Morpometric and molecular characterization of Surguli goat through CO1 gene in district Kohat.

The present study was designed with the aim to study morphometric characterization as well as phylogeny and diversity of the local Surguli goat at their breeding tract district Kohat through mitochondrial DNA region, i.e., Cytochrome C Oxidase Subunit One (CO1) gene. Morphometric data and blood samples were collected from thirty (30) pure goats. Morphometric analysis showed that sex had significant effect (p < 0.05) on body weight, body length, hearth girth and horn length while no significant effect (p > 0.05) was observed for other characteristics. The results also indicated that age had significant effect (p < 0.05) on height at rump, ear length, horn length and tail length while no significant effect (p > 0.05) was observed for other characteristics. The phylogenetic analysis through CO1 nucleotide sequences within nucleotide range 1-767 showed nine polymorphic sites segregating into eight haplotypes. The mean intraspecific diversity and mean interspecific diversity were calculated as 0.23 and 2.36%, respectively. Phylogenetic tree revealed that Capra Ibex and native Surguli goat have common ancestors. The morphometric and molecular results obtained from the present study can be exploited as a selection tool for breeding and overall improvement.

Exploring the Role of Platelets in Virus-Induced Inflammatory Demyelinating Disease and Myocarditis.

Theiler's murine encephalomyelitis virus (TMEV) infection has been used as a mouse model for two virus-induced organ-specific immune-mediated diseases. TMEV-induced demyelinating disease (TMEV-IDD) in the central nervous system (CNS) is a chronic inflammatory disease with viral persistence and an animal model of multiple sclerosis (MS) in humans. TMEV infection can also cause acute myocarditis with viral replication and immune cell infiltration in the heart, leading to cardiac fibrosis. Since platelets have been reported to modulate immune responses, we aimed to determine the role of platelets in TMEV infection. In transcriptome analyses of platelets, distinct sets of immune-related genes, including major histocompatibility complex (MHC) class I, were up- or downregulated in TMEV-infected mice at different time points. We depleted platelets from TMEV-infected mice by injecting them with platelet-specific antibodies. The platelet-depleted mice had significantly fewer viral antigen-positive cells in the CNS. Platelet depletion reduced the severities of TMEV-IDD and myocarditis, although the pathology scores did not reach statistical significance. Immunologically, the platelet-depleted mice had an increase in interferon (IFN)-γ production with a higher anti-TMEV IgG2a/IgG1 ratio. Thus, platelets may play roles in TMEV infection, such as gene expression, viral clearance, and anti-viral antibody isotype responses.

Association of polymorphism in the promotor area of the caprine BMPR1B gene with litter size and body measurement traits in Damani goats.

This study aimed to explore polymorphisms in the promoter region of the caprine BMPR1B (Bone morphogenetic protein receptor 1 beta) gene and its association with body measurement and litter size traits in Damani does. A total of 53 blood samples were collected to analyze the association between the BMPR1B gene polymorphism and 11 phenotypic traits in Damani female goats. The results revealed that three novel SNPs were identified in the promoter region of the caprine BMPR1B gene, including g.67 A > C (SNP1), g.170 G > A(SNP2), and g.501A > T (SNP3), among which the SNP1 and SNP2 were significantly (p < 0.05) associated with litter size and body measurement traits in Damani goats. In SNP1 the AC genotype could be used as a marker for litter size, and the CC genotype for body weight in Damani goats. In SNP2, the genotype GG was significantly (p < 0.05) associated with ear and head length. Therefore, we can conclude from the present study, that genetic variants AC and CC of the caprine BMPR1B gene could be used as genetic markers for economic traits through marker-assisted selection for the breed improvement program of the Damani goat.

Multinomial classification of NLRP3 inhibitory compounds based on large scale machine learning approaches.

