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Abstract Background Necrotic enteritis (NE) is an economically important disease of broiler chickens caused by Clostridium perfringens (CP). The pathogenesis, or disease process, of NE is still not clear. This study aimed to identify the alterations of metabolites and metabolic pathways associated with subclinical or clinical NE in CP infected birds and to investigate the possible variations in the metabolic profile of birds infected with different isolates of CP. Methodology Using a well-established NE model, the protein content of feed was changed abruptly before exposing birds to CP isolates with different toxin genes combinations (cpa, cpb2, netB, tpeL; cpa, cpb2, netB; or cpa, cpb2). Metabolomics analysis of jejunal contents was performed by a targeted, fully quantitative LC-MS/MS based assay. Results This study detected statistically significant differential expression of 34 metabolites including organic acids, amino acids, fatty acids, and biogenic amines, including elevation of butyric acid at onset of NE in broiler chickens. Subsequent analysis of broilers infected with CP isolates with different toxin gene combinations confirmed an elevation of butyric acid consistently among 21 differentially expressed metabolites including organic acids, amino acids, and biogenic amines, underscoring its potential role during the development of NE. Furthermore, protein-metabolite network analysis revealed significant alterations in butyric acid and arginine-proline metabolisms. Conclusion This study indicates a significant metabolic difference between CP-infected and non-infected broiler chickens. Among all the metabolites, butyric acid increased significantly in CP-infected birds compared to non-infected healthy broilers. Logistic regression analysis revealed a positive association between butyric acid (coefficient: 1.23, P

Introduction: Dermoscopy of mucosa is known as mucoscopy. Mucoscopy can aid in delineating minute aspects of mucosal lesions and will guide in the differentiation of similar-looking lesions. To date, there are only a few studies on mucoscopy of genital dermatoses especially from India. Aim and Objectives: The study aims to describe mucoscopic features and correlate histopathologically in various genital mucosal diseases. Materials and Methods: The study was conducted in a tertiary care center in Central India after IHEC approval between October 2020 and April 2022, and the sampling technique was based on a convenience purposive method. Any genital mucosal diseases were included in patients above 18 years of age. Sexually transmitted diseases in general were excluded, however, warts and molluscum contagiosum were included. All patients fulfilling the inclusion criteria were examined after proper informed consent, and the clinical images were photographed using iPhone 11. Dermoscopic images were taken using a DermLite DL4 dermoscope in polarized mode at 10X magnification. Results: A total of 206 patients were recruited, and mucoscopy features were analyzed. Dermoscopic findings of physiological conditions such as vestibular papillomatosis, pearly penile papules, and Fordyce spots were evaluated. Inflammatory conditions such as lichen planus, pemphigus, and psoriasis were analyzed. Mucoscopy of lichen sclerosus showed white structureless areas (100%), follicular plugs (35%), as well as dotted and linear vessels (80%). Circinate balanitis revealed regular red dotted vessels (100%), coalescing pustules in annular and polycyclic patterns (90%). Squamous cell carcinoma of the penis showed ulceration, serpentine, looped vessels, white structureless area, and yellow-brown crust in a pink background. Limitations: In our study, because of the inclusion of various diseases, sample size was inadequate, biopsies were not performed in all cases, and variations in mucoscopic features in patients who are already on therapy could not be assessed. Haziness while capturing pictures because of mist formation was hindering the quality of pictures. As patients with premalignant and malignant cases were less, the predicting features for malignant transformation or pathognomoniic signs could not be assessed. Conclusion: Various dermoscopies have been studied extensively, but the mucoscopy is still a gray area. The results of this study revealed the dermoscopic features of various genital disorders and histopathological correlation in few cases. However, biopsy was not performed in all mucosal disorders; hence, conclusive correlation could not be extrapolated.

Background: Uncomplicated crown fractures of maxillary anterior teeth are common dental injuries, and the bonding of fractured fragments is recommended for management. Rehydration of fragments improves bonding and fracture resistance. Therefore, the aim of this study was to compare the fracture resistance of the reattached tooth fragment of the incisor crown after rehydration using either a steamer or a humidifier. MATERIALS AND METHODS: Bovine teeth were used as a model. Fractured fragments were divided into three groups: Group I (no rehydration), Group II (rehydration by humidifier), and Group III (rehydration by steamer). Fragments were reattached using a standard bonding protocol. Fracture resistance was tested using a universal testing machine. Statistical analysis was performed using analysis of variance and Chi-square tests. Results: The force required to fracture the reattached fragments was significantly higher in Group II (humidifier) compared to Group I (no rehydration) (P = 0.005). Group III (steamer) had a force value similar to Group I, indicating no significant improvement in fracture resistance with steamer rehydration. The temperature inside the steam-based chamber reached an average of 95.7°C with 95% humidity, whereas the conventional humidification chamber had an average temperature of 39.2°C and 84% humidity. Conclusion: Within the limitations of the present study, the rehydration protocol using a steam-based chamber was found to have a significantly lower force required to fracture the reattached fragments as compared to humidifier-based chamber. This was not significantly different from the fragments which were reattached without rehydration.

Abstract Background Type II diabetes mellitus is posing a severe health threat throughout the globe due to its associated pathophysiological risks and high mortality rate. Carbohydrate catabolic enzymes, including α-amylase, α-glucosidase and aldose reductase, play an important role in the development of diabetes. The natural or synthetic inhibitors of these enzymes are crucial in reducing diabetes and its related complications. Tinospora cordifolia is a plant of great significance in Ayurveda due to its unique biological activities, including anti-diabetic properties. The present study aims to identify the active constituents of T. cordifolia leaves and evaluate the in vitro inhibitory potential of its ethanol extract constituents against α-amylase, α-glucosidase and aldose reductase activities. Results The ethanolic leaf extract of T. cordifolia inhibited the activities of α-amylase, α-glucosidase and aldose reductase in a dose-dependent manner. It was on par with the standard inhibitors acarbose and quercetin. At 5 mg/ml, the noted % inhibition values of extract were 69.27 ± 0.17, 67.8 ± 0.26 and 62.55 ± 0.24, respectively, for α-amylase, α-glucosidase and aldose reductase. Using GC-MS analysis, neophytadiene, γ-sitosterol, phytol, phytyl palmitate, and phytyl acetate were identified as prominent constituents of the ethanolic extract. Based on molecular docking and ADME analysis, γ-sitosterol was found as the major reactive phytoconstituent, which showed the highest inhibitory potential against α-amylase, α-glucosidase and aldose reductase activities. Conclusions The present study identified γ-sitosterol as triplet inhibitor of α-amylase, α-glucosidase and aldose reductase and affirmed the ethno-medicinal significance of T. cordifolia leaves in the development of new anti-diabetic leads.

