Serum β-hcg levels between 12 to 20 weeks of gestation in prediction of hypertensive disordrers of pregnancy

Background: This study was undertaken to study the association of serum β hCG levels between 12 to 20 weeks of gestation and development of hypertensive disorders of pregnancy and to assess the association between the levels of β hCG and severity of hypertensive disorders of pregnancy. Study design: Prospective cohort study (200 uncomplicated primigravida).Methods: All women between 12 to 20 weeks of pregnancy meeting the selection criteria, attended antenatal OPD in JIPMER were recruited for this study after informed consent. The venous blood samples were obtained from the subjects for β-hCG analysis. Serum β hCG level was measured by Enzyme Linked Immunoassay System (ELISA) and expressed as mIU/ml. Multiples of median were calculated from the median of the sample population and were considered as raised if it was >2 MOM. The cases were followed up until delivery and observed for development of hypertensive disorders of pregnancy.Results: Out of 200 cases, 185 cases were followed completely till term. Among 185 cases who were followed up, 10 women developed hypertensive disorders of pregnancy, accounting for 5.4% in the study group. Out of the total 185 women who were studied, 132 had β hCG levels ≤2 MOM and 53 had β hCG levels >2 MOM. Among 132 women (94.7%) with β hCG levels ≤2 MOM, 7 (5.3%) developed hypertensive disorders. Among 53 cases (94.3%) with β hCG levels >2 MOM, 3 women (5.7%) developed hypertensive disorders. The incidence of HDP was almost similar in both the groups, 5.3% among those whose β hCG levels were ≤2MOM and 5.7% among those who had β hCG levels >2 MOM (p value - 0.923).Conclusions: From the present study, it may be concluded that high serum β hCG levels (2 MOM) estimated between 12 to 20 weeks of pregnancy were not predictive of development of hypertensive disorders later in pregnancy.

An Ensemble Learning Approach for Fast Disaster Response using Social Media Analytics

Natural disaster happens, as a result of natural hazards that cause financial, environmental or human losses. Natural disasters strike unexpectedly, affecting the lives of tens of thousands of people. During the flood, social media sites were also heavily used to disseminate information about flooded areas, rescue agencies, food and relief centres. This work proposes an ensemble learning strategy for combining and analysing social media data in order to close the gap and progress in catastrophic situation. To enable scalability and broad accessibility of the dynamic streaming of multimodal data namely text, image, audio and video, this work is designed around social media data. A fusion technique was employed at the decision level, based on a database of 15 characteristics for more than 300 disasters around the world (Trained with MNIST dataset 60000 training images and 10000 testing images).  This work allows the collected multimodal social media data to share a common semantic space, making individual variable prediction easier. Each  merged numerical vector(tensors) of text and audio  is sent into the K-CNN algorithm, which is an  unsupervised learning algorithm (K-CNN), and the  image and video data is given to a deep learning  based Progressive Neural Artificial Search (PNAS).  The trained data acts as a predictor for future  incidents, allowing for the estimation of total  deaths, total individuals impacted, and total  damage, as well as specific suggestions for food,  shelter and housing inspections. To make such a prediction, the trained model is presented a satellite image from before the accident as well as the geographic and demographic conditions, which is expected to result in a prediction accuracy of more than 85%

Cryptography: Advances in Secure Communication and Data Protection

In the innovative work secure communication and data protection are being main field, which are emerged by cryptography as a fundamental pillar. Strong cryptographic methods are now essential given the rising reliance on digital technologies and the threats posed by bad actors. This abstract examines the evolution of secure communication protocols and data protection techniques as it relates to the advancements in cryptography. The development of post-quantum cryptography is the most notable development in cryptography discussed in this study. As quantum computers become more powerful, they pose a serious threat to traditional cryptographic algorithms, such as RSA and ECC. Designing algorithms that are immune to attacks from quantum computers is the goal of post-quantum cryptography. Lattice-based, code-based, and multivariate-based cryptography are only a few of the methods that have been investigated in this context

Infant and Adult Human Intestinal Enteroids Are Morphologically and Functionally Distinct

