Redefining a new frontier in alkaptonuria therapy with AI-driven drug candidate design via in- silico innovation.

A rare metabolic condition called alkaptonuria (AKU) is caused by a decrease in homogentisate 1,2 dioxygenase (HGO) activity due to a mutation in homogentisate dioxygenase (HGD) gene. Homogentisic acid is a byproduct of the catabolism of tyrosine and phenylalanine that darkens the urine and accumulates in connective tissues which causes an agonizing arthritis. Employing the use of deep learning artificial intelligence (AI) drug design, this study aims to alleviate the current toxicity of the AKU drugs currently in use, particularly nitisinone, by utilizing the natural flavanol kaempferol molecule as a 4-hydroxyphenylpyruvate dioxygenase inhibitor. Kaempferol was employed to generate three effective de novo drug candidates targeting the enzyme 4-hydroxyphenylpyruvate dioxygenase using an AI drug design tool. We present novel AIK formulations in the present study. The AIK's (Artificial Intelligence Kaempferol) examination of drug-likeliness among the three led to its choice as a possible target. The toxicity assessment research of AIK demonstrates that it is not only safer to use than other treatments, but also more efficient. The docking of the AIGT with 4-hydroxyphenylpyruvate dioxygenase, which revealed a binding affinity of around -9.099 kcal/mol, highlights the AIK's potential as a therapeutic candidate. An innovative approach to deal with challenging circumstances is thus presented in this study by new formulations kaempferol that have been meticulously designed by AI. The results of the in vitro tests must be confirmed in vivo, even though AI-designed AIK is effective and sufficiently safe as computed.

A multi-objective optimisation approach with improved pareto-optimal solutions to enhance economic and environmental dispatch in power systems.

This work implements the recently developed nth state Markovian jumping particle swarm optimisation (PSO) algorithm with local search (NS-MJPSOloc) awareness method to address the economic/environmental dispatch (EED) problem. The proposed approach, known as the Non-dominated Sorting Multi-objective PSO with Local Best (NS-MJPSOloc), aims to enhance the performance of the PSO algorithm in multi-objective optimisation problems. This is achieved by redefining the concept of best local candidates within the search space of multi-objective optimisation. The NS-MJPSOloc algorithm uses an evolutionary factor-based mechanism to identify the optimum compromise solution, a Markov chain state jumping technique to control the Pareto-optimal set size, and a neighbourhood's topology (such as a ring or a star) to determine its size. Economic dispatch refers to the systematic allocation of available power resources in order to fulfill all relevant limitations and effectively meet the demand for electricity at the lowest possible operating cost. As a result of heightened public consciousness regarding environmental pollution and the implementation of clean air amendments, nations worldwide have compelled utilities to adapt their operational practises in order to comply with environmental regulations. The (NS-MJPSOloc) approach has been utilised for resolving the EED problem, including cost and emission objectives that are not commensurable. The findings illustrate the efficacy of the suggested (NS-MJPSOloc) approach in producing a collection of Pareto-optimal solutions that are evenly dispersed within a single iteration. The comparison of several approaches reveals the higher performance of the suggested (NS-MJPSOloc) in terms of the diversity of the Pareto-optimal solutions achieved. In addition, a measure of solution quality based on Pareto optimality has been incorporated. The findings validate the effectiveness of the proposed (NS-MJPSOloc) approach in addressing the multi-objective EED issue and generating a trade-off solution that is both optimal and of high quality. We observed that our approach can reduce ∼ 6.4% of fuel costs and ∼ 9.1% of computational time in comparison to the classical PSO technique. Furthermore, our method can reduce ∼ 9.4% of the emissions measured in tons per hour as compared to the PSO approach.

Integrating 16S rRNA profiling and in-silico analysis for an epitope-based vaccine strategy against Achromobacter xylosoxidans infection.

