Article
Multidisciplinary Sciences
Piia Lavikainen, Emma Aarnio, Miika Linna, Kari Jalkanen, Hilkka Tirkkonen, Paivi Rautiainen, Tiina Laatikainen, Janne Martikainen
Summary: Customized treatments are crucial for improving health outcomes and maximizing treatment benefits for patients with diabetes. Identifying data-driven trajectories based on similarities in glycated haemoglobin patterns can provide insights into the clinical and economic relevance for different patient groups, enabling personalized medicine.
Article
Medicine, General & Internal
Muhammad Abu Tailakh, Shlomo-yaron Ishay, Jenan Awesat, Liat Poupko, Gidon Sahar, Victor Novack
Summary: The study found that diabetes patients with HbA1c levels above 7% before coronary artery bypass grafting are at higher risk for long-term mortality, especially late mortality; while patients with HbA1c levels below 7% have a relatively lower mortality rate.
JOURNAL OF CLINICAL MEDICINE
(2021)
Article
Endocrinology & Metabolism
Katherine A. Sauder, Jeanette M. Stafford, Shelley Ehrlich, Jean M. Lawrence, Angela D. Liese, Santica Marcovina, Amy K. Mottl, Catherine Pihoker, Sharon Saydah, Amy S. Shah, Ralph B. D'Agostino, Dana Dabelea
Summary: Disparities in HbA(1c) testing frequency were observed primarily based on health care-related factors, which were associated with diabetes outcomes in type 1 diabetes. Higher frequency of HbA(1c) testing was linked to lower HbA(1c) levels and decreased odds of microvascular complications over time. However, these associations were attenuated after adjusting for HbA(1c) testing correlates.
Article
Surgery
Emily Y. Fan, Allison S. Crawford, Tammy Nguyen, Dejah Judelson, Allison Learned, Julie Chan, Andres Schanzer, Jessica P. Simons, Douglas W. Jones
Summary: The role of HbA1c monitoring before lower extremity bypass surgery in patients with diabetes remains unclear. This study found that HbA1c monitoring before surgery did not correlate with better outcomes, and the practice varied widely among medical centers. Centers with the highest rates of monitoring had inferior outcomes compared to those with the lowest rates, likely due to other unmeasured variables.
JOURNAL OF VASCULAR SURGERY
(2022)
Article
Surgery
Flavia Carvalho Silveira, Gabrielle Maranga, Fernanda Mitchell, Brittany A. Nowak, Christine J. Ren-Fielding, George A. Fielding
Summary: The study investigated the prognostic utility of early weight loss after LAGB for predicting long-term weight outcomes, finding a strong association between weight loss exceeding 20% in the first year and achieving similar weight loss at 8-12 years.
ANZ JOURNAL OF SURGERY
(2021)
Article
Medicine, General & Internal
Ygal Plakht, Harel Gilutz, Arthur Shiyovich
Summary: This study evaluated the prognostic significance of HbA(1C) levels and changes among diabetic patients after non-fatal AMI. The results showed that fluctuations in HbA(1C) values, especially rapid increases, were associated with a higher risk of mortality. Monitoring both absolute HbA(1C) values and their changes could help predict long-term outcomes in AMI-DM patients.
JOURNAL OF CLINICAL MEDICINE
(2021)
Article
Biochemistry & Molecular Biology
Zvi H. Perry, Uri Netz, Sharon Tzelnick, Ofri Berar, Shahar Atias, Leonid Lantsberg, Eliezer Avinoach, Solly Mizrahi
Summary: Obesity is a worldwide epidemic that is strongly associated with comorbid diseases such as diabetes mellitus (DM). Laparoscopic Adjustable Gastric Banding (LAGB) is an effective surgical treatment for morbid obesity and can improve control of DM and hypertension (HTN).
Article
Public, Environmental & Occupational Health
Ilana Graetz, Jie Huang, Emilie R. Muelly, Loretta Hsueh, Anjali Gopalan, Mary E. Reed
Summary: This study examined the association between video telehealth access and changes in HbA1c among people with diabetes. The results showed that video visit access was associated with a reduction in HbA1c, especially among patients with higher baseline HbA1c.