Abstract Oligodeoxynucleotides containing CpG motifs (CpG-ODN) can promote antimicrobial immunity in chickens by enriching immune compartments and activating immune cells. Innate memory, or trained immunity, has been demonstrated in humans and mice, featuring the absence of specificity to the initial stimulus and subsequently cross-protection against pathogens. We hypothesize that CpG-ODN can induce trained immunity in chickens. We delivered single or multiple administrations of CpG-ODN to birds and mitochondrial oxidative phosphorylation (OXPHOS) and glycolysis of peripheral blood mononuclear cells were quantified using Seahorse XFp. Next, chickens were administered with CpG-ODN twice at 1 and 4 day of age and challenged with Escherichia coli at 27 days of age. The CpG-ODN administered groups had significantly higher mitochondrial OXPHOS until 21 days of age while cellular glycolysis gradually declined by 14 days of age. The group administered with CpG-ODN twice at 1 and 4 days of age had significantly higher survival, lower clinical score and bacterial load following challenge with E. coli at 27 d of age. This study demonstrated the induction of trained immunity in broiler chickens following administration of CpG-ODN twice during the first 4 days of age to protect birds against E. coli septicemia at 27 days of age.

This study records a total of 212 taxa (201 species and 11 varieties) in 131 genera and 37 families of flowering plants. The family Asteraceae dominated with 32 species and 17 genera, followed by Poaceae with 31 species and 21 genera. Twenty‑five species are recorded under different threat categories and 22 are native to the Himalayan region. Lancea tibetica Hook. f. & Thomson and Waldheimia stoliczkae (C.B. Clarke) Ostenf. are endemic to the cold desert areas of the Indian Himalayan Region. This study provides baseline data on floristic diversity for effective implementation of conservation approaches in selected high‑altitude wetlands of the Ladakh region.

The amount of data being produced and used every day is increasing rapidly. Different operations are performed on the data that is stored in database systems to generate meaningful information. The task of retrieving data from the database is difficult for inexperienced users who don’t have great knowledge of Database Management System (DBMS) languages such as Structured Query Language (SQL). Using Natural Language Processing, anyone can directly interact with the database system. To achieve this type of communication, we have developed a novel and improved Intelligent Search Engine (ISE) Tool using natural language processing. Using this search engine, the user can query the database system in natural language (human-understandable language). The intelligent search engine will convert the natural language query into the DBMS language query to retrieve the data from the database. The proposed system also has a query recommendation engine that recommends the possible queries in case of any error or if the result is not found. The intelligent search engine proposed in this work is a generic tool that is not dependent on the front or back end of the system, therefore it can be used for any database system.

Introduction: The fabella is a sesamoid bone found in the posterior and lateral region of the knee, identified on X-rays behind the femoral condyle in a true lateral view. Occasionally, it is a source of knee pain and is associated with radiological evidence of osteoarthritic knees. Due to its uncommon occurrence, there are very few studies related to an ossified fabella. While posteromedial pain and varus are common entities in knee arthritis, attention needs to be given to posterolateral structures like the fabella, as its radiological appearance may indicate the presence of arthritis. Aim: To determine the occurrence of the fabella and its association with arthritis and knee deformities, such as varus or valgus, in Indian knees on X-rays. Materials and Methods: This was a single-centre, X-ray-based, cross-sectional study conducted in the Joint Replacement Unit-II of the Department of Orthopaedics between June 2022 and March 2023 at KLE's Dr. Prabhakar Kore Hospital in Belagavi, Karnataka, India. A total of 500 knees were radiologically studied using Medsynapse/Picture Archiving and Communication System (PACS), and Cohen's Kappa Test statistics were employed to measure the agreement between the radiologist and orthopaedician regarding the presence or absence of the fabella interpreted on X-rays. Results: The occurrence of ossified fabella was observed in 87 (17.4%) subjects. Amongst these 27 (31.03%) had bilateral fabella, while remaining 60 (68.97%) had it either on left or right side. There was a high association between the occurrence of the fabella with age, Osteoarthritis (OA), and knee deformity (p-value0.05). Conclusion: The study revealed that ossified fabella is significantly associated with knee OA, age, and knee deformities.

ABSTRACT: In the past, we demonstrated that oligodeoxynucleotides containing CpG motifs (CpG-ODN) mimicking bacterial DNA, stimulate the innate immune system of neonatal broiler chickens and protect them against Escherichia coli and Salmonella Typhimurium (S. Typhimurium) septicemia. The first line of innate immune defense mechanism is formed by heterophils and plays a critical protective role against bacterial septicemia in avian species. Therefore, the objectives of this study were 1) to explore the kinetics of CpG-ODN mediated antibacterial mechanisms of heterophils following single or twice administration of CpG-ODN in neonatal broiler chickens and 2) to investigate the kinetics of the immunoprotective efficacy of single versus twice administration of CpG-ODN against S. Typhimurium septicemia. In this study, we successfully developed and optimized flow cytometry-based assays to measure phagocytosis, oxidative burst, and degranulation activity of heterophils. Birds that received CpG-ODN had significantly increased (p < 0.05) phagocytosis, oxidative burst, and degranulation activity of heterophils as early as 24 h following CpG-ODN administration. Twice administration of CpG-ODN significantly increased the phagocytosis activity of heterophils. In addition, our newly developed CD107a based flow cytometry assay demonstrated a significantly higher degranulation activity of heterophils following twice than single administration of CpG-ODN. However, the oxidative burst activity of heterophils was not significantly different between birds that received CpG-ODN only once or twice. Furthermore, delivery of CpG-ODN twice increased immunoprotection against S. Typhimurium septicemia compared to once but the difference was not statistically significant. In conclusion, we demonstrated enhanced bactericidal activity of heterophils after administration of CpG-ODN to neonatal broiler chickens. Further investigations will be required to identify other activated innate immune cells and the specific molecular pathways associated with the CpG-ODN mediated activation of heterophils.

Temperature and liquid flow monitoring are required in many industrial applications in order to maximize machine performance. When exploring polymers, fabricating synthetic films and transparent materials, and manufacturing metal-based equipment, frictional forces and thermal flow rates need to be controlled. The significance of the study of prominent characteristics of Diffusion-Thermo, Quadratic thermal radiation and radiation absorption over a permeable stretching geometry are discussed. Similarity transformations reduced the boundary layer partial differential to an ODE. The acquired system of ODEs is solved in numerical-manner using MATLAB bvp4c. The distributions f '(η), θ(η) and φ(η) are described graphical aspect, with specified governed parameters. As Diffusion thermo parameter raises, temperature field enhances. As radiation absorption raises, the temperature and velocity enhance and concentration decreases. A rise in radiation absorption parameter causes a raise in the buoyancy, which in turn raises the flow rate, and that this is reflected in the velocity profiles. The radiation absorption parameter raises temperatures nearer porous boundary layer and lowers concentration. Rising temperature ratio parameter θw values were accompanied by rising temperatures. Temperature is enhancing when improving of Biot parameter. The skin-friction is heightened with raising ‘n’ values. Nusselt number is declined, raising values of Df. The Sherwood number is enhanced with raising values of ‘Sc’. An incorporation of Diffusion thermo, Quadratic thermal radiation and radiation absorption effects in a nano-Carreau flow across Wedge and Cone is the novelty. The flow of a boundary-layer across a wedge gets made growingly significant, not long ago, owing to its many practical applications, including those in medical, bioengineering, crude oil extraction, nuclear power plants, a polymer extrusion process, production of plastic sheet, metal spinning, friction drag of a ship, and electronic gadgets, etc. This study will be extended by incorporating micro-polar, tangent hyperbolic, Sutterby, with distinct non-Newtonian fluids.