Achromobacter xylosoxidans is an aerobic, catalase-positive, non-pigment-forming, Gram-negative, and motile bacterium. It potentially causes a wide range of human infections in cystic fibrosis and non-cystic fibrosis patients. However, developing a safe preventive or therapeutic solution against A. xylosoxidans remains challenging. This study aimed to construct an epitope-based vaccine candidate using immunoinformatic techniques. A. xylosoxidans was isolated from an auto workshop in Lahore, and its identification was confirmed through 16S rRNA amplification and bioinformatic analysis. Two protein targets with GenBank accession numbers AKP90890.1 and AKP90355.1 were selected for the vaccine construct. Both proteins exhibited antigenicity, with scores of 0.757 and 0.580, respectively and the epitopes were selected based on the IC50 value using the ANN 4.0 and NN-align 2.3 epitope prediction method for MHC I and MHC II epitopes respectively and predicted epitopes were analyzed for antigenicity, allergenicity and pathogenicity. The vaccine construct demonstrated structural stability, thermostability, solubility, and hydrophilicity. The vaccine produced 250 B-memory cells per mm3 and approximately 16,000 IgM + IgG counts, indicating an effective immune response against A. xylosoxidans. Moreover, the vaccine candidate interacted stably with toll-like receptor 5, a pattern recognition receptor, with a confidence score of 0.98. These results highlight the potency of the designed vaccine candidate, suggesting its potential to withstand rigorous in vitro and in vivo clinical trials. This epitope-based vaccine could serve as the first preventive immunotherapy against A. xylosoxidans infections, addressing this bacterium's health and financial burdens. The findings demonstrate the value of employing immunoinformatic tools in vaccine development, paving the way for more precise and tailored approaches to combating microbial threats.

Designing a Multiepitope Vaccine against the Foodborne Pathogenic Bacteria Listeria monocytogenes Using Subtractive Immunoinformatics Approaches.

BACKGROUND: Listeria monocytogenes, a Gram-positive bacterium, is a prominent foodborne pathogen that causes listeriosis and poses substantial health hazards worldwide. The continuing risk of listeriosis outbreaks underlies the importance of designing an effective prevention strategy and developing a robust immune response by reverse vaccinology approaches. This study aimed to provide a critical approach for developing a potent multiepitope vaccine against this foodborne disease. METHODS: A chimeric peptide construct containing 5 B-cell epitopes, 16 major histocompatibility complex I (MHC-I) epitopes, and 18 MHC-II epitopes were used to create a subunit vaccination against L. monocytogenes. The vaccine safety was evaluated by several online methods, and molecular docking was performed using ClusPro to determine the binding affinity. Immune simulation was performed using the C-ImmSimm server to demonstrate the immune response. RESULTS: The results validated the antigenicity, non-allergenicity, and nontoxicity of the chimeric peptide construct, confirming its suitability as a subunit vaccine. Molecular docking showed a good score of 1276.5 and molecular dynamics simulations confirmed the construct's efficacy, demonstrating its promise as a good candidate for listeriosis prophylaxis. The population coverage was as high as 91.04% with a good immune response, indicating good antigen presentation with dendritic cells and production of memory cells. CONCLUSIONS: The findings of this study highlight the potential of the designed chimeric peptide construct as an effective subunit vaccine against Listeria, paving the way for future advances in preventive methods and vaccine design.

Whole Genome Analysis of Tibetan Kefir-Derived Lactiplantibacillus Plantarum 12-3 Elucidates Its Genomic Architecture, Antimicrobial and Drug Resistance, Potential Probiotic Functionality and Safety.