UNLABELLED: Human intestinal enteroids (HIEs) are gaining recognition as physiologically relevant models of the intestinal epithelium. While HIEs from adults are used extensively in biomedical research, few studies have used HIEs from infants. Considering the dramatic developmental changes that occur during infancy, it is important to establish models that represent infant intestinal characteristics and physiological responses. We established jejunal HIEs from infant surgical samples and performed comparisons to jejunal HIEs from adults using RNA sequencing (RNA-Seq) and morphologic analyses. We then validated differences in key pathways through functional studies and determined whether these cultures recapitulate known features of the infant intestinal epithelium. RNA-Seq analysis showed significant differences in the transcriptome of infant and adult HIEs, including differences in genes and pathways associated with cell differentiation and proliferation, tissue development, lipid metabolism, innate immunity, and biological adhesion. Validating these results, we observed a higher abundance of cells expressing specific enterocyte, goblet cell, and enteroendocrine cell markers in differentiated infant HIE monolayers, and greater numbers of proliferative cells in undifferentiated 3D cultures. Compared to adult HIEs, infant HIEs portray characteristics of an immature gastrointestinal epithelium including significantly shorter cell height, lower epithelial barrier integrity, and lower innate immune responses to infection with an oral poliovirus vaccine. HIEs established from infant intestinal tissues reflect characteristics of the infant gut and are distinct from adult cultures. Our data support the use of infant HIEs as an IMPORTANCE: Tissue or biopsy stem cell-derived human intestinal enteroids are increasingly recognized as physiologically relevant models of the human gastrointestinal epithelium. While enteroids from adults and fetal tissues have been extensively used for studying many infectious and non-infectious diseases, there are few reports on enteroids from infants. We show that infant enteroids exhibit both transcriptomic and morphological differences compared to adult cultures. They also differ in functional responses to barrier disruption and innate immune responses to infection, suggesting that infant and adult enteroids are distinct model systems. Considering the dramatic changes in body composition and physiology that begin during infancy, tools that appropriately reflect intestinal development and diseases are critical. Infant enteroids exhibit key features of the infant gastrointestinal epithelium. This study is significant in establishing infant enteroids as age-appropriate models for infant intestinal physiology, infant-specific diseases, and responses to pathogens

Rotavirus infection

Q1Q1Artículo original1-16Rotavirus infections are a leading cause of severe, dehydrating gastroenteritis in children 200,000 deaths annually, mostly in low-income countries. Rotavirus primarily infects enterocytes and induces diarrhoea through the destruction of absorptive enterocytes (leading to malabsorption), intestinal secretion stimulated by rotavirus non-structural protein 4 and activation of the enteric nervous system. In addition, rotavirus infections can lead to antigenaemia (which is associated with more severe manifestations of acute gastroenteritis) and viraemia, and rotavirus can replicate in systemic sites, although this is limited. Reinfections with rotavirus are common throughout life, although the disease severity is reduced with repeat infections. The immune correlates of protection against rotavirus reinfection and recovery from infection are poorly understood, although rotavirus-specific immunoglobulin A has a role in both aspects. The management of rotavirus infection focuses on the prevention and treatment of dehydration, although the use of antiviral and anti-emetic drugs can be indicated in some cases

Report of the Assay Guidance Workshop on 3-Dimensional Tissue Models for Antiviral Drug Development

The National Center for Advancing Translational Sciences (NCATS) Assay Guidance Manual (AGM) Workshop on 3D Tissue Models for Antiviral Drug Development, held virtually on 7-8 June 2022, provided comprehensive coverage of critical concepts intended to help scientists establish robust, reproducible, and scalable 3D tissue models to study viruses with pandemic potential. This workshop was organized by NCATS, the National Institute of Allergy and Infectious Diseases, and the Bill and Melinda Gates Foundation. During the workshop, scientific experts from academia, industry, and government provided an overview of 3D tissue models\u27 utility and limitations, use of existing 3D tissue models for antiviral drug development, practical advice, best practices, and case studies about the application of available 3D tissue models to infectious disease modeling. This report includes a summary of each workshop session as well as a discussion of perspectives and challenges related to the use of 3D tissues in antiviral drug discovery

Effectiveness of Nursing Care on Clients with Poisoning at Melmaruvathur Adhiparasakthi Institute of Medical Sciences and Research