The role of NLRP3 inflammasome in innate immunity is newly recognized. The NLRP3 protein is a family of nucleotide-binding and oligomerization domain-like receptors as well as a pyrin domain-containing protein. It has been shown that NLRP3 may contribute to the development and progression of a variety of diseases, such as multiple sclerosis, metabolic disorders, inflammatory bowel disease, and other auto-immune and auto-inflammatory conditions. The use of machine learning methods in pharmaceutical research has been widespread for several decades. An important objective of this study is to apply machine learning approaches for the multinomial classification of NLRP3 inhibitors. However, data imbalances can affect machine learning. Therefore, a synthetic minority oversampling technique (SMOTE) has been developed to increase the sensitivity of classifiers to minority groups. The QSAR modelling was performed using 154 molecules retrieved from the ChEMBL database (version 29). The accuracy of the multiclass classification top six models was found to fall within ranges of 0.99 to 0.86, and log loss ranges of 0.2 to 2.3, respectively. The results showed that the receiver operating characteristic curve (ROC) plot values significantly improved when tuning parameters were adjusted and imbalanced data was handled. Moreover, the results demonstrated that SMOTE offers a significant advantage in handling imbalanced datasets as well as substantial improvements in overall accuracy of machine learning models. The top models were then used to predict data from unseen datasets. In summary, these QSAR classification models exhibited robust statistical results and were interpretable, which strongly supported their use for rapid screening of NLRP3 inhibitors.

Detection of A2A2 genotype of beta casein protein (CSN2) gene in local, exotic and cross bred cattle in Pakistan.

Genetic variants of bovine Beta-casein protein (CSN2) gene especially A1 and A2 are the most important variants in dairy cattle. A1 milk protein is considered as risk factor for different disease and milk intolerance which release Beta-Casomorphin-7 during digestion which is a bioactive opioid but not released from A2 milk protein. This opioid is responsible for several human health problems like Coronary Heart disease, type 1 diabetics, milk intolerance and other neurological disorders. In present study, 360 blood sample were collected from Lohani, Achai, jersey, Holstein Friesian, Achai x jersey, Friesian x Sahiwal and Sahiwal x Friesian from different region of Khyber Pakhtunkhwa (KP) province. The polymerase chain reaction (PCR) amplicons were sequenced for the identification of polymorphism in exon 7 of Beta-casein protein (CSN2) gene. Sequencing analysis explored CSN2 genotype in exon 7 using the Genomic sequence from GenBank (X.71104) g.8101 C > A at codon 67. The allelic and genotypic frequencies of CSN2 gene were analyzed and observed that Holstein Friesian cattle exhibited A1A2 33%, A1A1 50% and A2A2 17%, Jersey cattle show 68% A1A1, 18% A1A2 and 14% A2A2, Sahiwal x Friesian 56% A1A1, 26% A1A2 and 18% A2A2, Jersey × Achai 78% A2A2, 15% A1A2 and 7% A1A1, Achai 100% A2A2 Lohani 100% A2A2. This is a preliminary study, conducted with meager resources, therefore, it is very difficult to make conclusion that which particular breed possess harmful alleles and which breed possess useful alleles of beta-casein gene. Therefore, a comprehensive molecular work is needed to be performed with greater number of samples sequencing.

Bioinformatics and genetic variants analysis of FGF10 gene promoter with their association at carcass quality and body measurement traits in Qinchuan beef cattle.

The fibroblast growth factor 10 (FGF10) gene regulates adipogenesis and myogensis. In this study, sequencing of FGF10 prompter region identified three SNPs at loci g.78G > A, g.116C > T and g.201A > T. Each SNP yields three genotypes as GG, GA and AA at loci g.78G > A, CC, CT and TT at loci g.116C > T and AA, AT and TT at loci g.201A > T. Allelic and genotypic frequencies of all three SNPs deviated from the Hardy-Weinberg equilibrium (HWE) (P < 0.05) and were found highly polymorphic as PIC (0.25 < PIC < 0.50). Moreover, we found highest LD (D'/γ2) between SNP2 and SNP3 (0.989/0.909), followed by SNP1 and SNP3 (0.944/0.796). Moreover, three variants of FGF10 gene promoter exhibited significant (P < 0.05) association with body measurement and carcass quality traits in Qinchuan beef cattle. At loci g.78G > A, the genotype GG showed significantly (P < 0.01) larger body length (BL), rump length (RL), chest depth (CD), chest circumference (CC) and ultrasound loin area (ULA). The genotype TC at loci g.116C > T showed significantly (P < 0.01 and 0.05) larger body measurement and intramuscular fat, and ultrasound loin area (ULA). In addition to that, at loci g.201A > T, genotype TT showed significantly (P < 0.01 and P < 0.05) larger body length (BL), rump length (RL), hip width (HW), chest circumference (CC) and ultrasound loin area (ULA). Additionally, screening of promoter sequence of FGF10 gene explored loss of four TFs binding sites (KLF3, ZNF37α, GLIS2 and BCL11A) at g.116C > T because of SNP2. However, a single TF binding site was lost at g.202A > T due to SNP3. Interestingly, none of TF binding site was lost at g.78G > A in SNP1; however, one new TF binding site was gained at this location due to SNP1. These findings conclude that genotype GG, TC and TT could be used as genetic markers of FGF10 gene for body measurement and carcass quality traits in Qinchuan beef cattle.

