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1. RISE-iEEG: Robust to Inter-Subject Electrodes Implantation Variability iEEG Classifier

Author

Memar, Maryam Ostadsharif, Ziaei, Navid, Nazari, Behzad, and Yousefi, Ali

Subjects
Quantitative Biology - Neurons and Cognition, Computer Science - Human-Computer Interaction, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Signal Processing
Abstract

Utilization of intracranial electroencephalography (iEEG) is rapidly increasing for clinical and brain-computer interface applications. iEEG facilitates the recording of neural activity with high spatial and temporal resolution, making it a desirable neuroimaging modality for studying neural dynamics. Despite its benefits, iEEG faces challenges such as inter-subject variability in electrode implantation, which makes the development of unified neural decoder models across different patients difficult. In this research, we introduce a novel decoder model that is robust to inter-subject electrode implantation variability. We call this model RISE-iEEG, which stands for Robust Inter-Subject Electrode Implantation Variability iEEG Classifier. RISE-iEEG employs a deep neural network structure preceded by a patient-specific projection network. The projection network maps the neural data of individual patients onto a common low-dimensional space, compensating for the implantation variability. In other words, we developed an iEEG decoder model that can be applied across multiple patients' data without requiring the coordinates of electrode for each patient. The performance of RISE-iEEG across multiple datasets, including the Audio-Visual dataset, Music Reconstruction dataset, and Upper-Limb Movement dataset, surpasses that of state-of-the-art iEEG decoder models such as HTNet and EEGNet. Our analysis shows that the performance of RISE-iEEG is 10\% higher than that of HTNet and EEGNet in terms of F1 score, with an average F1 score of 83\%, which is the highest result among the evaluation methods defined. Furthermore, the analysis of projection network weights in the Music Reconstruction dataset across patients suggests that the Superior Temporal lobe serves as the primary encoding neural node. This finding aligns with the auditory processing physiology.

Published
2024

2. Genome-wide detection of somatic mosaicism at short tandem repeats.

Author

Sehgal, Aarushi, Ziaei Jam, Helyaneh, Shen, Andrew, and Gymrek, Melissa

Subjects
Humans, Mosaicism, Microsatellite Repeats, Genome, Human, High-Throughput Nucleotide Sequencing, Alleles, Software
Abstract

MOTIVATION: Somatic mosaicism has been implicated in several developmental disorders, cancers, and other diseases. Short tandem repeats (STRs) consist of repeated sequences of 1-6 bp and comprise >1 million loci in the human genome. Somatic mosaicism at STRs is known to play a key role in the pathogenicity of loci implicated in repeat expansion disorders and is highly prevalent in cancers exhibiting microsatellite instability. While a variety of tools have been developed to genotype germline variation at STRs, a method for systematically identifying mosaic STRs is lacking. RESULTS: We introduce prancSTR, a novel method for detecting mosaic STRs from individual high-throughput sequencing datasets. prancSTR is designed to detect loci characterized by a single high-frequency mosaic allele, but can also detect loci with multiple mosaic alleles. Unlike many existing mosaicism detection methods for other variant types, prancSTR does not require a matched control sample as input. We show that prancSTR accurately identifies mosaic STRs in simulated data, demonstrate its feasibility by identifying candidate mosaic STRs in Illumina whole genome sequencing data derived from lymphoblastoid cell lines for individuals sequenced by the 1000 Genomes Project, and evaluate the use of prancSTR on Element and PacBio data. In addition to prancSTR, we present simTR, a novel simulation framework which simulates raw sequencing reads with realistic error profiles at STRs. AVAILABILITY AND IMPLEMENTATION: prancSTR and simTR are freely available at https://github.com/gymrek-lab/trtools. Detailed documentation is available at https://trtools.readthedocs.io/.

Published
2024

3. LongTR: genome-wide profiling of genetic variation at tandem repeats from long reads.

Author

Ziaei Jam, Helyaneh, Zook, Justin, Javadzadeh, Sara, Park, Jonghun, Sehgal, Aarushi, and Gymrek, Melissa

Subjects
Long reads, Microsatellites, Tandem repeats, Humans, Tandem Repeat Sequences, Genome, Human, Genetic Variation, Software, Sequence Analysis, DNA, High-Throughput Nucleotide Sequencing, Nanopore Sequencing
Abstract

Tandem repeats are frequent across the human genome, and variation in repeat length has been linked to a variety of traits. Recent improvements in long read sequencing technologies have the potential to greatly improve tandem repeat analysis, especially for long or complex repeats. Here, we introduce LongTR, which accurately genotypes tandem repeats from high-fidelity long reads available from both PacBio and Oxford Nanopore Technologies. LongTR is freely available at https://github.com/gymrek-lab/longtr and https://zenodo.org/doi/10.5281/zenodo.11403979 .

Published
2024

4. AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environments

Author

Schmidgall, Samuel, Ziaei, Rojin, Harris, Carl, Reis, Eduardo, Jopling, Jeffrey, and Moor, Michael

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Computation and Language
Abstract

Evaluating large language models (LLM) in clinical scenarios is crucial to assessing their potential clinical utility. Existing benchmarks rely heavily on static question-answering, which does not accurately depict the complex, sequential nature of clinical decision-making. Here, we introduce AgentClinic, a multimodal agent benchmark for evaluating LLMs in simulated clinical environments that include patient interactions, multimodal data collection under incomplete information, and the usage of various tools, resulting in an in-depth evaluation across nine medical specialties and seven languages. We find that solving MedQA problems in the sequential decision-making format of AgentClinic is considerably more challenging, resulting in diagnostic accuracies that can drop to below a tenth of the original accuracy. Overall, we observe that agents sourced from Claude-3.5 outperform other LLM backbones in most settings. Nevertheless, we see stark differences in the LLMs' ability to make use of tools, such as experiential learning, adaptive retrieval, and reflection cycles. Strikingly, Llama-3 shows up to 92% relative improvements with the notebook tool that allows for writing and editing notes that persist across cases. To further scrutinize our clinical simulations, we leverage real-world electronic health records, perform a clinical reader study, perturb agents with biases, and explore novel patient-centric metrics that this interactive environment firstly enables.

Published
2024

5. Latent Variable Double Gaussian Process Model for Decoding Complex Neural Data

Author

Ziaei, Navid, Stim, Joshua J., Goodman-Keiser, Melanie D., Sponheim, Scott, Widge, Alik S., Krikorian, Sasoun, and Yousefi, Ali

Subjects
Computer Science - Machine Learning, Quantitative Biology - Neurons and Cognition
Abstract

Non-parametric models, such as Gaussian Processes (GP), show promising results in the analysis of complex data. Their applications in neuroscience data have recently gained traction. In this research, we introduce a novel neural decoder model built upon GP models. The core idea is that two GPs generate neural data and their associated labels using a set of low-dimensional latent variables. Under this modeling assumption, the latent variables represent the underlying manifold or essential features present in the neural data. When GPs are trained, the latent variable can be inferred from neural data to decode the labels with a high accuracy. We demonstrate an application of this decoder model in a verbal memory experiment dataset and show that the decoder accuracy in predicting stimulus significantly surpasses the state-of-the-art decoder models. The preceding performance of this model highlights the importance of utilizing non-parametric models in the analysis of neuroscience data.

