Search

Aims: The importance of screening for hemoglobinopathies is well-documented in India. However, information on the distribution of hemoglobinopathies in Karnataka is lacking. The present study focuses on determining the spectrum of hemoglobinopathies for various districts of Karnataka. Materials and Methods and Results: A retrospective analysis of samples registered for hemoglobinopathies for a period of 5 years (2017–2021) was carried out. A total of 17066 records registered only from the Karnataka region, were anonymized and retrieved. The data included gender, age, district, and results of the tests. The results were based on complete blood count, peripheral smear, and capillary electrophoresis (CE) pattern. The data were revalidated by pathologists, and the unambiguous data were analyzed for the study. One-fourth of the records (25%) showed abnormal hematological parameters. The number of female records (66%) was twice that of males and both genders showed higher distribution of thalassemia, followed by variants and double heterozygotes (DH). Several cases of thalassemia major were identified below the age of 17 years. The majority of thalassemia cases were β thal and 93% of them were β thal trait. Among the variants, HbS was more prevalent than HbE. Among the districts, Hassan had a 35.2% thal, Mysuru had a 7.2% variant, and Chitradurga had a 5.5% DH. Thalassemia, variants, and DH were distributed across several districts of Karnataka to various levels. Conclusion: The comprehensive retrospective analysis of the spectrum of hemoglobinopathies in various districts of Karnataka serves as evidence to carry out a prospective study on population screening where the incidence of thalassemia and structural variants is high.

Antimicrobial drug resistance within ESKAPE pathogens is a formidable global challenge, necessitating innovative solutions. This review explores a multifaceted strategy incorporating nanotechnology, CRISPR/Cas9, and other cutting-edge approaches to effectively combat multidrug resistance in ESKAPE bacteria. Nanotechnology presents a promising avenue through targeted drug delivery systems like antibiotic nanoparticles and antibiotic–antibody conjugates (AACs). While these nanostructures aim to enhance therapeutic efficacy and mitigate resistance spread, challenges such as anti-PEG antibodies and optimal drug release must be considered. Inspired by successful anticancer nanomedicines, nanotechnology seeks to optimize drug penetration and retention within infected tissues. The revolutionary CRISPR/Cas9 gene-editing technology offers a precise and tailored approach by selectively targeting and modifying bacterial resistance genes. This holds the potential to reverse or eliminate drug resistance in ESKAPE pathogens, though challenges like off-target effects and efficient delivery mechanisms require attention for clinical translation. Additionally, alternative approaches such as fecal microbial transplantation, bacteriophage therapy, and probiotic bacterial replacement are actively explored in clinical trials. These strategies diversify the arsenal against antibiotic resistance by targeting unique vulnerabilities in ESKAPE pathogens. A comprehensive and multidisciplinary strategy is imperative to effectively address antimicrobial drug resistance in ESKAPE pathogens. Integration of nanotechnology, CRISPR/Cas9, and emerging approaches offers a synergistic solution, holding promise in overcoming the challenges posed by these resilient multidrug-resistant bacteria. This review provides insights into current research, challenges, and potential breakthroughs, emphasizing the urgency for collaborative efforts to safeguard global health.

We study the oscillatory behavior of the second-order quasi-linear retarded difference equation \Delta(p(n)(\Delta y(n))^\alpha)+\eta(n) y^\beta(n- k)=0 under the condition $\sum_{n=n_0}^\infty p^{-\frc1{\alpha}}(n)

Background: The presumptive diagnosis of hemoglobinopathies relies on routine tests such as Complete Blood Count (CBC), peripheral blood smear, Liquid Chromatography (LC), and Capillary Electrophoresis (CE), along with clinical findings. Pathologists suggest molecular sequencing of HBA and HBB genes to correlate blood picture with clinical findings in order to identify unknown rare haemoglobin (Hb) variants or variants that coelute with Hb. This paper presents a low-resolution mass spectrometry (MS)-based method for presumptive identification of variants that eluted in zone 12 of CE, followed by molecular sequencing of the HBB gene for a definitive diagnosis of hemoglobinopathies. Methods: Eight patient samples with a variant peak in zone 12 of CE (Sebia) were analyzed using MS. The mass-to-charge ratio (m/z) observed was deconvoluted to determine the mass of Hb variants. The β variants were subsequently confirmed through molecular sequencing. Results: Based on the intact mass of the variants, there were two samples of the α variant (α + 58 Da and α + 44 Da), and six samples of the β variant. Out of these six β variant samples, three were the β + 58 Da variant, and three were the β + 30 Da variant. By correlating the intact mass information with the CE pattern and considering the ethnicity of the patients, it was presumed that the α variants were HbJ Meerut (α + 58 Da, x-axis 102) and HbJ Paris-I (α + 44 Da, x-axis 80). Molecular analysis confirmed the identity of β variants as Hb Rambam/HbJ Cambridge, HbJ Bangkok (+58 Da), and Hb Hofu (+30 Da). Conclusion: The mass information of Hb variants obtained using Electrospray triple quadrupole MS assists pathologists in recommending the appropriate molecular sequencing for identifying unknown variants.