The growth curve determination and economic trait correlation for Qinchuan bull population.

Carcass weight, as a measure of meat yield, and body measurements are directly correlated traits in livestock. However, longitudinally collected phenotype records of local breeds are not comprehensive. The research was performed on Qinchuan bull population to understand their growth and development, and data from Qinchuan bull that was weighed and measured at birth, 6, 12, 18, and 24 months of age was analyzed. Furthermore, Logistic, Brody, Gompertz, and Bertallanffy were used to fit the growth curves for weight and body size traits. The results showed that the four curve models have good fitting degrees for the weight and body size (R2 > 0.99), and the Bertallanffy model exhibited a good fit to the measured data of body weight, and the model estimated the inflection point of body weight as (5.43 months of age, 122.01 kg). Particularly, the limited mature body weight can reach 557.8 kg by the Brody model. Body weight was significantly positively correlated with body height, hip height, body length, chest circumference, abdominal girth, and calf girth (p < 0.0001), and the correlation between body weight and body length was the highest (r = 0.975). The regression equation predicting body weight was Y = -275.691 + 3.28 X3 + 1.311 X4 - 0.397 X5.

Comprehensive Analysis of Compressible Perceptual Encryption Methods-Compression and Encryption Perspectives.

Perceptual encryption (PE) hides the identifiable information of an image in such a way that its intrinsic characteristics remain intact. This recognizable perceptual quality can be used to enable computation in the encryption domain. A class of PE algorithms based on block-level processing has recently gained popularity for their ability to generate JPEG-compressible cipher images. A tradeoff in these methods, however, is between the security efficiency and compression savings due to the chosen block size. Several methods (such as the processing of each color component independently, image representation, and sub-block-level processing) have been proposed to effectively manage this tradeoff. The current study adapts these assorted practices into a uniform framework to provide a fair comparison of their results. Specifically, their compression quality is investigated under various design parameters, such as the choice of colorspace, image representation, chroma subsampling, quantization tables, and block size. Our analyses have shown that at best the PE methods introduce a decrease of 6% and 3% in the JPEG compression performance with and without chroma subsampling, respectively. Additionally, their encryption quality is quantified in terms of several statistical analyses. The simulation results show that block-based PE methods exhibit several favorable properties for the encryption-then-compression schemes. Nonetheless, to avoid any pitfalls, their principal design should be carefully considered in the context of the applications for which we outlined possible future research directions.

Anti-Glycolipid Antibody Examination in Five EAE Models and Theiler's Virus Model of Multiple Sclerosis: Detection of Anti-GM1, GM3, GM4, and Sulfatide Antibodies in Relapsing-Remitting EAE.

Anti-glycolipid antibodies have been reported to play pathogenic roles in peripheral inflammatory neuropathies, such as Guillain-Barré syndrome. On the other hand, the role in multiple sclerosis (MS), inflammatory demyelinating disease in the central nervous system (CNS), is largely unknown, although the presence of anti-glycolipid antibodies was reported to differ among MS patients with relapsing-remitting (RR), primary progressive (PP), and secondary progressive (SP) disease courses. We investigated whether the induction of anti-glycolipid antibodies could differ among experimental MS models with distinct clinical courses, depending on induction methods. Using three mouse strains, SJL/J, C57BL/6, and A.SW mice, we induced five distinct experimental autoimmune encephalomyelitis (EAE) models with myelin oligodendrocyte glycoprotein (MOG)35-55, MOG92-106, or myelin proteolipid protein (PLP)139-151, with or without an additional adjuvant curdlan injection. We also induced a viral model of MS, using Theiler's murine encephalomyelitis virus (TMEV). Each MS model had an RR, SP, PP, hyperacute, or chronic clinical course. Using the sera from the MS models, we quantified antibodies against 11 glycolipids: GM1, GM2, GM3, GM4, GD3, galactocerebroside, GD1a, GD1b, GT1b, GQ1b, and sulfatide. Among the MS models, we detected significant increases in four anti-glycolipid antibodies, GM1, GM3, GM4, and sulfatide, in PLP139-151-induced EAE with an RR disease course. We also tested cellular immune responses to the glycolipids and found CD1d-independent lymphoproliferative responses only to sulfatide with decreased interleukin (IL)-10 production. Although these results implied that anti-glycolipid antibodies might play a role in remissions or relapses in RR-EAE, their functional roles need to be determined by mechanistic experiments, such as injections of monoclonal anti-glycolipid antibodies.