BACKGROUND: Lactiplantibacillus plantarum 12-3 holds great promise as a probiotic bacterial strain, yet its full potential remains untapped. This study aimed to better understand this potential therapeutic strain by exploring its genomic landscape, genetic diversity, CRISPR-Cas mechanism, genotype, and mechanistic perspectives for probiotic functionality and safety applications. METHODS: L. plantarum 12-3 was isolated from Tibetan kefir grains and, subsequently, Illumina and Single Molecule Real-Time (SMRT) technologies were used to extract and sequence genomic DNA from this organism. After performing pan-genomic and phylogenetic analysis, Average Nucleotide Identity (ANI) was used to confirm the taxonomic identity of the strain. Antibiotic resistance gene analysis was conducted using the Comprehensive Antibiotic Resistance Database (CARD). Antimicrobial susceptibility testing, and virulence gene identification were also included in our genomic analysis to evaluate food safety. Prophage, genomic islands, insertion sequences, and CRISPR-Cas sequence analyses were also carried out to gain insight into genetic components and defensive mechanisms within the bacterial genome. RESULTS: The 3.4 Mb genome of L. plantarum 12-3, was assembled with 99.1% completeness and low contamination. A total of 3234 genes with normal length and intergenic spacing were found using gene prediction tools. Pan-genomic studies demonstrated gene diversity and provided functional annotation, whereas phylogenetic analysis verified taxonomic identity. Our food safety study revealed a profile of antibiotic resistance that is favorable for use as a probiotic. Analysis of insertional sequences, genomic islands, and prophage within the genome provided information regarding genetic components and their possible effects on evolution. CONCLUSIONS: Pivotal genetic elements uncovered in this study play a crucial role in bacterial defense mechanisms and offer intriguing prospects for future genome engineering efforts. Moreover, our findings suggest further in vitro and in vivo studies are warranted to validate the functional attributes and probiotic potential of L. plantarum 12-3. Expanding the scope of the research to encompass a broader range of L. plantarum 12-3 strains and comparative analyses with other probiotic species would enhance our understanding of this organism's genetic diversity and functional properties.

Mutational analysis of FOLR1 and FOLR2 genes in children with Myelomeningocele.

Myelomeningocele (MMC) is a congenital disease. For a long time, molecular mechanism of MMC, the role of folate receptor and transporter proteins remain unclear. Folate from maternal lumen to developing embryo is carried out with the help of folate transporters (SLC46A1, SLC19A1, FOLH1 and SLC25A32) and folate receptor (FOLR1, FOLR2 and FOLR3). Due to the loss of function of these important genes, complications can facilitate the risk of MMC. This study focused on the mutational analysis of FOLR1 and FOLR2 genes in children suffering from MMC. Myelomeningocele is a rare disorder so twenty blood samples from the children were collected. Primers of selected exons for FOLR1 and FOLR2 genes were designed with the help of PrimerFox software. Extracted DNA was amplified, and PCR based mutational analysis was done to check any type of mutation/SNPs in these genes. Sanger sequencing method was performed to confirm mutation in FOLR1 and FOLR2 genes. The results showed that certain environmental factors (smoking, low socio-economic status of mother bearing MMC fetus) were found to be significantly (P<0.05) associated with MMC but no mutation in the selected exons of FOLR1 and FOLR2 genes was detected. Thus, genetic variations in the folate transporter gene may have no role in the progression of MMC in the studied population.

Assessing the probiotic potential, antioxidant, and antibacterial activities of oat and soy milk fermented with Lactiplantibacillus plantarum strains isolated from Tibetan Kefir.

Sufficient intake of probiotics has been shown to help in the digestion, protect the body against pathogenic microorganisms and boost the immune system. Recently, due to high prevalence of milk allergies and lactose intolerance in population, the non-dairy based probiotic alternative are becoming increasing popular. In this context, the oat milk and soya milk-based fermented products can be an ideal alternative for the development of Lactic acid bacteria bacteria based probiotics. These bacteria can not only improve the product's flavor and bioavailability but also increases its antibacterial and antioxidant capabilities due to fermentation process. The purpose of the resent work was to assess the antioxidant and probiotic properties of oat and soy milk that had been fermented with three different strains of Lactiplantibacillus plantarum (L. plantarum) including L. plantarum 12-3, L. plantarum K25, and L. plantarum YW11 isolated from Tibetan Kefir. Different validated assays were used to evaluate the probiotic properties, adhesion and survival in the digestive system (stomach, acid and bile salts resistance), antioxidant and antimicrobial activities and safety (ABTS and DPPH scavenging assays) of these strains. Results of the study showed that soya milk and oat milk fermented with L. plantarum strains possess promising probiotic, antibacterial and antioxidant properties. These results can be helpful to produce dairy-free probiotic replacements, which are beneficial for those who are unable to consume dairy products due to dietary or allergic restrictions.