A novel design of Return Flow Solar Air Heater (RFSAH) with different arrangements of baffles especially V-Type Artificial roughness is simulated and numerically analyzed with energy balance equations. To enhance the effectiveness of baffles, numerous studies have been conducted. The performance of the RFSAH is studied in terms of thermal efficiency, thermo-hydraulic efficiency, and optimization of baffle parameters. Maximum Thermal efficiency and thermo-hydraulic efficiency are found in RFSAH with baffle on both sides of the absorber plate and mass flow rate above 0.2kg/s. Sensitivity analysis of the influencing parameters is carried out and reported the best performance of the system on selective geometrical parameters (ψ=0.7, β=20%, e/H=1, p/e=0.8, α=60∘). The results obtained from the present model are validated with the published experimental results and have been found in quite reasonable agreement with an average error of 16.45%. Thermal and Thermohydraulic efficiency of RFSAH with a baffle on both sides of the absorber plate is maximum among baffles below, above, and on both sides of the absorber plate. It is observed that the thermal efficiency of RFSAH is greater than SF-SAH. The proposed optimum baffles roughness is suggested to increase the air upholding time period for more efficient output.

Given that some suspected perpetrators were wrongly convicted, a defective bitemark analysis is comparable to dentists’ most crucial clinical decisions regarding assessment. Bias affects human bitemark analysis beyond the limitation of the evidence itself. The aim of this study was to explore the potential for different types of bias in bitemark analysis and the methods involved in that analysis by conducting a scoping review. Results showed that the 14 articles that explore the topic of bias in bitemark analysis were published from 2006-2022. Publications were from the USA mainly (n = 7), followed by the UK (n = 3), Australia (n = 2), New Zealand, (n = 1) and the Netherlands (n = 1). Of these publications, 36% addressed contextual bias, while 57% acknowledged cognitive bias. According to the findings, preventive measures consist of limiting the availability of unrelated data during research, employing several comparison samples for a more impartial assessment, and repeating the analysis while being blind to past findings. Nevertheless, the physical limitations of the evidence such as distortions are still strongly present.

We report the case of a 48 year old man brought-in-dead to the trauma unit following an alleged accidental fall from a multi-storied building. Autopsy findings were consistent with traumatic injuries to the head, chest and spine. Incidentally, a bit of the diaphragm with a pearly white lobulated mass over the pleural surface was observed. Histopathological examination detected a calcifying fibrous pseudotumour (CFPT), confirmed by positive immunostaining for cluster of differentiation protein-34 (CD34) and vimentin (focally). CFPTs are slow-growing pseudotumours that are clinically benign with extremely low rate of recurrence and this might just be the first reported case of CFPT on the diaphragm. This shall further aid clinicians to diagnose these rare yet significant soft tissue tumors in uncommon sites.

South Asia is home to almost a quarter of the world's total population and is home to significant ethnolinguistic diversity. Previous studies of linguistic and genetic affiliations of Indian populations suggest that the formation of these distinct groups was a protracted and complex phenomenon involving multiple waves of migration, cultural assimilation, and genetic admixture. The evolutionary processes of migration, mixing and merging of populations thus impact the culture and linguistic diversity of different groups, some of which may retain their linguistic affinities despite genetic admixture with other groups, or vice versa. Our study examines the relationship of genetic and linguistic affinities between Austroasiatic and Indo-European speakers in adjacent geographical regions of Eastern India. We analyzed 224 mitogenomes and 0.65 million SNP genotypes from 40 unrelated individuals belonging to the Bathudi, Bhumij, Ho, and Mahali ethnic groups from the Eastern Indian state of Odisha. These four groups are speakers of Austroasiatic languages who have adopted elements from Indo-European languages spoken in neighbouring regions. Our results suggest that these groups have the greatest maternal genetic affinity with other Austroasiatic-speaking groups in India. Allele frequency-based analyses, genome-wide SNPs, haplotype-based methods and IBD sharing further support the genetic similarity of these East Indian groups to Austroasiatic speakers of South Asia rather than regional populations speaking Indo-European and Dravidian languages. Our study shows that these populations experienced linguistic mixing, likely due to industrialization and modernization that brought them into close cultural contact with neighbouring Indo-European-speaking groups. However, linguistic change in these groups is not reflected in genetic mixing in these populations, as they appear to maintain strict genetic boundaries while simultaneously experiencing cultural mixing.

Abstract Background Traditional breeding methods have long been employed worldwide for the evaluation and development of pepper cultivars. However, these methods necessitate multiple generations of screening, line development, evaluation, recognition, and crossing to obtain highly homozygous lines. In contrast, in vitro anther-derived microspore culture represents a rapid method to generate homozygous lines within a single generation. In the present study, we have optimized a protocol for microspore embryogenesis from anther cultures of pepper hybrids Orobelle and Bomby. Results We achieved early and successful embryo formation from both genotypes by subjecting the buds to a cold pretreatment at 4 °C for 4 days. Our optimized culture medium, comprised of MS medium supplemented with 4 mg/L NAA, 1 mg/L BAP, 0.25% activated charcoal, 2.6 g/L gelrite, 30 g/L sucrose, and 15 mg/L silver nitrate, exhibited the highest efficiency in embryo formation (1.85% and 1.46%) for Orobelle and Bomby, respectively. Furthermore, successful plant regeneration from the anther derived microspore embryos was accomplished using half-strength MS medium fortified with 2% sucrose and 0.1 mg/L 6-benzylaminopurine (BA), solidified with 2.6 g/L gelrite. The ploidy status of the microspore-derived plantlets was analyzed using flow cytometry technique. Notably, the haploid plants exhibited distinct characteristics such as reduced plant height, leaf length, leaf width, and shorter internode length when compared to their diploid counterparts derived from seeds. Conclusion Our findings highlight the potential of anther culture and microspore embryogenesis as an advanced method for accelerating pepper breeding programs, enabling the rapid production of superior homozygous lines.

Many real-world problems can be modelled in the form of complex networks. Social networks such as research collaboration networks and facebook, biological neural networks such as human brains, biomedical networks such as drug-target interactions and protein-protein interactions, technological networks such as telephone networks, transportation networks and power grids are a few examples of complex networks. Any complex system with entities and interactions existing between the entities can be modelled as a graph mathematically, with nodes representing entities and edges reflecting interactions. In numerous real-world circumstances, interactions are not confined to pair of entities. Majority of these intricate systems inherently possess hypergraph structures, characterized by interactions that extend beyond pairwise connections. Existing studies often transform complex interactions at a higher level into pairwise interactions and subsequently analyze them. This conversion frequently leads to both the loss of information and the inability to reconstruct the original hypergraph from the transformed network with pairwise interactions. One of the most essential tasks that can be performed on these graphs is Link Prediction (LP), which is the task of predicting future edges (links) in a graph. LP in graphs is well investigated. This article presents a novel methodology for predicting links in hypergraphs. Unlike conventional approaches that transform hypergraphs into graphs with pairwise interactions, the proposed method directly leverages the inherent structure of hypergraphs in predicting future interaction between a pair of nodes. This is motivated by the fact that hypergraphs enable the depiction of intricate higher-order relationships through hyperlinks, enhancing their representation. Their capacity to capture complex structural patterns improves predictive capabilities. Node neighborhoods within hypergraphs offer a comprehensive framework for LP, where hyperlinks simplify interactions between nodes across cliques. We propose a novel method of Link Prediction in Hypergraphs (LPH) to predict interactions within hypergraphs, maintaining their original structure without conversion to graphs, thus preserving information integrity. The proposed approach LPH extends local similarity measures like Common Neighbors, Jaccard Coefficient, Adamic Adar, and Resource Allocation, along with a global measure, Katz index, to hypergraphs. LPH’s effectiveness is assessed on six benchmark hyper-networks, employing evaluation metrics such as Area under ROC curve, Precision, and F1-score. The proposed measures of LP on hypergraphs resulted in an average enhancement of 10% in terms of Area under ROC curve compared to contemporary as well as conventional measures. Additionally, there is an average improvement of 70% in precision and around 50% in F1-score. This methodology presents a promising avenue for predicting pairwise interactions within hypergraphs while retaining their inherent structural complexity as well as information integrity.