The efficiency of boric acid as an alternate to NaCl for the preservation of cattle hides.

The fresh buffalo hides (n = 6) were cut into two equal parts and categorized into three equal groups. The first group was treated with 50% NaCl; the second group hides were treated with 5% of boric acid (BA), and the third group hides were with NaCl + BA (10:1). Hair loss was seen at the sample margins of hides treated with 50% NaCl, with a slight odor. In the second group, there was neither hair loss nor a pungent smell was felt. The nitrogen content of the preserved hide was measured at different durations during the experimental period, i.e., 0 h, 24 h on day 7th, and day 14th. The nitrogen level reduced significantly (P < 0.05) from 0 h to day 14th of the experiment in hides treated with 50% of NaCl and 5% of boric acid, while this trend was found non-significant (P > 0.05) in hides treated with the combination of NaCl + BA. At 0 h, the moisture content for 50% of NaCl-treated hides was 64.82 ± 0.38% moisture content for 5% of boric acid was 63.89 ± 0.59, while for the NaCl + BA combination 61.69 ± 1.09 was observed. Moisture content for 50% of NaCl on day 14th was 38.87 ± 0.42; for boric acid, it was 37.76 ± 1.12, and for the combination of both, the moisture content was 34.56 ± 0.41%. A similar decreasing trend of moisture contents was found in hides treated with different preservatives. After 14 days of treatment, the bacterial count for 50% of NaCl was 2 × 109; for boric acid, it was 1 × 109, and for the combination of both, the bacterial count was 3 × 109. The lowest pollution load was observed hides treated with the combination of NaCl + BA (10:1). Total solids (TS) were 21.69 ± 0.57 while total dissolved solids (TDS) were 21.10 ± 0.57, and total suspended solids were 0.60 ± 0.57 mg/l. It is concluded from the present study that boric acid alone or in combination with NaCl efficiently reduced nitrogen content and bacterial count and can reduce water pollution in tannery and hence could be used as a preservative for the hide in the tannery industry.

Polymorphism and association study of lactoferrin (LF) gene with milk yield, milk composition, and somatic cell count in Beetal goats.

The sequence analysis of PCR product exhibited four novel SNPs in the promoter region of the LF gene at loci g.98T>C, g.143T>A, g.189AC>A, and g.346A>G. Each SNP yielded three genotypes; the genotypes TT (SNP1), AA (SNP3), and GG (SNP4) decreased SCC and increase milk quality traits such as density, protein, and milk yield (P < 0.01). The genotype CC (SNP2) and CA (SNP4) significantly (P < 0.01) decreased the milk quality parameters, while genotypes TC (SNP2) and GG (SNP4) showed significantly (P < 0.01) less SCC and increase lactose % in milk. Furthermore, screening of the LF promoter sequence explored the gain of four TF binding sites at locus g.98T˃C and three TF binding sites at g.346A˃G. However, the loss of four and two TF binding sites was seen at locus g.143T˃A and g.189C˃A, respectively. We can conclude from the present study that the GG, TT, and AA genotype might be utilized as genetic markers in marker-assisted selection for the breed improvement program of Beetal goats.

Effect of dietary inclusion of mealworm frass on growth, hematology, and serum biochemistry of sheep.