AMERICAN JOURNAL OF PREVENTIVE MEDICINE
(2022)
Article
Medicine, General & Internal
Qiuhong Zhang, Chee Shin Lee, Lixia Zhang, Qi Wu, Yunyan Chen, Danqing Chen, Lu Qi, Zhaoxia Liang
Summary: Different factors, such as advanced age and high pre-pregnancy BMI, contribute to elevated HbA1c levels in pregnant women with GDM. Monitoring and controlling blood glucose levels have shown effectiveness in reducing adverse pregnancy outcomes, especially in cases of excessive GWG.
FRONTIERS IN MEDICINE
(2022)
Article
Engineering, Electrical & Electronic
Namho Kim, Da Young Lee, Wonju Seo, Nan Hee Kim, Sung-Min Park
Summary: The study aimed to develop clustering-based personalized models to estimate hemoglobin A1c (HbA1c) levels from continuous glucose monitoring (CGM) values. The proposed models showed improved performance in estimating HbA1c levels and provided real-time integrated information for better glycemic control.
IEEE SENSORS JOURNAL
(2022)
Article
Obstetrics & Gynecology
Ayamo Oben, Victoria Jauk, Ashley Battarbee, Sherri Longo, Jeff Szychowski, Alan Tita, Lorie Harper
Summary: The study aimed to assess the association of hemoglobin A1c (HbA1c) with adverse perinatal outcomes in obese women with gestational diabetes mellitus. Results showed that a single HbA1c measurement was not significantly associated with adverse perinatal outcomes, but an increase or stability of HbA1c between 14 to 20 weeks and 24 to 28 weeks was linked to an increased risk of preterm delivery.
AMERICAN JOURNAL OF PERINATOLOGY
(2022)
Article
Cardiac & Cardiovascular Systems
Dan Huang, Yong-Quan Huang, Qun-Ying Zhang, Yan Cui, Tian-Yi Mu, Yin Huang
Summary: The study found that greater variability of HbA1c is associated with higher risk for cardiovascular complications and all-cause death in patients with type 2 diabetes. It highlights the significance of well-controlled glycemic levels in improving cardiovascular outcomes. Further randomized clinical trials are needed to confirm these findings.
FRONTIERS IN CARDIOVASCULAR MEDICINE
(2021)
Article
Medicine, General & Internal
Frederic Arnold, Julia Kappes, Felix A. Rottmann, Lukas Westermann, Thomas Welte
Summary: This study finds that HbA1c levels are a strong predictor for the decline in kidney function, regardless of diabetes status or stage of CKD.
JOURNAL OF INTERNAL MEDICINE
(2023)
Article
Endocrinology & Metabolism
Guanhua Chen, Rui Zhang, Chunlu Tan, Xubao Liu, Lei Yu, Yonghua Chen
Summary: Using HbA1c alone as a diagnostic criterion for diabetes may not be sensitive enough in patients with pancreatic diseases. The optimal values of 5.8% and 6.0% for HbA1c improved the accuracy of diagnosing prediabetes and diabetes and should be considered. Furthermore, combining HbA1c and FPG tests is advocated for diagnosing diabetes in patients with pancreatic diseases.
FRONTIERS IN ENDOCRINOLOGY
(2023)
Article
Medicine, General & Internal
Alexandra Halalau, Sujoy Roy, Arpitha Hegde, Sumesh Khanal, Emily Langnas, Maidah Raja, Ramin Homayouni
Summary: This study aimed to determine the risk factors associated with rapid progression from normal or prediabetic hemoglobin A1c levels to type 2 diabetes mellitus. The results showed that progression to diabetes within a four-year period is associated with baseline BMI. A steady rise in HbA1c during the same period is associated with age and family history of type 2 diabetes, while rapid rise in HbA1c is associated with age and personal history of major cardiovascular events.
ANNALS OF MEDICINE
(2023)
Article
Mechanics
Praveen Ailawalia, Deepali Gupta
Summary: This research article investigates deformation in a non-homogeneous orthotropic micropolar medium and analyzes the effect of anisotropy on physical quantities using normal mode analysis and numerical computations.
