Secular trends in the utility of SGLT-2 inhibitors in heart failure patients with type 2 diabetes mellitus across Metro South Health hospitals in South-East Queensland.

BACKGROUND: The 2018 Australian Heart Failure (HF) guidelines strongly recommended commencing sodium-glucose co-transporter-2 inhibitors (SGLT-2is) in HF patients with type 2 diabetes mellitus (T2DM). The uptake of SGLT-2is for HF patients with T2DM in our health service is unknown. AIMS: To determine the adoption of the 2018 HF guidelines by assessing the temporal trends of SGLT-2is' usage in HF patients with T2DM at Metro South Health (MSH) hospitals, in South-East Queensland. METHODS: Retrospective analysis of all HF patients (ejection fraction (EF) < 50%) with T2DM who were managed within MSH hospitals between June 2018 and June 2021. RESULTS: A total of 666 patients met the inclusion criteria with 918 HF encounters. Mean age was 72 years and 71% were male (473/666). Mean EF was 30% (SD ± 11%), and mean estimated glomerular filtration rate was 48 mL/min/1.73 m2 (SD ± 25). Fifty-four per cent (362/666) had contraindications to SGLT-2is. Among those without contraindications, there was a five-fold increase in the utility of SGLT-2is, 7% (2/29) before versus 38% (103/275) after implementation of the HF guidelines (P < 0.001). Patients on SGLT-2is were younger (64 years vs 69 years, P = 0.002) and had a lower number of HF hospitalisations (1.1 vs 2.1, P = 0.01). CONCLUSIONS: During the study period, 54% of our HF patients with T2DM were not on SGLT-2is due to prescribing guidelines/limitations in the Australian context. We observed a five-fold significant increase in the uptake of SGLT-2is before and after implementation of HF guidelines among patients without contraindications to SGLT-2is. There were significantly fewer HF hospitalisations among patients on SGLT-2is compared to those without.

Evaluation of Growth Responses of Lettuce and Energy Efficiency of the Substrate and Smart Hydroponics Cropping System.

Smart sensing devices enabled hydroponics, a concept of vertical farming that involves soilless technology that increases green area. Although the cultivation medium is water, hydroponic cultivation uses 13 ± 10 times less water and gives 10 ± 5 times better quality products compared with those obtained through the substrate cultivation medium. The use of smart sensing devices helps in continuous real-time monitoring of the nutrient requirements and the environmental conditions required by the crop selected for cultivation. This, in turn, helps in enhanced year-round agricultural production. In this study, lettuce, a leafy crop, is cultivated with the Nutrient Film Technique (NFT) setup of hydroponics, and the growth results are compared with cultivation in a substrate medium. The leaf growth was analyzed in terms of cultivation cycle, leaf length, leaf perimeter, and leaf count in both cultivation methods, where hydroponics outperformed substrate cultivation. The results of the 'AquaCrop simulator also showed similar results, not only qualitatively and quantitatively, but also in terms of sustainable growth and year-round production. The energy consumption of both the cultivation methods is compared, and it is found that hydroponics consumes 70 ± 11 times more energy compared to substrate cultivation. Finally, it is concluded that smart sensing devices form the backbone of precision agriculture, thereby multiplying crop yield by real-time monitoring of the agronomical variables.

Algorithmic Approach to Virtual Machine Migration in Cloud Computing with Updated SESA Algorithm.

Cloud computing plays an important role in every IT sector. Many tech giants such as Google, Microsoft, and Facebook as deploying their data centres around the world to provide computation and storage services. The customers either submit their job directly or they take the help of the brokers for the submission of the jobs to the cloud centres. The preliminary aim is to reduce the overall power consumption which was ignored in the early days of cloud development. This was due to the performance expectations from cloud servers as they were supposed to provide all the services through their services layers IaaS, PaaS, and SaaS. As time passed and researchers came up with new terminologies and algorithmic architecture for the reduction of power consumption and sustainability, other algorithmic anarchies were also introduced, such as statistical oriented learning and bioinspired algorithms. In this paper, an indepth focus has been done on multiple approaches for migration among virtual machines and find out various issues among existing approaches. The proposed work utilizes elastic scheduling inspired by the smart elastic scheduling algorithm (SESA) to develop a more energy-efficient VM allocation and migration algorithm. The proposed work uses cosine similarity and bandwidth utilization as additional utilities to improve the current performance in terms of QoS. The proposed work is evaluated for overall power consumption and service level agreement violation (SLA-V) and is compared with related state of art techniques. A proposed algorithm is also presented in order to solve problems found during the survey.

