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Byline: M. Niamatullah, M. Sadiq, C. S Hayat H. Farid and M. Mumtaz ABSTRACT An experimental study was conducted to determine the effects of phosphorus applied by various methods in [...]

The present study was accomplished on with the objective to determine the effectiveness of various ethno-veterinary practices for the treatments of anoestrus in Nili-Ravi buffalo and to compare them with hormonal treatment. A total of 60 Nili-Ravi buffalo with the history of anoestrus maintained at Buffalo Research Institute, Pattoki, District Kasur were divided into four groups (A, B, C, D). Group A (n=15) was given orally 800 grams lens esculents moench daily for three days where as group B (n=15) was given orally about 15 grams of randia dumetorum daily for four days. Group C (n=15) was given a single intra-muscular injection of GnRH at the dose rate of 100 μg where as group D (n=15) was given no treatment and served as control. The blood samples from each buffalo were collected before the start of treatments and after the treatments, samples were taken after every three days interval from all experimental buffaloes for progesterone (P4) estimation. In group A, the percentage of buffaloes showing estrus was 46.66% whereas in animals of group B, the respective value was 66.66%. The percentage of buffaloes exhibiting estrus in group C was 73.33% and in the control group (group D) was zero %. The estrus showing animals percentages were higher with GnRH treatment than lens esculents moench and randia dumetorum treated buffaloes. In all four groups, serum progesterone concentration was below 0.25 ng/ml before the start of treatments. At estrus, the progesterone concentration was 0.33, 0.34 and 0.38 in animals of group A, B and C respectively. It was concluded that the use of GnRH treatment is more effective as compared to lens esculents moench and randia dumetorum for the treatment of anoestrus buffaloes. [ABSTRACT FROM AUTHOR]

During the present survey, 100 buffaloes were examined for lice infestation at a private cattle farm, situated in Multan, Pakistan. Ninety two percent buffaloes were infested with Haematopinus spp., 6% with Damalinia spp. and 2% with Linognathus spp. The relationship between sex of animal and different lice was also determined. It was 94.1% in females for Haematopinus spp., 5.8% for Damalinia spp. and 2.35% for Linognathus spp., while in males it was 80, 6.66 and 0 percent, respectively. The relationship between age and different species of lice was also studied and in case of Haematopinus spp., it was significantly (P<0.05) higher (100%) in age group of 41 to 100 months compared to 14.2% in age group of 21 to 40 months. For Damalinia spp. it was 14% in the age group of 21 to 40 months, while it was 0% in age group of 1-20 months. At total of 8.33% buffaloes were infested with Linognathus spp. in age group of 61-80 months. [ABSTRACT FROM AUTHOR]

The present study was conducted to investigate the prevalence of lernaeid ectoparasites in grass carp (Ctenopharyngodon idella). For this purpose, 597 fishes (Ctenopharyngodon idella) were examined for lernaeid ectoparasites at a private fish farm located in Multan, Pakistan. Four species of the genus Lernaea i.e. L. cyprinacea, L. polymorpha, L. oryzophila, and L. lophiara were recorded. It was observed that L. polymorpha had the highest (P<0.05) overall prevalence (7.54%), followed by L. cyprinacea (6.53%), Learnaea species which were not identified (2.18%), L. oryzophila and L. lophiara (0.67% each). The relationship between body weight and Lernaea infestation showed that the infection of Lernaea species was significantly (P<0.05) more prevalent in the weight group of 2501-4500g, while the parasites were not found in the weight groups of 4500-6500 and 6501-8500g. Relationship between body length and Lernaea species in fish was also calculated. According to these results, the Lernaea species had significantly (P<0.05) highest prevalence in length group of 9-14 cm and lowest in length groups of 15-20 and >20 cm. [ABSTRACT FROM AUTHOR]