Rapid detection of micronutrient components in infant formula milk powder using near-infrared spectroscopy.

In order to achieve rapid detection of galactooligosaccharides (GOS), fructooligosaccharides (FOS), calcium (Ca), and vitamin C (Vc), four micronutrient components in infant formula milk powder, this study employed four methods, namely Standard Normal Variate (SNV), Multiplicative Scatter Correction (MSC), Normalization (Nor), and Savitzky-Golay Smoothing (SG), to preprocess the acquired original spectra of the milk powder. Then, the Competitive Adaptive Reweighted Sampling (CARS) algorithm and Random Frog (RF) algorithm were used to extract representative characteristic wavelengths. Furthermore, Partial Least Squares Regression (PLSR) and Support Vector Regression (SVR) models were established to predict the contents of GOS, FOS, Ca, and Vc in infant formula milk powder. The results indicated that after SNV preprocessing, the original spectra of GOS and FOS could effectively extract feature wavelengths using the CARS algorithm, leading to favorable predictive results through the CARS-SVR model. Similarly, after MSC preprocessing, the original spectra of Ca and Vc could efficiently extract feature wavelengths using the CARS algorithm, resulting in optimal predictive outcomes via the CARS-SVR model. This study provides insights for the realization of online nutritional component detection and optimization control in the production process of infant formula.

In silico explorations of bacterial mercuric reductase as an ecofriendly bioremediator for noxious mercuric intoxications.

Mercury is a major pollutant in the environment due to its high concentration in the soil. In this study, a mercuric reductase was extracted from Pseudomonas aeruginosa. The sequence of the enzyme was retrieved from the literature and structural homologs were identified. The protein bonded with Mercuric compounds and their interaction was briefly studied. Autodock Vina was used to perform a molecular docking with the target protein. Results showed that the sequence consists of most of the random coil 44.74% followed by α-helix and B-turns. Moreover, the protein was predicted to have a FAD/NAD(P)-binding domain. The virulence factor prediction using different approaches of Virulentpred and VICMpred suggested that P00392 is non-toxic. Next, the mutational analyses were performed to predict the active site residues in the resulting models and to determine mutants. The results show that the enzyme is involved in the bioremediation of mercury by using in-silico techniques. Finally, molecular docking studies were conducted on the best-selected model to find the active site residues and to generate a pattern of interaction to understand the mode of action of the substrate and its catalytic activity which refers to the binding with mercury.

A Huffman code LSB based image steganography technique using multi-level encryption and achromatic component of an image.

In the recent couple of years, due to the accelerated popularity of the internet, various organizations such as government offices, military, private companies, etc. use different transferring methods for exchanging their information. The Internet has various benefits and some demerits, but the primary bad mark is security of information transmission over an unreliable network, and widely uses of images. So, Steganography is the state of the art of implanting a message in the cover objects, that nobody can suspect or identify it. Therefore, in the field of cover steganography, it is very critical to track down a mechanism for concealing data by utilizing different blends of compression strategies. Amplifying the payload limit, and robustness, and working on the visual quality are the vital factors of this research to make a reliable mechanism. Different cover steganography research strategies have been recommended, and each adores its benefits and impediments but there is a need to foster some better cover steganography implements to accomplish dependability between the essential model of cover steganography. To handle these issues, in this paper we proposed a method in view of Huffman code, Least Significant Bits (LSB) based cover steganography utilizing Multi-Level Encryption (MLE) and colorless part (HC-LSBIS-MLE-AC) of the picture. It also used different substitution and flicking concepts, MLE, Magic matrix, and achromatic concepts for proving the proficiency, and significance of the method. The algorithm was also statistically investigated based on some Statistical Assessment Metrics (SAM) such as Mean Square Error (MSE), Peak Signal Noise Ratio (PSNR), Normalized Cross Correlation (NCC), Structural Similarity Index Metric (SSIM), etc. and different perspectives. The observational outcomes show the likelihood of the proposed algorithm and the capacity to give unwavering quality between security, payload, perception, computation, and temper protection.