MECHANICS BASED DESIGN OF STRUCTURES AND MACHINES
(2023)
Article
Biochemistry & Molecular Biology
Mukesh Kumar, Manish Kumar Tripathi, Deepali Gupta, Sanjit Kumar, Nihar Ranjan Biswas, A. S. Ethayathulla, Punit Kaur
Summary: Leishmania donovani is the causative agent of leishmaniasis, and its impact on developing countries is significant. The synthesis of glycophosphatidylinositol (GPI) plays a crucial role in the parasite, and disrupting this process may be a potential therapeutic strategy. Through computational screening and energy calculations, two compounds were identified to interact with the enzyme involved in GPI synthesis, suggesting their potential as anti-leishmaniasis agents.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2023)
Article
Green & Sustainable Science & Technology
Kanwalpreet Kour, Deepali Gupta, Kamali Gupta, Gaurav Dhiman, Sapna Juneja, Wattana Viriyasitavat, Hamidreza Mohafez, Mohammad Aminul Islam
Summary: This paper discusses artificial methods for saffron cultivation, evaluates six hydroponic approaches, and explores the factors influencing saffron growth and reasons for decline. The research also proposes a smart hydroponic system using NFT and renewable energy sources.
Article
Mathematical & Computational Biology
Sarang Sharma, Sheifali Gupta, Deepali Gupta, Sapna Juneja, Punit Gupta, Gaurav Dhiman, Sandeep Kautish
Summary: Blood cell count is important for disease diagnosis. This paper proposes a deep learning model using DenseNet121 to classify different types of white blood cells. The model achieves high accuracy through preprocessing techniques and outperforms with batch size 8.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
(2022)
Article
Medicine, General & Internal
Sarang Sharma, Sheifali Gupta, Deepali Gupta, Ayman Altameem, Abdul Khader Jilani Saudagar, Ramesh Chandra Poonia, Soumya Ranjan Nayak
Summary: Alzheimer's disease is a degenerative brain condition that affects memory and reasoning abilities. The current diagnostic methods are time-consuming and complex, so a deep learning model that combines transfer learning and machine learning has been developed for early diagnosis. The proposed model achieves high accuracy and specificity, making it a promising approach for clinical treatment.
Article
Biology
Priyanka Sharma, Mukesh Kumar, Manish Kumar Tripathi, Deepali Gupta, Poorvi Vishwakarma, Uddipan Das, Punit Kaur
Summary: This study analyzed the genome sequences of SARS-CoV-2 variants and their phylogenetic relationships. The findings showed that the delta and omicron variants have higher transmissibility and severity. This study provides a foundation for developing novel therapeutics and vaccine candidates against the virus.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Green & Sustainable Science & Technology
Mudita Uppal, Deepali Gupta, Amena Mahmoud, M. A. Elmagzoub, Adel Sulaiman, Mana Saleh Al Reshan, Asadullah Shaikh, Sapna Juneja
Summary: Industry 5.0 benefits from advancements in machine learning and IoT, with sensors installed in various IoT devices in different industries. To ensure the integrity and dependability of sensor nodes, it is necessary to predict faults before they occur. Cloud computing becomes essential for sustainable urban living as more data is collected. A proposed model uses ML algorithms to monitor IoT device health, with Random Forest showing the highest accuracy in predicting faults in smart offices.
Article
Green & Sustainable Science & Technology
Sonam Aggarwal, Sheifali Gupta, Deepali Gupta, Yonis Gulzar, Sapna Juneja, Ali A. Alwan, Ali Nauman
Summary: Predicting subcellular protein localization has become popular due to its utility in understanding disease mechanisms and developing drugs. Automated microscopic imaging technology has led to increased interest in using bio-images for protein localization. The Human Protein Atlas project aims to map the human proteome, but fewer techniques exist for predicting protein localization, particularly multi-label classification. Deep learning offers potential for automatic labeling, and this research proposes an ensemble technique to improve existing convolutional neural networks and pretrained models for more reliable and robust classification.
