Article
Pharmacology & Pharmacy
Sahar Mazloomi, Iraj Khodadadi, Shohreh Alimohammadi, Gholamreza Shafiee
Summary: This study revealed significantly decreased activities of eNOS and TrxR enzymes in preeclampsia patients, along with markedly lower concentrations of zinc, calcium, and selenium compared to healthy controls.
CLINICAL AND EXPERIMENTAL HYPERTENSION
(2021)
Article
Biochemistry & Molecular Biology
Ying Chen, Qi Xin Ou, Yu Chen, Qiao Ling Zhu, Min Hua Tan, Miao Miao Zhang, Su Zhen Wu, Huan Ying Xu
Summary: This study found that higher blood levels of magnesium and copper during mid-term pregnancy were associated with a lower risk of preeclampsia.
JOURNAL OF TRACE ELEMENTS IN MEDICINE AND BIOLOGY
(2022)
Review
Biochemistry & Molecular Biology
Hamdan Z. Hamdan, Sumaia Z. Hamdan, Ishag Adam
Summary: This meta-analysis found a significant association between low selenium levels and preeclampsia, especially among women from the African continent and low- or middle-income countries.
BIOLOGICAL TRACE ELEMENT RESEARCH
(2022)
Article
Medicine, General & Internal
Pengsheng Li, Haiyan Wang, Lan Guo, Xiaoyan Gou, Gengdong Chen, Dongxin Lin, Dazhi Fan, Xiaoling Guo, Zhengping Liu
Summary: A two-sample Mendelian randomization study found a causal association between Bifidobacterium and preeclampsia-eclampsia. However, there was no significant causal effect of preeclampsia-eclampsia on gut microbiota.
Article
Clinical Neurology
Jason Raina, Amira El-Messidi, Ahmad Badeghiesh, Togas Tulandi, Tuong-Vi Nguyen, Eva Suarthana
Summary: This population-based retrospective study of over 9 million pregnant women in the United States found increasing rates of maternal mental disorders, with anxiety showing the greatest increase. Only anxiety was consistently associated with an increased risk of gestational hypertension, preeclampsia, and eclampsia. Targeted screening for mental disorders in pregnant women, particularly anxiety, may aid in timely prevention and surveillance of hypertensive disorders of pregnancy.
JOURNAL OF AFFECTIVE DISORDERS
(2021)
Review
Public, Environmental & Occupational Health
Zixing Zhong, Qingmei Yang, Tao Sun, Qianqian Wang
Summary: This systematic review found that maternal copper levels are correlated with the risk of preeclampsia (PE), but the association varies across different geographical and economic contexts.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Biology
Isabella Bracchi, Juliana Guimaraes, Catarina Rodrigues, Rui Azevedo, Claudia Matta Coelho, Catia Pinheiro, Juliana Morais, Ines Barreiros-Mota, Virginia Cruz Fernandes, Cristina Delerue-Matos, Edgar Pinto, Andre Moreira-Rosario, Luis Filipe Ribeiro de Azevedo, Claudia Camila Dias, Jorge Lima, Ines Sapinho, Carla Ramalho, Conceicao Calhau, Joao Costa Leite, Agostinho Almeida, Diogo Pestana, Elisa Keating
Summary: This study aimed to evaluate the role of essential trace elements in pregnancy health. The findings suggest that high urinary zinc levels increase the risk of pre-eclampsia, but decrease the risk of small head circumference at birth.
Article
Multidisciplinary Sciences
Getachew Ossabo Babore, Tsegaye Gebre Aregago, Tadesse Lelago Ermolo, Mangistu Handiso Nunemo, Teshome Tesfaye Habebo
Summary: The study investigated maternal and foetal outcomes of pregnancy-induced hypertension among women giving birth at health facilities in Hossana town administration. It found that women with a previous history of pregnancy-induced hypertension had an increased risk of developing complications, while those with a higher number of previous pregnancies and lower educational status had decreased odds of developing pregnancy-induced hypertension.