Dietary Implications of the Bidirectional Relationship between the Gut Microflora and Inflammatory Diseases with Special Emphasis on Irritable Bowel Disease: Current and Future Perspective.

The immune system is vital for safeguarding the human body against infections and inflammatory diseases. The role of diet and meal patterns in modulating immune function is complex, and highlighting this topic is crucial for identifying potential ways to improve immune health. In Europe, the Mediterranean diet and Western diet are the most common dietary patterns, and gaining an understanding of how they affect immune function is essential for public health. There are numerous inflammatory diseases that are observed in younger and older people. Some of the common diseases include polymyalgia rheumatica (PMR), spinal muscular atrophy (SMA), vasculitis, sarcopenia, cirrhosis, cancer, and fibromyalgia, but the main focus in this review article is on irritable bowel disease (IBD). In general, dietary choices can have an immense impact on the microbial flora of the gut in people with inflammatory diseases. The intake of Mediterranean-style foods promotes the growth of healthy bacteria that enhances the function of the immune system. On the other hand, it is mostly seen that the intake of Western-style foods leads to the growth of harmful gut bacteria that contributes to inflammation and disease development by weakening the immune system. Additionally, inflammation in the gut can impact brain function, leading to mood disorders, such as anxiety and depression. Rare inflammatory diseases, such as psoriasis and sarcoidosis, are of main interest in this article. All the above-mentioned common and rare inflammatory diseases have a certain relationship with the microbiota of the gut. The gut microbiome plays a significant role in IBD; fiber and prebiotic interventions may represent promising adjunct therapies for pediatric IBD by targeting the gut microbiome. By advancing a good overall arrangement of microorganisms in the stomach through dietary mediations, working on the side effects and alleviating of diseases might be conceivable. The gut microbiota can be affected differently by various dietary fatty acid types. There is also an involvement of genetics in the progression of IBD, such as transcriptional factors, and one gene of interest is the LCT gene, which encodes for lactase, an enzyme responsible for digesting lactose in the gut.

Towards monitoring of antimicrobial resistance in the environment: For what reasons, how to implement it, and what are the data needs?

Antimicrobial resistance (AMR) is a global threat to human and animal health and well-being. To understand AMR dynamics, it is important to monitor resistant bacteria and resistance genes in all relevant settings. However, while monitoring of AMR has been implemented in clinical and veterinary settings, comprehensive monitoring of AMR in the environment is almost completely lacking. Yet, the environmental dimension of AMR is critical for understanding the dissemination routes and selection of resistant microorganisms, as well as the human health risks related to environmental AMR. Here, we outline important knowledge gaps that impede implementation of environmental AMR monitoring. These include lack of knowledge of the 'normal' background levels of environmental AMR, definition of high-risk environments for transmission, and a poor understanding of the concentrations of antibiotics and other chemical agents that promote resistance selection. Furthermore, there is a lack of methods to detect resistance genes that are not already circulating among pathogens. We conclude that these knowledge gaps need to be addressed before routine monitoring for AMR in the environment can be implemented on a large scale. Yet, AMR monitoring data bridging different sectors is needed in order to fill these knowledge gaps, which means that some level of national, regional and global AMR surveillance in the environment must happen even without all scientific questions answered. With the possibilities opened up by rapidly advancing technologies, it is time to fill these knowledge gaps. Doing so will allow for specific actions against environmental AMR development and spread to pathogens and thereby safeguard the health and wellbeing of humans and animals.

Delpinium uncinatum mediated green synthesis of AgNPs and its antioxidant, enzyme inhibitory, cytotoxic and antimicrobial potentials.

