9030, Q2 = 0.5390) and CoMSIA_EA ( R train 2 =0.880, Q2 = 0.547) models are having good predicting ability among other developed models. The molecules were virtually screened via molecular docking simulation with the active site of NA protein receptor (pH1N1) which confirms their resilient potency when compared with zanamivir standard drug. Molecule 11 as the most potent molecule formed more H-bond interactions with the key residues such as TRP178, ARG152, ARG292, ARG371, and TYR406 that triggered the catalytic reactions for NA inhibition. Furthermore, six (6) molecules (9, 10, 11, 17, 22, and 31) with relatively high inhibitory activities and docking scores were identified as the possible leads for in-silico exploration of novel NA inhibitors. The drug-likeness and ADMET predictions of the lead molecules revealed non-violation of Lipinski's rule and good pharmacokinetic profiles respectively, which are important guidelines for rational drug design. Hence, the outcome of this study overlaid a solid foundation for the in-silico design and exploration of novel NA inhibitors with improved potency.

Suspended sediment releases in rivers: Toward establishing a safe sediment dose for construction projects.

The harmful effects of suspended sediment (SS) exposures on aquatic ecosystems have been well documented. Integrating this knowledge into the management plans of in-stream construction projects that cause SS releases remains challenging. Commonly, these projects have fixed scopes that require decisions about trade-offs between elevated SS concentrations (SSC, mg∙L-1) and duration of exposure (DoE, h). Constraining SSC to levels below a regulatory guideline may lead to an increase in project duration, while extended SS exposure times have uncertain environmental impacts and reduce project efficiency. This paper evaluates an alternative limit of SS dose (SSD, mg∙h∙L-1), which is defined herein as the product of SSC and DoE, as a more useful regulatory guideline compared to maximum SSC for fixed scope projects. Managing SSD may lead to improved outcomes for project efficiency without jeopardizing environmental health. A dose-response model for salmonids is developed to contrast this approach with more common regulatory limits applied to fixed scope projects that focus on managing SS releases using maximum SSC values within a given time interval. Results demonstrate that the latter constrain the management operating space to a subset of the acceptable range of exposures, which may reduce project efficiency and increase environmental risk. Based on simulated predictions for mean salmonid probabilities of major physiological and lethal effects, an SSD limit of 600 mg∙h∙L-1 may offer a conservative upper range of SSC and DoE values when managing salmonid populations, according to a common regulatory guideline for short-term exposures to not exceed 25 mg∙L-1 over 24 h. This SSD limit would increase the available operating space to enhance project efficiency by not overly constraining SSC. The methods developed in this study may be used to evaluate other SS management limits by undertaking Monte Carlo simulations using dose-response models fit to available datasets to assess acceptable operating ranges.

Nitric oxide favours tumour-promoting inflammation through mitochondria-dependent and -independent actions on macrophages.

Production of nitric oxide (NO) has been demonstrated in several malignancies, however its role remains not fully understood, specifically in relation to the metabolic and functional implications that it may have on immune cells participating in tumorigenesis. Here, we show that inducible NO synthase (iNOS) is expressed in cancers of the colon and the prostate, mainly by tumour cells, and NO generation is evidenced by widespread nitrotyrosine (NT) staining in tumour tissue. Furthermore, presence of NT is observed in the majority of tumour-associated macrophages (TAMs), despite low iNOS expression by these cells, suggesting that NO from the tumour microenvironment affects TAMs. Indeed, using a co-culture model, we demonstrate that NO produced by colon and prostate cancer cells is sufficient to induce NT formation in neighbouring macrophages. Moreover, exposure to exogenous NO promotes mitochondria-dependent and -independent changes in macrophages, which orientate their polarity towards an enhanced pro-inflammatory phenotype, whilst decreasing antigen-presenting function and wound healing capacity. Abrogating endogenous NO generation in murine macrophages, on the other hand, decreases their pro-inflammatory phenotype. These results suggest that the presence of NO in cancer may regulate TAM metabolism and function, favouring the persistence of inflammation, impairing healing and subverting adaptive immunity responses.

QSAR, homology modeling, and docking simulation on SARS-CoV-2 and pseudomonas aeruginosa inhibitors, ADMET, and molecular dynamic simulations to find a possible oral lead candidate.

Background: In seek of potent and non-toxic iminoguanidine derivatives formerly assessed as active Pseudomonas aeruginosa inhibitors, a combined mathematical approach of quantitative structure-activity relationship (QSAR), homology modeling, docking simulation, ADMET, and molecular dynamics simulations were executed on iminoguanidine derivatives. Results: The QSAR method was employed to statistically analyze the structure-activity relationships (SAR) and had conceded good statistical significance for eminent predictive model; (GA-MLR: Q2 LOO = 0.8027; R 2 = 0.8735; R 2 ext = 0.7536). Thorough scrutiny of the predictive models disclosed that the Centered Broto-Moreau autocorrelation - lag 1/weighted by I-state and 3D topological distance-based autocorrelation-lag 9/weighted by I-state oversee the biological activity and rendered much useful information to realize the properties required to develop new potent Pseudomonas aeruginosa inhibitors. The next mathematical model work accomplished here emphasizes finding a potential drug that could aid in curing Pseudomonas aeruginosa and SARS-CoV-2 as the drug targets Pseudomonas aeruginosa. This involves homology modeling of RNA polymerase-binding transcription factor DksA and COVID-19 main protease receptors, docking simulations, and pharmacokinetic screening studies of hits compounds against the receptor to identify potential inhibitors that can serve to regulate the modeled enzymes. The modeled protein exhibits the most favorable regions more than 90% with a minimum disallowed region less than 5% and is simulated under a hydrophilic environment. The docking simulations of all the series to the binding pocket of the built protein model were done to demonstrate their binding style and to recognize critical interacting residues inside the binding site. Their binding constancy for the modeled receptors has been assessed through RMSD, RMSF, and SASA analysis from 1-ns molecular dynamics simulations (MDS) run. Conclusion: Our acknowledged drugs could be a proficient cure for SARS-CoV-2 and Pseudomonas aeruginosa drug discovery, having said that extra testing (in vitro and in vivo) is essential to explain their latent as novel drugs and manner of action. Supplementary Information: The online version contains supplementary material available at 10.1186/s43141-022-00362-z.