An accurate prediction of house prices is a fundamental requirement for various sectors, including real estate and mortgage lending. It is widely recognized that a property’s value is not solely determined by its physical attributes but is significantly influenced by its surrounding neighborhood. Meeting the diverse housing needs of individuals while balancing budget constraints is a primary concern for real estate developers. To this end, we addressed the house price prediction problem as a regression task and thus employed various machine learning (ML) techniques capable of expressing the significance of independent variables. We made use of the housing dataset of Ames City in Iowa, USA to compare XGBoost, support vector regressor, random forest regressor, multilayer perceptron, and multiple linear regression algorithms for house price prediction. Afterwards, we identified the key factors that influence housing costs. Our results show that XGBoost is the best performing model for house price prediction. Our findings present valuable insights and tools for stakeholders, facilitating more accurate property price estimates and, in turn, enabling more informed decision making to meet the housing needs of diverse populations while considering budget constraints.

Macroeconomic factors have a critical impact on banking credit risk, which cannot be directly controlled by banks, and therefore, there is a need for an early credit risk warning system based on the macroeconomy. By comparing different predictive models (traditional statistical and machine learning algorithms), this study aims to examine the macroeconomic determinants’ impact on the UK banking credit risk and assess the most accurate credit risk estimate using predictive analytics. This study found that the variance-based multi-split decision tree algorithm is the most precise predictive model with interpretable, reliable, and robust results. Our model performance achieved 95% accuracy and evidenced that unemployment and inflation rate are significant credit risk predictors in the UK banking context. Our findings provided valuable insights such as a positive association between credit risk and inflation, the unemployment rate, and national savings, as well as a negative relationship between credit risk and national debt, total trade deficit, and national income. In addition, we empirically showed the relationship between national savings and non-performing loans, thus proving the “paradox of thrift”. These findings benefit the credit risk management team in monitoring the macroeconomic factors’ thresholds and implementing critical reforms to mitigate credit risk.

(1) This research paper aims to conduct a comprehensive review of the existing scientific literature on intentional dental modifications within the African population. By synthesizing and analysing studies, this paper aims to shed light on the prevalence, cultural significance, and forensic implications of intentional dental modifications. (2) A scoping review was conducted according to PRISMA for Scoping Reviews and a search performed in June 2023 on the three electronic databases Scopus, PubMed, and Web of Science. (3) The search resulted in 30 studies and showed that intentional dental modifications, also referred to as nontherapeutic dental modifications, are prevalent across the African population for reasons linked to traditional medicine, ethnic affiliation, and individualism, with the highest-reported modification being infant oral mutilation at 53%, followed by tooth filing at 10%, and others such as lip plates, diastema piercings, dental avulsion, dental tattooing, crowns, and oral piercings. (4) The quality and quantity of the available literature on intentional dental modifications in the African population is limited due to bias in reporting, as most studies are those of individuals with severe health complications. The data gathered from this study could further aid in the analysis and identification of nontherapeutic dental modifications, be used in profiling, and assist in the estimation of population affiliation.

Abstract Background Necrotic enteritis (NE) is a severe intestinal infection that affects both humans and poultry. It is caused by the bacterium Clostridium perfringens (CP), but the precise mechanisms underlying the disease pathogenesis remain elusive. This study aims to develop an NE broiler chicken model, explore the impact of the microbiome on NE pathogenesis, and study the virulence of CP isolates with different toxin gene combinations. Methods This study established an animal disease model for NE in broiler chickens. The methodology encompassed inducing abrupt protein changes and immunosuppression in the first experiment, and in the second, challenging chickens with CP isolates containing various toxin genes. NE was evaluated through gross and histopathological scoring of the jejunum. Subsequently, jejunal contents were collected from these birds for microbiome analysis via 16S rRNA amplicon sequencing, followed by sequence analysis to investigate microbial diversity and abundance, employing different bioinformatic approaches. Results Our findings reveal that CP infection, combined with an abrupt increase in dietary protein concentration and/or infection with the immunosuppressive variant infectious bursal disease virus (vIBDV), predisposed birds to NE development. We observed a significant decrease (p

Abstract Background Pigeon pea is affected by the cyst nematode Heterodera cajani limiting the production. H. cajani can be managed by biological agents such as Trichoderma harzianum. Thus, the determination of this experiment was to estimate native strains of T. harzianum isolated from pigeon pea fields in India on population of cyst, eggs and juveniles of H. cajani. Pots experiment was conducted at the playhouse of Sam Higginbottom University of Science and Technology, Prayagraj (UP), India, during the year of 2018–2020. Earthen pots were filled with sterilized soil @ 10 kg/pot for each replicate of the treatments. Ten days before sowing of the pigeon pea seed, about 5000 spores of T. harzianum were amended in to the soil for proper colonization. Fifteen days after seed germination, 200 cysts/pot were inoculated near the root zone of pigeon pea plant. The pots were irrigated when required. Observations were recorded of cyst population, eggs and second juveniles of H. cajani/500gm of pigeon pea rhizospheric soil at 90 days after sowing. Results Among all the isolates of T. harzianum, the treatment (T 7) reduced of cyst population (12), eggs population (234) and juveniles’ population (153) as compared with all other treatments including control at 90 days after sowing of pigeon pea seeds in the year 2018–2019. Similarly, in 2019–2020 reduction in cyst population (11), eggs population (189) and juveniles population (160) was observed at 90 days after sowing in Trichoderma isolates (T 7) as compared to control. Conclusions The findings of this study are very relevant since seven isolates of native T. harzianum were promising to suppress the number of cysts in 79.31 and 83.07%, eggs in 22.00 and 38.83% and juveniles’ population in 17.74 and 20.39% of the nematode H. cajani, besides promoting the pigeon pea plant growth.