Green synthesis of nanoparticles is becoming a method of choice for biological research due to its environmentally benign outcomes, stability and ease of synthesis. In this study, silver nanoparticles (AgNPs) were synthesized using stem (S-AgNPs), root (R-AgNPs) and mixture of stem and root (RS-AgNPs) of Delphinium uncinatum. The synthesized nanoparticles were characterized by standardized techniques and evaluated for their antioxidant, enzyme inhibition, cytotoxic and antimicrobial potentials. The AgNPs exhibited efficient antioxidant activities and considerable enzyme inhibition potential against alpha amylase, acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzymes. S-AgNPs showed strong cytotoxicity against human hepato-cellular carcinoma cells (HepG2) and high enzyme inhibitory effect (IC50 values 27.5µg/ml for AChE and 22.60 µg/ml for BChE) compared to R-AgNPs and RS-AgNPs. RS-AgNPs showed significant inhibition of Klebsiella pneumoniae and Aspergillus flavus and exhibited higher biocompatibility (<2% hemolysis) in human red blood cells hemolytic assays. The present study showed that biologically synthesized AgNPs using the extract of various parts of D. uncinatum have strong antioxidant and cytotoxic potentials.

Particle Nanoarchitectonics for Nanomedicine and Nanotherapeutic Drugs with Special Emphasis on Nasal Drugs and Aging.

Aging is a multifunctional physiological manifestation. The nasal cavity is considered a major site for easy and cost-effective drug and vaccine administration, due to high permeability, low enzymatic activity, and the presence of a high number of immunocompetent cells. This review article primarily focuses on aging genetics, physical parameters, and the use of nanoparticles as delivery systems of drugs and vaccines via the nasal cavity. Studies have identified various genes involved in centenarian and average-aged people. VEGF is a key mediator involved in angiogenesis. Different therapeutic approaches induce vascular function and angiogenesis. FOLR1 gene codes for folate receptor alpha protein that helps in regulating the transport of vitamin B folate, 5-methyltetrahydrofolate and folate analogs inside the cell. This gene also aids in slowing the aging process down by cellular regeneration and promotes healthy aging by reducing aging symptoms. It has been found through the literature that GATA 6, Yamanaka factors, and FOLR1 work in synchronization to induce healthy and delayed aging. The role and applications of genes including CBS, CISD, SIRT 1, and SIRT 6 play a significant role in aging.

Genome Investigation and Functional Annotation of Lactiplantibacillus plantarum YW11 Revealing Streptin and Ruminococcin-A as Potent Nutritive Bacteriocins against Gut Symbiotic Pathogens.

All nutrient-rich feed and food environments, as well as animal and human mucosae, include lactic acid bacteria known as Lactobacillus plantarum. This study reveals an advanced analysis to study the interaction of probiotics with the gastrointestinal environment, irritable bowel disease, and immune responses along with the analysis of the secondary metabolites' characteristics of Lp YW11. Whole genome sequencing of Lp YW11 revealed 2297 genes and 1078 functional categories of which 223 relate to carbohydrate metabolism, 21 against stress response, and the remaining 834 are involved in different cellular and metabolic pathways. Moreover, it was found that Lp YW11 consists of carbohydrate-active enzymes, which mainly contribute to 37 glycoside hydrolase and 28 glycosyltransferase enzyme coding genes. The probiotics obtained from the BACTIBASE database (streptin and Ruminococcin-A bacteriocins) were docked with virulent proteins (cdt, spvB, stxB, and ymt) of Salmonella, Shigella, Campylobacter, and Yersinia, respectively. These bacteria are the main pathogenic gut microbes that play a key role in causing various gastrointestinal diseases. The molecular docking, dynamics, and immune simulation analysis in this study predicted streptin and Ruminococcin-A as potent nutritive bacteriocins against gut symbiotic pathogens.

HPLC, FTIR and GC-MS Analyses of Thymus vulgaris Phytochemicals Executing In Vitro and In Vivo Biological Activities and Effects on COX-1, COX-2 and Gastric Cancer Genes Computationally.

