Search results for: gene expression data analysis

Authors: Dong-An Wang

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All kinds of microspheres have been extensively employed as carriers for drug, gene and therapeutic cell delivery. Most therapeutic cell delivery microspheres rely on a two-step methodology: fabrication of microspheres and subsequent seeding of cells onto them. In this study, we have developed a novel one-step cell encapsulation technique using a convenient and instant water-in-oil single emulsion approach to form cell-encapsulated gelatin microspheres. This technology is adopted for hyaline cartilage tissue engineering, in which autologous chondrocytes are used as therapeutic cells. Cell viability was maintained throughout and after the microsphere formation (75-100 µm diameters) process that avoids involvement of any covalent bonding reactions or exposure to any further chemicals. Further encapsulation of cell-laden microspheres in alginate gels were performed under 4°C via a prompt process. Upon the formation of alginate constructs, they were immediately relocated into CO2 incubator where the temperature was maintained at 37°C; under this temperature, the cell-laden gelatin microspheres dissolved within hours to yield similarly sized cavities and the chondrocytes were therefore suspended within the cavities inside the alginate gel bulk. Hence, the gelatin cell-laden microspheres served two roles: as cell delivery vehicles which can be removable through temperature curing, and as porogens within an alginate hydrogel construct to provide living space for cell growth and tissue development as well as better permeability for mutual diffusions. These cell-laden microspheres, namely “temperature-cured dissolvable gelatin microsphere based cell carriers” (tDGMCs), were further encapsulated in a chondrocyte-laden alginate scaffold system and analyzed by WST-1, gene expression analyses, biochemical assays, histology and immunochemistry stains. The positive results consistently demonstrated the promise of tDGMC technology in delivering these non-anchorage dependent cells (chondrocytes). It can be further conveniently translated into delivery of other non-anchorage dependent cell species, including stem cells, progenitors or iPS cells, for regeneration of tissues in internal organs, such as engineered hepatogenesis or pancreatic regeneration.

Keywords: biomaterials, tissue engineering, microsphere, hydrogel, porogen, anchorage dependence

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Authors: Maddalena Arigoni, Maria Luisa Ratto, Raffaele A. Calogero, Luca Alessandri

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The presence of tumor heterogeneity, where distinct cancer cells exhibit diverse morphological and phenotypic profiles, including gene expression, metabolism, and proliferation, poses challenges for molecular prognostic markers and patient classification for targeted therapies. Understanding the causes and progression of cancer requires research efforts aimed at characterizing heterogeneity, which can be facilitated by evolving single-cell sequencing technologies. However, analyzing single-cell data necessitates computational methods that often lack objective validation. Therefore, the establishment of benchmarking datasets is necessary to provide a controlled environment for validating bioinformatics tools in the field of single-cell oncology. Benchmarking bioinformatics tools for single-cell experiments can be costly due to the high expense involved. Therefore, datasets used for benchmarking are typically sourced from publicly available experiments, which often lack a comprehensive cell annotation. This limitation can affect the accuracy and effectiveness of such experiments as benchmarking tools. To address this issue, we introduce omics benchmark experiments designed to evaluate bioinformatics tools to depict the heterogeneity in single-cell tumor experiments. We conducted single-cell RNA sequencing on six lung cancer tumor cell lines that display resistant clones upon treatment of EGFR mutated tumors and are characterized by driver genes, namely ROS1, ALK, HER2, MET, KRAS, and BRAF. These driver genes are associated with downstream networks controlled by EGFR mutations, such as JAK-STAT, PI3K-AKT-mTOR, and MEK-ERK. The experiment also featured an EGFR-mutated cell line. Using 10XGenomics platform with cellplex technology, we analyzed the seven cell lines together with a pseudo-immunological microenvironment consisting of PBMC cells labeled with the Biolegend TotalSeq™-B Human Universal Cocktail (CITEseq). This technology allowed for independent labeling of each cell line and single-cell analysis of the pooled seven cell lines and the pseudo-microenvironment. The data generated from the aforementioned experiments are available as part of an online tool, which allows users to define cell heterogeneity and generates count tables as an output. The tool provides the cell line derivation for each cell and cell annotations for the pseudo-microenvironment based on CITEseq data by an experienced immunologist. Additionally, we created a range of pseudo-tumor tissues using different ratios of the aforementioned cells embedded in matrigel. These tissues were analyzed using 10XGenomics (FFPE samples) and Curio Bioscience (fresh frozen samples) platforms for spatial transcriptomics, further expanding the scope of our benchmark experiments. The benchmark experiments we conducted provide a unique opportunity to evaluate the performance of bioinformatics tools for detecting and characterizing tumor heterogeneity at the single-cell level. Overall, our experiments provide a controlled and standardized environment for assessing the accuracy and robustness of bioinformatics tools for studying tumor heterogeneity at the single-cell level, which can ultimately lead to more precise and effective cancer diagnosis and treatment.

Keywords: single cell omics, benchmark, spatial transcriptomics, CITEseq

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Authors: Anna D. Kotrova, Alexandr N. Shishkin, Elena I. Ermolenko

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The aim. To study the quantitative and qualitative colon bacteria ratio from patients with metabolic syndrome. Materials and methods. Fecal samples from patients of 2 groups were identified and analyzed: the first group was formed by patients with metabolic syndrome, the second one - by healthy individuals. The metagenomics method was used with the analysis of 16S rRNA gene sequences. The libraries of the variable sites (V3 and V4) gene 16S RNA were analyzed using the MiSeq device (Illumina). To prepare the libraries was used the standard recommended by Illumina, a method based on two rounds of PCR. Results. At the phylum level in the microbiota of patients with metabolic syndrome compared to healthy individuals, the proportion of Tenericutes was reduced, the proportion of Actinobacteria was increased. At the genus level, in the group with metabolic syndrome, relative to the second group was increased the proportion of Lachnospira. Conclusion. Changes in the colon bacteria ratio in the gut microbiota of patients with metabolic syndrome were found both at the type and the genus level. In the metabolic syndrome group, there is a decrease in the proportion of bacteria that do not have a cell wall. To confirm the revealed microbiota features in patients with metabolic syndrome, further study with a larger number of samples is required.

