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The three-dimensional protein structure is pivotal in comprehending biological phenomena. It directly governs protein function and hence aids in drug discovery. The development of protein prediction algorithms, such as AlphaFold2, ESMFold, and trRosetta, has given much hope in expediting protein-based therapeutic discovery. Though no study has reported a conclusive application of these algorithms, the efforts continue with much optimism. We intended to test the application of these algorithms in rank-ordering therapeutic proteins for their instability during the pre-translational modification stages, as may be predicted according to the confidence of the structure predicted by these algorithms. The selected molecules were based on a harmonized category of licensed therapeutic proteins; out of the 204 licensed products, 188 that were not conjugated were chosen for analysis, resulting in a lack of correlation between the confidence scores and structural or protein properties. It is crucial to note here that the predictive accuracy of these algorithms is contingent upon the presence of the known structure of the protein in the accessible database. Consequently, our conclusion emphasizes that these algorithms primarily replicate information derived from existing structures. While our findings caution against relying on these algorithms for drug discovery purposes, we acknowledge the need for a nuanced interpretation. Considering their limitations and recognizing that their utility may be constrained to scenarios where known structures are available is important. Hence, caution is advised when applying these algorithms to characterize various attributes of therapeutic proteins without the support of adequate structural information. It is worth noting that the two main algorithms, AlfphaFold2 and ESMFold, also showed a 72% correlation in their scores, pointing to similar limitations. While much progress has been made in computational sciences, the Levinthal paradox remains unsolved.

Cellular homeostasis is a continuous phenomenon that if compromised can lead to several disorders including cancer. There is a need to understand the dynamics of cellular proliferation to get deeper insights into the prevalence of cancer. Mechanistic Target of Rapamycin (mTOR) is implicated as the central regulator of the metabolic pathway involved in growth whereas its two distinct complexes mTORC1 and mTORC2 perform particular functions in cellular propagation. To date, mTORC1 is a well defined therapeutic target to inhibit uncontrolled cell division, while the role of mTORC2 is not well characterized. Therefore, the current study is designed to understand the signaling dynamics of mTOR and its partner proteins such as PI3K, PTEN, mTORC2, PKB (Akt), mTORC1, and FOXO. For this purpose, a qualitative model of mTOR-associated Biological Regulatory Network (BRN) is constructed to predict its regulatory behaviors which may not be predictable otherwise. The depleted expression of PTEN and FOXO along with the overexpression of PI3K, mTORC2, mTORC1 and Akt is predicted as a stable steady state which is in accordance with their observed expression levels in the progression of various cancers. The qualitative model also predicts the homeostasis of all the entities in the form of qualitative cycles. The significant qualitative (discrete) cycle is identified by analyzing betweenness centralities of the qualitative (discrete) states. This cycle is further refined as a linear hybrid automaton model with the production (activation) and degradation (inhibition) time delays in order to analyze the real-time constraints for its existence. The analysis of the hybrid model provides a formal proof that during homeostasis the inhibition time delay of Akt is less than the inhibition time delay of mTORC2. In conclusion, our observations characterize that in homeostasis Akt is degraded with a faster rate than mTORC2 which suggests that the inhibition of Akt along with the activation of mTORC2 may be a better therapeutic strategy for the treatment of cancer.

IntroductionRheumatoid arthritis (RA) is a chronic autoimmune disease characterized by synovial infiltration and pannus formation, and its rising incidence is significantly contributing to the global disability rate. Despite advances in biological drugs, no treatment has successfully cured or averted its progression. Consequently, natural drugs are being explored as alternative therapeutic strategies.ObjectiveThis study aims to evaluate the therapeutic potential of Pennisetum glaucum (pearl millet) and to identify its bioactive compounds to assess their effectiveness against RA targets.MethodsThe therapeutic potential of P. glaucum extracts was evaluated by antioxidant and anti-inflammatory assays. Gas chromatography-mass spectrometry (GC-MS) was utilized to identify the compounds in P. glaucum extract. The pharmacokinetics and safety profile of these compounds were studied by absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis. Network pharmacology, molecular docking, and molecular dynamic (MD) simulation were employed to identify the active compounds and their therapeutic targets in P. glaucum for RA treatment.ResultsAcidified methanol (AM) extract of P. glaucum showed the highest phenolic (213 ± 0.008 mg GAE/g DW) and flavonoid content (138.1 ± 0.03 mg RE/g DW), demonstrating significant antioxidant and anti-inflammatory potential. GC-MS of AM extract identified 223 compounds. Lipinski and toxicity parameters screened out 17 compounds. Protein–protein interaction (PPI) analysis shortlisted 20 key targets in RA pathways, nine of which were upregulated in five microarray datasets. Molecular docking and MD simulations revealed that compound-7 (benzenesulfonamide, 2-nitro-N-phenyl-) and compound-9 (Pregnane-3,20-diamine, (3.beta.,5.alpha.,20S)-) bind strongly with MMP9, JAK2, PTGS2, and HIF1a compared to the reference, predicting stable interaction with these upregulated genes. Finally, PASS (prediction of activity spectra for biological active substances) analysis further validated the anti-arthritic potential of these compounds based on their chemical structure.ConclusionThis study uncovered a therapeutic drug candidate against HIF1a, MMP9, JAK2, and PTGS2 for RA from P. glaucum active compounds, laying the groundwork for future research.