Article
Environmental Sciences
Meilin Yan, Nana Liu, Yunfei Fan, Liangkun Ma, Tianjia Guan
Summary: This study found that exposure to ambient particulate matter pollution adversely affects gestational hypertension, gestational diabetes mellitus, and preeclampsia among Chinese pregnant women. Considering the hazardous levels of air pollution in most regions of China, these findings highlight the importance of protecting pregnant women from the risks of air pollution.
ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY
(2022)
Article
Environmental Sciences
Hao-Long Zeng, Bo Zhang, Xu Wang, Qing Yang, Liming Cheng
Summary: The study found that urinary levels of various metal elements in COVID-19 severe patients were higher than non-severe cases, and were also higher in the deceased group compared to the recovered group. These urinary elements were positively inter-correlated and correlated with other inflammatory markers such as white blood cell count and serum cytokines.
ENVIRONMENTAL RESEARCH
(2021)
Review
Biochemistry & Molecular Biology
Aifang Wu, Jingna Li, Jing Yuan, Ningning Zhang, Ying Zhang, Min Li, Tongyu Zhu
Summary: This systematic review and meta-analysis found that pregnant women with preeclampsia have significantly lower blood manganese levels compared to normotensive pregnant women. Subgroup analysis showed that the study country, timing of blood sampling, mean blood manganese level of controls, and confounding factors adjusted did not significantly affect the results, while the method for measuring blood manganese levels might affect the results. Additionally, a high level of blood manganese was associated with a lower risk of preeclampsia.
BIOLOGICAL TRACE ELEMENT RESEARCH
(2023)
Article
Nutrition & Dietetics
Xinrui Yao, Na Zuo, Wenzheng Guan, Lingjie Fu, Shuyi Jiang, Jiao Jiao, Xiuxia Wang
Summary: This study investigated the relationship between two enterotypes and blood trace elements in infertile women. It found significant differences in copper, zinc, magnesium, and iron levels between Prevotella enterotype and Bacteroides enterotype in infertile participants. Prevotella enterotype was associated with low iron levels in the obesity population, while Bacteroides enterotype was associated with high iron levels in the lean/normal and overweight populations.
Article
Immunology
Kamil Demircan, Thilo Samson Chillon, Tommy Bracken, Ilaria Bulgarelli, Irene Campi, Gijs Du Laing, Samira Fafi-Kremer, Laura Fugazzola, Alejandro Abner Garcia, Raban Heller, David J. Hughes, Louis Ide, Georg Jochen Klingenberg, Pawel Komarnicki, Zbigniew Krasinski, Alain Lescure, Patrick Mallon, Arash Moghaddam, Luca Persani, Mirko Petrovic, Marek Ruchala, Morgane Solis, Linos Vandekerckhove, Lutz Schomburg
Summary: In COVID-19 patients in Europe, serum levels of selenium and zinc are associated with mortality risk, with lower levels observed in non-survivors.
FRONTIERS IN IMMUNOLOGY
(2022)
Article
Emergency Medicine
Marina Boushra, Sreeja M. Natesan, Alex Koyfman, Brit Long
Summary: Eclampsia is a serious postpartum condition with high morbidity and mortality rates. It is often difficult to diagnose, but emergency clinicians can improve recognition and management by understanding its clinical features.
AMERICAN JOURNAL OF EMERGENCY MEDICINE
(2022)
Article
Environmental Sciences
Shuangmei Tong, Linsheng Yang, Hongqiang Gong, Li Wang, Hairong Li, Jiangping Yu, Yonghua Li, Yangzong Deji, Cangjue Nima, Shengcheng Zhao, Zongji Gesang, Chang Kong, Xiaoya Wang, Zhuming Men
Summary: The study found that the concentrations of trace elements in drinking water and human urine in plateau region of China generally met the guideline values, with selenium contributing to the excretion of several elements in the body. Different trace elements showed associations with each other, and age and gender appeared to play a role in the excretion of trace elements.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Review
Chemistry, Multidisciplinary
Md. Nasim Khan, Thomas Wirth
Summary: Triptycenes are unique scaffolds with a pi-structure, propeller-like shape, and saddle-like cavities, making them key molecules in polymer chemistry, supramolecular chemistry, and material science. Chirality in triptycenes arises when unsymmetrical substituents are attached in at least two different aromatic rings. Understanding and developing the chirality of triptycenes is crucial for the advancement of functional molecules.
