An Approach of Stipulation Change Management Using Cloud Computing

Every technology project's successful implementation depends on the requirements. Changes in stipulations at any point of the software development life cycle are considered a healthy operation. Nevertheless, this transition is a little simpler in a co-located setting than in a decentralized system in which participants are spread over more than one area. This presents numerous challenges, such as coordination, communication & control, effective and efficient management of changes and the management of central repositories. Cloud computing can therefore be used to mitigate these stakeholder problems. We used a case study to test the system of cloud computing

Comparative analysis of the DCNN and HFCNN Based Computerized detection of liver cancer

Liver cancer detection is critically important in the discipline of biomedical image testing and diagnosis. Researchers have explored numerous machine learning (ML) techniques and deep learning (DL) approaches aimed at the automated recognition of liver disease by analysing computed tomography (CT) images. This study compares two frameworks, Deep Convolutional Neural Network (DCNN) and Hierarchical Fusion Convolutional Neural Networks (HFCNN), to assess their effectiveness in liver cancer segmentation. The contribution includes enhancing the edges and textures of CT images through filtering to achieve precise liver segmentation. Additionally, an existing DL framework was employed for liver cancer detection and segmentation. The strengths of this paper include a clear emphasis on the criticality of liver cancer detection in biomedical imaging and diagnostics. It also highlights the challenges associated with CT image detection and segmentation and provides a comprehensive summary of recent literature. However, certain difficulties arise during the detection process in CT images due to overlapping structures, such as bile ducts, blood vessels, image noise, textural changes, size and location variations, and inherent heterogeneity. These factors may lead to segmentation errors and subsequently different analyses. This research analysis compares two advanced methodologies, DCNN and HFCNN, for liver cancer detection. The evaluation of DCNN and HFCNN in liver cancer detection is conducted using multiple performance metrics, including precision, F1-score, recall, and accuracy. This comprehensive assessment provides a detailed evaluation of these models’ effectiveness compared to other state-of-the-art methods in identifying liver cancer.Princess Nourah Bint Abdulrahman University, PNU, (PNURSP2025R234); Princess Nourah Bint Abdulrahman University, PNUThis research was supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2025R234), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

Rapid iPSC inclusionopathy models shed light on formation, consequence, and molecular subtype of α-synuclein inclusions

The heterogeneity of protein-rich inclusions and its significance in neurodegeneration is poorly understood. Standard patient-derived iPSC models develop inclusions neither reproducibly nor in a reasonable time frame. Here, we developed screenable iPSC "inclusionopathy" models utilizing piggyBac or targeted transgenes to rapidly induce CNS cells that express aggregation-prone proteins at brain-like levels. Inclusions and their effects on cell survival were trackable at single-inclusion resolution. Exemplar cortical neuron α-synuclein inclusionopathy models were engineered through transgenic expression of α-synuclein mutant forms or exogenous seeding with fibrils. We identified multiple inclusion classes, including neuroprotective p62-positive inclusions versus dynamic and neurotoxic lipid-rich inclusions, both identified in patient brains. Fusion events between these inclusion subtypes altered neuronal survival. Proteome-scale α-synuclein genetic- and physical-interaction screens pinpointed candidate RNA-processing and actin-cytoskeleton-modulator proteins like RhoA whose sequestration into inclusions could enhance toxicity. These tractable CNS models should prove useful in functional genomic analysis and drug development for proteinopathies

Global overview of the management of acute cholecystitis during the COVID-19 pandemic (CHOLECOVID study)