Background: The genetic diversity of malaria parasites contributes to their ability to adapt to environmental changes, develop drug resistance and circumvent the host immune system. This study aimed to analyse the genetic diversity of the Pfmsp1 and Pfmsp2 genes in Plasmodium falciparum and the Pvmsp-3α gene in Plasmodium vivax isolates from District Nowshera in Pakistan., Methods: Blood samples from 124 consenting patients with uncomplicated malaria presenting to different hospitals from the Nowshera district were collected between March and August 2019, representing 28 P. falciparum and 96 P. vivax isolates. The genomic DNA extracted from the isolates were subjected to nested PCR and allele-specific analysis. Pvmsp-3α amplified fragments were further treated with restriction fragment length polymorphism (RFLP)-based Hha1 restriction enzyme., Results: Of the analyzed P. falciparum, 21 distinct alleles were detected, including 14 alleles for Pfmsp-1 and 7 alleles for Pfmsp-2. The sub-allelic families MAD20 (50%) of Pfmsp-1and FC27 (75%) of Pfmsp-2 were predominant. The multiplicity of infection (MOI) was calculated as 1.4 and 1.2 for Pfmsp-1 and Pfmsp-2, respectively, with an overall mean MOI of 1.34. In P. vivax, 4 allelic variants, Pvmsp-3α types A, B, C and D, were detected, while RFLP digestion of amplicons, detected 9 sub-allelic variants (A1-A4, B1, B2, C1, C2 and D1) at the Pvmsp-3α locus., Conclusion: This first ever report of molecular characterization of P. falciparum and P. vivax genotypes from District Nowshera, Pakistan reveals moderate to high allelic diversity in parasite population from District Nowshera, Pakistan., Competing Interests: Declarations. Ethics approval and consent to participate: The study protocol was approved by the Ethical Review Committee of Abdul Wali Khan University Mardan under the letter of AWKUM/ERC/578. Consent was obtained from all participants before conducting the study. Consent for publication: All authors have given their consent for publication of this manuscript. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Single-point mutations in the Kirsten rat sarcoma (KRAS) viral proto-oncogene are the most common cause of human cancer. In humans, oncogenic KRAS mutations are responsible for about 30% of lung, pancreatic, and colon cancers. One of the predominant mutant KRAS G12D variants is responsible for pancreatic cancer and is an attractive drug target. At the time of writing, no Food and Drug Administration (FDA) approved drugs are available for the KRAS G12D mutant. So, there is a need to develop an effective drug for KRAS G12D. The process of finding new drugs is expensive and time-consuming. On the other hand, in silico drug designing methodologies are cost-effective and less time-consuming. Herein, we employed machine learning algorithms such as K-nearest neighbor (KNN), support vector machine (SVM), and random forest (RF) for the identification of new inhibitors against the KRAS G12D mutant. A total of 82 hits were predicted as active against the KRAS G12D mutant. The active hits were docked into the active site of the KRAS G12D mutant. Furthermore, to evaluate the stability of the compounds with a good docking score, the top two complexes and the standard complex (MRTX-1133) were subjected to 200 ns MD simulation. The top two hits revealed high stability as compared to the standard compound. The binding energy of the top two hits was good as compared to the standard compound. Our identified hits have the potential to inhibit the KRAS G12D mutation and can help combat cancer. To the best of our knowledge, this is the first study in which machine-learning-based virtual screening, molecular docking, and molecular dynamics simulation were carried out for the identification of new promising inhibitors for the KRAS G12D mutant.

Nod-like receptor protein 3 (NLRP-3), is an intracellular sensor that is involved in inflammasome activation, and the aberrant expression of NLRP3 is responsible for diabetes mellitus, its complications, and many other inflammatory diseases. NLRP3 is considered a promising drug target for novel drug design. Here, a pharmacophore model was generated from the most potent inhibitor, and its validation was performed by the Gunner-Henry scoring method. The validated pharmacophore was used to screen selected compounds databases. As a result, 646 compounds were mapped on the pharmacophore model. After applying Lipinski's rule of five, 391 hits were obtained. All the hits were docked into the binding pocket of target protein. Based on docking scores and interactions with binding site residues, six compounds were selected potential hits. To check the stability of these compounds, 100 ns molecular dynamic (MD) simulations were performed. The RMSD, RMSF, DCCM and hydrogen bond analysis showed that all the six compounds formed stable complex with NLRP3. The binding free energy with the MM-PBSA approach suggested that electrostatic force, and van der Waals interactions, played a significant role in the binding pattern of these compounds. Thus, the outcomes of the current study could provide insights into the identification of new potential NLRP3 inflammasome inhibitors against diabetes and its related disorders., (© 2024. The Author(s).)