In today's digital era, the rise of hate speech has emerged as a critical concern, driven by the rapid information-sharing capabilities of social media platforms and online communities. As the internet expands, the proliferation of harmful content, including hate speech, presents considerable obstacles in ensuring a secure and inclusive online environment. In response to this challenge, researchers have embraced machine learning and deep learning methods to create automated systems that can effectively detect hate speech and conduct sentiment analysis, offering potential solutions to address this pressing issue. This survey article provides a comprehensive overview of recent advancements in hate speech detection and sentiment analysis using machine learning and deep learning models. We present an in-depth analysis of various methodologies and datasets employed in this domain. Additionally, we explore the unique challenges faced by these models in accurately identifying and classifying hate speech and sentiment in online text. Finally, we outline areas where more study is needed and suggest potential new avenues for exploration in the field of hate speech identification and sentiment analysis. Using the results of this survey, we hope to encourage the development of more effective machine learning and deep learning-based solutions to curb hate speech and promote a more inclusive online environment.

In the field of chemical and medical sciences, topological indices are used to study the chemical, biological, clinical, and therapeutic aspects of pharmaceuticals. The COVID-19 pandemic is largely recognized as the most life-threatening crisis confronting medical advances. Scientists have tested various antiviral drugs and discovered that they help people recover from viral infections like COVID-19. Antiviral medications, such as Arbidol, Chloroquine, Hydroxy-Chloroquine, Lopinavir, Remdesivir, Ritonavir, Thalidomide and Theaflavin, are often used to treat COVID-19. In this paper, we define Diameter Eccentricity Based vertex degree and employ it to introduce a new polynomial called $ D\varepsilon- $ Polynomial. Using the newly introduced polynomial, we derive new topological indices, namely, diameter eccentricity based and hyper diameter eccentricity based indices. In order to check the efficacy of our indices, we derive the $ D\varepsilon- $ polynomials for the eight COVID-19 drugs mentioned above. Using these polynomials, we compute our proposed topological descriptors for the eight COVID-19 drugs. We perform quantitative structure-property relationship (QSPR) analysis by identifying the best fit curvilinear/multilinear regression models based on our topological descriptors for 8 physico- chemical properties of the COVID-19 drugs. We also perform quantitative structure-activity relationship (QSAR) analysis by identifying the best fit multilinear regression model for predicting the $ IC_{50} $ values for the eight COVID-19 drugs. Our findings and models may be useful in the development of new COVID-19 medication.

Impairment of the intestinal epithelial barrier is frequently seen as collateral damage in various local and systemic inflammatory conditions. The inflammatory process is characterized by reciprocal interactions between the host intestinal epithelium and mucosal innate immune cells, e.g., macrophages. This article provides step-by-step instructions on how to set up a murine enteroid–macrophage co-culture by culturing cellular elements in proximity separated by a porous membrane. Unlike previously published co-culture systems, we have combined enteroids grown from C57BL6j mice with syngeneic bone marrow-derived macrophages to preclude potential allo-reactions between immune cells and epithelium. Transformation of intestinal crypts into proliferative enteroids was achieved by cultivation in Wnt3a-Noggin-R-Spondin-conditioned medium supplemented with ROCK inhibitor Y-27632. The differentiated phenotype was promoted by the use of the Wnt3-deprived EGF-Noggin-R-Spondin medium. The resulting co-culture of primary cells can be employed as a basic model to better understand the reciprocal relationship between intestinal epithelium and macrophages. It can be used for in vitro modelling of mucosal inflammation, mimicked by stimulation of macrophages either while being in co-culture or before being introduced into co-culture, to simulate enterogenic sepsis or systemic conditions affecting the intestinal tract.