Published
2024

7. Addressing cognitive bias in medical language models

Author

Schmidgall, Samuel, Harris, Carl, Essien, Ime, Olshvang, Daniel, Rahman, Tawsifur, Kim, Ji Woong, Ziaei, Rojin, Eshraghian, Jason, Abadir, Peter, and Chellappa, Rama

Subjects
Computer Science - Computation and Language, Computer Science - Human-Computer Interaction
Abstract

There is increasing interest in the application large language models (LLMs) to the medical field, in part because of their impressive performance on medical exam questions. While promising, exam questions do not reflect the complexity of real patient-doctor interactions. In reality, physicians' decisions are shaped by many complex factors, such as patient compliance, personal experience, ethical beliefs, and cognitive bias. Taking a step toward understanding this, our hypothesis posits that when LLMs are confronted with clinical questions containing cognitive biases, they will yield significantly less accurate responses compared to the same questions presented without such biases. In this study, we developed BiasMedQA, a benchmark for evaluating cognitive biases in LLMs applied to medical tasks. Using BiasMedQA we evaluated six LLMs, namely GPT-4, Mixtral-8x70B, GPT-3.5, PaLM-2, Llama 2 70B-chat, and the medically specialized PMC Llama 13B. We tested these models on 1,273 questions from the US Medical Licensing Exam (USMLE) Steps 1, 2, and 3, modified to replicate common clinically-relevant cognitive biases. Our analysis revealed varying effects for biases on these LLMs, with GPT-4 standing out for its resilience to bias, in contrast to Llama 2 70B-chat and PMC Llama 13B, which were disproportionately affected by cognitive bias. Our findings highlight the critical need for bias mitigation in the development of medical LLMs, pointing towards safer and more reliable applications in healthcare.

Published
2024

8. A Bayesian Gaussian Process-Based Latent Discriminative Generative Decoder (LDGD) Model for High-Dimensional Data

Author

Ziaei, Navid, Nazari, Behzad, Eden, Uri T., Widge, Alik, and Yousefi, Ali

Subjects
Computer Science - Machine Learning, I.5.1, G.3
Abstract

Extracting meaningful information from high-dimensional data poses a formidable modeling challenge, particularly when the data is obscured by noise or represented through different modalities. This research proposes a novel non-parametric modeling approach, leveraging the Gaussian process (GP), to characterize high-dimensional data by mapping it to a latent low-dimensional manifold. This model, named the latent discriminative generative decoder (LDGD), employs both the data and associated labels in the manifold discovery process. We derive a Bayesian solution to infer the latent variables, allowing LDGD to effectively capture inherent stochasticity in the data. We demonstrate applications of LDGD on both synthetic and benchmark datasets. Not only does LDGD infer the manifold accurately, but its accuracy in predicting data points' labels surpasses state-of-the-art approaches. In the development of LDGD, we have incorporated inducing points to reduce the computational complexity of Gaussian processes for large datasets, enabling batch training for enhanced efficient processing and scalability. Additionally, we show that LDGD can robustly infer manifold and precisely predict labels for scenarios in that data size is limited, demonstrating its capability to efficiently characterize high-dimensional data with limited samples. These collective attributes highlight the importance of developing non-parametric modeling approaches to analyze high-dimensional data., Comment: 40 pages, 6 figures

Published
2024
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9. Gene-environment interactions: Epstein-Barr virus infection and risk of pediatric-onset multiple sclerosis.

Author

Solomon, Olivia, Casper, T, Waltz, Michael, Weinstock-Guttman, Bianca, Aaen, Greg, Wheeler, Yolanda, Graves, Jennifer, Benson, Leslie, Gorman, Mark, Rensel, Mary, Mar, Soe, Lotze, Tim, Chitnis, Tanuja, Waldman, Amy, Krupp, Lauren, James, Judith, Hart, Janace, Barcellos, Lisa, Waubant, Emmanuelle, Greenberg, Barry, and Ziaei, Amin

Subjects
CD68, DRB1*15, Epstein–Barr virus, Pediatric onset, gene–environment interaction, multiple sclerosis, Adult, Child, Humans, Epstein-Barr Virus Infections, Herpesvirus 4, Human, Multiple Sclerosis, Risk Factors, HLA-DRB1 Chains, Antibodies
Abstract

BACKGROUND AND OBJECTIVE: Prior Epstein-Barr virus (EBV) infection is associated with an increased risk of pediatric-onset multiple sclerosis (POMS) and adult-onset multiple sclerosis (MS). It has been challenging to elucidate the biological mechanisms underlying this association. We examined the interactions between candidate human leukocyte antigen (HLA) and non-HLA variants and childhood EBV infection as it may provide mechanistic insights into EBV-associated MS. METHODS: Cases and controls were enrolled in the Environmental and Genetic Risk Factors for Pediatric MS study of the US Network of Pediatric MS Centers. Participants were categorized as seropositive and seronegative for EBV-viral capsid antigen (VCA). The association between prior EBV infection and having POMS was estimated with logistic regression. Interactions between EBV serostatus, major HLA MS risk factors, and non-HLA POMS risk variants associated with response to EBV infection were also evaluated with logistic regression. Models were adjusted for sex, age, genetic ancestry, and the mothers education. Additive interactions were calculated using relative risk due to interaction (RERI) and attributable proportions (APs). RESULTS: A total of 473 POMS cases and 702 controls contributed to the analyses. Anti-VCA seropositivity was significantly higher in POMS cases compared to controls (94.6% vs 60.7%, p

Published
2024

15. Language models are susceptible to incorrect patient self-diagnosis in medical applications

Author

Ziaei, Rojin and Schmidgall, Samuel

Subjects
Computer Science - Computation and Language
Abstract

Large language models (LLMs) are becoming increasingly relevant as a potential tool for healthcare, aiding communication between clinicians, researchers, and patients. However, traditional evaluations of LLMs on medical exam questions do not reflect the complexity of real patient-doctor interactions. An example of this complexity is the introduction of patient self-diagnosis, where a patient attempts to diagnose their own medical conditions from various sources. While the patient sometimes arrives at an accurate conclusion, they more often are led toward misdiagnosis due to the patient's over-emphasis on bias validating information. In this work we present a variety of LLMs with multiple-choice questions from United States medical board exams which are modified to include self-diagnostic reports from patients. Our findings highlight that when a patient proposes incorrect bias-validating information, the diagnostic accuracy of LLMs drop dramatically, revealing a high susceptibility to errors in self-diagnosis., Comment: 4 pages, Deep Generative Models for Health NeurIPS 2023

Published
2023

16. Agreement of a Pyramidal Wavefront-Based Autorefraction with Dry, Cycloplegic, and Subjective Refraction in Myopic Refractive Surgery Candidates

Author

Siamak Zarei-Ghanavati, Marzieh Najjaran, Samira Hassanzadeh, Mehdi Khabazkhoob, Akilesh Gokul, and Mohammed Ziaei

Subjects
aberrometry, autorefraction, cycloplegic refraction, subjective refraction, wavefront refraction, Ophthalmology, RE1-994
Abstract

Purpose To evaluate the repeatability of a pyramidal wavefront-based refraction (WFR) measurement and its agreement with dry autorefraction (DR), cycloplegic autorefraction (CR), and subjective refraction (SR) in myopic refractive surgery candidates. Methods One hundred eighty-nine eyes from 189 participants were evaluated. PERAMIS aberrometry (PERAMIS; SCHWIND eye-tech-solutions, Kleinostheim, Germany), DR, and CR, as well as SR, were completed for all candidates. The repeatability of PERAMIS measurements was assessed, and the Bland–Altman plots were used to test the agreement between different methods. Results Repeatability of the PERAMIS aberrometer was very high in the measurement of all refractive elements (Sphere, cylinder, spherical equivalent [M], J0, and J45) (interclass correlation coefficient >0.980 for all). A significant myopic shift was found with WFR compared to CR (0.45 diopter [D]) and SR (0.28 D) (P < 0.05). For the M component, there was a significant difference between WFR and CR (P < 0.05). J0 component measured with WFR was significantly different from SR and CR (P < 0.05). For the J45 variable, all three refraction methods were comparable (all, P > 0.05). In M > 5.00 D, a difference of 0.79 D (limit of agreement: −3.50–1.90) was found between WFR and CR. Conclusions In lower degrees of myopia, WFR was in good agreement with the manifest autorefraction. WFR, CR, and SR techniques were comparable in measuring astigmatism, especially in oblique astigmatism.