Frass is the main component of worm by-product which exhibit anti-microbial and anti-pathogenic properties. In the present study, we assessed the possibility of mealworm frass in sheep feeding regime and evaluated its effect on health and growth performance of sheep. A total of 09 experimental sheep (18-24 months of age) were grouped into three categories (T1, T3, and T3); each group comprised 3 animals including 2 males and 1 female. Group T1 was considered control, group T2 contains 75% commercial feed and 25 mealworm frass, and T3 was 50:50 of commercial feed and mealworm frass. The sheep in group T2 showed average weight gain of 2.9 kg; however, when the dietary inclusion increased up to 50% of mealworm frass or decreased up to 50% of concentrate feed, the average weight gain decreased up to 2.01 kg (group T3). Moreover, the sheep fed with 25% mealworm frass exhibited the lowest feed refusal percentage (6.33%) in total duration of the dietary period (6 weeks). The highest volume of RBC was found in blood collected from sheep fed within group T2 (10.22 1012/L ± 0.34), followed by sheep fed in group T3 (8.96 × 1012/L ± 0.99) (P < 0.05). Significantly (P < 0.05) highest MCV volume in fL (femtoliter) was found in group T2 (32.83 ± 0.44) followed by group T3 (31.23 ± 0.23). The animals in group T3 showed significantly (P < 0.05) highest MCHC volume (40.47 g/dL ± 0.62) followed by group T2 (38.77 ± 0.97). Similar trend was found in MPV (fL); significantly (P < 0.05) highest MPV volume was found in group T3 (12.63 ± 0.09) followed by group T2 (12.53 ± 0.33). Significantly (P < 0.05) high serum phosphorous (P) (6.00 ± 0.29), TG (60.03 ± 3.11), and TP (7.63 g/dL ± 0.23) levels were found in group T3, followed by animals in group T2. We can conclude that inclusion of mealworm frass to replace 25% commercial concentrate feed improved the growth rate and overall health status of the sheep. The present study laid a foundation for the utilization of the mealworm frass (waste product) in ruminant feeding.

Novel splicing-site mutation in DCAF17 gene causing Woodhouse-Sakati syndrome in a large consanguineous family.

BACKGROUND: Woodhouse-Sakati syndrome is a rare autosomal recessive disease with endocrine and neuroectodermal aberrations with heterogeneous phenotypes and disease course. The most common phenotypes of the disease are progressive sensorineural hearing loss and alopecia, mild-to-moderate mental retardation and hypogonadism. The disease results from mutations in the DCAF17 gene. METHOD: Here, we reported a large consanguineous pedigree with multiple affected individuals with Woodhouse-Sakati syndrome phenotypes. Laboratory tests confirmed the endocrine perturbance in affected individuals. To find out the underlying genetic change, whole-exome sequencing was carried out. RESULT: Analysis of the exome data identified a splicing-site deletion NM_025000.3:c.1423-1_1425delGACA in DCAF17 gene. Sanger sequencing confirmed the co-segregation of the variant with the disease phenotypes in the family. CONCLUSION: The variant is predicted to cause aberrant splicing, i.e., exon skipping, resulting in the translation of a truncated functionless protein which results in appearance of typical phenotypic features and clinical laboratory findings of Woodhouse-Sakati syndrome in affected members of the family.

Bioinformatics analysis and the association of polymorphisms within the caprine GDF9 gene promoter with economically useful traits in Damani goats.

The blood sample from 60 Damani does were collected and genomic DNA was extracted, and DNA integrity were investigated. A 447 bp promoter fragment of the GDF9 gene was amplified and Sanger sequenced for the identification of GDF9 gene polymorphism. Three novel SNPs were identified at positions g. 97(T > A), g. 142 (G > G) and g. 313(C > T) in the promoter region of the caprine GDF9 gene which significantly (P < 0.05) influenced litter size, body measurement, and milk production traits in Damani goats. The genotype CT of SNP1 significantly (P < 0.05) improved litter size, genotype GG of SNP2 significantly (P < 0.05) enhanced milk production, while the genotypes CC of SNP3 significant (P < 0.05) increased body measurement traits in Damani goats. Moreover, in SNP1 loss of 3 transcription factors (TF) binding sites occurred, SNP2 caused loss of two TFs binding sites, and SNP3 caused loss of a single TF binding site. Similarly, SNP1 and SNP2 caused the gain of three new potential TF binding sites, and SNP3 caused gain of two new TF binding sites. It is concluded that caprine GDF9 gene could be used as a candidate gene for litter size, milk production and body measurement traits in Damani goats through marker-assisted selection for future breeding program.

IIB-CPE: Inter and Intra Block Processing-Based Compressible Perceptual Encryption Method for Privacy-Preserving Deep Learning.