Keywords: gut microbiota, metabolic syndrome, metagenomics, tenericutes

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Authors: Kamila Duś-Szachniewicz, Kinga M. Walaszek, Paweł Skiba, Paweł Kołodziej, Piotr Ziółkowski

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Cell adhesion is of fundamental importance in the cell communication, signaling, and motility, and its dysfunction occurs prevalently during cancer progression. The knowledge of the molecular and cellular processes involved in abnormalities in cancer cells adhesion has greatly increased, and it has been focused mainly on cellular adhesion molecules (CAMs) and tumor microenvironment. Unfortunately, most of the data regarding CAMs expression relates to study on cells maintained in standard oxygen condition of 21%, while the emerging evidence suggests that culturing cells in ambient air is far from physiological. In fact, oxygen in human tissues ranges from 1 to 11%. The aim of this study was to compare the effects of physiological lymph node normoxia (5% O2), and hyperoxia (21% O2) on the expression of cellular adhesion molecules of primary diffuse large B-cell lymphoma cells (DLBCL) isolated from 10 lymphoma patients. Quantitative RT-PCR and immunohistochemistry were used to confirm the differential expression of several CAMs, including ICAM, CD83, CD81, CD44, depending on the level of oxygen. Our findings also suggest that DLBCL cells maintained at ambient O2 (21%) exhibit reduced growth rate and migration ability compared to the cells growing in normoxia conditions. Taking into account all the observations, we emphasize the need to identify the optimal human cell culture conditions mimicking the physiological aspects of tumor growth and differentiation.

Keywords: adhesion molecules, diffuse large B-cell lymphoma, physiological normoxia, quantitative RT-PCR

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Authors: Lali Shanshiashvili, Marika Chikviladze, Nino Mamulashvili, Maia Sepashvili, Nana Narmania, David Mikeladze

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Purpose: During demyelinating inflammatory diseases and after the damage of the myelin sheet, myelin-derived proteins, including myelin basic protein (MBP), are secreted into the extracellular space. MBP shows extensive post-translational modifications, including the deimination of arginine residues. Deiminated MBP is structurally less ordered, susceptible to proteolytic attack, and more immunogenic than the unmodified one. It is hypothesized that MBP could change the inflammatory response in astrocytes. Methods: MBP was isolated and purified from bovine brain white matter. Primary astrocyte cultures were prepared from whole brains of 2-day-old Wistar rats. For evaluation of glutamate uptake/release in astrocytes following treatment of cells with MBP charge isomers, Glutamate Assay Kit was used. The expression of EAAT-2 (excitatory amino acid transporters), peroxisome proliferator-activated receptor gamma (PPAR- γ), inhibitor of nuclear factor kappa B (IkB), and high mobility group protein B1 (HMGB1) in astrocytes were assayed by Western Blot analysis. Results: This study investigated the action of deiminated isomer (C8) on the cultured primary astrocytes and compared its effects with the effects of unmodified C1 isomers. The study found that C8 and C1 MBP differently act on the uptake and release of glutamate in astrocytes: nonmodified C1 MBP increases the uptake of glutamate and does not change the release, whereas C8 decreases the release of glutamate but does not alter the uptake. Nevertheless, both isomers increased the expression of PPAR-γ and EAAT2 in the same intensity. However, immunostaining and Western Blots of cell lysates showed a decrease of IkB and increased expression of HMGB1 after the treatment of astrocytes by C8. Moreover, in the presence of C8, astrocytes release more nitric oxide than unmodified C1 isomers. Conclusion: These data suggest that the deiminated isomer of MBP evokes an inflammatory response and enhances the ability of astrocytes to release proinflammatory mediators through activation of NF-kB after the breakdown of myelin sheets. Acknowledgment: This research was supported by the SRNSF Georgia RF17_534 grant.

Keywords: myelin basic protein, glutamate, deimination, astrocytes, inflammation

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Authors: Yan Zeng, Li Tao, Liujun Han, Tianye Zhang, Yongan Yu, Kaijun Ma, Long Chen

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Mechanical asphyxia is one of the main cause of death; however, death by mechanical asphyxia may be difficult to prove in court, particularly in cases in which corpses exhibit no obvious signs of asphyxia. To identify a credible biomarker of asphyxia, we first examined the expression levels of all the mRNAs in human cardiac tissue specimens subjected to mechanical asphyxia and compared these expression levels with those of the corresponding mRNAs in specimens subjected to craniocerebral injury. A total of 119 differentially expressed mRNAs were selected and the expression levels of these mRNAs were examined in 44 human cardiac tissue specimens subjected to mechanical asphyxia, craniocerebral injury, hemorrhagic shock and other causes of death. We found that DUSP1 and KCNJ2 were up-regulated in tissue specimens of mechanical asphyxia compared with control tissues, with no significant correlation between age, environmental temperature and PMI, indicating that DUSP1 and KCNJ2 may associate with mechanical asphyxia-induced death and can thus serve as useful biomarkers of death by mechanical asphyxia.

Keywords: mechanical asphyxia, biomarkers, DUSP1, KCNJ2, cardiac tissue

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Authors: M. Sakthivel, A. Devaki, D. Balasubramanyam, P. Kumarasamy, A. Raja, R. Anilkumar, H. Gopi

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The New Zealand White breed of rabbit is one of the most commonly used, well adapted exotic breeds in India. Earlier studies were limited only to analyze the environmental factors affecting the growth and reproductive performance. In the present study, the population of the New Zealand White rabbits in a closed herd was evaluated for its genetic structure. Data on pedigree information (n=2508) for 18 years (1995-2012) were utilized for the study. Pedigree analysis and the estimates of population genetic parameters based on gene origin probabilities were performed using the software program ENDOG (version 4.8). The analysis revealed that the mean values of generation interval, coefficients of inbreeding and equivalent inbreeding were 1.489 years, 13.233 percent and 17.585 percent, respectively. The proportion of population inbred was 100 percent. The estimated mean values of average relatedness and the individual increase in inbreeding were 22.727 and 3.004 percent, respectively. The percent increase in inbreeding over generations was 1.94, 3.06 and 3.98 estimated through maximum generations, equivalent generations, and complete generations, respectively. The number of ancestors contributing the most of 50% genes (fₐ₅₀) to the gene pool of reference population was 4 which might have led to the reduction in genetic variability and increased amount of inbreeding. The extent of genetic bottleneck assessed by calculating the effective number of founders (fₑ) and the effective number of ancestors (fₐ), as expressed by the fₑ/fₐ ratio was 1.1 which is indicative of the absence of stringent bottlenecks. Up to 5th generation, 71.29 percent pedigree was complete reflecting the well-maintained pedigree records. The maximum known generations were 15 with an average of 7.9 and the average equivalent generations traced were 5.6 indicating of a fairly good depth in pedigree. The realized effective population size was 14.93 which is very critical, and with the increasing trend of inbreeding, the situation has been assessed to be worse in future. The proportion of animals with the genetic conservation index (GCI) greater than 9 was 39.10 percent which can be used as a scale to use such animals with higher GCI to maintain balanced contribution from the founders. From the study, it was evident that the herd was completely inbred with very high inbreeding coefficient and the effective population size was critical. Recommendations were made to reduce the probability of deleterious effects of inbreeding and to improve the genetic variability in the herd. The present study can help in carrying out similar studies to meet the demand for animal protein in developing countries.