Identification of polypharmacological anticancerous molecules against Aurora kinase family of proteins.

The Human Aurora Kinase (AURK) protein family is the key player of cell cycle events including spindle assembly, kinetochore formation, chromosomal segregation, centrosome separation, microtubule dynamics, and cytokinesis. Their aberrant expression has been extensively linked with chromosomal instability in addition to derangement of multiple tumor suppressors and oncoprotein regulated pathways. Therefore, the AURK family of kinases is a promising target for the treatment of various types of cancer. Over the past few decades, several potential inhibitors of AURK proteins have been identified and have reached various phases of clinical trials. But very few molecules have currently crossed the safety criteria due to their various toxic side effects. In the present study, we have adopted a computational polypharmacological strategy and identified four novel molecules that can target all three AURKs. These molecules were further investigated for their binding stabilities at the ATP binding pocket using molecular dynamics based simulation studies. The molecules selected adopting a multipronged computational approach can be considered as potential AURKs inhibitors for cancer therapeutics.

Structural and functional insights into the spike protein mutations of emerging SARS-CoV-2 variants.

Since the emergence of the first case of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus (SARS-CoV-2), the viral genome has constantly undergone rapid mutations for better adaptation in the host system. These newer mutations have given rise to several lineages/ variants of the virus that have resulted in high transmission and virulence rates compared to the previously circulating variants. Owing to this, the overall caseload and related mortality have tremendously increased globally to > 233 million infections and > 4.7 million deaths as of Sept. 28th, 2021. SARS-CoV-2, Spike (S) protein binds to host cells by recognizing human angiotensin-converting enzyme 2 (hACE2) receptor. The viral S protein contains S1 and S2 domains that constitute the binding and fusion machinery, respectively. Structural analysis of viral S protein reveals that the virus undergoes conformational flexibility and dynamicity to interact with the hACE2 receptor. The SARS-CoV-2 variants and mutations might be associated with affecting the conformational plasticity of S protein, potentially linked to its altered affinity, infectivity, and immunogenicity. This review focuses on the current circulating variants of SARS-CoV-2 and the structure-function analysis of key S protein mutations linked with increased affinity, higher infectivity, enhanced transmission rates, and immune escape against this infection.

Monitoring Ambient Parameters in the IoT Precision Agriculture Scenario: An Approach to Sensor Selection and Hydroponic Saffron Cultivation.

The world population is on the rise, which demands higher food production. The reduction in the amount of land under cultivation due to urbanization makes this more challenging. The solution to this problem lies in the artificial cultivation of crops. IoT and sensors play an important role in optimizing the artificial cultivation of crops. The selection of sensors is important in order to ensure a better quality and yield in an automated artificial environment. There are many challenges involved in selecting sensors due to the highly competitive market. This paper provides a novel approach to sensor selection for saffron cultivation in an IoT-based environment. The crop used in this study is saffron due to the reason that much less research has been conducted on its hydroponic cultivation using sensors and its huge economic impact. A detailed hardware-based framework, the growth cycle of the crop, along with all the sensors, and the block layout used for saffron cultivation in a hydroponic medium are provided. The important parameters for a hydroponic medium, such as the concentration of nutrients and flow rate required, are discussed in detail. This paper is the first of its kind to explain the sensor configurations, performance metrics, and sensor-based saffron cultivation model. The paper discusses different metrics related to the selection, use and role of sensors in different IoT-based saffron cultivation practices. A smart hydroponic setup for saffron cultivation is proposed. The results of the model are evaluated using the AquaCrop simulator. The simulator is used to evaluate the value of performance metrics such as the yield, harvest index, water productivity, and biomass. The values obtained provide better results as compared to natural cultivation.