The World Health Organisation (WHO) revealed approximately 280 million people in the world suffer from depression. Yet, existing studies on early-stage depression detection using machine learning (ML) techniques are limited. Prior studies have applied a single stand-alone algorithm, which is unable to deal with data complexities, prone to overfitting, and limited in generalization. To this end, our paper examined the performance of several ML algorithms for early-stage depression detection using two benchmark social media datasets (D1 and D2). More specifically, we incorporated sentiment indicators to improve our model performance. Our experimental results showed that sentence bidirectional encoder representations from transformers (SBERT) numerical vectors fitted into the stacking ensemble model achieved comparable F1 scores of 69% in the dataset (D1) and 76% in the dataset (D2). Our findings suggest that utilizing sentiment indicators as an additional feature for depression detection yields an improved model performance, and thus, we recommend the development of a depressive term corpus for future work.

Background: Recent advancements in three-dimensional (3D) printing have introduced novel materials for removable partial dentures (RPD) base fabrication, promising improved mechanical properties, and biocompatibility. Materials and Methods: In this study, three different RPD base materials were evaluated: conventional heat-cured acrylic resin (Control), biocompatible 3D-printed resin (Test Group A), and a novel nanocomposite 3D-printed resin (Test Group B). A total of 30 standardized RPD base specimens (n = 10 per group) were fabricated according to established protocols. Microstructural analysis was performed using scanning electron microscopy (SEM), and the mechanical properties, including flexural strength and modulus, were determined using a universal testing machine. Results: Microstructural analysis revealed distinct differences among the materials. SEM images showed a well-defined and homogeneous microstructure in Test Group B, while Test Group A exhibited fewer voids compared to the Control group. Mechanical testing results indicated that Test Group B had the highest flexural strength (120 ± 5 MPa), followed by Test Group A (90 ± 4 MPa), and the Control group (75 ± 3 MPa). Similarly, Test Group B demonstrated the highest flexural modulus (3.5 ± 0.2 GPa), followed by Test Group A (2.8 ± 0.1 GPa), and the Control group (2.1 ± 0.1 GPa). Conclusion: These findings suggest that 3D-printed RPD base materials, particularly nanocomposite resins, hold promise for improving the overall quality and durability of removable partial dentures.

Traumatic or irritation fibroma is the healed end product of the inflammatory hyperplastic lesion, which can occur at any age from almost any softtissue site, tongue, gingiva, and buccal mucosa being the most common. It is usually characterized by a slow, painless growth accumulated over a period of months or years.

Abstract Introduction: An accurate, simple, precise, rapid, economic and reproducible reverse-phase high-performance liquid chromatography method was developed and validated for the estimation of Esomeprazole (ESO) in bulk and tablet dosage form. Method: The separation was carried out on Finepak SIL C18T-5 column (250 × 4.6 mm, 5.0 µm i. d.) using potassium dihydrogen phosphate buffer (0.025M): ACN (20:80 v/v) and at a flow rate of 1.0 mL/min. using UV detector at 302 nm with a run time of 10 min. The method was validated for accuracy for linearity, accuracy, precision, limit of detection (LOD), limit of quantification (LOQ) and robustness. Results: The standard calibration curve was linear with R2 = 0.995. LOD and LOQ obtained for esomeprazole were 0.0001 and 0.0004 µg/mL respectively. The method was found robust for possible changes. Results of analysis of other parameters were also tested and validated as per ICH guidelines and recovery studies confirmed the accuracy of the proposed method. validation studies showed that the developed HPLC method is simple, reproducible, rapid, precise and reliable. The high recovery and low relative standard deviation confirm the suitability of the developed method for the determination of esomeprazole in the tablet dosage form. Conclusion: This method may be used as a more convenient and efficient option for the analysis of esomeprazole to establish the quality of the substance during routine analysis with consistent and reproducible results.

Study attempts to align HDI with the Sustainable Human Development approach. Modified HDI, integrating employment, human values, environmental sustainability, quality aspects of health and education, as a simple generalization within the structure of the existing methodology, is developed for BRICS countries for the period 2000-2019. Proposed MHDI’s environmental sustainability dimension index was created using Principal Component Analysis. Framed dimensional indices were regressed on the MHDI values, followed by post-hoc analysis, assisted in generating policy implications. Computed MHDI scores were lower than HDI values for all BRICS members, indicating a lower human development scenario in these countries than what HDI perceives.

Abstract Background Left ventricular diastolic dysfunction is frequently noticed in patients with multiple co-morbidities. Echocardiography is used to determine the presence of diastolic dysfunction and to grade its severity. In left ventricular diastolic dysfunction, the ventricular diastolic distensibility, filling, or relaxation is abnormal; however, the left ventricular ejection fraction may be normal or decreased. Case presentation We present anesthetic management of two patients with diastolic dysfunction grade III for renal transplant. During declamping in renal transplant, high central venous pressures are required for adequate perfusion of the transplanted kidney. In the operation theater standard monitors including NIBP, SpO2 and five lead ECG were attached. An arterial line (radial) and central line (right internal jugular) were established for IBP and CVP monitoring. Infusions of furosemide and dopamine were started. Nitrogycerine and milrinone infusions were prepared but were not required intraoperatively. Both the patients were extubated at the end of surgery. Conclusions Increased incidence of major adverse cardiovascular events has been reported in surgical patients having grade III diastolic dysfunction. Hemodynamic instability and fluid overload in this set of patients are known to generate pulmonary edema.

The use of generative artificial intelligence (GenAI) in academia is a subjective and hotly debated topic. Currently, there are no agreed guidelines towards the usage of GenAI systems in higher education (HE) and, thus, it is still unclear how to make effective use of the technology for teaching and learning practice. This paper provides an overview of the current state of research on GenAI for teaching and learning in HE. To this end, this study conducted a systematic review of relevant studies indexed by Scopus, using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. The search criteria revealed a total of 625 research papers, of which 355 met the final inclusion criteria. The findings from the review showed the current state and the future trends in documents, citations, document sources/authors, keywords, and co-authorship. The research gaps identified suggest that while some authors have looked at understanding the detection of AI-generated text, it may be beneficial to understand how GenAI can be incorporated into supporting the educational curriculum for assessments, teaching, and learning delivery. Furthermore, there is a need for additional interdisciplinary, multidimensional studies in HE through collaboration. This will strengthen the awareness and understanding of students, tutors, and other stakeholders, which will be instrumental in formulating guidelines, frameworks, and policies for GenAI usage.

Abstract Chemokine receptors constitute an important subfamily of G protein-coupled receptors (GPCRs), and they are critically involved in a broad range of immune response mechanisms. Ligand promiscuity among these receptors makes them an interesting target to explore multiple aspects of biased agonism. Here, we comprehensively characterize two chemokine receptors namely, CXCR4 and CXCR7, in terms of their transducer-coupling and downstream signaling upon their stimulation by a common chemokine agonist, CXCL12, and a small molecule agonist, VUF11207. We observe that CXCR7 lacks G-protein-coupling while maintaining robust βarr recruitment with a major contribution of GRK5/6. On the other hand, CXCR4 displays robust G-protein activation as expected but exhibits significantly reduced βarr-coupling compared to CXCR7. These two receptors induce distinct βarr conformations even when activated by the same agonist, and CXCR7, unlike CXCR4, fails to activate ERK1/2 MAP kinase. We also identify a key contribution of a single phosphorylation site in CXCR7 for βarr recruitment and endosomal localization. Our study provides molecular insights into intrinsic-bias encoded in the CXCR4-CXCR7 system with broad implications for drug discovery.