Perceptual encryption (PE) of images protects visual information while retaining the intrinsic properties necessary to enable computation in the encryption domain. Block-based PE produces JPEG-compliant images with almost the same compression savings as that of the plain images. The methods represent an input color image as a pseudo grayscale image to benefit from a smaller block size. However, such representation degrades image quality and compression savings, and removes color information, which limits their applications. To solve these limitations, we proposed inter and intra block processing for compressible PE methods (IIB-CPE). The method represents an input as a color image and performs block-level inter processing and sub-block-level intra processing on it. The intra block processing results in an inside-out geometric transformation that disrupts the symmetry of an entire block thus achieves visual encryption of local details while preserving the global contents of an image. The intra block-level processing allows the use of a smaller block size, which improves encryption efficiency without compromising compression performance. Our analyses showed that IIB-CPE offers 15% bitrate savings with better image quality than the existing PE methods. In addition, we extended the scope of applications of the proposed IIB-CPE to the privacy-preserving deep learning (PPDL) domain.

A Novel Decentralized Blockchain Architecture for the Preservation of Privacy and Data Security against Cyberattacks in Healthcare.

Nowadays, in a world full of uncertainties and the threat of digital and cyber-attacks, blockchain technology is one of the major critical developments playing a vital role in the creative professional world. Along with energy, finance, governance, etc., the healthcare sector is one of the most prominent areas where blockchain technology is being used. We all are aware that data constitute our wealth and our currency; vulnerability and security become even more significant and a vital point of concern for healthcare. Recent cyberattacks have raised the questions of planning, requirement, and implementation to develop more cyber-secure models. This paper is based on a blockchain that classifies network participants into clusters and preserves a single copy of the blockchain for every cluster. The paper introduces a novel blockchain mechanism for secure healthcare sector data management, which reduces the communicational and computational overhead costs compared to the existing bitcoin network and the lightweight blockchain architecture. The paper also discusses how the proposed design can be utilized to address the recognized threats. The experimental results show that, as the number of nodes rises, the suggested architecture speeds up ledger updates by 63% and reduces network traffic by 10 times.

Characterization and Evaluation of Antimicrobial Potential of Trigonella incise (Linn) Mediated Biosynthesized Silver Nanoparticles.

The goal of the research was to explore a new green method used to synthesize silver nanoparticles (Ag NPs) from an aqueous extract of Trigonella incise, which serves as a reducing and stabilizing agent. The obtained results showed an 85% yield of nanoparticles by using 2:5 (v/v) of 5% plant extract with a 0.5 M solution of AgNO3. Different techniques were used to characterize the synthesized Ag NPs, including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), and UV-visible spectroscopy. The UV-visible spectra of green synthesized silver nanoparticles showed maximum absorption at a wavelength of 440 nm. The FT-IR studies revealed the stretching oscillation frequency of synthesized silver nanoparticles in the absorption band near 860 cm-1. Similarly, the bending and stretching oscillation frequencies of the NH function group were assigned to the band in the 3226 cm-1 and 1647 cm-1 regions. The bending vibration of C-O at 1159 cm-1 confirmed the carbonyl functional group that was also assigned to the small intensity band in the range of 2361 cm-1. The X-ray diffraction analysis of Ag NPs revealed four distinct diffraction peaks at 2θ of 38°, 45°, 65° and 78°, corresponds to (111), (200), (220) and (311) of the face-centered cubic shape. The round shape morphology of Ag NPs with a mean diameter in the range 20-80 nm was analyzed via SEM images. Furthermore, the nanoparticles showed more significant antimicrobial activity against Salmonella typhi (S. typhi) and Staphylococcus aureus (S. aureus) with an inhibition zone of 21.5 mm and 20.5 mm at 6 µg/mL concentrations, respectively, once compared to the standard reference. At concentrations of 2 µg/mL and 4 µg/mL, all of the bacterial strains showed moderate activity, with inhibition zones ranging from 11 mm to 18.5 mm. Even at high concentrations of AgNPs, S. typhi showed maximum resistance. The best antifungal activity was observed by synthesized Ag NPs against Candida albicans (C. albicans) with 21 mm zone of inhibition, as compared to a standard drug which gives 22 mm of inhibition. Therefore, we conclude that the antibacterial and antifungal activities showed satisfactory results from the synthesized Ag NPs.

Characterization, Antiplasmodial and Cytotoxic Activities of Green Synthesized Iron Oxide Nanoparticles Using Nephrolepis exaltata Aqueous Extract.