Visualization of Customized Convolutional Neural Network for Natural Language Recognition.

For analytical approach-based word recognition techniques, the task of segmenting the word into individual characters is a big challenge, specifically for cursive handwriting. For this, a holistic approach can be a better option, wherein the entire word is passed to an appropriate recognizer. Gurumukhi script is a complex script for which a holistic approach can be proposed for offline handwritten word recognition. In this paper, the authors propose a Convolutional Neural Network-based architecture for recognition of the Gurumukhi month names. The architecture is designed with five convolutional layers and three pooling layers. The authors also prepared a dataset of 24,000 images, each with a size of 50 × 50. The dataset was collected from 500 distinct writers of different age groups and professions. The proposed method achieved training and validation accuracies of about 97.03% and 99.50%, respectively for the proposed dataset.

Structural insights into the transient closed conformation and pH dependent ATPase activity of S.Typhi GyraseB N- terminal domain.

DNA Gyrase is a type II topoisomerase that utilizes the energy of ATP hydrolysis for introducing negative supercoils in DNA. The protein comprises two subunits GyrA and GyrB that form a GyrA2GyrB2 heterotetramer. GyrB subunit contains the N-terminal domain (GBNTD) for ATPase activity and the C-terminal domain (GBCTD) for interaction with GyrA and DNA. Earlier structural studies have revealed three different conformational states for GBNTD during ATP hydrolysis defined as open, semi-open, and closed. Here we report, the three-dimensional structure of a new transient closed conformation of GBNTD from Salmonella Typhi (StGBNTD) at 1.94 Å resolution. Based on the structural analysis of this transient closed conformation, we propose the role of protein in the mechanism of ATP hydrolysis. We further explored the effect of pH on ATPase activity and structural stability of the GBNTD using CD and fluorescence spectroscopy at varying pH environment. Kinetic parameters obtained from the ATPase assay were correlated with its secondary and tertiary structure at their respective pH environment. The protein possessed maximum ATPase activity and structural stability at optimum pH 8. At acidic pH, a remarkable decrease in both enzymatic activity and structural stability was observed whereas at alkaline pH there was no significant change. The structural analysis of StGBNTD reveals the role of polar interactions in stabilizing the overall dimeric conformation of the protein.

The energetic brain - A review from students to students.

The past 20 years have resulted in unprecedented progress in understanding brain energy metabolism and its role in health and disease. In this review, which was initiated at the 14th International Society for Neurochemistry Advanced School, we address the basic concepts of brain energy metabolism and approach the question of why the brain has high energy expenditure. Our review illustrates that the vertebrate brain has a high need for energy because of the high number of neurons and the need to maintain a delicate interplay between energy metabolism, neurotransmission, and plasticity. Disturbances to the energetic balance, to mitochondria quality control or to glia-neuron metabolic interaction may lead to brain circuit malfunction or even severe disorders of the CNS. We cover neuronal energy consumption in neural transmission and basic ('housekeeping') cellular processes. Additionally, we describe the most common (glucose) and alternative sources of energy namely glutamate, lactate, ketone bodies, and medium chain fatty acids. We discuss the multifaceted role of non-neuronal cells in the transport of energy substrates from circulation (pericytes and astrocytes) and in the supply (astrocytes and microglia) and usage of different energy fuels. Finally, we address pathological consequences of disrupted energy homeostasis in the CNS.

A suppressor screen of the chimeric AtCNGC11/12 reveals residues important for intersubunit interactions of cyclic nucleotide-gated ion channels.