Keywords: effective population size, genetic structure, pedigree analysis, rabbit genetics

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Authors: Camilo Cerda Sarabia, Fernanda Bravo Cornejo, Diego Santibanez Oyarce, Hugo Osses Prado, Esteban Gómez Terán, Belén Diaz Diaz, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

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Antimicrobial resistance (AMR) represents a significant and rapidly escalating global health threat. Projections estimate that by 2050, AMR infections could claim up to 10 million lives annually. Respiratory infections, in particular, pose a severe risk not only to individual patients but also to the broader public health system. Despite the alarming rise in resistant respiratory infections, AMR within the lung microbiome (microbial community) remains underexplored and poorly characterized. The lungs, as a complex and dynamic microbial environment, host diverse communities of microorganisms whose interactions and resistance mechanisms are not fully understood. Unlike studies that focus on individual genomes, analyzing the entire microbiome provides a comprehensive perspective on microbial interactions, resistance gene transfer, and community dynamics, which are crucial for understanding AMR. However, this holistic approach introduces significant computational challenges and exposes the limitations of traditional analytical methods such as the difficulty of identifying the AMR. Machine learning has emerged as a powerful tool to overcome these challenges, offering the ability to analyze complex genomic data and uncover novel insights into AMR that might be overlooked by conventional approaches. This study investigates microbial resistance within the lung microbiome using unsupervised machine learning approaches to uncover resistance patterns and potential clinical associations. it downloaded and selected lung microbiome data from HumanMetagenomeDB based on metadata characteristics such as relevant clinical information, patient demographics, environmental factors, and sample collection methods. The metadata was further complemented by details on antibiotic usage, disease status, and other relevant descriptions. The sequencing data underwent stringent quality control, followed by a functional profiling focus on identifying resistance genes through specialized databases like Antibiotic Resistance Database (CARD) which contains sequences of AMR gene sequence and resistance profiles. Subsequent analyses employed unsupervised machine learning techniques to unravel the structure and diversity of resistomes in the microbial community. Some of the methods employed were clustering methods such as K-Means and Hierarchical Clustering enabled the identification of sample groups based on their resistance gene profiles. The work was implemented in python, leveraging a range of libraries such as biopython for biological sequence manipulation, NumPy for numerical operations, Scikit-learn for machine learning, Matplotlib for data visualization and Pandas for data manipulation. The findings from this study provide insights into the distribution and dynamics of antimicrobial resistance within the lung microbiome. By leveraging unsupervised machine learning, we identified novel resistance patterns and potential drivers within the microbial community.

Keywords: antibiotic resistance, microbial community, unsupervised machine learning., sequences of AMR gene

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Authors: Shabnam Abdi, Behzad Toosi

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Background: Melanoma is the most lethal type of malignant skin cancer in humans and dogs since it spreads rapidly throughout the body. Despite significant advances in treatment, cancer at an advanced stage has a poor prognosis. Hence, more effective treatments are needed to enhance outcomes with fewer side effects. Erythropoietin-producing hepatocellular receptors are the largest family of receptor tyrosine kinases and are divided into two subfamilies, EphA and EphB, both of which play a significant role in disease, especially cancer. Due to their association with proliferation and invasion in many aggressive types of cancer, Eph receptor tyrosine kinases (Eph RTKs) are promising cancer therapy molecules. Because these receptors have not been studied in canine melanoma, we investigated how EphA2 influences survival and tumorigenicity of melanoma cells. Methods: Expression of EphA2 protein in canine melanoma cell lines and human melanoma cell line was evaluated by Western blot. Melanoma cells were transduced with lentiviral particles encoding Eph-targeting shRNAs or non-silencing shRNAs (control) for silencing the expression of EphA2 receptor, and silencing was confirmed by Western blotting and immunofluorescence. The effect of siRNA treatment on cellular proliferation, colony formation, tumorsphere assay, invasion was analyzed by Resazurin assay Matrigel invasion assay, respectively. Results: Expression of EphA2 was detected in canine and human melanoma cell lines. Moreover, stably silencing EphA2 by specific shRNAs significantly and consistently decreased the expression of EphA2 protein in both human and canine melanoma cells. Proliferation, colony formation, tumorsphere and invasion of melanoma cells were significantly decreased in EphA2 siRNA-treated cells compared to control. Conclusion: Our data provide the first functional evidence that the EphA2 receptor plays a critical role in the malignant cellular behavior of melanoma in both human and dogs.

Keywords: ephA2, targeting, melanoma, human, canine

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Authors: Lu Song Ma Li Zhi

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With the rapid advancement of artificial intelligence technology, large language models (LLMs) have become a milestone in the field of natural language processing, demonstrating remarkable capabilities in semantic understanding, intelligent question answering, and text generation. These models are gradually penetrating various industries, particularly showcasing significant application potential in the data analysis domain. However, retraining or fine-tuning these models requires substantial computational resources and ample downstream task datasets, which poses a significant challenge for many enterprises and research institutions. Without modifying the internal parameters of the large models, prompt engineering techniques can rapidly adapt these models to new domains. This paper proposes a prompt design strategy aimed at leveraging the capabilities of large language models to automate the generation of data analysis code. By carefully designing prompts, data analysis requirements can be described in natural language, which the large language model can then understand and convert into executable data analysis code, thereby greatly enhancing the efficiency and convenience of data analysis. This strategy not only lowers the threshold for using large models but also significantly improves the accuracy and efficiency of data analysis. Our approach includes requirements for the precision of natural language descriptions, coverage of diverse data analysis needs, and mechanisms for immediate feedback and adjustment. Experimental results show that with this prompt design strategy, large language models perform exceptionally well in multiple data analysis tasks, generating high-quality code and significantly shortening the data analysis cycle. This method provides an efficient and convenient tool for the data analysis field and demonstrates the enormous potential of large language models in practical applications.