The use of non-toxic synthesis of iron oxide nanoparticles (FeO NPs) by an aqueous plant extract has proven to be a viable and environmentally friendly method. Therefore, the present investigation is based on the FeO NPs synthesis by means of FeCl3·6H2O as a precursor, and the plant extract of Nephrolepis exaltata (N. exaltata) serves as a capping and reducing agent. Various techniques were used to examine the synthesized FeO NPs, such as UV-Visible Spectroscopy (UV-Vis), Fourier Transform Infrared Spectroscopy (FT-IR), X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), and Energy Dispersive X-ray (EDX). The FT-IR studies were used to identify different photoactive biomolecules at 3285, 2928, 1415, 1170, and 600 cm-1 in the wavenumber range from 4000 to 400 cm-1, indicating the -OH, C-H, C-O, C-C, and M-O groups, respectively. The XRD examination exhibited crystallinity, and the average diameter of the particle was 16 nm. The spherical nature of synthesized FeO NPs was recognized by SEM images, while the elemental composition of nanoparticles was identified by an EDX spectrophotometer. The antiplasmodial activity of synthesized FeO NPs was investigated against Plasmodium parasites. The antiplasmodial property of FeO NPs was evaluated by means of parasite inhibitory concentration, which showed higher efficiency (62 ± 1.3 at 25 µg/mL) against Plasmodium parasite if compared to plant extracts and precursor. The cytotoxicity of FeO NPs was also assessed in human peripheral blood mononuclear cells (PBMCs) under in vitro conditions. The lack of toxic effects through FeO NPs keeps them more effective for use in pharmaceutical and medical applications.

Antibacterial activity of silver nanoparticles against carbapenem-resistant Acinetobacter baumannii clinical isolates.

Carbapenem-resistant Acinetobacter baumannii (CRAB) produce resistance to various classes of antibiotics and left limited options for treatment. This study was designed to determine antibacterial activity of AgNPs against CRAB. Total 100 A. baumannii were collected from a tertiary care hospital, Lahore. Isolates were subcultured on blood and MacConkey agar. Preliminary identification was carried out by morphological and biochemical tests. Antibiogram was done by Kirby-Bauer disc diffusion method. Antibacterial activity of AgNPs was performed by agar well diffusion method, while minimum inhibitory concentration and minimum bactericidal concentration were determined by micro broth dilution assay. Of 100 A. baumannii, 24 were confirmed as carbapenem-resistant. These isolates were mainly recovered from tracheal secretion (8; 33%), CSF (5; 20.8%), and urine (4; 16.8%). Antibacterial activity of AgNPs revealed a maximum zone of inhibition, 22mm at 50mg/mL and 18mm at 40mg/mL by agar well diffusion method. MIC of AgNPs determined that 14 CRAB were inhibited at 12.5mg/mL and 7 at 25mg/mL. However, MBC revealed that 13 CRAB were killed at 25mg/mL and 7 at 50mg/mL. This study concluded that most of the CRAB were inhibited and killed at 12.5mg/mL and 25mg/mL, respectively. AgNPs can be used as an alternative therapeutic agent followed by their pharmacokinetics and pharmacognosy.

A Hybrid Deep Learning-Driven SDN Enabled Mechanism for Secure Communication in Internet of Things (IoT).

The Internet of Things (IoT) has emerged as a new technological world connecting billions of devices. Despite providing several benefits, the heterogeneous nature and the extensive connectivity of the devices make it a target of different cyberattacks that result in data breach and financial loss. There is a severe need to secure the IoT environment from such attacks. In this paper, an SDN-enabled deep-learning-driven framework is proposed for threats detection in an IoT environment. The state-of-the-art Cuda-deep neural network, gated recurrent unit (Cu- DNNGRU), and Cuda-bidirectional long short-term memory (Cu-BLSTM) classifiers are adopted for effective threat detection. We have performed 10 folds cross-validation to show the unbiasedness of results. The up-to-date publicly available CICIDS2018 data set is introduced to train our hybrid model. The achieved accuracy of the proposed scheme is 99.87%, with a recall of 99.96%. Furthermore, we compare the proposed hybrid model with Cuda-Gated Recurrent Unit, Long short term memory (Cu-GRULSTM) and Cuda-Deep Neural Network, Long short term memory (Cu- DNNLSTM), as well as with existing benchmark classifiers. Our proposed mechanism achieves impressive results in terms of accuracy, F1-score, precision, speed efficiency, and other evaluation metrics.