Pistacia chinensis is locally practiced for treating diabetes, pain, inflammation, and erectile dysfunction. Therefore, the current studies subjected the crude extract/fractions and the isolated compound (2-(3,4-dihydroxyphenyl)-7,8-dihydroxy-3-methoxy-4H-chromen-4-one) to α-glucosidase inhibitor and anti-glycation activities. The development of long-term complications associated with diabetes is primarily caused by chronic hyperglycemia. Regarding α-glucosidase, the most significant inhibitory effect was observed with compound 1 (93.09%), followed by the methanolic extract (80.87%) with IC50 values of 45.86 and 86.32 μM. The maximum anti-glycation potential was shown by an isolated compound 1 followed by methanolic extract with effect inhibition of 90.12 and 72.09, respectively. Compound 1 is expected to have the highest gastrointestinal absorption rate, with a predicted absorption rate of 86.156%. This indicates oral suitability. The compound 1 is expected to have no harmful effects on the liver. In addition, our docking results suggest that alpha-glucosidase and isolated compounds showed strong interaction with ILE821, GLN900, and ALA901 residues, along with a -11.95 docking score., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Monkeypox virus is an infectious agent that causes fever, Pneumonitis encephalitis, rash, lymphadenopathy and bacterial infection. The current outbreak of monkeypox has reawakened the global health concern. In the current situation of increasing viral infection, no vaccine or drug is available for monkeypox. Thus, there is an urgent need for viable vaccine development to prevent viral transmission by boosting human immunity. Herein, using immunoinformatics approaches, a multi-epitope vaccine was constructed for the Monkeypox virus. In this connection, B-Cell and T-cell epitopes were identified and joined with the help of adjutants and linkers. The vaccine construct was selected based on promising vaccine candidates and immunogenic potential. Further epitopes were selected based on antigenicity score, non-allergenicity and good immunological properties. Molecular docking reveals strong interactions between TLR-9 and the predicted vaccine construct. Finally, molecular dynamics simulations were performed to evaluate the stability and compactness of the constructed vaccine. The MD simulation results demonstrated the significant stability of the polypeptide vaccine construct. The predicted vaccine represented good stability, expression, immunostimulatory capabilities and significant solubility. Design vaccine was verified as efficient in different computer-based immune response investigations. Additionally, the constructed vaccine also represents a good population coverage in computer base analysis.Communicated by Ramaswamy H. Sarma.

Introduction: Monkeypox is a zoonotic disease caused by brick-shaped enveloped monkeypox (Mpox) virus that belongs to the family of ancient viruses known as Poxviridae. Subsequently, the viruses have been reported in various countries. The virus is transmitted by respiratory droplets, skin lesions, and infected body fluids. The infected patients experience fluid-filled blisters, maculopapular rash, myalgia, and fever. Due to the lack of effective drugs or vaccines, there is a need to identify the most potent and effective drugs to reduce the spread of monkeypox. The current study aimed to use computational methods to quickly identify potentially effective drugs against the Mpox virus., Methods: In our study, the Mpox protein thymidylate kinase (A48R) was targeted because it is a unique drug target. We screened a library of 9000 FDA-approved compounds of the DrugBank database by using various in silico approaches, such as molecular docking and molecular dynamic (MD) simulation., Results: Based on docking score and interaction analysis, compounds DB12380, DB13276, DB13276, DB11740, DB14675, DB11978, DB08526, DB06573, DB15796, DB08223, DB11736, DB16250, and DB16335 were predicted as the most potent. To examine the dynamic behavior and stability of the docked complexes, three compounds-DB16335, DB15796, and DB16250 -along with the Apo state were simulated for 300ns. The results revealed that compound DB16335 revealed the best docking score (-9.57 kcal/mol) against the Mpox protein thymidylate kinase., Discussion: Additionally, during the 300 ns MD simulation period, thymidylate kinase DB16335 showed great stability. Further, in vitro and in vivo study is recommended for the final predicted compounds., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Ajmal, Mahmood, Hayat, Hakami, Alotaibi, Umair, Abdalla, Li, He, Wadood and Hu.)