To investigate the structure-function relationship of plant cyclic nucleotide-gated ion channels (CNGCs), we identified a total of 29 mutant alleles of the chimeric AtCNGC11/12 gene that induces multiple defense responses in the Arabidopsis (Arabidopsis thaliana) mutant, constitutive expresser of PR genes22 (cpr22). Based on computational modeling, two new alleles, S100 (AtCNGC11/12:G459R) and S137 (AtCNGC11/12:R381H), were identified as counterparts of human CNGA3 (a human CNGC) mutants. Both mutants lost all cpr22-mediated phenotypes. Transient expression in Nicotiana benthamiana as well as functional complementation in yeast (Saccharomyces cerevisiae) showed that both AtCNGC11/12:G459R and AtCNGC11/12:R381H have alterations in their channel function. Site-directed mutagenesis coupled with fast-protein liquid chromatography using recombinantly expressed C-terminal peptides indicated that both mutations significantly influence subunit stoichiometry to form multimeric channels. This observation was confirmed by bimolecular fluorescence complementation in planta. Taken together, we have identified two residues that are likely important for subunit interaction for plant CNGCs and likely for animal CNGCs as well.

Effect of a selective cyclooxygenase type 2 inhibitor celecoxib on depression associated with obesity in mice: an approach using behavioral tests.

The biological mechanisms that link the development of depression to metabolic disorders such as obesity and diabetes remain ambiguous. In the present study the potential of a selective cyclooxygenase inhibitor celecoxib (15 mg/kg p.o.) was investigated in depression associated with obesity in mice. Behavioral tests used to assess depressive-like behavior were sucrose preference test, forced swim test (FST), tail suspension test (TST) and elevated plus maze (EPM). The basal locomotor score in obese mice was not altered. Furthermore, estimation of biochemical parameters was performed for plasma glucose, total cholesterol, triglycerides and total proteins. Escitalopram (10 mg/kg p.o.) served as reference standard drug. In the results, chronic treatment with celecoxib for 28 days significantly attenuated the behavioral alterations as indicated by increased the sucrose consumption, reduced the immobility time in FST and TST, increased the percent open arm time and entries in EPM in obese mice. In the biochemical parameters celecoxib significantly reversed the increased plasma glucose, total cholesterol, triglycerides and total proteins in obese mice. In conclusion, celecoxib exhibited potential antidepressant-like effect in depression associated with obesity, which to some extent is mediated by reversing the altered plasma glucose in obese mice.

Antidepressant-like effects of a novel 5-HT3 receptor antagonist 6z in acute and chronic murine models of depression.

AIM: To investigate the antidepressant-like effects of a novel 5-HT3 receptor antagonist N-(benzo[d]thiazol-2-yl)-3-methoxyquinoxalin-2-carboxamide (6z) in acute and chronic murine models of depression. METHODS: 5-HT3 receptor antagonism was examined in guinea pig ileum in vitro. A tail suspension test (TST) was used as acute depression model to evaluate the antidepressant-like behavior in mice treated with 6z (0.5-2 mg/kg, ip). In chronic depression model, mice were exposed to a 4-week chronic unpredictable stress (CUS) protocol, and treated with 6z (0.5-2 mg·kg(-1)·d(-1), po) or a positive drug fluoxetine (10 mg·kg(-1)·d(-1), po) in the last 2 weeks, followed by behavioral and biochemical assessments. RESULTS: The 5-HT3 receptor antagonism of 6z (pA2=7.4) in guinea pig ileum was more potent than that of a standard 5-HT3 receptor antagonist ondansetron (pA2=6.9). In acute depression model, 6z administration significantly decreased the immobility duration. In chronic depression model, 6z administration reversed CUS-induced depressive-like behavior, as evidenced by increased immobility duration in the forced swim test and sucrose preference in the sucrose preference test. Furthermore, chronic administration of 6z prevented CUS-induced brain oxidative stress, with significant reduction of pro-oxidant markers and elevation of antioxidant enzyme activity. Moreover, chronic administration of 6z attenuated CUS-induced hypothalamic-pituitary-adrenal axis hyperactivity, as shown by reduced plasma corticosterone levels. Similar results were observed in the fluoxetine-treated group. CONCLUSION: 6z is a novel 5-HT3 receptor antagonist with potential antidepressant-like activities, which may be related to modulating hypothalamic-pituitary-adrenal axis and attenuating brain oxidative damage.