Urinary tract infections (UTIs) are the second most prevalent infectious disease with E. coli being the most common etiological agent behind these infections, affecting more than 150 million people globally each year. In recent decades, the emergence of multi-drug resistant (MDR) pathogens has rapidly escalated. To combat antimicrobial resistance (AMR), it is important to synthesize new biologically effective alternatives like ionic liquids (ILs) to control the bacterial infection and their spread. Ionic liquids are poorly coordinated organic salts characterized by melting points typically below 100 °C. The ability of ILs to form anionic and cationic interactions contributes to their versatile chemical, physical and biological attributes. In the present study, a total of 9 previously chemically synthesized and characterized ILs were used. For exploration of their antibacterial potential against the urinary tract infections (UTIs) caused by MDR Uropathogenic E. coli (UPEC) strains, in vitro and in vivo evaluation of ILs were performed. ILs showed pronounced zone of inhibition (ZOI), minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) values of 29.5 mm, 3.81 μM and 5.08 μM by agar disk diffusion and broth micro-dilution methods, respectively. Scanning electron microscopy results depicted substantial morphological changes in UPEC biofilm formation ascertaining antibiofilm potential of tested ILs. Moreover, ILs showed exceptional antioxidant potential depicted by DPPH assay along with low cytotoxic effect toward mammalian cell lines (NB4), red blood cells and whole blood. Furthermore, the gene expression analysis results justified the antibacterial potential of ILs showing down-regulation of fimH, uvrY and up-regulation of csrA gene in UPEC after ILs treatment. In vivo dermal sensitivity assessment also established their non-cytotoxic behavior. In silico analysis validated these results, with the majority of the compounds exhibiting moderate to good absorption.Due to remarkable antibacterial and antioxidant potential and negligible cytoxicity, it could be inferred that ILs could serve as novel antimicrobial alternative agents in the treatment of UTIs.

BackgroundType 2 diabetes mellitus is a metabolic disease categorized by hyperglycemia, resistance to insulin, and ß-cell dysfunction. Around the globe, approximately 422 million people have diabetes, out of which 1.5 million die annually. In spite of innovative advancements in the treatment of diabetes, no biological drug has been known to successfully cure and avert its progression. Thereupon, natural drugs derived from plants are emerging as a novel therapeutic strategy to combat diseases like diabetes.ObjectiveThe current study aims to investigate the antidiabetic potential of natural compounds of Oryza sativa L. indica (black rice) in disease treatment.MethodsAntioxidant activity and alpha amylase assays were performed to evaluate the therapeutic potential of the extract of Oryza sativa L. indica. Gas chromatography–mass spectrometry (GC–MS) was used for identification of constituents from the ethanol extract. ADMET profiling (absorption, distribution, metabolism, excretion, and toxicity), network pharmacology, and molecular dynamics simulation were employed in order to uncover the active ingredients and their therapeutic targets in O. sativa L. indica against type 2 diabetes mellitus.ResultsGC–MS of the plant extract provided a list of 184 compounds. Lipinski filter and toxicity parameters screened out 18 compounds. The topological parameters of the protein–protein interaction (PPI) were used to shortlist the nine key proteins (STAT3, HSP90AA1, AKT1, SRC, ESR1, MAPK1, NFKB1, EP300, and CREBBP) in the type 2 diabetes mellitus pathways. Later, molecular docking analysis and simulations showed that C14 (1H-purine-8-propanoic acid, .alpha.-amino-2, 3, 6, 7-tetrahydro-1,3,7-trimethyl-2,6-dioxo-) and C18 (cyclohexane-carboxamide, N-furfuryl) bind with AKT1 and ESR1 with a binding energy of 8.1, 6.9, 7.3, and 7.2 kcal/mol, respectively. RMSD (root-mean-square deviation) and RMSF (root-mean-square fluctuation) values for AKT1 and ESR1 have shown very little fluctuation, indicating that proteins were stabilized after ligand docking.ConclusionThis study suggests therapeutic drug candidates against AKT1 and ESR1 to treat type 2 diabetes mellitus. However, further wet-lab analysis is required to discover the best remedy for type 2 diabetes mellitus.

Colonoscopy is a reliable diagnostic method to detect colorectal polyps early on and prevent colorectal cancer. The current examination techniques face a significant challenge of high missed rates, resulting in numerous undetected polyps and irregularities. Automated and real-time segmentation methods can help endoscopists to segment the shape and location of polyps from colonoscopy images in order to facilitate clinician’s timely diagnosis and interventions. Different parameters like shapes, small sizes of polyps, and their close resemblance to surrounding tissues make this task challenging. Furthermore, high-definition image quality and reliance on the operator make real-time and accurate endoscopic image segmentation more challenging. Deep learning models utilized for segmenting polyps, designed to capture diverse patterns, are becoming progressively complex. This complexity poses challenges for real-time medical operations. In clinical settings, utilizing automated methods requires the development of accurate, lightweight models with minimal latency, ensuring seamless integration with endoscopic hardware devices. To address these challenges, in this study a novel lightweight and more generalized Enhanced Nanonet model, an improved version of Nanonet using NanonetB for real-time and precise colonoscopy image segmentation, is proposed. The proposed model enhances the performance of Nanonet using Nanonet B on the overall prediction scheme by applying data augmentation, Conditional Random Field (CRF), and Test-Time Augmentation (TTA). Six publicly available datasets are utilized to perform thorough evaluations, assess generalizability, and validate the improvements: Kvasir-SEG, Endotect Challenge 2020, Kvasir-instrument, CVC-ClinicDB, CVC-ColonDB, and CVC-300. Through extensive experimentation, using the Kvasir-SEG dataset, our model achieves a mIoU score of 0.8188 and a Dice coefficient of 0.8060 with only 132,049 parameters and employing minimal computational resources. A thorough cross-dataset evaluation was performed to assess the generalization capability of the proposed Enhanced Nanonet model across various publicly available polyp datasets for potential real-world applications. The result of this study shows that using CRF (Conditional Random Fields) and TTA (Test-Time Augmentation) enhances performance within the same dataset and also across diverse datasets with a model size of just 132,049 parameters. Also, the proposed method indicates improved results in detecting smaller and sessile polyps (flats) that are significant contributors to the high miss rates.