INTRODUCTION: Poisoning refers to an injury that results from being exposed to an exogenous substance that causes cellular injury or death. Poisons can be inhaled, ingested, injected or absorbed. The exposure to poison may be acute or chronic and the clinical presentation will vary accordingly. There are many factors determining the severity of poisoning and its outcome. They are the type of poison, dose, formulation, route of exposure, age of the client, presence of other poisons, the state of nutrition of the client and the presence of other diseases or injuries. Cardiopulmonary cerebral resuscitation (CPCR) should be performed for poisoning clients if needed. Containers of the poisons and all drugs that might have been possibly taken by the poisoned person should be saved and given to the doctor or rescue personnel. Diagnostic procedure in Poisoning is to identify the poison, which is helpful in treatment. Labels on bottles and other information from the person, family members, or coworkers best enable the doctor to identify poisons. Laboratory testing is much less likely to identify the poison. Sometimes, urine and blood tests may help in identification. Blood tests can sometimes reveal the severity of poisoning, but only with only a small number of poisons. OBJECTIVES: 1. To assess the health status of the client with poisoning. 2. To evaluate the effectiveness of nursing care on clients with poisoning. 3. To associate the effectiveness of nursing care on clients with poisoning with specific demographic variables. METHODOLOGY: This chapter deals with methodology adapted for the study and includes the description of research design setting of study population, sample size, sampling technique, criteria for the selection of sample instruments and tools and data collection. RESEARCH DESIGN: One group pre-test post-test design of pre-experimental was used to evaluate the effectiveness of nursing care for clients with poisoning by assessing the clients condition and their needs and problems were assessed and nursing interventions were provided. SETTING OF THE STUDY: The study was conducted in Melmaruvathur Adhiparasakthi institute of Medical Science and research, Melmaruvathur, Kancheepuram District. POPULATION: The population of the study comprised of clients who had poisoning in the age group of 18-45 years admitted at Melmaruvathur Adhiparasakthi institute of Medical Science and Research, Melmaruvathur, Kancheepuram District. SAMPLE SIZE: The sample size includes 30 clients who fulfilled the inclusion criteria. SAMPLING TECHNIQUE: Sampling technique used by the investigator was nonprobability, convenient sampling method. The convenient sampling technique was used to select the clients with poisoning. Data was collected from Melmaruvathur Adhiparasakthi institute of Medical Science and Research, Melmaruvathur, Kancheepuram District. INCLUSION CRITERIA: 1. Both male and female clients with selected poisoning (pesticide, oleander, kerosene and drug poisoning). 2. The clients who are admitted at Melmaruvathur Adhiparasakthi institute of Medical Science and Research, Melmaruvathur, Kancheepuram District. 3. Client who understand Tamil and English. EXCLUSION CRITERIA: 1. Clients below the age group of 18 years and above 45 years. 2. Clients with arsenic, cyanide, lead, methyl mercury, food poisoning, bites and stings. 3. Clients who are not willing to participate in the study. SUMMARY: In India, suicide rate has been increasing steadily and has reached 17.38 per 100,000. The most common method of attempting suicide by the use of poisoning agents accounts for 38% and poisoning is the fourth most common cause of mortality in India. A study was conducted on nursing care of patients with poisoning. The highlighted fact of this study was timely nursing interventions can prevent the complications of the poisoning effect. Lydia Hall’s theory was used in this study. Individualized nursing care was provided for each patient. One group pretest- posttest design was adopted and the study was conducted in Melmaruvathur Adhiparasakthi Institute of Medical Science and Research, Melmaruvathur, Kancheepuram District. Convenient sampling technique was adapted and sample size was determined as 30. A tool was developed to assess the patient condition and to check the effectiveness of nursing care based on standardized nursing process prepared by the investigator. Comprehensive nursing care was evaluated by checking the patient’s progress and description of the care written every day

A Comprehensive Decision Algorithm for the Analysis of Renewable Energy Source Selection Problem using Pythagorean Neutrosophic Fuzzy Sets

Nowadays, to achieve sustainable development and avoid devastating impacts on the environment, India is making rapid and broad changes to green energy technology. In order to provide long-term energy security with lower emissions, renewable energy sources are essential. It is well known that renewable energy technologies, or RETs, have the capacity to significantly meet the demand for electricity while lowering pollution levels. The nation has set up an ecologically friendly energy route in recent years. In this paper, we apply multi-criteria decision making (MCDM) models to determine the best renewable energy technology for India. We use the MULTIMOORA model to identify the best technology under the pythagorean neutrosophic fuzzy set (PNFS) and the FUCOM to obtain the criteria weights. In this study, we investigate sources of renewable energy using the newly developed idea of the PNFS and recommend the best renewable energy source for India