Medicinal plants have played an essential role in the treatment of various diseases. Thymus vulgaris, a medicinal plant, has been extensively used for biological and pharmaceutical potential. The current study was performed to check the biopotential of active biological compounds. The GC-MS analysis identified 31 compounds in methanolic crude extract, among which thymol, carvacrol, p-cymene, and eugenol are the main phytoconstituents present in T. vulgaris. The HPLC analysis quantified that flavonoids and phenolic acids are present in a good concentration in the active fraction of ethyl acetate and n-butanol. FTIR confirmed the presence of functional groups such as phenols, a carboxylic group, hydroxy group, alcohols, and a benzene ring. Among both fractions, ethyl acetate showed high antioxidant activity in the DPPH (84.1 0.88) and ABTS (87.1 0.89) assays, respectively. The anti-inflammatory activity of the fractions was done in vitro and in vivo by using a carrageenan-induced paw edema assay, while the hexane-based extract showed high anti-inflammatory activity (57.1 0.54) in a dose-response manner. Furthermore, the lead compound responsible for inhibition in the denaturation of proteins is thymol, which exhibits the highest binding affinity with COX1 (-6.4 KJ/mol) and COX2 (-6.3 KJ/mol) inflammatory proteins. The hepatotoxicity analysis showed that plant-based phytoconstituents are safe to use and have no toxicity, with no necrosis, fibrosis, and vacuolar degeneration, even at a high concentration of 800 mg/kg body weight. Furthermore, the in silico analysis of HPLC phytochemical compounds against gastric cancer genes showed that chlorogenic acid exhibited anticancer activity and showed good drug-designing characteristics. Thrombolysis and hemolysis are the major concerns of individuals suffering from gastric cancer. However, the T. vulgaris fractions showed thrombolysis from 17.6 to 5.4%; similarly, hemolysis ranged from 9.73 to 7.1% at a concentration of 12 mg/mL. The phytoconstituents present in T. vulgaris have the potential for multiple pharmacological applications. This should be further investigated to isolate bioactive compounds that can be used for the treatment of different ailments.

Dynamic change of bacterial diversity, metabolic pathways, and flavor during ripening of the Chinese fermented sausage.

Chinese fermented sausage is a famous fermented meat product with a complex microbiota that has a potential impact on flavor and quality. In this study, Lactobacillus plantarum MSZ2 and Staphylococcus xylosus YCC3 were used as starter cultures to investigate the change in bacterial diversity, metabolic pathways, and flavor compounds during the ripening process of fermented sausages. High-throughput sequencing technology and headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC/MS) were applied for characterizing the profiles of bacterial diversity, metabolic pathways, and flavor compounds in sausage samples on days 0, 6, and 12 during ripening. Results showed that Lactobacillus, Staphylococcus, Lactococcus, Leuconostoc, and Weissella were the most abundant bacterial genera found in the sausage samples during all stages of fermentation. Functional prediction reveals the abundance of 12 different metabolic pathways, the most important pathways are carbohydrate metabolism, nucleotide metabolism, lipid metabolism, and amino acid metabolism. A total of 63 volatile compounds were successfully identified in fermented sausage samples. Correlational analysis demonstrated that Staphylococcus and Leuconostoc were closely related to the formation of flavor compounds. Therefore, the present study may provide guidance for future use of microbiota to improve flavor, quality, and preservation of fermented sausages.

Hepatoprotective effects of walnut oil and Caralluma tuberculata against paracetamol in experimentally induced liver toxicity in mice.