In this research work, the ZnFe2O4 and its composites with coal fly ash (CFA) were synthesized. Three photocatalysts ZnFe2O4, CFA-ZnFe2O4 (1:2), and CFA-ZnFe2O4 (1:1) were prepared, and their comparative dye degradation efficiencies have been evaluated. The catalysts were well characterized using FTIR spectroscopy, X-ray diffraction analysis, scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy, vibrating sample magnetometer, and X-ray photoelectron spectroscopy. The bandgap energies were calculated using Tauc plot method. The process optimization of various parameters like pH, catalysts dose, oxidant dose, reaction time in degradation studies under UV irradiations (254 nm) was done. The optimized conditions of parameters were pH = 3 and 6 for ZnFe2O4 and CFA-ZnFe2O4 (1:2, 1:1) composite, catalysts dose = 8 mg and 10 mg/100 mL for ZnFe2O4 and CFA-ZnFe2O4 (1:2, 1:1) composite, oxidant dose = 14 mM and 10 mM for ZnFe2O4 and CFA-ZnFe2O4 (1:2, 1:1) composite and reaction time = 60 min. The ZnFe2O4, CFA-ZnFe2O4(1:2), and CFA-ZnFe2O4(1:1) showed 76, 92, and 97% degradation of MB under optimized conditions, respectively. The photocatalytic degradation results showed that the loading of ZnFe2O4 nanoparticles on CFA improves the degradation of MB. The proposed research not only provided a simple approach for the synthesis of CFA-based nanocomposites but also reported the reclamation of waste residual material (CFA) to support solid waste management. The catalysts showed negligible Fe leaching with a small reduction in degradation efficiency after five reusability runs. [ABSTRACT FROM AUTHOR]

Abstract Plants require copper for normal growth and development and have evolved an efficient system for copper management based on transport proteins such as P1B-ATPases, also known as heavy metal ATPases (HMAs). Here, we report HMAs in eleven different Poaceae species, including wheat. Furthermore, the possible role of wheat HMAs in copper stress was investigated. BlastP searches identified 27 HMAs in wheat, and phylogenetic analysis based on the Maximum Likelihood method demonstrated a separation into four distinct clades. Conserved motif analysis, domain identification, gene structure, and transmembrane helices number were also identified for wheat HMAs using computational tools. Wheat seedlings grown hydroponically were subjected to elevated copper and demonstrated toxicity symptoms with effects on fresh weight and changes in expression of selected HMAs TaHMA7, TaHMA8, and TaHMA9 were upregulated in response to elevated copper, suggesting a role in wheat copper homeostasis. Further investigations on these heavy metal pumps can provide insight into strategies for enhancing crop heavy metal tolerance in the face of heavy metal pollution.

The complement system is an essential part of innate immunity. It is activated by invading pathogens causing inflammation, opsonization, and lysis via complement anaphylatoxins, complement opsonin’s and membrane attack complex (MAC), respectively. However, in SARS-CoV-2 infection overactivation of complement system is causing cytokine storm leading to multiple organs damage. In this study, the René Thomas kinetic logic approach was used for the development of biological regulatory network (BRN) to model SARS-CoV-2 mediated complement system signalling pathways. Betweenness centrality analysis in cytoscape was adopted for the selection of the most biologically plausible states in state graph. Among the model results, in strongly connected components (SCCs) pro-inflammatory cytokines (PICyts) oscillatory behaviour between recurrent generation and downregulation was found as the main feature of SARS-CoV-2 infection. Diversion of trajectories from the SCCs leading toward hyper-inflammatory response was found in agreement with in vivo studies that overactive innate immunity response caused PICyts storm during SARS-CoV-2 infection. The complex of negative regulators FI, CR1 and DAF in the inhibition of complement peptide (C5a) and PICyts was found desirable to increase immune responses. In modelling role of MAC and PICyts in lowering of SARS-CoV-2 titre was found coherent with experimental studies. Intervention in upregulation of C5a and PICyts by C3 was found helpful in back-and-forth variation of signalling pattern linked with the levels of PICyts. Moreover, intervention in upregulation of PICyts by C5a was found productive in downregulation of all activating factors in the normal SCCs. However, the computational model predictions require experimental studies to be validated by exploring the activation role of C3 and C5a which could change levels of PICyts at various phases of SARS-CoV-2 infection.

Peanut (Arachis hypogaea L.) harbors a plethora of flavonoids that impart its health-promoting properties. To understand its biosynthesis and accumulation, a comparative expression analysis of flavonoid biosynthetic genes encoding enzymes responsible for synthesizing the main structure of flavonoids has been conducted in two differentially performing peanut varieties (PG 1247 and Bari 2011) in response to photoperiod and water availability. Transcript profiling of flavonoid biosynthetic genes indicated time-dependent expression of genes except for AhFLS in selected varieties in response to photoperiod variation. Many genes depicted a low degree of variation within varieties and water-deficient treatments. However, AhANS showed the highest variation for stress duration and varieties. In conclusion, this study has characterized the role of flavonoid biosynthesis in peanuts in response to photoperiod and water availability. Moreover, correlation analysis unraveled the coordination among the expression of flavonoid biosynthetic genes.