This article offers a brief overview about cyber-physical systems enabled by blockchain (CPS). Dissects various blockchain-enabled CPS reported on the operations and blockchain characteristics used in the literature. Base of its time sensitiveness and throughput requirements, we identify and categories key common CPS operations that can be activated by blockchain. We also develop blockchain features and categories in terms of diverse levels of benefits to CPS like security, privacy, immutability, tolerance of defects, interoperability's, data origin, atomicity, automation, information/service sharing and trust. This paper provides an overview of the concept of intelligent cities as well as emerging technologies and a quick overview of cyber-physical systems. It then discusses CPS' potential role in the development of intelligent city apps and some real-life examples of CPS adaptation for city smart projects. A decentralized database based on distributed ledgers has been introduced. Distributed ledgers are a distributed database with a network connection node. These nodes include ledgers that list transactions with timestamps.

Recently, cyber-attacks used unusual different malicious code or highly developed attack approaches like zero-day attacks which makes the process of detection more complex and difficult and thus traditional intrusion detection systems are unsuitable. For instance, 'botnet attacks are recent cyber-security threats. The endpoints are attacked either through malicious code or vulnerabilities. This affected system connects a communications channel to a command and control (C&C) server and issues comments to attack target servers.Malicious attacks are slow in carrying out denial of service (DoS) against webserver son protocols at application level like HTTP. Conventional signature-based intrusion detection systems are not appropriate to detect these attacks. To overcome this challenge, an artificial intelligence regression based malicious attack detection system is proposed for real-time attack detection of over encrypted traffic at application level. The process of malicious attack detection is done by the proposed ElasticNet Regression Model (ENetRM). The method has been validated in a real time application which proved its feasibility and ability to detect various slow DoS attacks over trafficin real-time. This goal is consistently achieved and thus the proposed model outperforms few standard approaches which are considered like Intrusion Detection System (NIDS), Novel Nested-Arc Hidden semi-Markov Model (NAHSMM) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN).It is found that the proposed ENetRM method achieves 0.946 of precision. 0.9764 of recall, 0.9221 of F1-score, 97.04% of throughput and 53.48% of computation overhead.

With various malware, botnets are the legitimate risk increasing against cybersecurity providing criminal operations like malware dispersal, distributed denial of service attacks, fraud clicking, phishing, and identification of theft. Existing techniques used for detection of botnet, which are suitable only for specific command of botnet and protocol for controlling and do not support botnet detection at earlier stages. In several computer security defense systems, honeypots are deployed successfully by security defenders. As honeypots can attract botnet compromises and expose spies in botnet membership and behaviors of the attacker, they are broadly employed in botnet defense. Thus, attackers whose role is to construct and maintain botnets have to determine honeypot trap avoiding methods. To handle the issues related to botnet attacks, machine learning techniques are used to support detection and prevent bot attacks. An Ensemble Classifier Algorithm with Stacking Process (ECASP) is proposed in this paper to select optimal features fed as input to the machine learning classifiers to estimate the botnet detection performance. As a result, the method achieves proposed achieves 94.08% accuracy, 86.5% sensitivity, 85.68% specificity, and 78.24% F-measure.

Background At present, there are no validated quantitative scales available to measure patient-centred quality of care in health facilities providing services for tuberculosis (TB) patients in India and low-income and middle-income countries.Methods Initial themes and items reflective of TB patient’s perceived quality of care were developed using qualitative interviews. Content adequacy of the items were ascertained through Content validity Index (CVI) and content validity ratio (CVR). Pilot testing of the questionnaire for assessing validity and reliability was undertaken among 714 patients with TB. Sampling adequacy and sphericity were tested by Kaiser-Meyer-Olkin and Bartlett’s test, respectively. Exploratory and confirmatory factor analysis was undertaken to test validity. Cronbach’s α and test–retest scores were used to test reliability.Results A 32-item tool measuring patient-perceived quality of TB distributed across five domains was developed initially based on a CVI and CVR cut-off score of 0.78 and cognitive interviews with patients with TB. Bartlett’s test results showed a strong significance f (χ2=3756 and p1 which accounted for 60.9% of the total variance of items. Correlation (z-value >1.96) between items and factors was highly significant and Cronbach’s α was acceptable for the global scale (0.76) for the four factors. Intraclass correlation coefficient and the test retest scores for four factors were (