Background: This study provides a global overview of the management of patients with acute cholecystitis during the initial phase of the COVID-19 pandemic. Methods: CHOLECOVID is an international, multicentre, observational comparative study of patients admitted to hospital with acute cholecystitis during the COVID-19 pandemic. Data on management were collected for a 2-month study interval coincident with the WHO declaration of the SARS-CoV-2 pandemic and compared with an equivalent pre-pandemic time interval. Mediation analysis examined the influence of SARS-COV-2 infection on 30-day mortality. Results: This study collected data on 9783 patients with acute cholecystitis admitted to 247 hospitals across the world. The pandemic was associated with reduced availability of surgical workforce and operating facilities globally, a significant shift to worse severity of disease, and increased use of conservative management. There was a reduction (both absolute and proportionate) in the number of patients undergoing cholecystectomy from 3095 patients (56.2 per cent) pre-pandemic to 1998 patients (46.2 per cent) during the pandemic but there was no difference in 30-day all-cause mortality after cholecystectomy comparing the pre-pandemic interval with the pandemic (13 patients (0.4 per cent) pre-pandemic to 13 patients (0.6 per cent) pandemic; P = 0.355). In mediation analysis, an admission with acute cholecystitis during the pandemic was associated with a non-significant increased risk of death (OR 1.29, 95 per cent c.i. 0.93 to 1.79, P = 0.121). Conclusion: CHOLECOVID provides a unique overview of the treatment of patients with cholecystitis across the globe during the first months of the SARS-CoV-2 pandemic. The study highlights the need for system resilience in retention of elective surgical activity. Cholecystectomy was associated with a low risk of mortality and deferral of treatment results in an increase in avoidable morbidity that represents the non-COVID cost of this pandemic

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Hybrid Security and Energy Aware Routing for Wireless Ad hoc Networks

Wireless ad hoc networks are increased with respect to data transmission between different nodes via relay routing in real time network environment. Wireless ad hoc networks are the collection of different wireless nodes which communicate over common wireless medium. Relay configuration of particular node over relay routing is a complex task which improves the quality of service parameters based on basic standards in routing communication scenarios. Different security challenges appear in this scenario because of misbehaving nature of intermediate nodes in data transmission with respect to scalability and efficiency in wireless ad hoc network communication. So that in this paper we present and develop a Hybrid approach, which consists unital key distribution approach and dynamic source optimized routing scenario to improve scalability and efficiency for key sharing to all the nodes in wireless networks. Performance of proposed approach in terms of increasing quality of service (QOS) parameters in wireless ad hoc networks.</jats:p

ENDOSCOPIC AND HISTOPATHOLOGIC CHANGES IN CHILDREN WITH CHRONIC DYSPEPSIA IN A RURAL MEDICAL COLLEGE HOSPITAL IN MELMARUVATHUR- TAMILNADU

INTRODUCTION Chronic pain abdomen and dyspepsia is the most common presenting symptoms in the Paediatric Outpatient Department (OPD) after respiratory illnesses. It is increasing alarmingly both in the paediatric and adult population. We, therefore carried out a cross-sectional study among children with chronic dyspepsia aged between 5 to 15 years attending Paediatric OPD in a rural medical college hospital, Melmaruvathur, Tamilnadu, South India. OBJECTIVE To evaluate the gastroduodenal morbidity in children presenting to the paediatric department of a rural medical college hospital with chronic dyspeptic symptoms. METHODS Forty six children between the age group of 5 to 15 years with chronic dyspeptic symptoms of at least one month duration were evaluated for their symptom profile, epidemiological profile, nutritional status, endoscopic appearance and histopathological changes. Data analysis was done using SPSS version 18. RESULTS Of the 46 children studied, 43% were between the age group of 5-10 years and 70% were female children. Pain abdomen lasting for more than at least one month was the most common finding (93%) observed. Other common symptoms in the order of decreasing frequency were early satiety (87%), poor appetite (76%), nausea (57%) and not thriving (57%). History of loss of appetite was significantly associated with chronic dyspepsia with an odds ratio of 68.9394 and 95% confidence interval 26.62 to 178.54, p value of <0.0001. Most of the children belonged to lower income group predominantly of a rural background. 33 (72%) children had under nutrition as per IAP classification. 10 (30%) Grade I, 15 (45%) Grade II and eight (24%) had Grade III malnutrition. 26 children (57%) had abnormal endoscopic findings. Antral mucosal biopsy done showed chronic lymphocytic gastritis in 44 (96%) cases. 38 of these 44 (86%) were H. pylori positive. H. pylori positivity in chronic dyspepsia was highly statistically significant with a p value of 0.0001 CONCLUSION The incidence of dyspepsia is common among children between the age group of 5-10 years with a female preponderance. The predominant symptom noted among these rural children are abdominal pain and loss of appetite. Multiple gastric erosions is the common finding observed endoscopically and H. pylori associated gastritis is the overwhelming finding in our children with chronic dyspepsia