Closed flexor tendon injuries can often result from trauma that causes sudden forceful extension of an actively flexed digit. These closed tendon injuries commonly occur as avulsions in flexor zone I. Spontaneous midsubstance flexor tendon ruptures are rare, especially in the absence of an underlying pathology. Diagnosing such injuries accurately is challenging and critical. We present a case of a zone III spontaneous flexor tendon rupture of the long finger after forceful eccentric loading. Surgical exploration was performed, and the level of the rupture was identified during surgery. A side-to-side tendon repair technique was performed using a palmaris longus tendon graft. No underlying pathology to explain the rupture was found in this case. This report emphasizes the importance of considering spontaneous midsubstance ruptures, identifying the level of ruptures, and preoperative planning for such cases. It reviews the possible causes and treatment of spontaneous flexor tendon rupture.

Hepatitis C virus is a single-stranded RNA based virus which can cause chronic HCV and hepatocellular carcinoma. HCV genotype 3a has relatively higher rate of fibrosis progression, prevalence of steatosis and incidence of HCC. Despite HCVs variation in genomic sequence, the 5' untranslated region containing internal ribosome entry site (IRES) is highly conserved among all genotypes. It is responsible for translation and initiation of the viral protein. In present study, IRES was targeted by designing variants of reported antigen binding fragment (Fab) through affinity maturation approach. Affinity maturation strategy allowed the rational antibody designing with better biophysical properties and antibody-antigen binding interactions. Complementarity determining regions of reported Fab (wild type) were assessed and docked with IRES. Best generated model of Fab was selected and subjected to alanine scanning Three sets of insilico mutations for variants (V) designing were selected; single (1-71), double (a-j) and triple (I-X). Redocking of IRES-Fab variants consequently enabled the discovery of three variants exhibiting better docking score as compared to the wild type Fab. V1, V39 and V4 exhibited docking scores of -446.51, -446.52 and-446.29 kcal/mol respectively which is better as compared to the wild type Fab that exhibited the docking score of -351.23 kcal/mol. Variants exhibiting better docking score were screened for aggregation propensity by assessing the aggregation prone regions in Fab structure. Total A3D scores of wild type Fab, V1, V4 and V39 were predicted as -315.325, -312.727, -316.967 and -317.545 respectively. It is manifested that solubility of V4 and V39 is comparable to wild type Fab. In future, development and invitro assessment of these promising Fab HCV3 variants is aimed.

Objectives: The present study describes the draft genome sequence of a novel Bacillus sp. strain SD-4 isolated from animal feed. The study aims to get a deeper insight into antimicrobial resistance and secondary metabolite biosynthetic gene clusters (BGCs) and the association between them. Methods: The strain SD-4 was preliminarily evaluated for antibacterial activities, motility, biofilm formation, and enterotoxin production using in vitro assays. The genome of strain SD-4 was sequenced using the Illumina HiSeq 2500 platform with paired-end reads. The reads were assembled and annotated using SPAdes and PGAP, respectively. The genome was further analysed using several bioinformatics tools, including TYGS, AntiSMASH, RAST, PlasmidFinder, VFDB, VirulenceFinder, CARD, PathogenFinder, MobileElement finder, IslandViewer, and CRISPRFinder. Results: In vitro assays showed that the strain is motile, synthesises biofilm, and produces an enterotoxin and antibacterial metabolites. The genome analysis revealed that the strain SD-4 carries antimicrobial resistance genes (ARGs), virulence factors, and beneficial secondary metabolite BGCs. Further genome analysis showed interesting genome architectures containing several mobile genetic elements, including two plasmid replicons (repUS22 and rep20), five prophages, and at least four genomic islands (GIs), including one Listeria pathogenicity island LIPI-1. Moreover, the strain SD-4 is identified as a putative human pathogen. Conclusion: The genome of strain SD-4 harbours several BGCs coding for biologically active metabolites. It also contains antimicrobial resistance genes and is identified as a potential human pathogen. These results can be used to better comprehend antibiotic resistance in environmental bacteria that are not influenced by human intervention.

Abstract Breast cancer is among the lethal types of cancer with a high mortality rate, globally. Its high prevalence can be controlled through improved analysis and identification of disease‐specific biomarkers. Recently, long non‐coding RNAs (lncRNAs) have been reported as key contributors of carcinogenesis and regulate various cellular pathways through post‐transcriptional regulatory mechanisms. The specific aim of this study was to identify the novel interactions of aberrantly expressed genetic components in breast cancer by applying integrative analysis of publicly available expression profiles of both lncRNAs and mRNAs. Differential expression patterns were identified by comparing the breast cancer expression profiles of samples with controls. Significant co‐expression networks were identified through WGCNA analysis. WGCNA is a systems biology approach used to elucidate the pattern of correlation between genes across microarray samples. It is also used to identify the highly correlated modules. The results obtained from this study revealed significantly differentially expressed and co‐expressed lncRNAs and their cis‐ and trans‐regulating mRNA targets which include RP11‐108F13.2 targeting TAF5L, RPL23AP2 targeting CYP4F3, CYP4F8 and AL022324.2 targeting LRP5L, AL022324.3, and Z99916.3, respectively. Moreover, pathway analysis revealed the involvement of identified mRNAs and lncRNAs in major cell signalling pathways, and target mRNAs expression is also validated through cohort data. Thus, the identified lncRNAs and their target mRNAs represent novel biomarkers that could serve as potential therapeutics for breast cancer and their roles could also be further validated through wet labs to employ them as potential therapeutic targets in future.