Keywords: large language models, prompt design, data analysis, code generation

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Authors: Yungeng Xie, Cong Liu, Yi Liu, Xuanao Wan

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The study aims to explore microblog users’ emotion expression and sharing behaviors on the Chinese microblog (Weibo). The first theme of study analyzed whether microblog emotions impact readers’ message sharing behaviors, specifically, how the strength of emotion (positive and negative) in microblog messages facilitate/inhibit readers’ sharing behaviors. The second theme compared the differences among the three types of microblog users (i.e., verified enterprise users, verified individual users and unverified users) in terms of their profiles and microblog behaviors. A total of 7114 microblog messages about 24 hot public events in China were sampled from Sina Weibo. The first study results show that strength of negative emotions that microblog messages carry significantly increase the possibility of the message being shared. The second study results indicate that there are significant differences across the three types of users in terms of their emotion expression and its influence on microblog behaviors.

Keywords: emotion expression, information diffusion, microblog, sharing

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Authors: B. J. Mahen, N. E. Lloyd-Gale, S. Johnson, W. P. Rakowicz, M. J. Harris, A. D. Miller

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Background: Migraine is a leading cause of disability in the world. Calcitonin gene-related peptide (CGRP) receptor antagonists offer an approach to migraine prophylaxis by inhibiting the inflammatory and vasodilatory effects of CGRP. In recent years, NICE licensed the use of three CGRP-receptor antagonists: Fremanezumab, Galcanezumab, and Erenumab. Here, we present the outcomes of CGRP-antagonist treatment in a cohort of patients who suffer from episodic or chronic migraine and have failed at least three oral prophylactic therapies. Methods: We offered CGRP antagonists to 86 patients who met the NICE criteria to start therapy. We recorded the number of headache days per month (HDPM) at 0 weeks, 3 months, and 12 months. Of those, 26 patients were switched to an alternative treatment due to poor response or side effects. Of the 112 total cases, 9 cases did not sufficiently maintain their headache diary, and 5 cases were not followed up at 3 months. We have therefore included 98 sets of data in our analysis. Results: Fremanezumab achieved a reduction in HDPM by 51.7% at 3 months (p<0.0001), with 63.7% of patients meeting NICE criteria to continue therapy. Patients trialed on Galcanezumab attained a reduction in HDPM by 47.0% (p=0.0019), with 51.6% of patients meeting NICE criteria to continue therapy. Erenumab, however, only achieved a reduction in HDPM by 17.0% (p=0.29), and this was not statistically significant. Furthermore, 34.4%, 9.7%, and 4.9% of patients taking Fremanezumab, Galcanezumab, and Erenumab, respectively, continued therapy beyond 12 months. Of those who attempted drug holidays following 12 months of treatment, migraine symptoms relapsed in 100% of cases. Conclusion: We observed a significant improvement in HDPM amongst episodic and chronic migraine patients following treatment with Fremanezumab or Galcanezumab.

Keywords: migraine, CGRP, fremanezumab, galcanezumab, erenumab

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Authors: Digvijaysingh S. Bana, Kiran R. Trivedi

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This paper introduces various methods for the alpha wave to detect the difference between two states of brain. One healthy subject participated in the experiment. EEG was measured on the forehead above the eye (FP1 Position) with reference and ground electrode are on the ear clip. The data samples are obtained in the form of EEG raw data. The time duration of reading is of one minute. Various test are being performed on the alpha band EEG raw data.The readings are performed in different time duration of the entire day. The statistical analysis is being carried out on the EEG sample data in the form of various tests.

Keywords: electroencephalogram(EEG), biometrics, authentication, EEG raw data

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Authors: Priyanka Bhowmik, Subrata Majumdar, Debprasad Chattopadhyay

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Background: Cervical cancer is the third major cause of cancer in women and the second most frequent cause of cancer related deaths causing 300,000 deaths annually worldwide. Evasion of immune response by Human Papilloma Virus (HPV), the key contributing factor behind cancer and pre-cancerous lesions of the uterine cervix, makes immunotherapy a necessity to treat this disease. Objective: A Heat killed fraction of Mycobacterium indicus pranii (MIP), a non-pathogenic Mycobacterium has been shown to exhibit cytotoxic effects on different cancer cells, including human cervical carcinoma cell line HeLa. However, the underlying mechanisms remain unknown. The aim of this study is to decipher the mechanism of MIP induced HeLa cell death. Methods: The cytotoxicity of Mycobacterium indicus pranii against HeLa cells was evaluated by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Apoptosis was detected by annexin V and Propidium iodide (PI) staining. The assessment of reactive oxygen species (ROS) generation and cell cycle analysis were measured by flow cytometry. The expression of apoptosis associated genes was analyzed by real time PCR. Result: MIP could inhibit the proliferation of HeLa cell in a time and dose dependent manner but caused minor damage to normal cells. The induction of apoptosis was confirmed by the cell surface presentation of phosphatidyl serine, DNA fragmentation, and mitochondrial damage. MIP caused very early (as early as 30 minutes) transcriptional activation of p53, followed by a higher activation (32 fold) at 24 hours suggesting prime importance of p53 in MIP-induced apoptosis in HeLa cell. The up regulation of p53 dependent pro-apoptotic genes Bax, Bak, PUMA, and Noxa followed a lag phase that was required for the transcriptional p53 program. MIP also caused the transcriptional up regulation of Toll like receptor 2 and 4 after 30 minutes of MIP treatment suggesting recognition of MIP by toll like receptors. Moreover, MIP caused the inhibition of expression of HPV anti apoptotic gene E6, which is known to interfere with p53/PUMA/Bax apoptotic cascade. This inhibition might have played a role in transcriptional up regulation of PUMA and subsequently apoptosis. ROS was generated transiently which was concomitant with the highest transcription activation of p53 suggesting a plausible feedback loop network of p53 and ROS in the apoptosis of HeLa cells. Scavenger of ROS, such as N-acetyl-L-cysteine, decreased apoptosis suggesting ROS is an important effector of MIP induced apoptosis. Conclusion: Taken together, MIP possesses full potential to be a novel therapeutic agent in the clinical treatment of cervical cancer.

Keywords: cancer, mycobacterium, immunity, immunotherapy.