Article
Mathematics, Interdisciplinary Applications
Mudita Uppal, Deepali Gupta, Nitin Goyal, Agbotiname Lucky Imoize, Arun Kumar, Stephen Ojo, Subhendu Kumar Pani, Yongsung Kim, Jaeun Choi
Summary: This study presents an IoT-based office automation system with a user-friendly smartphone interface and real-time data monitoring. The system uses an Arduino Mega 2560 Rev3 microcontroller to connect different devices and sensors, and the collected data is sent to the cloud for access on smartphones from anywhere. A sensor fault prediction model based on a machine learning algorithm is also proposed and evaluated using performance metrics such as precision, recall, F1-score, and accuracy. This reliable and continuous automation system enhances smart office employees' work efficiency and resource-saving.
Article
Chemistry, Analytical
Monica Dutta, Deepali Gupta, Sangeeta Sahu, Suresh Limkar, Pawan Singh, Ashutosh Mishra, Manoj Kumar, Rahim Mutlu
Summary: Smart sensing devices enable hydroponics, a soilless technology that increases green area in vertical farming. Hydroponics uses 13 +/- 10 times less water and produces 10 +/- 5 times better quality products compared to substrate cultivation. Continuous real-time monitoring of nutrient requirements and environmental conditions made possible by smart sensing devices enhances year-round agricultural production. Lettuce cultivation using the Nutrient Film Technique (NFT) setup of hydroponics outperforms cultivation in a substrate medium in terms of leaf growth, as confirmed by the AquaCrop simulator. However, hydroponics consumes 70 +/- 11 times more energy compared to substrate cultivation.
Article
Green & Sustainable Science & Technology
Monica Dutta, Deepali Gupta, Yasir Javed, Khalid Mohiuddin, Sapna Juneja, Zafar Iqbal Khan, Ali Nauman
Summary: Vertical farming methods are becoming increasingly important in the era of urbanization and industrialization 5.0. They enhance sustainability by conserving space and reducing carbon and greenhouse gas emissions. The Green Internet of Things (G-IoT) improves environmental sustainability by consuming less energy. Different farming methods have varying effects on plant shoot and root growth, so it is necessary to identify the most suitable method for each crop. A comparative analysis of barley growth in hydroponics and substrate cultivation methods using G-IoT showed that hydroponics resulted in twice the shoot growth compared to substrate cultivation. The results were validated and confirmed the hydroponic method's ability to produce high-quality year-round crops.
Article
Engineering, Chemical
Jaspreet Singh, Gurpreet Singh, Deepali Gupta, Ghulam Muhammad, Ali Nauman
Summary: This article introduces an improved OCI-OLSR routing protocol that aims to enhance the performance of the regular OLSR protocol in wireless ad hoc networks. By optimizing control interval management, an advanced MPR selection process, reducing neighbor hold time, and decreasing flooding, the suggested protocol shows promise in terms of performance metrics under diverse conditions.
Article
Medicine, General & Internal
Vatsala Anand, Sheifali Gupta, Deepali Gupta, Yonis Gulzar, Qin Xin, Sapna Juneja, Asadullah Shah, Asadullah Shaikh
Summary: Early diagnosis of brain tumors is crucial for successful treatment and patient outcomes. Deep learning, specifically through the use of a weighted ensemble model, can analyze MRI images rapidly and improve accuracy in tumor classification. The proposed model outperforms individual models in terms of accuracy, precision, and F1-score, making it a valuable tool for radiologists in tumor diagnosis.
Article
Agronomy
Kanwalpreet Kour, Deepali Gupta, Junaid Rashid, Kamali Gupta, Jungeun Kim, Keejun Han, Khalid Mohiuddin
Summary: This article explores the agronomic variables of saffron cultivation in the Punjab region of India and calculates the corresponding set points. The relationship between canopy cover, growth percentage, and agronomic variables is investigated. An IoT-based automated saffron cultivation environment is proposed, along with sensors for quality and adulteration checks.
Article
Medicine, General & Internal
Gurjinder Kaur, Meenu Garg, Sheifali Gupta, Sapna Juneja, Junaid Rashid, Deepali Gupta, Asadullah Shah, Asadullah Shaikh
Summary: This paper proposes a modified UNet model to accurately detect glomeruli in kidney tissue. The model has been enhanced in terms of feature extraction capacity and depth, and it exhibits superior performance in the experiments.