Background Breast cancer is the second leading cause of cancer-related deaths globally, and its prevalence rates are increasing daily. In the past, studies predicting therapeutic drug targets for cancer therapy focused on the assumption that one gene is responsible for producing one protein. Therefore, there is always an immense need to find promising and novel anti-cancer drug targets. Furthermore, proteases have an integral role in cell proliferation and growth because the proteolysis mechanism is an irreversible process that aids in regulating cellular growth during tumorigenesis. Therefore, an inactive rhomboid protease known as iRhom2 encoded by the gene RHBDF2 can be considered an important target for cancer treatment. Speculatively, previous studies on gene expression analysis of RHBDF2 showed heterogenous behaviour during tumorigenesis. Consistent with this, several studies have reported the antagonistic role of iRhom2 in tumorigenesis, i.e., either they are involved in negative regulation of EGFR ligands via the ERAD pathway or positively regulate EGFR ligands via the EGFR signalling pathway. Additionally, different opinions suggest iRhom2 mediated cleavage of EGFR ligands takes place TACE dependently or TACE independently. However, reconciling these seemingly opposing roles is still unclear and might be attributed to more than one transcript isoform of iRhom2. Methods To observe the differences at isoform resolution, the current strategy identified isoform switching in RHBDF2 via differential transcript usage using RNA-seq data during breast cancer initiation and progression. Furthermore, interacting partners were found via correlation and enriched to explain their antagonistic role. Results Isoform switching was observed at DCIS, grade 2 and grade 3, from canonical to the cub isoform. Neither EGFR nor ERAD was found enriched. However, pathways leading to TACE-dependent EGFR signalling pathways were more observant, specifically MAPK signalling pathways, GPCR signalling pathways, and toll-like receptor pathways. Nevertheless, it was noteworthy that during CTCs, the cub isoform switches back to the canonical isoform, and the proteasomal degradation pathway and cytoplasmic ribosomal protein pathways were significantly enriched. Therefore, it could be inferred that cub isoform functions during cancer initiation in EGFR signalling. In contrast, during metastasis, where invasion is the primary task, the isoform switches back to the canonical isoform.

Summary:. A severely protruding premaxilla in a patient with bilateral cleft lip and palate prevents functional closure of the orbicularis oris muscle and acceptable reconstruction of the nasolabial components during primary cheiloplasty. This is typically corrected with vomerine osteotomy and premaxillary setback, followed by cheiloplasty and rhinoplasty. Due to the risk of vascular compromise to the prolabium and premaxillary segment, the lip and nose repair is often staged after the vomerine osteotomy and premaxillary setback has healed. Stabilizing the premaxillary segment to allow adequate healing has been a topic of interest. Several methods have been described, but each is associated with varying degrees of compromise of the blood supply to the premaxilla. To combat this, the authors created a custom oral splint that effectively maintained the position of the premaxilla with minimal impingement of the blood supply. The authors present two cases in which a two-stage premaxillary setback with a custom-stabilizing oral splint was performed, followed by primary cheiloplasty and rhinoplasty in an age-appropriate and delayed presentation of bilateral cleft lip and palate and protruding premaxilla.

Sphingomyelin (SM) belongs to a class of lipids termed sphingolipids. The disruption in the sphingomyelin signaling pathway is associated with various neurodegenerative disorders. TNF-α, a potent pro-inflammatory cytokine generated in response to various neurological disorders like Alzheimer’s disease (AD), Parkinson’s disease (PD), and Multiple Sclerosis (MS), is an eminent regulator of the sphingomyelin metabolic pathway. The immune-triggered regulation of the sphingomyelin metabolic pathway via TNF-α constitutes the sphingomyelin signaling pathway. In this pathway, sphingomyelin and its downstream sphingolipids activate various signaling cascades like PI3K/AKT and MAPK/ERK pathways, thus, controlling diverse processes coupled with neuronal viability, survival, and death. The holistic analysis of the immune-triggered sphingomyelin signaling pathway is imperative to make necessary predictions about its pivotal components and for the formulation of disease-related therapeutics. The current work offers a comprehensive in silico systems analysis of TNF-α mediated sphingomyelin and downstream signaling cascades via a model-based quantitative approach. We incorporated the intensity values of genes from the microarray data of control individuals from the AD study in the input entities of the pathway model. Computational modeling and simulation of the inflammatory pathway enabled the comprehensive study of the system dynamics. Network and sensitivity analysis of the model unveiled essential interaction parameters and entities during neuroinflammation. Scanning of the key entities and parameters allowed us to determine their ultimate impact on neuronal apoptosis and survival. Moreover, the efficacy and potency of the FDA-approved drugs, namely Etanercept, Nivocasan, and Scyphostatin allowed us to study the model’s response towards inhibition of the respective proteins/enzymes. The network analysis revealed the pivotal model entities with high betweenness and closeness centrality values including recruit FADD, TNFR_TRADD, act CASP2, actCASP8, actCASP3 and 9, cytochrome C, and RIP_RAIDD which profoundly impacted the neuronal apoptosis. Whereas some of the entities with high betweenness and closeness centrality values like Gi-coupled receptor, actS1PR, Sphingosine, S1P, actAKT, and actERK produced a high influence on neuronal survival. However, the current study inferred the dual role of ceramide, both on neuronal survival and apoptosis. Moreover, the drug Nivocasan effectively reduces neuronal apoptosis via its inhibitory mechanism on the caspases.