Background: Borrelia burgdorferi is regarded as an extremely dangerous bacteria causing infectious disease in humans, resulting in musculoskeletal pain, fatigue, fever and cardiac symptom. Because of all alarming concerns, no such prophylaxis setup has been available against Borrelia burgdorferi till now. In fact, vaccine construction using traditional methods is so expensive and time-consuming. Therefore, considering all concerns, we designed a multi-epitope-based vaccine design against Borrelia burgdorferi using in silico approaches., Objective: To design an effective and safe vaccine that can activate cell-mediated and humoral immunity against Borrelia burgdorferi by using various bioinformatics tools., Methods: The present study utilized different computational methodologies, covering different ideas and elements in bioinformatics tools. The protein sequence of Borrelia burgdorferi was retrieved from the NCBI database. Different B and T cell epitopes were predicated using the IEDB tool. Efficient B and T cell epitopes were further assessed for vaccine construction using linkers AAY, EAAAK and GPGPG, respectively. Furthermore, the tertiary structure of constructed vaccine was predicated, and its interaction was determined with TLR9 using ClusPro software. In addition, further atomic level detail of docked complex and their immune response were further determined by MD simulation and C-ImmSim tool, respectively., Results: A protein with immunogenic potential and good vaccine properties (candidate) was identified based on high binding scores, low percentile rank, non-allergenicity and good immunological properties, which were further used to calculate epitopes. Additionally, molecular docking possesses strong interaction; seventeen H-bonds interactions were reported, such as THR101-GLU264, THR185-THR270, ARG 257-ASP210, ARG 257-ASP 210, ASP259-LYS 174, ASN263-GLU237, CYS 265-GLU 233, CYS 265-TYR 197, GLU267- THR202, GLN 270-THR202, TYR345-ASP 210, TYR345-THR 213, ARG 346-ASN209, SER350- GLU141, SER350-GLU141, ASP 424-ARG220 and ARG426-THR216 with TLR-9. Finally, high expression was determined in E. coli (CAI = (0.9045), and GC content = (72%)). Using the IMOD server, all-atom MD simulations of docked complex affirmed its significant stability. The outcomes of immune simulation indicate that both T and B cells represent a strong response to the vaccination component., Conclusion: This type of in-silico technique may precisely decrease valuable time and expenses in vaccine designing against Borrelia burgdorferi for experimental planning in laboratories. Currently, scientists frequently utilize bioinformatics approaches that speed up their vaccine-based lab work., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the ongoing coronavirus disease 2019 (COVID-19) pandemic which has brought a great challenge to public health. After the first emergence of novel coronavirus SARS-CoV-2 in the city of Wuhan, China, in December 2019. As of March 2020, SARS-CoV-2 was first reported in Bangladesh and since then the country has experienced a steady rise in infections, resulting in 13,355,191 cases and 29,024 deaths as of 27 February 2022. Bioinformatics techniques are used to predict B cell and T cell epitopes from the new SARS-CoV-2 spike glycoprotein in order to build a unique multiple epitope vaccine. The immunogenicity, antigenicity scores, and toxicity of these epitopes were evaluated and chosen based on their capacity to elicit an immune response., Result: The best multi-epitope of the possible immunogenic property was created by combining epitopes. EAAAK, AAY, and GPGPG linkers were used to connect the epitopes. In several computer-based immune response analyses, this vaccine design was found to be efficient, as well as having high population coverage., Conclusion: This research is entirely reliant on the development of epitope-based vaccines, and these in silico findings would represent a major step forward in the development of a vaccine that might eradicate SARS-CoV-2 in Bangladeshi patients., (© 2022. The Author(s).)

Background: Burkholderia pseudomallei is an infectious agent causing severe disease melioidosis resulting in pneumonia, fever, and acute septicemia in humans. B. pseudomallei show resistance to drugs. No such FDA-approved vaccine is available against B. pseudomallei, and treatment is limited to therapy. Therefore, the scientific study was designed to develop a vaccine for B. pseudomallei. The protein sequence of B. pseudomallei was retrieved from NCBI. B-cell and T-cell epitopes were identified and further screened for allergenicity, antigenicity docking, and simulation., Results: Here, in this study, in silico approach was applied to design a multi-epitope subunit vaccine peptide consisting of linear B-cell and T-cell epitopes of proteins considered to be potential novel vaccine candidates. Peptide epitopes were joined by adjuvant and EAAAK, CPGPG, and AAY linkers. This constructed vaccine was subjected to in silico immune simulations by C-ImmSim. The protein construct was cloned into PET28a (+) vector for expression study in Escherichia coli using SnapGene., Conclusion: The designed multi-epitope vaccine was analyzed for its physicochemical, structural, and immunological characteristics, and it was found to be antigenic, soluble, stable, nonallergenic, and have a high affinity to its target receptor. The immune simulation studies were carried out on the C-ImmSim showing increased production of cellular and humoral responses indicating that the constructed vaccine proved effective and able to provoke humoral and cell-mediated response immune responses. In silico study could be a breakthrough in designing effective vaccines to eradicate B. pseudomallei globally., (© 2022. The Author(s).)

Cancer is one of the deadliest complex diseases having multigene nature where the role of single-nucleotide polymorphism (SNP) has been well explored in multiple genes. TOX high mobility group box family member 3 ( TOX3 ) is one such gene, in which SNPs have been found to be associated with breast cancer. In this study, we have examined the potentially damaging nonsynonymous SNPs(nsSNPs) in TOX3 gene using in silico tools, namely PolyPhen2, SNP&GO, PhD-SNP and PROVEAN, which were further confirmed by I-Mutant, MutPred1.2 and ConSurf for their stability, functional and structural effects. nsSNPs rs368713418 (A266D), rs751141352 (P273S, P273T), rs200878352 (A275T) have been found to be the most deleterious that may have a vital role in breast cancer. Premature stop codon producing SNPs (Q527STOP), rs1259790811 (G495STOP), rs1294465822 (S395STOP) and rs1335372738 (G8STOP) were also found having prime importance in truncated and malfunctional protein formation. We also characterized regulatory SNPs for its potential effect on TOX3 gene regulation and found nine SNPs that may affect the gene regulation. Further, we have also designed 3D models using I-TASSER for the wild type and four mutant TOX3 proteins. Our study concludes that these SNPs can be of prime importance while studying breast cancer and other associated diseases as well. They are required to be studied in model organisms and cell cultures, and may have potential importance in personalized medicines and gene therapy.