Published
2024
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17. Trainees’ perspectives and recommendations for catalyzing the next generation of NeuroAI researchers

Author

Andrea I. Luppi, Jascha Achterberg, Samuel Schmidgall, Isil Poyraz Bilgin, Peer Herholz, Maximilian Sprang, Benjamin Fockter, Andrew Siyoon Ham, Sushrut Thorat, Rojin Ziaei, Filip Milisav, Alexandra M. Proca, Hanna M. Tolle, Laura E. Suárez, Paul Scotti, and Helena M. Gellersen

Subjects
Science
Abstract

At this critical juncture in the development of NeuroAI, we outline challenges and training needs of junior researchers working across AI and neuroscience. We also provide advice and resources to help trainees plan their NeuroAI careers.

Published
2024
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18. Evaluation and mitigation of cognitive biases in medical language models

Author

Samuel Schmidgall, Carl Harris, Ime Essien, Daniel Olshvang, Tawsifur Rahman, Ji Woong Kim, Rojin Ziaei, Jason Eshraghian, Peter Abadir, and Rama Chellappa

Subjects
Computer applications to medicine. Medical informatics, R858-859.7
Abstract

Abstract Increasing interest in applying large language models (LLMs) to medicine is due in part to their impressive performance on medical exam questions. However, these exams do not capture the complexity of real patient–doctor interactions because of factors like patient compliance, experience, and cognitive bias. We hypothesized that LLMs would produce less accurate responses when faced with clinically biased questions as compared to unbiased ones. To test this, we developed the BiasMedQA dataset, which consists of 1273 USMLE questions modified to replicate common clinically relevant cognitive biases. We assessed six LLMs on BiasMedQA and found that GPT-4 stood out for its resilience to bias, in contrast to Llama 2 70B-chat and PMC Llama 13B, which showed large drops in performance. Additionally, we introduced three bias mitigation strategies, which improved but did not fully restore accuracy. Our findings highlight the need to improve LLMs’ robustness to cognitive biases, in order to achieve more reliable applications of LLMs in healthcare.

Published
2024
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19. Investigating the Usability and Comfort of Safety Harness in Construction Projects: The Reasons for Non-Use among Iranian Workers

Author

Parvin Sepehr, Mousa Jabbari, Hassan Sadeghi Naeini, Ali Salehi Sahl Abadi, Mansour Ziaei, Vahid Ahmadi Moshiran, Maryam Ahmadian, and Younes Mehrifar

Subjects
safety harness, comfort and satisfaction, construction workers, usability, maxqda, falling from a height, Environmental pollution, TD172-193.5
Abstract

Introduction: The safety harness is a critical device for preventing falls from height, particularly in the construction industry. This study aimed to identify the factors contributing to the non-use of safety harnesses during work at height and to evaluate the comfort, satisfaction, and usability of these harnesses among construction workers in Tehran using a custom-designed tool. Material and Methods: A semi-structured interview was conducted with construction workers to identify the factors influencing the non-use of safety harnesses. The collected data were analyzed using MAXQDA 10 software. Based on the results, which revealed dissatisfaction with the current safety harnesses, the levels of comfort, satisfaction, and usability were assessed using the Safety Harness Usability and Comfort Assessment Tool (SHUCAT) questionnaire. Results: The reasons for not using safety harnesses were categorized into four main groups: management factors, worker attitudes, comfort, and harness design. These were further subdivided into 27 subgroups. The average satisfaction and comfort scores for safety harnesses were 26.8 ± 6.25, indicating that workers generally felt uncomfortable and dissatisfied with their harnesses. The average usability score was 38.70 ± 5.60, reflecting poor usability of the harnesses. Conclusion: Improving the safety harness design could enhance workers’ comfort and satisfaction, increasing their willingness to use the equipment. Incorporating feedback from users and experts into the design process can help address the identified shortcomings and result in better product development.

Published
2024

20. Clinical and laboratory characteristics of ocular syphilis, co-infection, and therapy response

Author

Sahin O and Ziaei A

Subjects
Ocular syphilis, Scleritis, Anterior uveitis, Intermediate uveitis, Retinochoroiditis, Panuveitis, Optic neuritis, Penicillin, Methotrexate, Human immunodeficiency virus, Toxoplasma gondii, Ophthalmology, RE1-994
Abstract

Ozlem Sahin,1 Alireza Ziaei1–3 1Department of Ophthalmology/Uveitis, Dunya Goz Hospital, Ankara, Turkey; 2Department of Ophthalmology, Boston University School of Medicine, Boston, MA, USA; 3Department of Ophthalmology, Dunya Eye Hospital Ltd, Ankara, Turkey Purpose: To describe the clinical presentation of patients diagnosed with presumed latent ocular syphilis and congenital ocular syphilis at tertiary referral center in Turkey, and to compare the clinical findings with patients described in other studies, specifically focusing on demographics and co-infections. Methods: This is a retrospective study reviewing the medical records of patients diagnosed with ocular inflammation between January 2012 and June 2014 at a tertiary referral center in Turkey. Ocular syphilis was diagnosed on the basis of non-treponemal and treponemal antibody tests, and cerebrospinal fluid analysis. All the patients diagnosed with ocular syphilis were tested for human immunodeficiency virus (HIV), Toxoplasma gondii, rubella, cytomegalovirus, and herpes. Results: A total of 1,115 patients were evaluated between January 2012 and June 2014, and 12 patients (1.07%) were diagnosed with ocular syphilis based on the inclusion criteria. None of the patients were seropositive for HIV. Two patients were seropositive for T. gondii-specific IgG. Clinical presentations include non-necrotizing anterior scleritis, non-necrotizing sclerokeratitis, anterior uveitis, intermediate uveitis, posterior uveitis, panuveitis, and optic neuritis. All of the patients showed clinical improvement in the level of ocular inflammation with intravenous penicillin 24 million U/day for 10 days. Three patients received additional oral methotrexate as an adjunctive therapy. Two cases received low-dose trimethoprim–sulfamethoxazole. Conclusion: Ocular syphilis is an uncommon cause of ocular inflammation in HIV-negative patients. Central retinochoroiditis is the most common ocular manifestation, and it is the most common cause of visual impairment. Ocular syphilis might present associated with co-infections such as T. gondii in developing countries. Oral methotrexate might be beneficial as an adjunctive therapy for ocular syphilis in resolving the residual intraocular inflammation and cystoid macular edema after specific therapy with intravenous penicillin. Keywords: ocular syphilis, scleritis, uveitis, methotrexate, human immunodeficiency virus, T. gondii

Published
2015

21. Bayesian Time-Series Classifier for Decoding Simple Visual Stimuli from Intracranial Neural Activity

Author

Ziaei, Navid, Saadatifard, Reza, Yousefi, Ali, Nazari, Behzad, Cash, Sydney S., and Paulk, Angelique C.