The foundation of the upcoming generation of cutting-edge gadgets and digitally augmented technologies is expected to be smart soft materials. Because of their responsiveness and adaptability, liquid crystals (LCs) are promising smart soft materials. In the 20th century, LCs were crucial to changing the information display sector. However, several beyond-display uses for LCs have been proven at the turn of the twentieth century, neatly using their controlled stimuli-responsive and adaptable properties. New LC materials have been developed and engineered for such applications. The review comes close with a summary and viewpoints on the potential and problems facing LCs as smart soft materials. This review is expected to inspire a wide range of concepts for the application of nature's delicate phase of matter in the generation and beyond of smart and augmented devices.

The genus of Clematis is a buttercup family (Ranunculaceae), recognized for its flowers and adaptable as an ornamental plant in colder climates. It contains around 300 species. Clematis has a variety of active phytoconstituents or secondary metabolites which are responsible for health benefits in human beings. Traditionally various species of the clematis genus used for centuries to treat various ailments including syphilis, bone disorders, gout, rheumatism, diuretics, wound healing, blood sugar control, blood diseases, spleen difficulties, leprosy, fevers, skin diseases. A systematic review of scientific electronic database and reference books were consulted to find all relevant literature for this work. This review discusses the ethno-medicinal usage, health advantages, phytoconstituents and bioactivities of clematis species.

ObjectiveTo generate longitudinal fetal growth data in an Indian population and compare it with Intergrowth-21st.Material and methodsFetal biometry data was collected in a prospective longitudinal observational study (REVAMP: Research Exploring Various Aspects and Mechanisms in Preeclampsia) from 2017 to 2022. Fetal crown-rump length (CRL) was measured at 11-14 weeks gestation, and biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), and femur length (FL) at 18-22 and 32-35 weeks, and converted into Z-scores using the Intergrowth standard. Generalized Additive Models for Location, Scale and Shape (GAMLSS) models were used to construct fetal growth centile curves compared against Intergrowth centiles.ResultsOut of 1096 singleton pregnancies in REVAMP, this analysis included 655 'healthy' pregnancies (uncomplicated by pre-eclampsia, diabetes, pre-term delivery or low birth weight) and a sub-set of 106 'low-risk' pregnancies defined using Intergrowth criteria. The 'healthy' study subjects showed lower mean CRL Z-score [-0.45 SD (95% CI:-0.54,-0.37)] at 11-14 weeks, and BPD Z-score [-1.2 SD (-1.28,-1.11) and -1.17 SD (-1.23,-1.1)] at 18-22 and 32-35 weeks respectively. Mean HC Z-score was comparable to the Intergrowth standard at 18-22 weeks [-0.08 SD (-0.16, 0.02)] but smaller at 32-35 weeks [-0.25 SD (-0.32,-0.19)]. Mean AC Z-score was lower at 18-22 weeks [-0.32 SD (-0.41,-0.23)] but comparable at 32-35 weeks [0.004 SD (-0.07, 0.07)]. FL was comparable to or larger than the Intergrowth standard at both time points [0.05 SD (-0.05, 0.14); 0.82 SD (0.75, 0.89), respectively]. These findings were similar, though measurements were slightly larger, in the 'low-risk' sample.ConclusionsThis data from healthy and low-risk pregnant women in urban western India indicates that some fetal dimensions and growth trajectories differ significantly from the Intergrowth-21st. Our data suggest the need for a larger representative study to define a population-specific fetal growth reference for India, for identification of fetal growth restriction.

BackgroundTuberculosis is a serious life-threatening disease among the top global health challenges and rapid and effective diagnostic biomarkers are vital for early diagnosis especially given the increasing prevalence of multidrug resistance.MethodsTwo human whole blood microarray datasets, GSE42826 and GSE42830 were retrieved from publicly available gene expression omnibus (GEO) database. Deregulated genes (DEGs) were identified using GEO2R online tool and Gene Ontology (GO), protein-protein interaction (PPI) network analysis was performed using Metascape and STRING databases. Significant genes (n = 8) were identified using T-test/ANOVA and Molecular Complex Detection (MCODE) score ≥10, which was validated in GSE34608 dataset. The diagnostic potential of three biomarkers was assessed using Area Under Curve (AUC) of Receiver Operating Characteristic (ROC) plot. The transcriptional levels of these genes were also examined in a separate dataset GSE31348, to monitor the patterns of variation during tuberculosis treatment.ResultsA total of 62 common DEGs (57 upregulated, 7 downregulated genes) were identified in two discovery datasets. GO functions and pathway enrichment analysis shed light on the functional roles of these DEGs in immune response and type-II interferon signaling. The genes in Module-1 (n = 18) were linked to innate immune response, interferon-gamma signaling. The common genes (n = 8) were validated in GSE34608 dataset, that corroborates the results obtained from discovery sets. The gene expression levels demonstrated responsiveness to Mtb infection during anti-TB therapy in GSE31348 dataset. In GSE34608 dataset, the expression levels of three specific genes, GBP5, IFITM3, and EPSTI1, emerged as potential diagnostic makers. In combination, these genes scored remarkable diagnostic performance with 100% sensitivity and 89% specificity, resulting in an impressive Area Under Curve (AUC) of 0.958. However, GBP5 alone showed the highest AUC of 0.986 with 100% sensitivity and 89% specificity.ConclusionsThe study presents valuable insights into the critical gene network perturbed during tuberculosis. These genes are determinants for assessing the effectiveness of an anti-TB response and distinguishing between active TB and healthy individuals. GBP5, IFITM3 and EPSTI1 emerged as candidate core genes in TB and holds potential as novel molecular targets for the development of interventions in the treatment of TB.

Toxic leukoencephalopathy (TLE) is a rare neurological debilitating and fatal condition. It has been previously associated with exposure to leukotoxic offenders such as chemotherapy, cranial radiation, certain drugs, and environmental factors. Currently, it is a commoner white matter syndrome resulting from increased substance abuse, classically by inhaled heroin and other opioids. Herein, we report a case of fatal TLE unveiled in an autopsy of a drug abuser. A 24-year-old male was found dead on the roadside. A day before, he was located in a state of delirium. In this case, the autopsy findings and histopathology characteristics of cerebral cortex involvement particularly directed to speculate the heroine as the principal offender.