Insulin reverses anxiety-like behavior evoked by streptozotocin-induced diabetes in mice.

Clinical and preclinical data suggest that diabetes is often associated with anxiety. Insulin, a peptide hormone has been reported to have key functions in the brain and in alleviating several psychological impairments, occur as a consequence of diabetes. However, its effects in diabetes-induced anxiety are scanty. The present study examined whether; insulin can reverse the anxiety-like behavior in streptozotocin (STZ)-induced diabetes in mice. After 8-weeks of diabetes induced by STZ (200 mg/kg, intraperitoneally (i.p.)), mice were given insulin (1-2 IU/kg/day, i.p.)/ diazepam (1 mg/kg/day, i.p.)/ vehicle for 14 days and evaluated for behavioral effects in three validated models of anxiety viz. elevated plus maze (EPM), light-dark (L/D) and hole board (HB) tests. STZ-induced diabetic mice elicited significant behavioral effects which include, decreased percentage open arm entries and time in EPM, reduced latency and time spent in light chamber in L/D, decreased number of head dips, squares crossed and rearings in HB tests respectively. Insulin treatment attenuated the behavioral effects evoked by STZ-induced diabetes in mice as indicated by increased open arms activity in EPM, decreased aversion in light chamber during L/D test and increased exploratory behavior in HB test. In conclusion, this study revealed that insulin can reverse anxiety-like behavior in STZ-induced diabetes in mice.

Ondansetron attenuates depression co-morbid with obesity in obese mice subjected to chronic unpredictable mild stress; an approach using behavioral battery tests.

The aim of the present work was to investigate the role of ondansetron on the high fat diet (HFD) induced obese mice for behavioral and biochemical alterations using chronic unpredictable mild stress (CUMS) model of depression. Animals were fed with high fat diet for 14 weeks and subjected to different stress procedures for 4 weeks. Treatment with ondansetron was started on day 15. After day 28 behavioral assays and biochemical estimations were performed. Behavioral paradigms viz. sucrose preference test, locomotor score, forced swim test (FST) and elevated plus maze (EPM), whereas biochemical parameters like plasma glucose, total cholesterol, triglycerides and total proteins were estimated. Results examines that in behavioral assays, ondansetron significantly (P < 0.05) increased sucrose consumption, reduced immobility time in FST, increased the percent entries and time in open arm in EPM. In biochemical assessments elevated plasma glucose, total cholesterol, triglycerides and total proteins were significantly (P < 0.05) reversed by ondansetron treatment in HFD obese animals subjected to CUMS. The study indicates that the obese mice subjected to CUMS exhibited severe depressive-like symptoms and ondansetron significantly reversed the behavioral and biochemical alterations. In the present study the plasma glucose level indicates that, it could be "altered glucose level" playing an important role in depression co-morbid with obesity. Ondansetron through allosteric modulation of serotonergic system elevates the serotonin level and thereby regulates the insulin secretion and hence, reversing the "altered glucose level", could be the possible antidepressive-like mechanism against depression co-morbid with obesity.

Rehabilitation of a Chronic Guillain-Barré Syndrome Patient With Vibratory Motor Stimulation of Dorsiflexors: A Case Report.