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Authors: Mengdi Zhang, Zhenji Gao, Ning Kang, Rongmei Liu

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Management and application of geological big data is an important part of China's national big data strategy. With the implementation of a national big data strategy, geological big data management becomes more and more critical. At present, there are still a lot of technology barriers as well as cognition chaos in many aspects of geological big data management and application, such as data sharing, intellectual property protection, and application technology. Therefore, it’s a key task to make better use of new technologies for deeper delving and wider application of geological big data. In this paper, we briefly introduce the basic principle of blockchain technology at the beginning and then make an analysis of the application dilemma of geological data. Based on the current analysis, we bring forward some feasible patterns and scenarios for the blockchain application in geological big data and put forward serval suggestions for future work in geological big data management.

Keywords: blockchain, intellectual property protection, geological data, big data management

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Authors: Li Chen, Feng Zhang, Shizhong Zheng

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SaikosaponinD (SSD) is a major component of saikosaponins isolated from Bupleurumfalactum. Our current study was to examine the toxic effect of SSD on liver cells and explore the possible mechanism. The results demonstrated that SSD induced mouse liver injury and led to apoptosis in LO2 cells. HE staining and TUNEL analyses showed that SSD stimulated liver injury and hepatocyte apoptosis in vivo. Subsequent experiments showed that SSD down-regulated Bcl-2 but up-regulated Bax. In vitro, SSD-treated LO2 cells exhibited apparent down-regulated expression of p-p38. Moreover, PDGF-βR agonist PDGF-BB alone significantly upregulated p38 phosphorylation, while combined with SSD, p38 phosphorylation expression was reduced. Furthermore, shRNA-mediated PDGF-βR knockdown augmented the inactivation of p-p38 and Bcl2 but abrogated the activation of Bax, these results were more obvious when shRNA combined with SSD. These data indicated that SSD stimulated liver injury and apoptosis in hepatocytes and PDGF-βR /p38 pathway may be the potential mechanistic.

Keywords: saikosaponin D, hepatotoxicity, liver injury, apoptosis, platelet-derived growth factor-β receptor, p38

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Authors: Sahar Javadi-Novashnagh, Mohammad Moradi-Shahrbabak, Mostafa Sadeghi, Katarzyna Ropka-Molik, Hossein Moradi-Shahrbabak, Maria Consuelo Mura

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The objective of this study was to investigate two single nucleotide polymorphisms located in exon 2 (g.939A > G) and intron 3 (g.4349A > G) of fatty acid binding protein 3 (FABP3) gene in two Iranian sheep breeds, Lori-Bakhtiari and Zel, using polymerase chain reaction -restriction fragment length polymorphism (PCR-RFLP) approach. The association of the polymorphisms with growth traits and blood parameters was also examined. Results revealed a g.939A > G SNP (single nucleotide polymorphism) in the exon 2 exhibiting three genotypes: AA, AG, and GG. Statistical analysis indicated that this polymorphism significantly influenced blood triglyceride (P < 0.05) and cholesterol (P < 0.08) levels as well as weaning weight (P < 0.05). Animals with AG genotype had the highest blood triglyceride level and weaning weight while the highest amount of blood cholesterol was observed in animals with GG genotype. On the other hand, no significant effect was observed on birth and fat-tail weight traits. The intron 3 (g.4349A > G) was monomorphic across the studied samples. Lori-Bakhtiari breed showed significantly higher blood triglyceride and cholesterol levels, as also birth and weaning weight compared to Zel breed (P < 0.01). Considering that the literature is bereft of any report on the association study between FABP3 SNPs and sheep growth traits and blood parameters, our findings suggest that the investigated polymorphism might be one of the main genetic factors affecting growth and physiological traits in sheep.

Keywords: FABP3 gene, fatness, weaning weight, blood triglyceride, cholesterol, Zel, Lori-Bakhtiari

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Authors: Paula Buldres, Jorge Toledo

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Objectives: This study aimed to characterize potential probiotic strains isolated from canine breast milk for use in dogs with enteropathies. Methodology: Six canine breast milk strains, one canine colostrum strain, and one control porcine breast milk strain were characterized. According to its functional properties of resistance to acids, different concentrations of bile salts, and pancreatin, its presumptive properties of safety and inhibitory effect on pathogens, non-cytotoxic characteristics, and adhesion to the intestine. The immunomodulatory effect of formulations with better probiotic characterization in vitro and in vivo was also analyzed. Results: Two strains characterized as potential probiotics were obtained, which corresponded to the canine strains (TUCO-16 and TUCO-17), presenting resistance to acidic pH, bile salts, and pancreatin, as well as an inhibitory effect on pathogenic Escherichia coli, Salmonella sp., and Clostridium perfringens. Strains TUCO-16 and TUCO-17 induced a significant increase in the expression of TNF-α and IL-8 in canine macrophages, respectively. Expression analyses of pattern recognition receptors in DH82 cells suggest that TUCO-16 and TUCO-17 might increase the TLR2 expression marker, and porcine strain (TUCO-4) increases the NOD2 expression marker. Based on the count obtained and the encapsulation yield, the best formulations correspond to FOS-Inulin for the TUCO-17 and TUCO-4 strains; Maltodextrin-Inulin for TUCO-16. All the strains are non-cytotoxic. The strain that showed the highest adhesion to intestinal epithelial cells was TUCO-17 with the FOS-Inulin formulation. On the other hand, the probiotics decreased the expression of pro-inflammatory markers in vivo, both in the intestine and in the spleen of mice. Conclusion: The combination of these three strains under study (TUCO-16, TUCO-17, and TUCO-4) would cover the probiotic properties in formulation and immunomodulation of all the markers under study.

Keywords: probiotics, gastrointestinal infec, dog, probiotic formulation, immunomodulatory probiotics

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Authors: Carmela Nardelli, Laura Iaffaldano, Valentina Capobianco, Antonietta Tafuto, Maddalena Ferrigno, Angela Capone, Giuseppe Maria Maruotti, Maddalena Raia, Rosa Di Noto, Luigi Del Vecchio, Pasquale Martinelli, Lucio Pastore, Lucia Sacchetti