Alzheimer’s is a type of dementia that affects the affected person’s thinking, memory, and behavior. It is a multifactorial disease, developed by the breakdown of the neurotransmitter acetylcholine via acetylcholinesterase (AChE). The present study was designed to evaluate potential inhibitors of acetylcholinesterase that could be used as a therapeutic agent against Alzheimer’s disease (AD). For this course, synthetic compounds of the Schiff bases class of 2-mercaptobenzimidazole hydrazone derivatives (9–14) were determined to be potent acetylcholinesterase inhibitors with IC50 values varying between 37.64 ± 0.2 and 74.76 ± 0.3 μM. The kinetic studies showed that these are non-competitive inhibitors of AChE. Molecular docking studies revealed that all compounds accommodate well in the active site and are stabilized by hydrophobic interactions and hydrogen bonding. Molecular dynamics (MD) simulations of selected potent inhibitors confirm their stability in the active site of the enzyme. Moreover, all compounds showed antispasmodic and Ca2+ antagonistic activities. Among the selected compounds of 2-mercaptobenzimidazole hydrazone derivatives, compound 11 exhibited the highest activity on spontaneous and K+-induced contractions, followed by compound 13. Therefore, the Ca2+ antagonistic, AChE inhibition potential, and safety profile of these compounds in the human neutrophil viability assay make them potential drug candidates against AD in the future.

Summary:. A female child was investigated for insidious onset of temporomandibular joint dysfunction and trismus in the setting of a mandibular myofibroma. Myofibromas, benign mesenchymal neoplasms composed of spindle cells, are rarely found in the oral cavity, most commonly in the mandible. These lesions are historically described as indolent with a high cure rate and minimal recurrence rates following surgical resection. The patient initially presented with concerns regarding snoring, retrognathia, and jaw ankylosis, as well as a history of trouble latching as an infant but without obvious physical deformities. Imaging revealed a large expansile lytic mass of the mandible, but no temporomandibular joint involvement; surgical biopsy evidenced myofibroma, and the lesion was resected. Over the course of disease, the lesion continued to expand, and the patient’s maximal incisal opening continued to decrease despite conservative management with jaw physiotherapy; eventually she could not open her mouth despite the absence of joint involvement. Re-exploration along with formal jaw physiotherapy was achieved and optimal jaw opening was maintained. Myofibromas are rare benign desmoid tumors that can present anywhere in the body in solitary and multicentric forms, and previously did not present significant challenges to surgical and medical management. Tumors of the mandible may present with trismus and soft tissue ankylosis, which can mimic temporomandibular joint dysfunction in the absence of joint involvement. Physical therapy, rehabilitation, and soft tissue contracture release are key to management and improving outcomes in oral cancer patients, regardless of tumor pathology.

Reduction in friction ensures fuel economy, control on emissions and durability of components in internal combustion engines. A modern gasoline internal combustion engine was instrumented to determine the friction values at the cam–roller interface considering the effects of surface treatment and engine operating state. A series of tests under different operating speeds and lubricant inlet temperatures were undertaken using both an original surface roller and a Wonder Process Craft (WPC) surface-treated engine roller. The results clearly revealed a substantial reduction in friction magnitude for the WPC surface-treated engine roller in comparison to the original roller while operating under similar conditions, indicating their strong potential for employment in engines. An increase in friction with the rise in temperature was also observed for both types of rollers, whereas increased lubricant entraining velocity due to higher operating speed had the opposite impact. A considerable reduction in frictional drive torque ranging from 8% to 28% was observed by employing the WPC-treated roller in comparison to original/untreated roller at various operating conditions, which signifies the strong potential for employment of WPC surface treatment in the roller/follower valve train engines.

Critical heat flux (CHF) is an essential parameter that plays a significant role in ensuring the safety and economic efficiency of nuclear power facilities. It imposes design and operational restrictions on nuclear power plants due to safety concerns. Therefore, accurate prediction of CHF using a hybrid framework can assist researchers in optimizing system performance, mitigating risk of equipment failure, and enhancing safety measures. Despite the existence of numerous prediction methods, there remains a lack of agreement regarding the underlying mechanism that gives rise to CHF. Hence, developing a precise and reliable CHF model is a crucial and challenging task. In this study, we proposed a hybrid model based on an artificial neural network (ANN) to improve the prediction accuracy of CHF. Our model leverages the available knowledge from a lookup table (LUT) and then employs ANN to further reduce the gap between actual and predicted outcomes. To develop and assess the accuracy of our model, we compiled a dataset of around 5877 data points from various sources in the literature. This dataset encompasses a diverse range of operating parameters for two-phase flow in vertical tubes. The results of this study demonstrate that the proposed hybrid model performs better than standalone machine learning models such as ANN, random forest, support vector machine, and data-driven lookup tables, with a relative root-mean-square error (rRMSE) of only 9.3%. We also evaluated the performance of the proposed hybrid model using holdout and cross-validation techniques, which demonstrated its robustness. Moreover, the proposed approach offers valuable insights into the significance of various input parameters in predicting CHF. Our proposed system can be utilized as a real-time monitoring tool for predicting extreme conditions in nuclear reactors, ensuring their safe and efficient operation.

Chemotherapy resistance and peculiar tumor microenvironment, which diminish or mitigate the effects of therapies, make pancreatic cancer one of the deadliest malignancies to manage and treat. Advanced immunotherapies are under consideration intending to ameliorate the overall patient survival rate in pancreatic cancer. Oncolytic viruses therapy is a new type of immunotherapy in which a virus after infecting and lysis the cancer cell induces/activates patients’ immune response by releasing tumor antigen in the blood. The current review covers the pathways and molecular ablation that take place in pancreatic cancer cells. It also unfolds the extensive preclinical and clinical trial studies of oncolytic viruses performed and/or undergoing to design an efficacious therapy against pancreatic cancer.