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Signal Processing, Quantitative Biology - Neurons and Cognition
Abstract

Understanding how external stimuli are encoded in distributed neural activity is of significant interest in clinical and basic neuroscience. To address this need, it is essential to develop analytical tools capable of handling limited data and the intrinsic stochasticity present in neural data. In this study, we propose a straightforward Bayesian time series classifier (BTsC) model that tackles these challenges whilst maintaining a high level of interpretability. We demonstrate the classification capabilities of this approach by utilizing neural data to decode colors in a visual task. The model exhibits consistent and reliable average performance of 75.55% on 4 patients' dataset, improving upon state-of-the-art machine learning techniques by about 3.0 percent. In addition to its high classification accuracy, the proposed BTsC model provides interpretable results, making the technique a valuable tool to study neural activity in various tasks and categories. The proposed solution can be applied to neural data recorded in various tasks, where there is a need for interpretable results and accurate classification accuracy.

Published
2023
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30. Brain-inspired learning in artificial neural networks: a review

Author

Schmidgall, Samuel, Achterberg, Jascha, Miconi, Thomas, Kirsch, Louis, Ziaei, Rojin, Hajiseyedrazi, S. Pardis, and Eshraghian, Jason

Subjects
Computer Science - Neural and Evolutionary Computing, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Quantitative Biology - Neurons and Cognition
Abstract

Artificial neural networks (ANNs) have emerged as an essential tool in machine learning, achieving remarkable success across diverse domains, including image and speech generation, game playing, and robotics. However, there exist fundamental differences between ANNs' operating mechanisms and those of the biological brain, particularly concerning learning processes. This paper presents a comprehensive review of current brain-inspired learning representations in artificial neural networks. We investigate the integration of more biologically plausible mechanisms, such as synaptic plasticity, to enhance these networks' capabilities. Moreover, we delve into the potential advantages and challenges accompanying this approach. Ultimately, we pinpoint promising avenues for future research in this rapidly advancing field, which could bring us closer to understanding the essence of intelligence.

Published
2023

31. CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting

Author

Graham, Simon, Vu, Quoc Dang, Jahanifar, Mostafa, Weigert, Martin, Schmidt, Uwe, Zhang, Wenhua, Zhang, Jun, Yang, Sen, Xiang, Jinxi, Wang, Xiyue, Rumberger, Josef Lorenz, Baumann, Elias, Hirsch, Peter, Liu, Lihao, Hong, Chenyang, Aviles-Rivero, Angelica I., Jain, Ayushi, Ahn, Heeyoung, Hong, Yiyu, Azzuni, Hussam, Xu, Min, Yaqub, Mohammad, Blache, Marie-Claire, Piégu, Benoît, Vernay, Bertrand, Scherr, Tim, Böhland, Moritz, Löffler, Katharina, Li, Jiachen, Ying, Weiqin, Wang, Chixin, Kainmueller, Dagmar, Schönlieb, Carola-Bibiane, Liu, Shuolin, Talsania, Dhairya, Meda, Yughender, Mishra, Prakash, Ridzuan, Muhammad, Neumann, Oliver, Schilling, Marcel P., Reischl, Markus, Mikut, Ralf, Huang, Banban, Chien, Hsiang-Chin, Wang, Ching-Ping, Lee, Chia-Yen, Lin, Hong-Kun, Liu, Zaiyi, Pan, Xipeng, Han, Chu, Cheng, Jijun, Dawood, Muhammad, Deshpande, Srijay, Bashir, Raja Muhammad Saad, Shephard, Adam, Costa, Pedro, Nunes, João D., Campilho, Aurélio, Cardoso, Jaime S., S, Hrishikesh P, Puthussery, Densen, G, Devika R, C V, Jiji, Zhang, Ye, Fang, Zijie, Lin, Zhifan, Zhang, Yongbing, Lin, Chunhui, Zhang, Liukun, Mao, Lijian, Wu, Min, Vo, Vi Thi-Tuong, Kim, Soo-Hyung, Lee, Taebum, Kondo, Satoshi, Kasai, Satoshi, Dumbhare, Pranay, Phuse, Vedant, Dubey, Yash, Jamthikar, Ankush, Vuong, Trinh Thi Le, Kwak, Jin Tae, Ziaei, Dorsa, Jung, Hyun, Miao, Tianyi, Snead, David, Raza, Shan E Ahmed, Minhas, Fayyaz, and Rajpoot, Nasir M.

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovation in this area, we setup a community-wide challenge using the largest available dataset of its kind to assess nuclear segmentation and cellular composition. Our challenge, named CoNIC, stimulated the development of reproducible algorithms for cellular recognition with real-time result inspection on public leaderboards. We conducted an extensive post-challenge analysis based on the top-performing models using 1,658 whole-slide images of colon tissue. With around 700 million detected nuclei per model, associated features were used for dysplasia grading and survival analysis, where we demonstrated that the challenge's improvement over the previous state-of-the-art led to significant boosts in downstream performance. Our findings also suggest that eosinophils and neutrophils play an important role in the tumour microevironment. We release challenge models and WSI-level results to foster the development of further methods for biomarker discovery.

Published
2023

32. Peripapillary Retinal Nerve Fiber Layer Thickness Changes in Preterm Children with or without Retinopathy of Prematurity History

Author

Siamak Zarei-Ghanavati, Hadi Ostadimoghaddam, Marzieh Najjaran, Nasser Shoeibi, and Mohammed Ziaei

Subjects
intravitreal bevacizumab, peripapillary retinal nerve fiber layer, retinopathy of prematurity, Ophthalmology, RE1-994
Abstract

Purpose: To investigate peripapillary retinal nerve fiber layer (pRNFL) thickness changes in preterm children with or without retinopathy of prematurity (ROP) history compared to full-term children. Methods: A retrospective comparative cohort study assessing pRNFL thickness was completed in children aged 4–8 years. Four groups of children were included (n = 30 each group): children with a history of ROP who were treated with intravitreal bevacizumab, children with ROP who received no treatment, and preterm children without ROP compared to age- and gender-matched full-term children. Results: A total of 120 eyes from 120 children were enrolled in this study. Both treated and regressed ROP children showed a significantly thinner pRNFL in the nasal quadrant compared to full-term children (P = 0.017 and P = 0.008, respectively). The pRNFL in the superior quadrant of treated ROP children was thinner than the preterm and control groups (P = 0.015 and P = 0.023, respectively), whereas the inferior quadrant of treated ROP children was thinner than the preterm group alone (P = 0.008). The pRNFL thickness in the temporal quadrant was comparable between groups (P = 0.129). The average spatial distribution profile of pRNFL thickness in treated ROP children was significantly thinner than in the preterm group (P = 0.041). Conclusion: pRNFL thickness is significantly altered in children with a prior history of treated ROP with thinning of the nasal and superior quadrants compared to full-term children.