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Maternal obesity and nutrient excess in utero increase the risk of future metabolic diseases in the adult life. The mechanisms underlying this process are probably based on genetic, epigenetic alterations and changes in foetal nutrient supply. In mammals, the placenta is the main interface between foetus and mother, it regulates intrauterine development, modulates adaptive responses to sub optimal in uterus conditions and it is also an important source of human amniotic mesenchymal stem cells (hA-MSCs). We previously highlighted a specific microRNA (miRNA) profiling in amnion from obese (Ob) pregnant women, here we compared the miRNA expression profile of hA-MSCs isolated from (Ob) and control (Co) women, aimed to search for any alterations in metabolic pathways that could predispose the new-born to the obese phenotype. Methods: We isolated, at delivery, hA-MSCs from amnion of 16 Ob- and 7 Co-women with pre-pregnancy body mass index (mean/SEM) 40.3/1.8 and 22.4/1.0 kg/m2, respectively. hA-MSCs were phenotyped by flow cytometry. Globally, 384 miRNAs were evaluated by the TaqMan Array Human MicroRNA Panel v 1.0 (Applied Biosystems). By the TargetScan program we selected the target genes of the miRNAs differently expressed in Ob- vs Co-hA-MSCs; further, by KEGG database, we selected the statistical significant biological pathways. Results: The immunophenotype characterization confirmed the mesenchymal origin of the isolated hA-MSCs. A large percentage of the tested miRNAs, about 61.4% (232/378), was expressed in hA-MSCs, whereas 38.6% (146/378) was not. Most of the expressed miRNAs (89.2%, 207/232) did not differ between Ob- and Co-hA-MSCs and were not further investigated. Conversely, 4.8% of miRNAs (11/232) was higher and 6.0% (14/232) was lower in Ob- vs Co-hA-MSCs. Interestingly, 7/232 miRNAs were obesity-specific, being expressed only in hA-MSCs isolated from obese women. Bioinformatics showed that these miRNAs significantly regulated (P<0.001) genes belonging to several metabolic pathways, i.e. MAPK signalling, actin cytoskeleton, focal adhesion, axon guidance, insulin signaling, etc. Conclusions: Our preliminary data highlight an altered miRNA profile in Ob- vs Co-hA-MSCs and suggest that an epigenetic miRNA-based mechanism of gene regulation could affect pathways involved in placental growth and function, thereby potentially increasing the newborn’s risk of metabolic diseases in the adult life.

Keywords: hA-MSCs, obesity, miRNA, biosystem

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Authors: Aditya Arya, Hairin Taha, Ataul Karim Khan, Nayiar Shahid, Hapipah Mohd Ali, Mustafa Ali Mohd

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This study has investigated the antidiabetic and antioxidant potential of Pseudovaria macrophylla bark extract on streptozotocin–nicotinamide induced type 2 diabetic rats. LCMS-QTOF and NMR experiments were done to determine the chemical composition in the methanolic bark extract. For in vivo experiments, the STZ (60 mg/kg/b.w, 15 min after 120 mg/kg/1 nicotinamide, i.p.) induced diabetic rats were treated with methanolic extract of Pseuduvaria macrophylla (200 and 400 mg/kg∙bw) and glibenclamide (2.5 mg/kg) as positive control respectively. Biochemical parameters were assayed in the blood samples of all groups of rats. The pro-inflammatory cytokines, antioxidant status and plasma transforming growth factor βeta-1 (TGF-β1) were evaluated. The histological study of the pancreas was examined and its expression level of insulin was observed by immunohistochemistry. In addition, the expression of glucose transporters (GLUT 1, 2 and 4) were assessed in pancreas tissue by western blot analysis. The outcomes of the study displayed that the bark methanol extract of Pseuduvaria macrophylla has potentially normalized the elevated blood glucose levels and improved serum insulin and C-peptide levels with significant increase in the antioxidant enzyme, reduced glutathione (GSH) and decrease in the level of lipid peroxidation (LPO). Additionally, the extract has markedly decreased the levels of serum pro-inflammatory cytokines and transforming growth factor beta-1 (TGF-β1). Histopathology analysis demonstrated that Pseuduvaria macrophylla has the potential to protect the pancreas of diabetic rats against peroxidation damage by downregulating oxidative stress and elevated hyperglycaemia. Furthermore, the expression of insulin protein, GLUT-1, GLUT-2 and GLUT-4 in pancreatic cells was enhanced. The findings of this study support the anti-diabetic claims of Pseudovaria macrophylla bark.

Keywords: diabetes mellitus, Pseuduvaria macrophylla, alkaloids, caffeic acid

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Authors: K. H. Reeta, Bhavana Prasher, Mitali Mukerji, Dhwani Dholakia, Sangeeta Khanna, Archana Vats, Shivam Pandey, Sandeep Seth, Subir Kumar Maulik

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Introduction Research has demonstrated a connection between coronary artery disease (CAD) and genetics. We did a deep literature mining using both bioinformatics and manual efforts to identify the susceptible polymorphisms in coronary artery disease. Further, the study sought to validate these findings in an Asian population. Methodology In first phase, we used an automated pipeline which organizes and presents structured information on SNPs, Population and Diseases. The information was obtained by applying Natural Language Processing (NLP) techniques to approximately 28 million PubMed abstracts. To accomplish this, we utilized Python scripts to extract and curate disease-related data, filter out false positives, and categorize them into 24 hierarchical groups using named Entity Recognition (NER) algorithms. From the extensive research conducted, a total of 466 unique PubMed Identifiers (PMIDs) and 694 Single Nucleotide Polymorphisms (SNPs) related to coronary artery disease (CAD) were identified. To refine the selection process, a thorough manual examination of all the studies was carried out. Specifically, SNPs that demonstrated susceptibility to CAD and exhibited a positive Odds Ratio (OR) were selected, and a final pool of 324 SNPs was compiled. The next phase involved validating the identified SNPs in DNA samples of 96 CAD patients and 37 healthy controls from Indian population using Global Screening Array. ResultsThe results exhibited out of 324, only 108 SNPs were expressed, further 4 SNPs showed significant difference of minor allele frequency in cases and controls. These were rs187238 of IL-18 gene, rs731236 of VDR gene, rs11556218 of IL16 gene and rs5882 of CETP gene. Prior researches have reported association of these SNPs with various pathways like endothelial damage, susceptibility of vitamin D receptor (VDR) polymorphisms, and reduction of HDL-cholesterol levels, ultimately leading to the development of CAD. Among these, only rs731236 had been studied in Indian population and that too in diabetes and vitamin D deficiency. For the first time, these SNPs were reported to be associated with CAD in Indian population. Conclusion: This pool of 324 SNP s is a unique kind of resource that can help to uncover risk associations in CAD. Here, we validated in Indian population. Further, validation in different populations may offer valuable insights and contribute to the development of a screening tool and may help in enabling the implementation of primary prevention strategies targeted at the vulnerable population.