This study seeks to investigate the interaction profile of the L5 protein of oncolytic adenovirus with the overexpressed surface receptors of pancreatic cancer. This is an important area of research because pancreatic cancer is one of the most fatal malignancies with a very low patient survival rate. Multiple therapies to date to improve the survival rate are reported; however, they show a comparatively low success rate. Among them, oncolytic virus therapy is a type of immunotherapy that is currently under deliberation by researchers for multiple cancer types in various clinical trials. Talimogene laherparepvec (T-VEC) is the first oncolytic virus approved by the US Food and Drug Administration (FDA) for melanoma. The oncolytic virus not only kills cancer cells but also activates the anticancer immune response. Therefore, it is preferred over others to deal with aggressive pancreatic cancer. The efficacy of therapy primarily depends on how effectively the oncolytic virus enters and infects the cancer cell. Cell surface receptors and their interactions with virus coat proteins are a crucial step for oncolytic virus entry and a pivotal determinant. The L5 proteins of the virus coat are the first to interact with host cell surface receptors. Therefore, the objective of this study is to analyze the interaction profile of the L5 protein of oncolytic adenovirus with overexpressed surface receptors of pancreatic cancer. The L5 proteins of three adenovirus serotypes HAdV2, HAdV5, and HAdV3 were utilized in this study. Overexpressed pancreatic cancer receptors include SLC2A1, MET, IL1RAP, NPR3, GABRP, SLC6A6, and TMPRSS4. The protein structures of viral and cancer cell protein were docked using the High Ambiguity Driven protein–protein DOCKing (HADDOCK) server. The binding affinity and interaction profile of viral proteins against all the receptors were analyzed. Results suggest that the HAdV3 L5 protein shows better interaction as compared to HAdV2 and HAdV5 by elucidating high binding affinity with 4 receptors (NPR3, GABRP, SLC6A6, and TMPRSS4). The current study proposed that HAdV5 or HAdV2 virus pseudotyped with the L5 protein of HAdV3 can be able to effectively infect pancreatic cancer cells. Moreover, the current study surmises that the affinity maturation of HAdV3 L5 can enhance virus attachment with all the receptors of cancer cells.

Several natural mutants of the human G6PD enzyme exist and have been reported. Because the enzymatic activities of many mutants are different from that of the wildtype, the genetic polymorphism of G6PD plays an important role in the synthesis of nucleic acids via ribulose-5-phosphate and formation of reduced NADP in response to oxidative stress. G6PD mutations leading to its deficiency result in the neonatal jaundice and acute hemolytic anemia in human. Herein, we demonstrate the molecular dynamics simulations of the wildtype G6PD and its three mutants to monitor the effect of mutations on dynamics and stability of the protein. These mutants are Chatham (A335T), Nashville (R393H), Alhambra (V394L), among which R393H and V394L lie closer to binding site of structural NADP+. MD analysis including RMSD, RMSF and protein secondary structure revealed that decrease in the stability of mutants is key factor for loss of their activity. The results demonstrated that mutations in the G6PD sequence resulted in altered structural stability and hence functional changes in enzymes. Also, the binding site, of structural NADP+, which is far away from the catalytic site plays an important role in protein stability and folding. Mutation at this site causes changes in structural stability and hence functional deviations in enzyme structure reflecting the importance of structural NADP+ binding site. The calculation of binding free energy by post processing end state method of Molecular Mechanics Poisson Boltzmann SurfaceArea (MM-PBSA) has inferred that ligand binding in wildtype is favorable as compared to mutants which represent destabilised protein structure due to mutation that in turn may hinder the normal physiological function. Exploring individual components of free energy revealed that the van der Waals energy component representing non-polar/hydrophobic energy contribution act as a dominant factor in case of ligand binding. Our study also provides an insight in identifying the key inhibitory site in G6PD and its mutants which can be exploited to use them as a target for developing new inhibitors in rational drug design.

Summary:. Cherubism is a rare, autosomal dominant condition characterized by the replacement of medullary bone by fibro-osseous lesions, predominantly in the bilateral maxillae and/or mandibles. The clinical presentation of cherubism can vary widely, from clinically undetectable to severe facial disfigurement. Although there are no established management guidelines for this condition, conservative management with observation is typically favored in most cases due to the possibility of spontaneous regression following puberty. In this article, we present three cases of moderate to severe cherubism managed with early surgical intervention utilizing curettage and osteotomy followed by bony repositioning. We aimed to show the feasibility and safety of this minimally invasive surgical technique in the management of moderate to severe cases of cherubism to provide improvement in patient quality of life, aesthetics, and function while also possibly mitigating the need for later reconstructive surgery.

Background Cotton leaf curl disease (CLCuD) is a disease of cotton caused by begomoviruses, leading to a drastic loss in the annual yield of the crop. Pakistan has suffered two epidemics of this disease leading to the loss of billions in annual exports. The speculation that a third epidemic of CLCuD may result as consequence of the frequent occurrence of Tomato leaf curl New Delhi virus (ToLCNDV) and Cotton leaf curl Kokhran Virus-Burewala Strain (CLCuKoV-Bu) in CLCuD infected samples, demand that the interactions taking between the two viruses be properly evaluated. This study is designed to assess virus-virus interactions at the molecular level and determine the type of co-infection taking place. Methods Based on the amino acid sequences of the gene products of both CLCuKoV-Bu and ToLCNDV, protein structures were generated using different software, i.e., MODELLER, I-TASSER, QUARKS, LOMETS and RAPTORX. A consensus model for each protein was selected after model quality assessment using ERRAT, QMEANDisCo, PROCHECK Z-Score and Ramachandran plot analysis. The active and passive residues in the protein structures were identified using the CPORT server. Protein–Protein Docking was done using the HADDOCK webserver, and 169 Protein–Protein Interaction (PPIs) were performed between the proteins of the two viruses. The docked complexes were submitted to the PRODIGY server to identify the interacting residues between the complexes. The strongest interactions were determined based on the HADDOCK Score, Desolvation energy, Van der Waals Energy, Restraint Violation Energy, Electrostatic Energy, Buried Surface Area and Restraint Violation Energy, Binding Affinity and Dissociation constant (Kd). A total of 50 ns Molecular Dynamic simulations were performed on complexes that exhibited the strongest affinity in order to validate the stability of the complexes, and to remove any steric hindrances that may exist within the structures. Results Our results indicate significant interactions taking place between the proteins of the two viruses. Out of all the interactions, the strongest were observed between the Replication Initiation protein (Rep) of CLCuKoV-Bu with the Movement protein (MP), Nuclear Shuttle Protein (NSP) of ToLCNDV (DNA-B), while the weakest were seen between the Replication Enhancer protein (REn) of CLCuKoV-Bu with the REn protein of ToLCNDV. The residues identified to be taking a part in interaction belonged to domains having a pivotal role in the viral life cycle and pathogenicity. It maybe deduced that the two viruses exhibit antagonistic behavior towards each other, and the type of infection may be categorised as a type of Super Infection Exclusion (SIE) or homologous interference. However, further experimentation, in the form of transient expression analysis, is needed to confirm the nature of these interactions and increase our understanding of the direct interactions taking place between two viruses.