Walnut Oil and Caralluma are edible and form part of the traditional medicine system in many countries. These are frequently used in traditional medicine as remedies to relieve a wide range of illnesses and health problems. Walnut Oil and Caralluma species have demonstrated anti-inflammatory, anti-nociceptive, antidiabetics, hepatoprotective, gastric mucosa protecting, antimalarial, antioxidant, anti-trypanosomal, appetite suppressant and cytotoxic activities. The current study was planned to study the impacts of 21 days' oral administration of walnut oil and methanolic extract of Caralluma tuberculata on the levels of some liver-associated parameters and hematological parameters in paracetamol intoxicated mice. It was observed that paracetamol intoxication resulted in a considerable rise in serum ALT, cholesterol, triglycerides, Creatinine, and urea levels while a decrease in HDL level in comparison to mice normal control group (P<0.05). Serum ALT, cholesterol, triglycerides, creatinine, and urea levels of mice that were administered with walnut oil and methanolic extract of C. tuberculata at the doses of (1 ml/kg, 2 ml/kg and 3 ml/kg body weight) were significantly lower when compared to toxic control mice group (P<0.05), While HDL level was significantly increased. The significant reduction had also been observed in the levels of serum parameters of mice group, which received standard hepato-protective drug i.e., vitamin C, at the dose of 8 mg/kg body weight (P<0.05). Based on these results, it was evident that liver toxicity caused by the paracetamol administration has recovered toward the normal range by the walnut oil and C. tuberculata extract. Therefore, the present study revealed that (walnut oil and C. tuberculata) exhibit hepatoprotective activities in paracetamol intoxicated mice.

Immunoinformatics Approach to Design Multi-Epitope-Based Vaccine against Machupo Virus Taking Viral Nucleocapsid as a Potential Candidate.

The family members of Arenaviridae include members of the genus Machupo virus, which have bi-segmented negative sense RNA inside the envelope and can be transferred to humans through rodent carriers. Machupo virus, a member of the mammarenavirus genus, causes Bolivian hemorrhage fever, its viral nucleocapsid protein being a significant virulence factor. Currently, no treatment is available for Bolivian hemorrhage fever and work to develop a protective as well as post-diagnosis treatment is underway. Adding to these efforts, this study employed a reverse-vaccinology approach to design a vaccine with B and T-cell epitopes of the viral nucleocapsid protein of the Machupo virus. Five B-cell specific, eight MHC-I restricted, and 14 MHC-II restricted epitopes were finalized for the construct based on an antigenicity score of >0.5 and non-allergenicity as a key characteristic. The poly-histidine tag was used to construct an immunogenic and stable vaccine construct and 50S ribosomal 46 protein L7/L12 adjuvant with linkers (EAAAK, GPGPG, and AYY). It covers 99.99% of the world's population, making it highly efficient. The physicochemical properties like the aliphatic index (118.31) and the GRAVY index (0.302) showed that the vaccine is easily soluble. The overall Ramachandran score of the construct was 90.7%, and the instability index was 35.13, endorsing a stable structure. The immune simulations demonstrated a long-lasting antibody response even after the excretion of the antigen from the body in the first 5 days of injection. The IgM + IgG titers were predicted to rise to 6000 10 days post-injection and were illustrated to be stable (around 3000) after a month, elucidating that the vaccine would be effective and provide enduring protection. Lastly, the molecular interaction between the construct and the IKBKE receptor was significant and a higher eigenfactor value in MD simulations confirmed the stable molecular interaction between the receptor and the vaccine, validating our construct.

Multi-scale-average-filter-assisted level set segmentation model with local region restoration achievements.

Segmentation of noisy images having light in the background it is a challenging task for the existing segmentation approaches and methods. In this paper, we suggest a novel variational method for joint restoration and segmentation of noisy images which are having intensity and inhomogeneity in the existence of high contrast light in the background. The proposed model combines statistical local region information of circular regions centered at each pixel with a multi-phase segmentation technique enabling inhomogeneous image restoration. The proposed model is written in the fuzzy set framework and resolved through alternating direction minimization approach of multipliers. Through experiments, we have tested the performance of the suggested approach on diverse types of synthetic and real images in the existence of intensity and in-homogeneity; and evaluate the precision, as well as, the robustness of the suggested model. Furthermore, the outcomes are, then, compared with other state-of-the-art models including two-phase and multi-phase approaches and show that our method has superiority for images in the existence of noise and inhomogeneity. Our empirical evaluation and experiments, using real images, evaluate and assess the efficiency of the suggested model against several other closest rivals. We observed that the suggested model can precisely segment all the images having brightness, diffuse edges, high contrast light in the background, and inhomogeneity.