Keywords: coronary artery disease, single nucleotide polymorphism, susceptible SNP, bioinformatics

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Authors: Huai-Feng Wang, Meng-Lin Lou, Ru-Lin Zhang

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One good analysis method in seismic response analysis is direct time integration, which widely adopts Rayleigh damping. An approach is presented for selection of Rayleigh damping coefficients to be used in seismic analyses to produce a response that is consistent with Modal damping response. In the presented approach, the expression of the error of peak response, acquired through complete quadratic combination method, and Rayleigh damping coefficients was set up and then the coefficients were produced by minimizing the error. Two finite element modes of soil layers, excited by 28 seismic waves, were used to demonstrate the feasibility and validity.

Keywords: Rayleigh damping, modal damping, damping coefficients, seismic response analysis

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Authors: Muhammad Saad Shoaib Khan, Rasbin Basnet, Qingyao Shu

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Phospholipids are one of the major classes of lipid comprising 10% of total grain lipid in rice. Phospholipids are the main phosphorus containing lipid in the rice endosperm, contributing to rice palatability and seed storage property. However, in the rice grain, the majority of phosphorus occur in the form of phytic acid and are highly abundant in the bran. Phytic acid, also known as hexaphosphorylated inositol (IP6), are strong chelating agents which reduces the bioavailability of essential dietary nutrients and are therefore less desirable by rice breeders. We used the CRISPR/Cas9 system to generate mutants of a phospholipase D gene (PLDα1), which is responsible for the degradation of phospholipids into phosphatidic acid (PA). In the mutants, we found a significant reduction in the concentration of phytic acid in the grain as compared to the wild-type. The biochemical analysis of the PLDα1 mutants showed that the decrease in production of phosphatidic acid is due to reduced accumulation of CDP-diacylglycerolderived phosphatidylinositol (PI), ultimately leading to lower accumulation of phytic acid in mutants. These results showed that loss of function of PLD in rice leads to lower production of phytic acid, suggesting the potential application of Ospldα1 in breeding rice with less phytic acid.

Keywords: CRISPR/Cas9, phospholipase D, phytic acid, rice

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Authors: Mukesh N. Kher, Anju P. Kunjadia, Dev S. Nauriyal, Chaitanya G. Joshi, Navin R. Sheth, Vaibhav D. Bhatt

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In-vivo immunotherapeutic potential on cytokines production and antibacterial activity of a topical herbal gel was evaluated in two breeds of cattle in bovine subclinical mastitis. The response to treatment was evaluated by enumerating somatic cell count (SCC), determining total bacterial count and studying the expression of different cytokines like (interleukin 6, 8, 12, GMCSF, interferon–γ and TNF‑α). The pre‑ and post‑treatment SCC in mastitic quarters did not differ statistically-significantly. However, total bacterial count declined significantly from day 0 onwards in both the breeds. Significant differences (P < 0.01) were observed in all types of cytokines production on day 0, 5, and 21 post last treatments in both the breeds. The comparison of cytokine expression profiles between crossbred and Gir cattle affirmed a significant difference in expression of IL-6 and TNF-α. The topical herbal gel showed immunomodulatory and antimicrobial activities in subclinical mastitis, and therefore the work supports its use as substitute herbal therapy against subclinical mastitis in bovines.

Keywords: antibacterial activity, immunomodulation, herbal gel, subclinical mastitis

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Authors: K. S. Vimal, D. Bodhini, K. Ramya, N. Lakshmipriya, R. M. Anjana, V. Sudha, J. A. Lovegrove, V. Mohan, V. Radha

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Gene-lifestyle interaction studies have been carried out in various populations. However, to date there are no studies in an Asian Indian population. Hence, we examined whether lifestyle factors such as diet and physical activity modify the association between fat mass and obesity–associated (FTO) gene variants and obesity and type 2 diabetes (T2D) in an Asian Indian population. We studied 734 unrelated T2D and 884 normal glucose-tolerant (NGT) participants randomly selected from the Chennai Urban Rural Epidemiology Study (CURES) in Southern India. Obesity was defined according to the World Health Organization Asia Pacific Guidelines (non-obese, BMI < 25 kg/m2; obese, BMI ≥ 25 kg/m2). Six single nucleotide polymorphisms (SNPs) in the FTO gene (rs9940128, rs7193144, rs8050136, rs918031, rs1588413 and rs11076023) identified from recent genome-wide association studies for T2D were genotyped by polymerase chain reaction-restriction fragment length polymorphism and direct sequencing. Dietary assessment was carried out using a validated food frequency questionnaire and physical activity was based upon the self-report. Interaction analyses were performed by including the interaction terms in the model. A joint likelihood ratio test of the main SNP effects and the SNP-diet/physical activity interaction effects was used in the linear regression analyses to maximize statistical power. Statistical analyses were performed using STATA version 13. There was a significant interaction between FTO SNP rs8050136 and carbohydrate energy percentage (Pinteraction=0.04) on obesity, where the ‘A’ allele carriers of the SNP rs8050136 had 2.46 times higher risk of obesity than those with ‘CC’ genotype (P=3.0x10-5) among individuals in the highest tertile of carbohydrate energy percentage. Furthermore, among those who had lower levels of physical activity, the ‘A’ allele carriers of the SNP rs8050136 had 1.89 times higher risk of obesity than those with ‘CC’ genotype (P=4.0x10-5). We also found a borderline interaction between SNP rs11076023 and carbohydrate energy percentage (Pinteraction=0.08) on T2D, where the ‘A’ allele carriers in the highest tertile of carbohydrate energy percentage, had 1.57 times higher risk of T2D than those with ‘TT’ genotype (P=0.002). There was also a significant interaction between SNP rs11076023 and physical activity (Pinteraction=0.03) on T2D. No further significant interactions between SNPs and macronutrient intake or physical activity on obesity and T2D were observed. In conclusion, this is the first study to provide evidence for a gene-diet and gene-physical activity interaction on obesity and T2D in an Asian Indian population. These findings suggest that the association between FTO gene variants and obesity and T2D is influenced by carbohydrate intake and physical activity levels. Greater understanding of how FTO gene influences obesity and T2D through dietary and exercise interventions will advance the development of behavioral intervention and personalised lifestyle strategies predicted to reduce the development of metabolic diseases in ‘A’ allele carriers of both SNPs in this Asian Indian population.

Keywords: dietary intake, FTO, obesity, physical activity, type 2 diabetes, Asian Indian.