Hyperspectral Image (HSI) is a spatially sampled image collected from a lot of neighboring narrowed spectrum bands via hyperspectral sensor. The process of HSIs is a difficult obligation because of the high-dimensional image features. Conventional techniques mainly utilize hand-made characteristics that are not fit for classification. For the purpose of enhancing the correctness and reducing the overall time complexity, an efficient technique called Gaussian Bilateral Filtered Hartley Feature Transformation Based Infomax Boost Classification (GBFHFT-IBC) is introduced. The input hyperspectral image is divided into the number of spectral bands. The proposed GBFHFT-IBC method includes three fundamental procedures, which include preprocessing, characteristics classification and extraction. Preprocessing is carried out using a Gaussian kernelized bilateral filter that replaces the pixel intensity from the picture with the weighted to take the position of the intensity of every pixel from the picture with the prejudiced average of neighboring pixels resulting in it removes the noisy pixels and improve the image quality. After preprocessing, the different characteristics like texture, color and shape are extracted from the image using the Discrete Hartley transformation technique. With the extracted features, the Infomax Boost method is applicable when classifying different scenes from the spectrum band, which has to be grouped into various categories with the top categorization accuracy that consider the minimal error rates. The experiments are done using the hyperspectral picture dataset composed of various factors like categorization accuracy, PSNR, positive and negative rate, and timeline complexity considering the number of spectral bands. The observed result shows that the presented GBFHFT-IBC method improves the hyperspectral image classification correctness, PSNR and minimized negative and positive rates, which include timeline complexity compared to using the sophisticated techniques.

Let be a graph and let be a positive integer. Let = and . The -token graph is the graph with vertex set and two vertices and are adjacent if and , where denotes the symmetric difference. In this paper we present several basic results on 2-token graphs.

For bacteria to thrive in an environment with competitors, phages and environmental cues, they use different strategies, including Type VI Secretion Systems (T6SSs) and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) to compete for space. Bacteria often use quorum sensing (QS), to coordinate their behavior as the cell density increases. Like other aliivibrios, Aliivibrio wodanis 06/09/139 harbors two QS systems, the main LuxS/LuxPQ system and an N-acyl homoserine lactone (AHL)-mediated AinS/AinR system and a master QS regulator, LitR. To explore the QS and survival strategies, we performed genome analysis and gene expression profiling on A. wodanis and two QS mutants (ΔainS and ΔlitR) at two cell densities (OD600 2.0 and 6.0) and temperatures (6 and 12°C). Genome analysis of A. wodanis revealed two CRISPR systems, one without a cas loci (CRISPR system 1) and a type I-F CRISPR system (CRISPR system 2). Our analysis also identified three main T6SS clusters (T6SS1, T6SS2, and T6SS3) and four auxiliary clusters, as well about 80 potential Type VI secretion effectors (T6SEs). When comparing the wildtype transcriptome data at different cell densities and temperatures, 13–18% of the genes were differentially expressed. The CRISPR system 2 was cell density and temperature-independent, whereas the CRISPR system 1 was temperature-dependent and cell density-independent. The primary and auxiliary clusters of T6SSs were both cell density and temperature-dependent. In the ΔlitR and ΔainS mutants, several CRISPR and T6SS related genes were differentially expressed. Deletion of litR resulted in decreased expression of CRISPR system 1 and increased expression of CRISPR system 2. The T6SS1 and T6SS2 gene clusters were less expressed while the T6SS3 cluster was highly expressed in ΔlitR. Moreover, in ΔlitR, the hcp1 gene was strongly activated at 6°C compared to 12°C. AinS positively affected the csy genes in the CRISPR system 2 but did not affect the CRISPR arrays. Although AinS did not significantly affect the expression of T6SSs, the hallmark genes of T6SS (hcp and vgrG) were AinS-dependent. The work demonstrates that T6SSs and CRISPR systems in A. wodanis are QS dependent and may play an essential role in survival in its natural environment.

Background Quorum Sensing (QS) is a cell-to-cell communication system that bacteria utilize to adapt to the external environment by synthesizing and responding to signalling molecules called autoinducers. The psychrotrophic bacterium Aliivibrio wodanis 06/09/139, originally isolated from a winter ulcer of a reared Atlantic salmon, produces the autoinducer N-3-hydroxy-decanoyl-homoserine-lactone (3OHC10-HSL) and encodes the QS systems AinS/R and LuxS/PQ, and the master regulator LitR. However, the role of QS in this bacterium has not been investigated yet. Results In the present work we show that 3OHC10-HSL production is cell density and temperature-dependent in A. wodanis 06/09/139 with the highest production occurring at a low temperature (6 °C). Gene inactivation demonstrates that AinS is responsible for 3OHC10-HSL production and positively regulated by LitR. Inactivation of ainS and litR further show that QS is involved in the regulation of growth, motility, hemolysis, protease activity and siderophore production. Of these QS regulated activities, only the protease activity was found to be independent of LitR. Lastly, supernatants harvested from the wild type and the ΔainS and ΔlitR mutants at high cell densities show that inactivation of QS leads to a decreased cytopathogenic effect (CPE) in a cell culture assay, and strongest attenuation of the CPE was observed with supernatants harvested from the ΔlitR mutant. Conclusion A. wodanis 06/09/139 use QS to regulate a number of activities that may prove important for host colonization or interactions. The temperature of 6 °C that is in the temperature range at which winter ulcer occurs, plays a role in AHL production and development of CPE on a Chinook Salmon Embryo (CHSE) cell line.