CHEMISTRY-A EUROPEAN JOURNAL
(2021)
Review
Chemistry, Medicinal
Md Nasim Khan, Digvijaysinh K. Parmar, Debasis Das
Summary: Azo compounds are widely used in various industries and play important roles in medicinal chemistry, such as antibacterial, antifungal, and antioxidant. However, their application in medicinal chemistry is limited by safety concerns related to metabolic degradation.
MINI-REVIEWS IN MEDICINAL CHEMISTRY
(2021)
Article
Engineering, Civil
Md Nasim Khan, Mohamed M. Ahmed
Summary: Driver performances can be impaired in adverse weather, so providing accurate weather information is crucial. This study developed an affordable detection system using a machine learning technique and video data to provide trajectory-level weather information in real time, achieving an overall accuracy of 93%. The proposed model is cost-efficient and can enhance current weather-based variable speed limit systems.
TRANSPORTATION RESEARCH RECORD
(2021)
Article
Transportation
Md Nasim Khan, Mohamed M. Ahmed
Summary: This study developed an affordable automatic road weather and surface condition detection system using roadside webcam data. The detection models achieved high accuracy in classifying weather and surface conditions. The study has the potential to provide accurate and consistent real-time weather information and optimize maintenance vehicles' routes and time.
INTERNATIONAL JOURNAL OF TRANSPORTATION SCIENCE AND TECHNOLOGY
(2022)
Article
Endocrinology & Metabolism
Jagannath Malo, Md Jahangir Alam, Salequl Islam, Md Abdul Mottalib, Md Mehedi Hasan Rocki, Ginok Barmon, Shamema Akter Tinni, Swapan K. Barman, Tapas Sarker, Md Nayeemul Islam Khan, Kanakaraju Kaliannan, Muhammad Abul Hasanat, Salimur Rahman, Md Faruque Pathan, A. K. Azad Khan, Madhu S. Malo
Summary: This study confirms that IAPD increases the risk of developing T2DM, and regular STAP tests can predict individual susceptibility to T2DM. Oral IAP supplementation may help prevent T2DM.
BMJ OPEN DIABETES RESEARCH & CARE
(2022)
Review
Ergonomics
Mohamed M. Ahmed, Md Nasim Khan, Anik Das, Seyedehsan Ehsan Dadvar
Summary: Investigating traffic safety and operation traditionally relies on spot sensors and crash data, but recent studies show the potential of Naturalistic Driving Studies (NDS) in providing real-time driving data for a more detailed analysis. Leveraging NDS data can help researchers understand the impact of human behavior on safety and operations, leading to advancements in the development of Connected and Autonomous Vehicles (CAV).
ACCIDENT ANALYSIS AND PREVENTION
(2022)
Article
Transportation
Anik Das, Md Nasim Khan, Mohamed M. Ahmed, Shaun S. Wulff
Summary: This study investigated lane-changing characteristics with regard to drivers' aggressiveness in rain and clear weather. The results showed that various factors, such as vehicle kinematics, traffic, driver behavior, and weather conditions, significantly influenced lane-changing durations. These findings have important implications for improving safety in Connected and Autonomous Vehicles (CAV).
JOURNAL OF TRANSPORTATION SAFETY & SECURITY
(2022)
Article
Engineering, Civil
Anik Das, Md Nasim Khan, Mohamed M. Ahmed
Summary: This study proposes reliable lane change detection models based on deep learning, which consider features from vehicle kinematics, machine vision, roadway geometries, and driver demographics. The models were trained and tested using the SHRP2 Naturalistic Driving Study and Roadway Information Database. Results show that the model based on vehicle kinematic features performs well, while the reduced model based on XGBoost achieves the best detection performance when considering all features.
TRANSPORTATION RESEARCH RECORD
(2022)
Article
Engineering, Civil
Md Nasim Khan, Mohamed M. Ahmed
Summary: The main goal of this study is to develop a system that can accurately detect fog in real time at a trajectory level. By leveraging video data and using different algorithms for classification, the study demonstrates the accurate detection of different levels of foggy weather conditions. The proposed detection models can be integrated into smartphones, allowing for real-time collection of road weather information and improvement of variable speed limit systems.