Published
2024
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33. An in vitro study for reducing the cytotoxicity and dose dumping risk of remdesivir via entrapment in nanostructured lipid carriers

Author

Fatemeh Amiri, Sepideh Ziaei Chamgordani, and Hedayatollah Ghourchian

Subjects
Medicine, Science
Abstract

Abstract The aim of this study was to synthesize and evaluate nanostructured lipid carriers (NLCs) loaded with Remdesivir (RDV) to control its side effects in COVID-19 patients. Due to the low solubility and short half-life of RDV in the blood, an injectable formulation was prepared using sulphobutylether-beta-cyclodextrin. However, it can accumulate in the kidney and cause renal impairment. NLCs improve the parenteral delivery of hydrophobic drugs such as RDV by increasing drug solubility and bioavailability. For the synthesis of RDV-NLCs, the aqueous phase containing Tween 80 was injected into the lipid phase under rapid stirring and was sonicated. The experimental conditions were optimized using Box-Behnken design and Design Expert software. The optimum formulation contained a total lipid of 2.13%, a total surfactant of 1%, and a hot bath time of 71 min. The optimum formulation showed particle size, polydispersity index, zeta potential, and entrapment efficiency values of 151.0 ± 1.7 nm (from 149.1 to 152.1), 0.4 ± 0.1 (from 0.3 to 0.5), −43.8 ± 1.2 mV (from −42.4 to −44.7), and 81.34 ± 1.57% (from 79.52 to 82.33%), respectively. RDV-NLCs showed acceptable stability for 30 days at 25 ℃ and were compatible with commonly used intravenous infusion fluids for 48 h. FE-SEM images of RDV-NLC showed spherical particles with a mean diameter of 207 nm. The NLC-RDV formulation showed a sustained release of RDV with a low risk of dose-dumping, minimizing potential side effects. In addition, RDV in the form of RDV-NLC causes less cytotoxicity to healthy normal kidney cells, which is expected to reduce renal impairment in COVID-19 patients.

Published
2024
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34. Intra-canopy LED lighting outperformed top LED lighting in improving tomato yield and expression of the genes responsible for lycopene, phytoene and vitamin C synthesis

Author

Negar Ziaei, Majid Talebi, Badraldin Ebrahim Sayed Tabatabaei, Mohammad R. Sabzalian, and Masoud Soleimani

Subjects
Intra-canopy lighting, LED, Lycopene, Metabolic genes, Tomato, Top-lighting, Medicine, Science
Abstract

Abstract Greenhouses located at high latitudes and in cloudy areas often experience a low quality and quantity of light, especially during autumn and winter. This low daily light integral (DLI) reduces production rate, quality, and nutritional value of many crops. This study was conducted on Sakhiya RZ F1 tomato plants to evaluate the impact of LED lights on the growth and nutritional value of tomatoes in a greenhouse with low daily light due to cloudy weather. The treatments included LED growth lights in three modes: top lighting, intra-canopy lighting, and combined top and intra-canopy lighting. The results showed that although the combined top and intra-canopy lighting reached the maximum increase in tomato yield, exposure to intra-canopy LED lighting alone outperformed in tomato fruit yield increase (28.46%) than exposure to top LED lighting alone (12.12%) when compared to no supplemental lighting during the entire production year. Intra-canopy exposure demonstrated the highest increase in tomato lycopene (31.3%), while top and intra-canopy lighting exhibited the highest increase in vitamin C content (123.4%) compared to the control. The LED light treatment also had a very positive effect on the expression of genes responsible for metabolic cycles, including Psy1, LCY-β, and VTC2 genes, which had collinearity with the increase in tomato fruit production.

Published
2024
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35. Healthy eating index and risk of diminished ovarian reserve: a case–control study

Author

Hatav Ghasemi-Tehrani, Gholamreza Askari, Fatemeh Zahra Allameh, Mahdi Vajdi, Reza Amiri Khosroshahi, Sepide Talebi, Rahele Ziaei, Abed Ghavami, and Farzaneh Askari

Subjects
Diminished ovarian reserve, Infertility, Ovarian function, Healthy eating index, Medicine, Science
Abstract

Abstract Diminished ovarian reserve (DOR) is associated with reduced fertility and poor reproductive outcomes. The association between dietary patterns and DOR was not well studied. The purpose of this study was to evaluate the relationship between adhering to the healthy eating index (HEI-2015) and the risk of DOR. In this case–control study, 370 Iranian women (120 with DOR and 250 age- and BMI-matched controls) were examined. A reliable semi-quantitative food frequency questionnaire was used to collect diet-related data. We analyzed the HEI-2015 and their dietary intake data to determine major dietary patterns. The multivariable logistic regression was used in order to analyze the association between HEI-2015 and risk of DOR. We found no significant association between HEI-2015 score and risk of DOR in the unadjusted model (OR 0.78; 95%CI 0.59, 1.03). After controlling for physical activity and energy intake, we observed that women in the highest quartile of the HEI-2015 score had 31% decreased odds of DOR (OR 0.69; 95%CI 0.46, 0.93). This association remained significant even after adjusting for all potential confounders. Overall, increased adherence to HEI may lead to a significant reduction in the odds ratio of DOR. Clinical trials and prospective studies are needed to confirm this association.

Published
2024
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36. Dislocated 4-haptic intraocular lens rescue with Gore-tex suture scleral re-fixation

Author

Luke Michaels, George Moussa, Hadi Ziaei, and Andrew Davies

Subjects
Dislocated, Subluxed, Intraocular lens, Akreos adapt, Gore-tex, Ophthalmology, RE1-994
Abstract

Abstract Background Dislocated IOL exchange conventionally involves manipulation within the anterior chamber which risks secondary injury to anterior chamber structures. We describe and evaluate a 4-haptic IOL rescue technique that avoids entering the anterior chamber and thus minimizes post operative inflammation, astigmatism and recovery time relative to conventional IOL explantation and replacement techniques. Methods Retrospective, non-randomized, interventional study of all patients undergoing 4-haptic IOL rescue performed by two independent vitreoretinal surgeons at a single UK centre over two years. Surgical technique: A limited peritomy is performed with four 25-gauge scleral ports placed to enable use of two forceps, an infusion and a chandelier. A further four 27-gauge sclerotomies are symmetrically placed on the nasal and temporal sclera at 3 mm from the limbus with a 5 mm vertical separation on either side. A pars plana vitrectomy is performed followed by chandelier illuminated, bimanual cleaning of the dislocated IOL using 27-gauge serrated forceps. Gore-tex sutures are threaded through the IOL islets within the vitreous cavity and externalized through the sclerotomies for scleral re-fixation followed by conjunctival closure. Results Seven patients underwent IOL recycling with Gore-Tex suture scleral re-fixation. All procedures were successful in repositioning the IOLs, with all patients satisfied with post-operative outcome. Mean (standard deviation) time to IOL dislocation was 13 (3) years. Median visual acuity significantly improved post-operatively from 0.85 logMAR (Interquartile Range [IQR]: 0.2–2.1) to 0.07 (0.02–0.60) logMAR (p = 0.02). No significant post-operative complications were noted apart from persistent cystoid macular oedema in one patient non-compliant with post-operative treatment. Conclusions Transscleral refixation using Gore-Tex suture is an effective, safe and practical approach in the management of dislocated 4-piece IOLs.