Abstract\nCULMINATIONSThe ureter typically experiences a frequency of one to five peristaltic contractions per minute. However, it is important to note that these contractions can be disrupted by various physical and mechanical irritants. Ionic contents in the urine make it electrically conducting and responsive to electromagnetic body forces. MHD can be deployed in bio magnetic therapy to control or mitigate symptoms associated with peristaltic pumping in the urinary system.  This article therefore focuses on the hydromagnetic effects on flow patterns of urine with debris (monoliths). The mechanism of urine flow is largely coordinated by the kidneys. The flow inside the ureter is interrupted by microliths, which are generated by the sedimentation of excretory products. To simulate this, a two-phase formulation is adopted, comprising the electromagnetic urological viscous fluid phase and the particulate phase for solid grains. The peristaltic propulsion of two-phase liquid in the ureter is simulated as a sinusoidal wave propagation of incompressible non-Newtonian fluid. The Williamson viscoelastic model is deployed for the rheology. Heat transfer is also included with Soret thermo-diffusion and viscous heating effects. Long wave and low Reynolds number approximations are employed based on lubrication theory. The mass, momentum, energy and concentration conservation equations with associated boundary conditions are rendered non-dimensional via appropriate scaling transformations. A numerical solution is achieved via BVP4C MATLAB quadrature.  Graphical visualizations of the velocity, temperature and concentration (solid grains) are given for the influence of suspension parameter (ζ), Hartmann number (M), Prandtl number (Pr), Weissenburg number (We), particle volume fraction (C), Eckert number (Ec), Soret number (Sr), Schmidt number (Sc). The novelty of the present work is therefore the simultaneous consideration of a generalized two-phase model, wall slip, non-Newtonian characteristics, cross diffusion, viscous dissipation, mass diffusion, magnetic body force and curvature effects in peristaltic urological transport, which has not been undertaken previously. The detailed simulations reveal that the flow velocity is reduced due to the presence of solid particles and the channel curvature, in comparison to the flow in an unobstructed channel devoid of solid particles. Enhancing the hydrodynamic slip parameter speeds up the movement of particles and fluid near the channel walls, boosts wall skin friction, raises pressure difference in the pumping area, and amplifies bolus magnitudes.The rise in peristaltic pumping results in a reduction in solid particle concentration, which is significant phenomena.This theoretical approach may aid in treating conditions such as Urinary Tract Infections (UTIs). The computations effectively demonstrate that significant manipulation of urological pumping characteristics can be achieved with an electromagnetic field. Some new features of two-phase ureteral dynamics are highlighted as relevant to magnetic therapy techniques, which may be beneficial to clinicians.A detailed new formulation is given for magnetohydrodynamic (MHD) two-phase Williamson non-Newtonian ureteral transport with mass diffusion, Soret cross diffusion, viscous heating and peristaltic wave propulsion.We compute numerically the pressure gradient, skin friction, Nusselt number, and wall shear stress in a planar channel with flexible walls, which serves as a model for the ureter under a transverse magnetic field.We also investigate the impact of Hartmann number and Weissenberg non-Newtonian number on fluid and particle phase velocities.The present work reveals some interesting insights into electromagnetic ureteral peristaltic multi-phase non-Newtonian thermo-solutal transport phenomena via extensive visualization.There is a strong suppression in the ureteral fluid phase velocity for greater magnetic field confirming the excellent flow control abilities of Magnetic Ureteral Therapy (MUT).A detailed new formulation is given for magnetohydrodynamic (MHD) two-phase Williamson non-Newtonian ureteral transport with mass diffusion, Soret cross diffusion, viscous heating and peristaltic wave propulsion.We compute numerically the pressure gradient, skin friction, Nusselt number, and wall shear stress in a planar channel with flexible walls, which serves as a model for the ureter under a transverse magnetic field.We also investigate the impact of Hartmann number and Weissenberg non-Newtonian number on fluid and particle phase velocities.The present work reveals some interesting insights into electromagnetic ureteral peristaltic multi-phase non-Newtonian thermo-solutal transport phenomena via extensive visualization.There is a strong suppression in the ureteral fluid phase velocity for greater magnetic field confirming the excellent flow control abilities of Magnetic Ureteral Therapy (MUT). [ABSTRACT FROM AUTHOR]