TRANSPORTATION RESEARCH RECORD
(2022)
Article
Ergonomics
Elhashemi Ali, Md Nasim Khan, Mohamed M. Ahmed
Summary: This study presents a new analysis protocol for detecting real-time snowy weather conditions on freeways using trajectory-level data extracted from the SHRP2 NDS dataset. Four non-parametric models were developed using different data assemblies to detect snowy weather with high accuracy. The results showed that data fusion between external sensors and image texture parameters can achieve accurate estimation of snowy weather without accessing CANbus data.
JOURNAL OF SAFETY RESEARCH
(2022)
Article
Transportation
Md Nasim Khan, Mohamed M. Ahmed
Summary: The main objective of this study was to develop a robust prediction model based on deep learning for timely prediction of injury and fatal crashes in adverse weather on rural mountainous freeways. The study utilized the ResNet18 deep learning technique and converted numeric crash data into images using DeepInsight. In addition, two data balancing techniques, Random Under Sampling (RUS) and Synthetic Minority Oversampling Technique (SMOTE), were employed to address the imbalanced nature of the crash data. Experimental results showed that the proposed model achieved high prediction accuracy for fatal and injury crashes when coupled with the best data sampling ratio and data balancing techniques. The study also identified the most important variables contributing to crash severity.
JOURNAL OF TRANSPORTATION SAFETY & SECURITY
(2023)
Article
Transportation
Subasish Das, Anandi Dutta, Reuben Tamakloe, Md Nasim Khan
Summary: Work zones are important for road infrastructure maintenance, but they pose risks to traffic safety. This study examines factors influencing work zone crashes and their variations by type, day, and time. By analyzing fatal crash data and applying association rules mining, the study identifies rear-end crashes and collisions as primary contributors and highlights the need for work zone-specific safety countermeasures to address temporal instability.
JOURNAL OF TRANSPORTATION SAFETY & SECURITY
(2023)
Article
Ergonomics
Jinli Liu, Subasish Das, Md Nasim Khan
Summary: Understanding the relationship between social disparities and traffic crash frequency is crucial for transportation planning and policymaking. This study examines the impact of socioeconomic and infrastructure-related disparities on traffic crash rates at a macro-level. The findings suggest that the Multiscale Geographically Weighted Regression (MGWR) model is effective in uncovering spatial relationships between contributing factors and different types of crashes. Improving infrastructure in low-income areas can lead to significant benefits in reducing crashes.
ACCIDENT ANALYSIS AND PREVENTION
(2024)
Proceedings Paper
Automation & Control Systems
Md Nasim Khan, Anik Das, Mohamed M. Ahmed
Summary: The research focuses on developing a weather-responsive variable speed limit (VSL) algorithm to improve traffic safety and operation under adverse weather conditions. The algorithm utilizes historical data from Wyoming Department of Transportation and driver behavior data from the Second Strategic Highway Research Program's naturalistic driving study. The algorithm was tested and proved to be superior in terms of time-to-collision, total travel time, average delay, and average speed. It can be incorporated into the connected vehicle environment to regulate driving speed and ensure a safe flow of traffic.
INTERNATIONAL CONFERENCE ON TRANSPORTATION AND DEVELOPMENT 2022: TRANSPORTATION SAFETY
(2022)
Proceedings Paper
Automation & Control Systems
Md Nasim Khan, Anik Das, Mohamed M. Ahmed
Summary: The main objective of this paper is to develop a low-cost rain detection system using an in-vehicle video camera capable of providing real-time trajectory-level road surface weather information. The study utilized naturalistic driving study (NDS) video data from the Second Strategic Highway Research Program (SHRP2) and employed image-based classification techniques. The detection models were trained using local binary pattern (LBP) based images' features and classification learners such as artificial neural network (ANN), random forest (RF), and support vector machine (SVM). The proposed weather detection system achieved high overall detection accuracy and can significantly improve VSL algorithms in a connected vehicle environment.
INTERNATIONAL CONFERENCE ON TRANSPORTATION AND DEVELOPMENT 2022: APPLICATION OF EMERGING TECHNOLOGIES
(2022)