Published
2024
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37. Maternal smoking during pregnancy and early childhood dental caries in children: a systematic review and meta-analysis

Author

Dorsa Samani, SeyedMehdi Ziaei, Farhan Musaie, Hooman Mokhtari, Rubina Valipour, Mahsa Etemadi, Narin Gharehdaghi, Seyede Fateme Rezaei, Soheil Raji, Tara Fazel, Alireza Mokhtari Sakhvidi, and Niloofar Deravi

Subjects
Maternal smoking, Pregnancy, Dental caries, Children, Systematic review, Meta-analysis, Dentistry, RK1-715
Abstract

Abstract Background Early childhood dental caries, or ECC, is a significant global oral health concern associated with various adverse outcomes. This systematic review and meta-analysis aimed to investigate the potential link between maternal smoking during pregnancy and the occurrence of dental caries in children. Method Through a comprehensive search of PubMed, Scopus, and Google Scholar databases for studies examining the correlation between maternal smoking during pregnancy and childhood caries, we identified 609 relevant articles up to October 2023. Studies were selected, and data extraction was based on the pre-established eligibility criteria and items. Meta-analysis was executed utilizing Comprehensive Meta-analysis (CMA) with a random effects model, ensuring a robust synthesis of the gathered evidence. Result 7 cohorts and five cross-sectional studies, totaling 12 studies, were included in our analysis. The combined results from the studies revealed a significant association between maternal smoking during pregnancy and an increased risk of dental caries in children (OR = 1.78, 95% CI = 1.55–2.05, I2 = 68.53). Sensitivity analyses confirmed the reliability of our results. However, there were indications of publication bias, as suggested by the funnel plot and Egger’s test (P = 0.011) concerning the connection between prenatal smoking and childhood caries. Conclusion This review underscores the association between maternal smoking during pregnancy and childhood dental caries. Nevertheless, confounding variables influence this link, necessitating more large-scale, longitudinal studies with adjusted factors. Additional randomized control trials are needed to validate these findings due to the observed heterogeneity. Future research should investigate the precise reasons behind this association. It is essential to raise awareness among pregnant women about the risks of smoking through educational programs.

Published
2024
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38. LongTR: genome-wide profiling of genetic variation at tandem repeats from long reads

Author

Helyaneh Ziaei Jam, Justin M. Zook, Sara Javadzadeh, Jonghun Park, Aarushi Sehgal, and Melissa Gymrek

Subjects
Tandem repeats, Long reads, Microsatellites, Biology (General), QH301-705.5, Genetics, QH426-470
Abstract

Abstract Tandem repeats are frequent across the human genome, and variation in repeat length has been linked to a variety of traits. Recent improvements in long read sequencing technologies have the potential to greatly improve tandem repeat analysis, especially for long or complex repeats. Here, we introduce LongTR, which accurately genotypes tandem repeats from high-fidelity long reads available from both PacBio and Oxford Nanopore Technologies. LongTR is freely available at https://github.com/gymrek-lab/longtr and https://zenodo.org/doi/10.5281/zenodo.11403979 .

Published
2024
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39. Effect of melatonin supplementation on cardiometabolic risk factors, oxidative stress and hormonal profile in PCOS patients: a systematic review and meta-analysis of randomized clinical trials

Author

Somayeh Ziaei, Motahareh Hasani, Mahsa Malekahmadi, Elnaz Daneshzad, Katayoun Kadkhodazadeh, and Javad Heshmati

Subjects
Melatonin, PCOS, Cardiometabolic risk factors, Hormones, Pregnancy, Gynecology and obstetrics, RG1-991
Abstract

Abstract Background To investigate whether melatonin supplementation can enhance cardiometabolic risk factors, reduce oxidative stress, and improve hormonal and pregnancy-related factors in patients with PCOS. Methods We conducted a systematic search of PubMed/Medline, Scopus, and the Cochrane Library for articles published in English from inception to March 2023. We included randomized controlled trials (RCTs) on the use of melatonin for patients with polycystic ovary syndrome (PCOS). We performed a meta-analysis using a random-effects model and calculated the standardized mean differences (SMDs) and 95% confidence intervals (CIs). Results Six studies met the inclusion criteria. The result of meta-analysis indicated that melatonin intake significantly increase TAC levels (SMD: 0.87, 95% CI: 0.46, 1.28, I2 = 00.00%) and has no effect on FBS, insulin, HOMA-IR, TC, TG, HDL, LDL, MDA, hs-CRP, mFG, SHBG, total testosterone, and pregnancy rate in patients with PCOS compare to controls. The included trials did not report any adverse events. Conclusion Melatonin is a potential antioxidant that may prevent damage from oxidative stress in patients with PCOS. However, the clear effect of melatonin supplementation on cardiometabolic risk factors, hormonal outcomes, and pregnancy-related outcomes needs to be evaluated further in large populations and long-term RCTs.

Published
2024
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40. Lymphocytic Choriomeningitis Virus (LCMV): Current Status and Future Directions for Clinical and Molecular Diagnostic Techniques

Author

22442/jlumhs.2024., Narges Eslami, Somaye Jahanabadi, Elham Ziaei, Mohammad Shenagari, Shokrollah Salmanzadeh, Samaneh Abbasi, and Milad Zandi

Subjects
diagnosis, chronic infection, lcmv, cns, Medicine
Abstract

Lymphocytic choriomeningitis virus is an RNA virus that is often overlooked despite the potential to cause severe illness. It is a significant cause of viral meningitis, particularly in specific clinical situations. LCMV is transmitted to humans when they come into contact with the secretions of infected mice, and its strong neurotropism primarily results in neurological symptoms. The most vulnerable populations are fetuses and immunosuppressed individuals. LCMV infection acquired through various means can manifest with a wide range of clinical symptoms, varying from being asymptomatic to severe manifestations. Additionally, in cases where individuals are affected by this viral infection, it can result in fatal central nervous system disorders. Specifically, in pregnant women, intrauterine LCMV infection has been observed to lead to fetal or neonatal mortality. Furthermore, it can cause chorioretinitis and hydrocephalus in infants, which not only causes significant harm but also results in long-term impairments. Timely identification and immediate intervention are crucial in improving the prognosis, especially among high-risk groups and regions where the infection is prevalent. Failure to promptly diagnose the condition can lead to significant mortality rates and leave survivors with long-term neurological complications. Consequently, it is imperative to utilize the most appropriate laboratory diagnostic approach, considering the patient's clinical symptoms, exposure history to the virus, and the prevalence of the pathogen in the area, to facilitate accurate clinical detection. This comprehensive review encompasses various diagnostic methodologies employed in managing LCMV, encompassing clinical manifestations, diagnosis, treatment, and potential complications associated with viral infections affecting the central nervous system.