There are various reports describing physiotherapy rehabilitation in Guillain-Barré syndrome (GBS) but the use of current to rehabilitate GBS patients has remained an untouched topic. To elaborate on this work, we describe a case report focusing on the intervention plan for the rehabilitation of a chronic GBS case by the use of vibratory motor stimulation (VMS) current. The study aimed to describe the therapeutic application of VMS current in improving muscle power of dorsiflexors and overall outcome measures in a case of GBS presenting in a tertiary care hospital in North India. A 29-year-old male patient came to Teerthanker Mahaveer University Hospital and consulted in the Department of Physiotherapy after 1.4 years of being diagnosed with acute motor axonal neuropathy-type GBS. Rehabilitation of this case included strengthening exercises of the upper and lower limbs along with balance exercises. Specifically, in this case, we gave VMS current after assessing the muscle power of the dorsiflexors, which was found to be grade-0 over the bilateral dorsiflexors, combined with passive dorsiflexion. Different outcome measures were used for assessment, including manual muscle testing, functional independence measurement, and the Berg Balance Scale. Improvement in the patient's condition was observed in his outcome measures after two months of treatment. There was an overall improvement in the muscle power of our patient's dorsiflexors, where muscle power was upgraded from grade-0 to grade-I and grade-I+ in the bilateral lower limbs by the use of VMS current. This study marks a novel application of VMS to the dorsiflexors of a GBS patient, yielding positive outcomes in upgrading muscle power grades from grade-0 to grade-I and grade-I+. Further research is needed to confirm VMS efficacy as an early intervention in GBS patient rehabilitation.

An Insight into the Development of Potential Antidiabetic Agents along with their Therapeutic Targets.

Diabetes is a metabolic disorder that has been reported to increase the mortality rate worldwide. About 40 million people across the globe suffer from diabetes, with people living in developing countries being affected the most due to this deadly disease. Although the therapeutic management of hyperglycaemia can treat diabetes, metabolic disorders associated with this disease are a greater challenge in its treatment. Hence, potential strategies to treat hyperglycaemia and its side effects are needed. In this review, we have summarized several therapeutic targets, like dipeptidyl peptidase-4 (DPP-4), glucagon receptor antagonists, glycogen phosphorylase or fructose-1,6- biphosphatase inhibitors, SGLT inhibitors, 11beta-HSD-1 inhibitors, glucocorticoids receptor antagonists, glucose-6-phosphatase and glycogen phosphorylase inhibitors. These targets can help in designing and developing novel antidiabetic agents.

A comprehensive review on role of Aurora kinase inhibitors (AKIs) in cancer therapeutics.

Aurora kinases (AURKs) are a family of serine /threonine protein kinases that have a crucial role in cell cycle process mainly in the event of chromosomal segregation, centrosome maturation and cytokinesis. The family consists of three members including Aurora kinase A (AURK-A), Aurora kinase B (AURK-B) and Aurora kinase C (AURK-C). All AURKs contain a conserved kinase domain for their activity but differ in their cellular localization and functions. AURK-A and AURK-B are expressed mainly in somatic cells while the expression of AURK-C is limited to germ cells. AURK-A promotes G2 to M transition of cell cycle by controlling centrosome maturation and mitotic spindle assembly. AURK-B and AURK-C form the chromosome passenger complex (CPC) that ensures proper chromosomal alignments and segregation. Aberrant expression of AURK-A and AURK-B has been detected in several solid tumours and malignancies. Hence, they have become an attractive therapeutic target against cancer. The first part of this review focuses on AURKs structure, functions, subcellular localization, and their role in tumorigenesis. The review also highlights the functional and clinical impact of selective as well as pan kinase inhibitors. Currently, >60 compounds that target AURKs are in preclinical and clinical studies. The drawbacks of existing inhibitors like selectivity, drug resistance and toxicity have also been addressed. Since, majority of inhibitors are Aurora kinase inhibitor (AKI) type-1 that bind to the active (DFGin and Cin) conformation of the kinase, this information may be utilized to design highly selective kinase inhibitors that can be combined with other therapeutic agents for better clinical outcomes.

UMobileNetV2 model for semantic segmentation of gastrointestinal tract in MRI scans.