Electronic absorption spectrums of methylene blue (MB) in the concentration range wherein monomer–dimer equilibria exist have been systematically investigated in aqueous solutions of polyethylene glycols (PEG's) having molar mass 400, 1000 and 4000 g∙mol–1, at 298 K. The data on the absorption spectrums (550–700 nm) of MB are resolved to obtain monomer and dimer spectrums as well the geometrical details of the species (such as oscillatory strength, dipole moment etc.) are calculated. The molar absorption extinction coefficients for monomer and dimer cations of MB, the dimer dissociation constant values are calculated as a function of PEG concentrations. It has been noted that, absorption maximum occurs at 664 ± 1 and 605 ± 1 nm, respectively, for monomer and dimers which do not get affected much by presence of polymeric molecules and the data show perfect obedience of Beer–Lambert's law. The changes in dimer geometry from sandwich type to end–on–end type have been studied by applying exciton theory of Kasha et al. The dimer dissociation constant values at finite as well for infinitely dilute concentration of PEG's exhibit orderly amendment with respect to molar mass of PEG's and alteration in chain length of molecules. We report the free energy changes of transfer of dimeric cations of different concentrations from water to aqueous solutions of PEG's of fixed concentration, that is, to probe the interactions of water and PEG molecules with a hope of getting information about salting–in/salting–out effects, as well of binding of dye molecules with PEG's. We have suggested complexation of end hydroxylic groups of PEG's with dimer cations. The results are further interpreted as salting–in of PEG complex with MB–dimers only in the limit of infinite dilution (solute–solvent interactions) while salting–out of these complexed species is observed as a function of MB–dimer concentration.

Workflow scheduling and resource provisioning are two of the most critical issues in cloud computing. Developing an optimal workflow scheduling strategy in the heterogeneous cloud environment is extremely difficult due to its NP-complete nature. Various optimization algorithms have been used to schedule the workflow so that users can receive Quality of Service (QoS) from cloud service providers as well as service providers can achieve maximum gain but there is no such model that can simultaneously minimize execution time and cost while balancing the load among virtual machines in a heterogeneous environment using JAYA approach. In this article, we employed the hybrid JAYA algorithm to minimize the computation cost and completion time during workflow scheduling. We considered the heterogeneous cloud computing environment and made an effort to evenly distribute the load among the virtual machines. To achieve our goals, we used the Task Duplication Heterogeneous Earliest Finish Time (HEFT-TD) and Predict Earliest Finish Time (PEFT). The makespan is greatly shortened by HEFT-TD which is based on the Optimistic Cost Table. We used a greedy technique to distribute the workload among Virtual Machines (VMs) in a heterogeneous environment. Greedy approach assigns the upcoming task to a VM which have lowest load. In addition, we also considered performance variation, termination delay, and booting time of virtual machines to achieve our objectives in our proposed model. We used Montage, LIGO, Cybershake, and Epigenomics datasets to experimentally analyze the suggested model in order to validate the concept. Our meticulous experiments show that our hybrid approach outperforms other recent algorithms in minimizing the execution cost and makespan, such as the Cost Effective Genetic Algorithm (CEGA), Cost-effective Load-balanced Genetic Algorithm (CLGA), Cost effective Hybrid Genetic Algorithm (CHGA), and Artificial Bee Colony Algorithm (ABC).

Link prediction plays a crucial role in identifying future connections within complex networks, facilitating the analysis of network evolution across various domains such as biological networks, social networks, recommender systems, and more. Researchers have proposed various centrality measures, such as degree, clustering coefficient, betweenness, and closeness centralities, to compute similarity scores for predicting links in these networks. These centrality measures leverage both the local and global information of nodes within the network. In this study, we present a novel approach to link prediction using similarity score by utilizing average centrality measures based on local and global centralities, namely Similarity based on Average Degree (SACD), Similarity based on Average Betweenness (SACB), Similarity based on Average Closeness (SACC), and Similarity based on Average Clustering Coefficient (SACCC). Our approach involved determining centrality scores for each node, calculating the average centrality for the entire graph, and deriving similarity scores through common neighbors. We then applied centrality scores to these common neighbors and identified nodes with above average centrality. To evaluate our approach, we compared proposed measures with existing local similarity-based link prediction measures, including common neighbors, the Jaccard coefficient, Adamic–Adar, resource allocation, preferential attachment, as well as recent measures like common neighbor and the Centrality-based Parameterized Algorithm (CCPA), and keyword network link prediction (KNLP). We conducted experiments on four real-world datasets. The proposed similarity scores based on average centralities demonstrate significant improvements. We observed an average enhancement of 24% in terms of Area Under the Receiver Operating Characteristic (AUROC) compared to existing local similarity measures, and a 31% improvement over recent measures. Furthermore, we witnessed an average improvement of 49% and 51% in the Area Under Precision-Recall (AUPR) compared to existing and recent measures. Our comprehensive experiments highlight the superior performance of the proposed method.

In recent years, there has been a notable surge in the utilization of stabilized bile acid liposomes, chemical conjugates, complexes, mixed micelles, and other drug delivery systems derived from bile acids, often referred to as bilosomes. The molecular structure and interactions of these amphiphilic compounds provide a distinctive and captivating subject for investigation. The enhanced stability of new generation bilosomes inside the gastrointestinal system results in the prevention of drug degradation and an improvement in mucosal penetration. These characteristics render bilosomes to be a prospective nanocarrier for pharmaceutical administration, prompting researchers to investigate their potential in other domains. This review paper discusses bilosomes that have emerged as a viable modality in the realm of drug delivery and have significant promise for use across several domains. Moreover, this underscores the need for additional investigation and advancement in order to comprehensively comprehend the prospective uses of bilosomes and their effectiveness in the field of pharmaceutical administration. This review study explores the current scholarly attention on bilosomes as prospective carriers for drug delivery. Therapeutic areas where bilosomes have shown outstanding performance in terms of drug delivery are outlined in the graphical abstract.

Introduction: Hypernatremic dehydration is commonly found in the first week of neonatal life. Hypernatremia develops when water loss exceeds sodium loss, as in lactational failure with inadequate breastfeeding, or when sodium intake exceeds water intake disproportionately (salt poisoning), such as when neonates receive concentrated formula or top milk. The common presentations include lethargy, irritability, poor feeding, dehydration, reduced urinary frequency, significant weight loss, and fever. Aim: The aim of this study was to investigate the clinico-etiological profile and outcome of hypernatremic dehydration in term neonates admitted to the Neonatal Intensive Care Unit (NICU) at a tertiary care centre. Additionally, the study aimed to examine the factors contributing to hypernatremic dehydration. Materials and Methods: This prospective cohort study was conducted at the NICU, Department of Paediatrics, of Geetanjali Medical College, Udaipur, Rajasthan, India from February 2021 to July 2022. A total of 51 term neonates with a history of inadequate breastfeeding, maternal history of lactational failure, significant weight loss (>10% weight loss within a short period of time), or dehydration fever, along with hypernatremia (serum sodium > 145 mEq/L), were enrolled in the study. Data regarding serum sodium level, serum bilirubin level, Kidney Function Test (KFT), Ultrasonography of Kidney, Ureters and Bladder (USG KUB), and neuroimaging were collected for all study subjects and statistically analysed using the Chi-square test. Results: A total of 51 neonates were admitted to the NICU during the study period, with a mean age of 6.05±2.2 days (range 0-15 days) and a mean birth weight of 2810 grams. The study showed that the mean weight (in %) loss was 13.75±4.1 (range 10.1-21%). The study also revealed that 64.7% of the mothers of neonates experienced lactational failure, with a p-value