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Authors: Hema Bhardwaj, D. Srinivasa Rao

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Technology for analysing, processing, and extracting meaningful data from enormous and complicated datasets can be termed as "big data." The technique of big data mining and big data analysis is extremely helpful for business movements such as making decisions, building organisational plans, researching the market efficiently, improving sales, etc., because typical management tools cannot handle such complicated datasets. Special computational and statistical issues, such as measurement errors, noise accumulation, spurious correlation, and storage and scalability limitations, are brought on by big data. These unique problems call for new computational and statistical paradigms. This research paper offers an overview of the literature on big data mining, its process, along with problems and difficulties, with a focus on the unique characteristics of big data. Organizations have several difficulties when undertaking data mining, which has an impact on their decision-making. Every day, terabytes of data are produced, yet only around 1% of that data is really analyzed. The idea of the mining and analysis of data and knowledge discovery techniques that have recently been created with practical application systems is presented in this study. This article's conclusion also includes a list of issues and difficulties for further research in the area. The report discusses the management's main big data and data mining challenges.

Keywords: big data, data mining, data analysis, knowledge discovery techniques, data mining challenges

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Authors: Durhane Wong-Rieger, Kawaldip Sehmi, Nicola Bedlington, Nicole Boice, Tamás Bereczky

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Patient-generated health data should be seen as the expression of the experience of patients, including the outcomes reflecting the impact a treatment or service had on their physical health and wellness. We discuss how the healthcare system can reach a place where digital is a determinant of health - where data is generated by patients and is respected and which acknowledges their contribution to science. We explore the biggest barriers facing this. The International Experience Exchange with Patient Organisation’s Position Paper is based on a global patient survey conducted in Q3 2021 that received 304 responses. Results were discussed and validated by the 15 patient experts and supplemented with literature research. Results are a subset of this. Our research showed patient communities want to influence how their data is generated, shared, and used. Our study concludes that a reasonable framework is needed to protect the integrity of patient data and minimise abuse, and build trust. Results also demonstrated a need for patient communities to have more influence and control over how health data is generated, shared, and used. The results clearly highlight that the community feels there is a lack of clear policies on sharing data.

Keywords: digital health, equitable access, humanise healthcare, patient data

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Authors: Magdalena Rusady Goey, Gordon Strathdee, Neil Perkins

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Background: Acute lymphoblastic leukaemia (ALL) is the most frequent type of childhood malignancy, accounting for 25% of all cases. TWIST2, a basic helix-loop-helix transcription factor, has been implicated in ALL development. Prior studies found that TWIST2 undergoes epigenetic silencing in more than 50% cases of ALL through promoter hypermethylation and suggested that re-expression of TWIST2 may inhibit cell growth/survival of leukaemia cell lines. TWIST2 has also been implicated as a regulator of NF-kappaB activity, which is constitutively active in leukaemia. Here, we use a lentiviral transductions system to confirm the importance of TWIST2 in controlling leukaemia cell growth and to investigate whether this is achieved through altered regulation of NF-kappaB activity. Method: Re-expression of TWIST2 in leukaemia cell lines was achieved using lentiviral-based transduction. The lentiviral vector also expresses enhanced green fluorescent protein (eGFP), allowing transduced cells to be tracked using flow cytometry. Analysis of apoptosis and cell proliferation were done using annexinV and VPD450 staining, respectively. Result and Discussion: TWIST2-expressing cells were rapidly depleted from a mixed population in ALL cell lines (NALM6 and Reh), indicating that TWIST2 inhibited cell growth/survival of ALL cells. In contrast, myeloid cell lines (HL60 and K562) were comparatively insensitive to TWIST2 re-expression. Analysis of apoptosis and cell proliferation found no significant induction of apoptosis, but did find a rapid induction of proliferation arrest in TWIST2-expressing Reh and NALM6 cells. Initial experiment with NF-kappaB inhibitor demonstrated that inhibition of NF-kappaB has similar impact on cell proliferation in the ALL cell lines, suggesting that TWITST2 may induce cell proliferation arrest through inhibition of NF-kappaB. Conclusion: The results of this study suggest that epigenetic inactivation of TWIST2 in primary ALL leads to increased proliferation, potentially by altering the regulation of NF-kappaB.

Keywords: leukaemia, acute lymphoblastic leukaemia, NF-kappaB, TWIST2, lentivirus

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Authors: Karthika Durairaj, Buvaneswari G., Gowdham M., Gilles M., Velmurugan G.

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Background: Hyperglycaemia is the primary cause of metabolic illness. Recently, researchers focused on the possibility that chemical exposure could promote metabolic disease. Hyperglycaemia causes a variety of metabolic diseases dependent on its etiologic conditions. According to animal and population-based research, individual chemical exposure causes health problems through alteration of endocrine function with the influence of microbial influence. We were intrigued by the function of gut microbiota variation in high fat and chemically induced hyperglycaemia. Methodology: C57/Bl6 mice were subjected to two different treatments to generate the etiologic-based diabetes model: I – a high-fat diet with a 45 kcal diet, and II - endocrine disrupting chemicals (EDCs) cocktail. The mice were monitored periodically for changes in body weight and fasting glucose. After 120 days of the experiment, blood anthropometry, faecal metagenomics and metabolomics were performed and analyzed through statistical analysis using one-way ANOVA and student’s t-test. Results: After 120 days of exposure, we found hyperglycaemic changes in both experimental models. The treatment groups also differed in terms of plasma lipid levels, creatinine, and hepatic markers. To determine the influence on glucose metabolism, microbial profiling and metabolite levels were significantly different between groups. The gene expression studies associated with glucose metabolism vary between hosts and their treatments. Conclusion: This research will result in the identification of biomarkers and molecular targets for better diabetes control and treatment.

Keywords: hyperglycaemia, endocrine-disrupting chemicals, gut microbiota, host metabolism

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Authors: S. Shujan, A. T. Rupasinghe, N. L. Gunawardena

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Numerous studies have determined that there is a direct correlation between the successful interviewee and the nonverbal behavioral patterns of that person during the interview. In this study, we focus on formations of interview questions in such a way that, it gets an opportunity for assessing interviewee through the answers using the nonverbal behavioral cues. From all the nonverbal behavioral factors we have identified, in this study priority is given to the ‘facial expression variations’ with the assistance of facial expression analytics tool; this research proposes a novel approach in question formation for the assessment of interviewees in ‘Software Industry’.

Keywords: assessments, hirability, interviews, non-verbal behaviour patterns, question formation

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