Gastrointestinal (GI) cancer is leading general tumour in the Gastrointestinal tract, which is fourth significant reason of tumour death in men and women. The common cure for GI cancer is radiation treatment, which contains directing a high-energy X-ray beam onto the tumor while avoiding healthy organs. To provide high dosages of X-rays, a system needs for accurately segmenting the GI tract organs. The study presents a UMobileNetV2 model for semantic segmentation of small and large intestine and stomach in MRI images of the GI tract. The model uses MobileNetV2 as an encoder in the contraction path and UNet layers as a decoder in the expansion path. The UW-Madison database, which contains MRI scans from 85 patients and 38,496 images, is used for evaluation. This automated technology has the capability to enhance the pace of cancer therapy by aiding the radio oncologist in the process of segmenting the organs of the GI tract. The UMobileNetV2 model is compared to three transfer learning models: Xception, ResNet 101, and NASNet mobile, which are used as encoders in UNet architecture. The model is analyzed using three distinct optimizers, i.e., Adam, RMS, and SGD. The UMobileNetV2 model with the combination of Adam optimizer outperforms all other transfer learning models. It obtains a dice coefficient of 0.8984, an IoU of 0.8697, and a validation loss of 0.1310, proving its ability to reliably segment the stomach and intestines in MRI images of gastrointestinal cancer patients.

Conditional spatial biased intuitionistic clustering technique for brain MRI image segmentation.

In clinical research, it is crucial to segment the magnetic resonance (MR) brain image for studying the internal tissues of the brain. To address this challenge in a sustainable manner, a novel approach has been proposed leveraging the power of unsupervised clustering while integrating conditional spatial properties of the image into intuitionistic clustering technique for segmenting MRI images of brain scans. In the proposed technique, an Intuitionistic-based clustering approach incorporates a nuanced understanding of uncertainty inherent in the image data. The measure of uncertainty is achieved through calculation of hesitation degree. The approach introduces a conditional spatial function alongside the intuitionistic membership matrix, enabling the consideration of spatial relationships within the image. Furthermore, by calculating weighted intuitionistic membership matrix, the algorithm gains the ability to adapt its smoothing behavior based on the local context. The main advantages are enhanced robustness with homogenous segments, lower sensitivity to noise, intensity inhomogeneity and accommodation of degree of hesitation or uncertainty that may exist in the real-world datasets. A comparative analysis of synthetic and real datasets of MR brain images proves the efficiency of the suggested approach over different algorithms. The paper investigates how the suggested research methodology performs in medical industry under different circumstances including both qualitative and quantitative parameters such as segmentation accuracy, similarity index, true positive ratio, false positive ratio. The experimental outcomes demonstrate that the suggested algorithm outperforms in retaining image details and achieving segmentation accuracy.

The acidic C-terminal tail of DNA Gyrase of Salmonella enterica serovar Typhi controls DNA relaxation in an acidic environment.

The intracellular bacteria, Salmonella Typhi adapts to acidic conditions in the host cell by resetting the chromosomal DNA topology majorly controlled by DNA Gyrase, a Type II topoisomerase. DNA Gyrase forms a heterodimer A2B2 complex, which manages the DNA supercoiling and relaxation in the cell. DNA relaxation forms a part of the regulatory mechanism to activate the transcription of genes required to survive under hostile conditions. Acid-induced stress attenuates the supercoiling activity of the DNA Gyrase, resulting in DNA relaxation. Salmonella DNA becomes relaxed as the bacteria adapt to the acidified intracellular environment. Despite comprehensive studies on DNA Gyrase, the mechanism to control supercoiling activity needs to be better understood. A loss in supercoiling activity in E. coli was observed upon deletion of the non-conserved acidic C-tail of Gyrase A subunit. Salmonella Gyrase also contains an acidic tail at the C-terminus of Gyrase A, where its deletion resulted in reduced supercoiling activity compared to wild-type Gyrase. Interestingly, we also found that wild-type Gyrase compromises supercoiling activity at acidic pH 2-3, thereby causing DNA relaxation. The absence of a C-tail displayed DNA supercoiling to some extent between pH 2-9. Hence, the C-tail of Gyrase A might be one of the controlling factors that cause DNA relaxation in Salmonella at acidic pH conditions. We propose that the presence of the C-tail of GyraseA causes acid-mediated inhibition of the negative supercoiling activity of Gyrase, resulting in relaxed DNA that attracts DNA-binding proteins for controlling the transcriptional response.