Published
2024
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41. Updated Customized Clinical Practice Guidelines for Management of Adult Cataract in Iran

Author

Zahra Karjou, Nazanin Behnaz, Mohammad Ali Javadi, Armin Shirvani, Hamideh Sabbaghi, Saeed Rahmani, Hossein Ziaei, Mohammad Reza Fallah Tafti, Sepehr Feizi, Seyed Javad Hashemian, Mohammad Reza Jafarinasab, Farid Karimian, Hossein Mohammad-Rabei, Mahmoodreza Panahi-Bazaz, Mohammad Reza Sedaghat, Shahin Yazdani, and Zhale Rajavi

Subjects
Ophthalmology, RE1-994
Published
2024
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42. Morphological and Molecular Identification of Acanthamoeba and Lophomonas Isolated from the Sputum of Suspected Tuberculosis Patients in Babolsar, Mazandaran Province in 2022-2023

Author

Hajar Ziaei Hezarjaribi, Rabeeh Tabaripour, Mahdi Fakhar, and Aliasghar Raoofi

Subjects
acanthamoeba, lophomonas, sputum, morphology, pcr, tuberculosis, Medicine, Medicine (General), R5-920
Abstract

Background and purpose: Lophomoniasis is a relatively common emerging parasitic disease caused by a pathogenic protozoan called Lophomonas, which mostly affects the lower respiratory tract (lungs and bronchi) of humans. The parasite lives symbiotically in the digestive system of insects such as cockroaches and mites. Acanthamoeba is a free-living amoeba that has two forms of trophozoite and cyst in its life cycle. The respiratory system and airways serve as passage and deployment sites for a wide range of non-pathogenic and pathogenic microorganisms, making it a suitable place for the entry and spread of different species of Acanthamoeba amoeba and the Lophomonas pathogen in the respiratory system, which can cause clinical manifestations similar to tuberculosis. Therefore, the present study aimed to investigate the frequency of these two parasites in sputum clinical samples from suspected tuberculosis patients referred to the tuberculosis laboratory in Babolsar City to rule out the two mentioned infections. Materials and methods: This descriptive-cross-sectional study was conducted on 201 sputum samples of people suspected of tuberculosis who were referred to the tuberculosis laboratory of Babolsar Health Center in Mazandaran province in 202-2023, and all the demographic and epidemiological information of the patients was recorded. In the morphological method, Giemsa staining was used for Lophomonas and Ziehl-Neelsen staining for Acanthamoeba. To identify the presence of Acanthamoeba, sputum samples were cultured in a 1.5% non-nutrient agar culture medium for 72 to 96 hours. Approximately 50 microliters of patients' sputum were added to the NNA medium, along with 20 microliters of trypticase-yeast extract and maltose (TYM) culture medium, and 20 microliters of an autoclaved Escherichia coli bacteria mixture to enrich the culture medium. The cultured plates were then placed in an incubator at 26ºC and checked daily under a light microscope for trophozoite growth. To accurately confirm the presence of parasites, DNA extraction was performed on the patient's sputum samples using the phenol-chloroform-isoamyl alcohol method. Subsequently, conventional polymerase chain reaction (PCR) was conducted using specific primers on the extracted DNA samples. Results: In the study of 201 people suspected of tuberculosis, it was found that 80 individuals (39.8%) lived in urban areas and 121 individuals (60.2%) lived in rural areas. The age range of participants varied from 7 to 88 years old. There were 113 females (56.2%) and 88 males (43.8%) in the study, with 12 individuals from Afghanistan living in urban areas. Out of the 201 sputum samples examined, a total of 23 samples (11.4%) tested positive for the Lophomonas parasite using the PCR method. Among these positive cases, 7 individuals (30.4%) resided in urban areas (Babolsar), while 16 individuals (69.5%) lived in rural areas. However, none of the samples tested positive for Acanthamoeba in this study using staining and PCR methods. Conclusion: The present study showed that due to the similarity of the clinical manifestations of tuberculosis and lophomoniasis, there is a possibility of mistaking these two diseases clinically. Therefore, it is recommended to check fresh sputum samples of people suspected of tuberculosis, especially in endemic areas, in terms of pulmonary lophomoniasis.

Published
2024

43. Studying the Pathogenic Effect of New Nucleotide Changes in the Promoter Region of the TERT Gene in Patients with Glioblastoma Brain Tumor

Author

Farzaneh Owlia, Mohammad Mehdi Heidari, Mehri Khatami, Ehsan Ziaei, and Mohammad Ali Broomand

Subjects
brain tumor, telomerase, glioblastoma multiform, tert gene, touchdown pcr, bioinformatics., Medicine (General), R5-920
Abstract

Introduction: Brain tumors are considered to be one of the most dangerous types of cancer, despite decades of research and treatment efforts. The activation of the telomerase enzyme is a critical factor in the immortality of these cells. Mutations in the promoter region of the TERT gene, particularly in the promoter hot spots, can influence the binding of activating transcription factors and inhibit the binding of negative regulatory factors of the TERT gene, ultimately regulating the gene's expression. This study aimed to identify and investigate the mutations of the TERT gene promoter region in glioblastoma, a malignant brain tumor, using bioinformatics. Methods: A study was conducted using the case-control method where 35 patients with glioblastoma multiform brain tumor were examined along with 40 people who were examined as control samples. In this research, the Touchdown PCR technique and direct DNA sequencing were used to detect mutations in the promoter region of the TERT gene in patients with glioblastoma. Furthermore, bioinformatic analyses were conducted to investigate the pathogenic effect of nucleotide changes in this gene region. Results: In the core region of the TERT gene promoter, three-point mutations were identified (c.*146C>T، c.*144C>G and c.*143G>C). Two of these mutations were novel and have been observed for the first time in glioblastoma multiform. The remaining mutation was located in the promoter core's hot spot of the gene. This mutation was known as c.*146C>T. Conclusion: In this research, the harmful impact of TERT promoter region mutations as a biomarker for glioblastoma was examined. These findings suggest that mutations in regulatory regions, as well as coding sequences, could be significant contributory factors in the process of carcinogenesis.

Published
2024

44. Dietary acid load and risk of diminished ovarian reserve: a case-control study

Author

Rahele Ziaei, Abed Ghavami, Hatav Ghasemi-Tehrani, Minoo Movahedi, Maryam Hashemi, Maryam Hajhashemi, Mahshid Elyasi, Mahdi Vajdi, and Maryam Kalatehjari

Subjects
Dietary acid load, Diminished ovarian reserve, Antimullerian hormone, Potential renal acid load, Antral follicle count, Gynecology and obstetrics, RG1-991, Reproduction, QH471-489
Abstract

Abstract Background The epidemiologic evidence on the association between acid load potential of diet and the risk of diminished ovarian reserve (DOR) is scarce. We aim to explore the possible relationship between dietary acid load (DAL), markers of ovarian reserve and DOR risk in a case-control study. Methods 370 women (120 women with DOR and 250 women with normal ovarian reserve as controls), matched by age and BMI, were recruited. Dietary intake was obtained using a validated 80-item semi-quantitative food frequency questionnaire (FFQ). The DAL scores including the potential renal acid load (PRAL) and net endogenous acid production (NEAP) were calculated based on nutrients intake. NEAP and PRAL scores were categorized by quartiles based on the distribution of controls. Antral follicle count (AFC), serum antimullerian hormone (AMH) and anthropometric indices were measured. Logistic regression models were used to estimate multivariable odds ratio (OR) of DOR across quartiles of NEAP and PRAL scores. Results Following increase in PRAL and NEAP scores, serum AMH significantly decreased in women with DOR. Also, AFC count had a significant decrease following increase in PRAL score (P = 0.045). After adjustment for multiple confounding variables, participants in the top quartile of PRAL had increased OR for DOR (OR: 1.26; 95%CI: 1.08–1.42, P = 0.254). Conclusion Diets with high acid-forming potential may negatively affect ovarian reserve in women with DOR. Also, high DAL may increase the risk of DOR. The association between DAL and markers of ovarian reserve should be explored in prospective studies and clinical trials.

Published
2024
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45. Gene-environment interactions increase the risk of paediatric-onset multiple sclerosis associated with household chemical exposures.