Variant avian reoviruses (ARVs) are economically important emerging pathogens of poultry, which mainly affect young broiler chickens and cause significant production losses. Currently, there are no effective commercial vaccines available for control and prevention of emerging variant ARVs. In this study, monovalent inactivated adjuvated (20% Emulsigen D) broiler breeder vaccines containing antigens from ARV genotype cluster (C) group -2, -4, -5, or -6, and a multivalent vaccine containing antigens from all the four indicated genotypic cluster groups were developed and evaluated for their efficacy in protecting broiler progenies against homologous or heterologous ARV challenge. The use of monovalent or multivalent inactivated vaccines in a prime-boost immunization strategy induced the production of ARV specific antibodies in broiler breeders. The maternal antibodies were effectively transferred to broiler progenies. Broiler progenies obtained from immunized breeders demonstrated milder clinical symptoms and reduced gross and histopathological lesions after homologous ARV challenge. More severe gross and histological lesions were observed in challenged progenies from unvaccinated broiler breeders. However, cross protection was not observed when either of the monovalent-vaccine groups were challenged with a heterologous virus. In addition, the progenies from the unvaccinated ARV challenged control or heterologous ARV challenged vaccinated groups had significantly reduced body weight gain (p < 0.01) than the unchallenged-control, challenged-multivalent, or homologous ARV-challenged monovalent vaccine groups. However, homologous ARV challenged progenies in the multivalent or monovalent vaccine groups had similar body weight gain as the control unchallenged group with significantly reduced viral load (p < 0.01) in the gastrocnemius tendon tissue. This study indicates that broad-spectrum protection of broiler progenies from variant ARV infections is feasible through the development of multivalent vaccines after proper characterization, selection and incorporation of multiple antigens based on circulating ARV genotypes in targeted regions.

Smart watches are trendy fashionable and wearable devices which were introduced in India in recent times. The main objective of this study is to understand the impact of social media in Islam on consumer buying behavior. The quantitative survey investigates the factors that influence user behavior towards smartwatches. Data of 160 respondents was collected and analyzed using SPSS and Microsoft Excel software. It has been observed that smart watches are trending in the digital age with the ability to replace smart phones. The findings of this study reveal various influencing factors such as friends, advertisements but most of the respondents are influenced by social factors to buy smart watches. The findings of this study will be useful for marketers and smart watch manufacturing companies to find out consumer perceptions of smart watches, and in Islamic studies this can be a da'wah facility in spreading goodness by optimizing developing technology.

Cloud computing plays a significant role in everyone’s lifestyle by snugly linking communities, information, and trades across the globe. Due to its NP-hard nature, recognizing the optimal solution for workflow scheduling in the cloud is a challenging area. We proposed a hybrid meta-heuristic cost-effective load-balanced approach to schedule workflow in a heterogeneous environment. Our model is based on a genetic algorithm integrated with predict earliest finish time (PEFT) to minimize makespan. Instead of assigning the task randomly to a virtual machine, we apply a greedy strategy that assigns the task to the lowest-loaded virtual machine. After completing the mutation operation, we verify the dependency constraint instead of each crossover operation, which yields a better outcome. The proposed model incorporates the virtual machine’s performance variance as well as acquisition delay, which concedes the minimum makespan and computing cost. One of the most astounding aspects of our cost-effective hybrid genetic algorithm (CHGA) is its capacity to anticipate by creating an optimistic cost table (OCT) while maintaining quadratic time complexity. Based on the results of our meticulous experiments on some real-world workflow benchmarks and comprehensive analysis of some recently successful scheduling algorithms, we concluded that the performance of our CHGA is melodious. CHGA is 14.58188%, 11.40224%, 11.75306%, and 9.78841% cheaper than standard Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Cost Effective Genetic Algorithm(CEGA), and Cost-Effective Load-balanced Genetic Algorithm (CLGA), respectively.

Sugarcane productivity is being hampered globally under changing environmental scenarios like drought and salinity. The highly complex nature of the plant responses against these stresses is determined by a variety of factors such as genotype, developmental phase of the plant, progression rate and stress, intensity, and duration. These factors influence plant responses and can determine whether mitigation approaches associated with acclimation are implemented. In this review, we attempt to summarize the effects of drought and salinity on sugarcane growth, specifically on the plant’s responses at various levels, viz., physiological, biochemical, and metabolic responses, to these stresses. Furthermore, mitigation strategies for dealing with these stresses have been discussed. Despite sugarcane’s complex genomes, conventional breeding approaches can be utilized in conjunction with molecular breeding and omics technologies to develop drought- and salinity-tolerant cultivars. The significant role of plant growth-promoting bacteria in sustaining sugarcane productivity under drought and salinity cannot be overlooked.

Carbon dots (CDs), which have particle size of less than 10 nm, are carbon-based nanomaterials that are used in a wide range of applications in the area of novel drug delivery in cancer, ocular diseases, infectious diseases, and brain disorders. CDs are biocompatible, eco-friendly, easy to synthesize, and less toxic with excellent chemical inertness, which makes them very good nanocarrier system to deliver multi-functional drugs effectively. A huge number of researchers worldwide are working on CDs-based drug delivery systems to evaluate their versatility and efficacy in the field of pharmaceuticals. As a result, there is a tremendous increase in our understanding of the physicochemical properties, diagnostic and drug delivery aspects of CDs, which consequently has led us to design and develop CDs-based theranostic system for the treatment of multiple disorders. In this review, we aim to summarize the advances in application of CDs as nanocarrier including gene delivery, vaccine delivery and antiviral delivery, that has been carried out in the last 5 years.

Coronavirus disease 2019 (COVID-19) is a recent global pandemic that is caused by the novel severe acute respiratory syndrome coronavirus 2. The patients of COVID-19 are susceptible to a diverse range of secondary infections, fungal being the most common. The increased risk is proposed to be due to the generous use of steroids for the treatment of COVID-19 infection and the presence of comorbidities, such as diabetes mellitus, hypertension, preexisting lung diseases, and/or old age. Invasive mixed fungal disease is potentially life-threatening to the patients of COVID-19. In the present series of seven cases, the authors intend to discuss the clinicopathological profile and gamut of histopathological findings in invasive mixed fungal infection comprising of Mucor and Aspergillus in treated patients of COVID-19. Six patients had a clinical diagnosis of sinonasal–orbital invasive fungal disease, while there was a case of lung infection. The acquaintance and knowledge about histomorphology of invasive fungi and the multidisciplinary diagnostic approach not only will aid in early and accurate diagnosis but can guide the clinician for necessary surgical intervention and initiation of appropriate antifungal medications in patients of COVID-19.

Most women generally have an ovarian cyst, causing the disorder. Pregnant cysts occur when many water-packed tumors appear in the womb. This is especially true for women who have a worthy cause for childbearing. Women are related to menstrual problems and cyst problems during pregnancy. Recently, ultrasound imaging and machine learning techniques have been used to detect ovarian cysts. Different domain experts provide their own decisions on finding out what kind of ovarian cyst it is from ultrasound images. However, a most accurate and uniform decision-making system is necessary for the early detection of cysts. To aid physicians, an automated detection system has been proposed in this paper to make it more effective for physicians to eliminate these problems. This system uses the extracted features from the image for cysts detection and classification. Automatic ovary cyst detection (OCD) and classification are implemented in this work using a fuzzy rule-based Convolutional Neural Network (FCNN). The proposed system (OCD-FCNN) has yielded 98.37% accurate results when tested with benchmark datasets.