Background The dehydration responsive element-binding (DREB) gene family plays a crucial role as transcription regulators and enhances plant tolerance to abiotic stresses. Although the DREB gene family has been identified and characterized in many plants, knowledge about it in Solanum tuberosum (Potato) is limited. Results In the present study, StDREB gene family was comprehensively analyzed using bioinformatics approaches. We identified 66 StDREB genes through genome wide screening of the Potato genome based on the AP2 domain architecture and amino acid conservation analysis (Valine at position 14th). Phylogenetic analysis divided them into six distinct subgroups (A1–A6). The categorization of StDREB genes into six subgroups was further supported by gene structure and conserved motif analysis. Potato DREB genes were found to be distributed unevenly across 12 chromosomes. Gene duplication proved that StDREB genes experienced tandem and segmental duplication events which led to the expansion of the gene family. The Ka/Ks ratios of the orthologous pairs also demonstrated the StDREB genes were under strong purification selection in the course of evolution. Interspecies synteny analysis revealed 45 and 36 StDREB genes were orthologous to Arabidopsis and Solanum lycopersicum, respectively. Moreover, subcellular localization indicated that StDREB genes were predominantly located within the nucleus and the StDREB family’s major function was DNA binding according to gene ontology (GO) annotation. Conclusions This study provides a comprehensive and systematic understanding of precise molecular mechanism and functional characterization of StDREB genes in abiotic stress responses and will lead to improvement in Solanum tuberosum.

Pancreatic cancer (PaCa) is the seventh most fatal malignancy, with more than 90% mortality rate within the first year of diagnosis. Its treatment can be improved the identification of specific therapeutic targets and their relevant pathways. Therefore, the objective of this study is to identify cancer specific biomarkers, therapeutic targets, and their associated pathways involved in the PaCa progression. RNA-seq and microarray datasets were obtained from public repositories such as the European Bioinformatics Institute (EBI) and Gene Expression Omnibus (GEO) databases. Differential gene expression (DE) analysis of data was performed to identify significant differentially expressed genes (DEGs) in PaCa cells in comparison to the normal cells. Gene co-expression network analysis was performed to identify the modules co-expressed genes, which are strongly associated with PaCa and as well as the identification of hub genes in the modules. The key underlaying pathways were obtained from the enrichment analysis of hub genes and studied in the context of PaCa progression. The significant pathways, hub genes, and their expression profile were validated against The Cancer Genome Atlas (TCGA) data, and key biomarkers and therapeutic targets with hub genes were determined. Important hub genes identified included ITGA1, ITGA2, ITGB1, ITGB3, MET, LAMB1, VEGFA, PTK2, and TGFβ1. Enrichment analysis characterizes the involvement of hub genes in multiple pathways. Important ones that are determined are ECM–receptor interaction and focal adhesion pathways. The interaction of overexpressed surface proteins of these pathways with extracellular molecules initiates multiple signaling cascades including stress fiber and lamellipodia formation, PI3K-Akt, MAPK, JAK/STAT, and Wnt signaling pathways. Identified biomarkers may have a strong influence on the PaCa early stage development and progression. Further, analysis of these pathways and hub genes can help in the identification of putative therapeutic targets and development of effective therapies for PaCa.

Psoriasis is the most common and chronic skin disease that affects individuals from every age group. The rate of psoriasis is increasing over the time in both developed and developing countries. Studies have revealed the possibility of association of psoriasis with skin cancers, particularly non-melanoma skin cancers (NMSC), which, include basal cell carcinoma and cutaneous squamous cell carcinoma (cSCC). There is a need to analyze the disease at molecular level to propose potential biomarkers and therapeutic targets in comparison to cSCC. Therefore, the second analyzed disease of this study is cSCC. It is the second most common prevalent skin cancer all over the world with the potential to metastasize and recur. There is an urge to validate the proposed biomarkers and discover new potential biomarkers as well. In order to achieve the goals and objectives of the study, microarray and RNA-sequencing data analyses were performed followed by network analysis. Afterwards, quantitative systems biology was implemented to analyze the results at a holistic level. The aim was to predict the molecular patterns that can lead psoriasis to cancer. The current study proposed potential biomarkers and therapeutic targets for psoriasis and cSCC. IL-17 signaling pathway is also identified as significant pathway in both diseases. Moreover, the current study proposed that autoimmune pathology, neutrophil recruitment, and immunity to extracellular pathogens are sensitive towards MAPKs (MAPK13 and MAPK14) and genes for AP-1 (FOSL1 and FOS). Therefore, these genes should be further studied in gene knock down based studies as they may play significant role in leading psoriasis towards cancer.