Author

Nasr, Zahra, Schoeps, Vinicius Andreoli, Ziaei, Amin, Virupakshaiah, Akash, Adams, Cameron, Casper, T Charles, Waltz, Michael, Rose, John, Rodriguez, Moses, Tillema, Jan-Mendelt, Chitnis, Tanuja, Graves, Jennifer S, Benson, Leslie, Rensel, Mary, Krupp, Lauren, Waldman, Amy T, Weinstock-Guttman, Bianca, Lotze, Tim, Greenberg, Benjamin, Aaen, Gregory, Mar, Soe, Schreiner, Teri, Hart, Janace, Simpson-Yap, Steve, Mesaros, Clementina, Barcellos, Lisa F, and Waubant, Emmanuelle

Subjects
Humans, Multiple Sclerosis, Genetic Predisposition to Disease, Proto-Oncogene Proteins c-bcl-2, Interleukin-6, HLA Antigens, Risk Factors, Case-Control Studies, Genotype, Child, HLA-DRB1 Chains, Gene-Environment Interaction, genetics, multiple sclerosis, paediatric neurology, Brain Disorders, Neurosciences, Autoimmune Disease, Clinical Research, Prevention, Genetics, Aetiology, 2.1 Biological and endogenous factors, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery
Abstract

BackgroundWe previously reported an association between household chemical exposures and an increased risk of paediatric-onset multiple sclerosis.MethodsUsing a case-control paediatric multiple sclerosis study, gene-environment interaction between exposure to household chemicals and genotypes for risk of paediatric-onset multiple sclerosis was estimated.Genetic risk factors of interest included the two major HLA multiple sclerosis risk factors, the presence of DRB1*15 and the absence of A*02, and multiple sclerosis risk variants within the metabolic pathways of common household toxic chemicals, including IL-6 (rs2069852), BCL-2 (rs2187163) and NFKB1 (rs7665090).Results490 paediatric-onset multiple sclerosis cases and 716 controls were included in the analyses. Exposures to insect repellent for ticks or mosquitos (OR 1.47, 95% CI 1.06 to 2.04, p=0.019), weed control products (OR 2.15, 95% CI 1.51 to 3.07, p

Published
2023

46. Niimpy: a toolbox for behavioral data analysis

Author

Ikäheimonen, A., Triana, A. M., Luong, N., Ziaei, A., Rantaharju, J., Darst, R., and Aledavood, T.

Subjects
Computer Science - Human-Computer Interaction
Abstract

Behavioral studies using personal digital devices typically produce rich longitudinal datasets of mixed data types. These data provide information about the behavior of users of these devices in real-time and in the users' natural environments. Analyzing the data requires multidisciplinary expertise and dedicated software. Currently, no generalizable, device-agnostic, freely available software exists within Python scientific computing ecosystem to preprocess and analyze such data. This paper introduces a Python package, Niimpy, for analyzing digital behavioral data. The Niimpy toolbox is a user-friendly open-source package that can quickly be expanded and adapted to specific research requirements. The toolbox facilitates the analysis phase by offering tools for preprocessing, extracting features, and exploring the data. It also aims to educate the user on behavioral data analysis and promotes open science practices. Over time, Niimpy will expand with extra data analysis features developed by the core group, new users, and developers. Niimpy can help the fast-growing number of researchers with diverse backgrounds who collect data from personal and consumer digital devices to systematically and efficiently analyze the data and extract useful information. This novel information is vital for answering research questions in various fields, from medicine to psychology, sociology, and others.

Published
2022

47. Anxiolytic Effect of Jasmine Aromatherapy in Pediatric Dental Procedures: A Single-Blinded Randomized Placebo-Controlled Trial

Author

Mehdi Jafarzadeh Samani, Sanaz Ziaei, Niloofar Monjezi, Razieh Fazaeli, Nahad Sedaghat, Hesam Panahi, and Shahrzad Mortazavi

Subjects
Jasmine Oil, Aromatherapy, Anxiety, Pain Perception, Pediatric Dentistry, Randomized Controlled Tria, Dentistry, RK1-715
Abstract

Objectives: The aim of the present investigation was to evaluate the possible anxiolytic effect of jasmine aromatherapy in pediatric dental procedures. Materials and Methods: A parallel randomized single-blinded placebo-controlled clinical trial was designed and conducted from February 19 until April 19, 2020, on children aged 7 to 12 years-old requiring class 1 restorative treatment of primary or permanent tooth with infiltration anesthesia. Interventions were defined as 15 minutes of aromatherapy using 2mL of jasmine extract for the intervention group, and with water for the control group. Outcomes were defined as child’s anxiety and pain perception, measured by modified child dental anxiety scale (MCDAS), visual analogue scale (VAS) and changes of vital signs. After the patients received interventions based on their groups, their data was collected and analyzed. We used parametric tests and linear regression for outcome comparisons. Results: 56 patients were randomized and allocated in two groups, 28 to each. The groups did not differ significantly regarding age, sex, heart rate and O2 saturation before, during, and after procedures. Based on multivariable regression, the intervention group showed a significantly reduced MCDAS (B (95% CI) =-2.11 (-4.09, -0.13), P=0.04) and VAS (B (95% CI) =-2.30 (-3.50, -1.10), P

Published
2024
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48. Reverse Survival Model (RSM): A Pipeline for Explaining Predictions of Deep Survival Models

Author

Rezaei, Mohammad R., Fard, Reza Saadati, Pourjafari, Ebrahim, Ziaei, Navid, Sameizadeh, Amir, Shafiee, Mohammad, Alavinia, Mohammad, Abolghasemian, Mansour, and Sajadi, Nick

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Machine Learning
Abstract

The aim of survival analysis in healthcare is to estimate the probability of occurrence of an event, such as a patient's death in an intensive care unit (ICU). Recent developments in deep neural networks (DNNs) for survival analysis show the superiority of these models in comparison with other well-known models in survival analysis applications. Ensuring the reliability and explainability of deep survival models deployed in healthcare is a necessity. Since DNN models often behave like a black box, their predictions might not be easily trusted by clinicians, especially when predictions are contrary to a physician's opinion. A deep survival model that explains and justifies its decision-making process could potentially gain the trust of clinicians. In this research, we propose the reverse survival model (RSM) framework that provides detailed insights into the decision-making process of survival models. For each patient of interest, RSM can extract similar patients from a dataset and rank them based on the most relevant features that deep survival models rely on for their predictions.

Published
2022

49. Reinforcement learning-based optimised control for tracking of nonlinear systems with adversarial attacks

Author

Rahimi, Farshad and Ziaei, Sepideh

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

This paper introduces a reinforcement learning-based tracking control approach for a class of nonlinear systems using neural networks. In this approach, adversarial attacks were considered both in the actuator and on the outputs. This approach incorporates a simultaneous tracking and optimization process. It is necessary to be able to solve the Hamilton-Jacobi-Bellman equation (HJB) in order to obtain optimal control input, but this is difficult due to the strong nonlinearity terms in the equation. In order to find the solution to the HJB equation, we used a reinforcement learning approach. In this online adaptive learning approach, three neural networks are simultaneously adapted: the critic neural network, the actor neural network, and the adversary neural network. Ultimately, simulation results are presented to demonstrate the effectiveness of the introduced method on a manipulator., Comment: Submitted for The 10th RSI International Conference on Robotics and Mechatronics (ICRoM 2022)

Published
2022

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