📌Our Focus:

1⃣

Our main focus at NAIRG is to provide a better understanding of neuroscience and AI and the application of different methods of AI to understand medical diseases, especially neurodegenerative and neuropsychiatric disorders, with the hope of improving predicting their prognosis and monitoring these diseases.

2⃣

We have projects on various neuroscience topics, including neurodegenerative diseases, cognitive neurosciences, and neuroimaging. In particular, we conduct experimental neurosciences using electrophysiology and behavioral techniques.

Research Interests:

📍Neurosciences
📍Neuroimaging
📍Computational Neuroscience
📍Brain Stimulation
📍Electrophysiology
📍Behavioral Neuroscience
📍Personalized Medicine


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#NAIRG_Membership

The NAIRG is a research group that fosters the development of young and keen researchers who are interested in the nervous system and its related fields. The NAIRG provides an environment where all the members are supported and challenged by mentors who are involved in every stage of every project. The NAIRG assigns each new member an important but manageable project that suits their level of expertise. The NAIRG values mentorship, responsibility, discipline, and punctuality and strives to create a culture of learning and teaching. Members are expected to become future mentors and pass the torch to the next generation of students. This approach has enabled the NAIRG to work on many projects and publish some of them in reputable journals within a span of just over a year. The NAIRG has also become an attractive place for many students in UMSHA who want to join the group and pursue their research interests. The NAIRG owes its success to hardworking mentors, members, and ever-caring supervisors. As a community, we look forward to continually improving and delivering a better understanding of neuroscience and artificial intelligence fields in medicine to help improve people's health everywhere.

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#NAIRG_Publication🧠

This study investigated the restorative and antimicrobial effects of Scrophularia striata hydroalcoholic extract (SHE) on first- and second-grade pressure ulcers in patients with brain and spinal cord lesions

📖 PDF file of this article is available in NAIRG channel


📋 Title: The antimicrobial and healing effect of Scrophularia striata Boiss hydroalcoholic extract on first-and second-grade pressure wounds in patients with brain and spinal cord injury: a randomized clinical trial. Evidence-Based Complementary and Alternative Medicine.

📥 Link: https://www.hindawi.com/journals/ecam/2022/8522937/

📎 doi: 10.1155/2022/8522937

📎 Journal name: Evidence-based Complementary and Alternative Medicine

📎 Authors: Zahra Bagheri, Amir Larki-Harchegani, Shabnam Pourmoslemi, Amir Nili-Ahmadabadi, Ebrahim Bakhtiari, Hamid Safarpour, Ali Fathi Jouzdani, Morteza Shamsizadeh

📎 Abstract: The study investigated the restorative and antimicrobial effects of Scrophularia striata hydroalcoholic extract (SHE) on first- and second-grade pressure ulcers in patients with brain and spinal cord lesions

📎 Result:This study analyzed 140 patients, dividing them into four groups based on demographic characteristics. The patients were not significantly different in terms of gender, age, occupation, education, marriage, and residence. The study found that most patients were hospitalized due to spinal cord injury (SCI) and cerebrovascular accident (CVA), with most having grade 2 ulcers. The mean ulcer size before and ten days after intervention showed a significant difference between the four groups. The decreasing process slope of the mean ulcer size in patients of experiment group 2 was steeper compared to the control and placebo groups. By the tenth day of intervention, 63.3% of patients in experiment group 1, 100% in experimental group 2, and 26.7% in the control group had healing ulcers. No complete recovery was observed in any placebo patients during ten days of intervention. The time of complete ulcer healing patients in experiment group 2 was less than in group 1 and the control group.

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📋 Title: The antimicrobial and healing effect of Scrophularia striata Boiss hydroalcoholic extract on first-and second-grade pressure wounds in patients with brain and spinal cord injury: a randomized clinical trial. Evidence-Based Complementary and Alternative Medicine.


📥 Link: https://www.hindawi.com/journals/ecam/2022/8522937/

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Aluminum phosphide (ALP) is among the most significant causes of brain toxicity and death in many countries. Curcumin (CUR), a major turmeric component, is a potent protective agent against many diseases, including brain toxicity. This study aimed to examine the probable protection potential of nanomicelle curcumin (nanomicelle-CUR) and its underlying mechanism in a rat model of ALP-induced brain toxicity.

📖 PDF file of this article is available in NAIRG channel

📋 Title: How can nanomicelle-curcumin modulate aluminum phosphide-induced neurotoxicity?: Role of SIRT1/FOXO3 signaling pathway

📥 Link: https://www.aimspress.com/article/doi/10.3934/Neuroscience.2023005

📎 doi:  10.3934/Neuroscience.2023005

📎 Journal name: AIMS Neuroscience
2023, Volume 10, Issue 1: 56-74.

📎 Authors:
Milad Khodavysi
Nejat Kheiripour
Hassan Ghasemi
Sara Soleimani-Asl
Ali Fathi Jouzdani
Mohammadmahdi Sabahi
Zahra Ganji
Zahra Azizi
Akram Ranjbar

📎 Result: The study compared the MDA, TTG, TAC, and SOD levels of the ALP and CUR groups in brain tissue. MDA levels were significantly increased in the ALP group compared to the control group, while TTG levels were decreased in the ALP group. The ALP + CUR and ALP + nanomicelle-CUR groups had no significant difference in MDA levels compared to the control group. TAC levels were also significantly decreased in the ALP group compared to the control group, while the tissue TAC levels increased in the ALP + CUR and ALP + nanomicelle-CUR groups. The brain SOD level was significantly decreased in the ALP group compared to the control group, and the levels in the ALP + CUR and ALP + nanomicelle-CUR groups were not significantly different. The CUR and nanomicelle-CUR groups had no significant difference compared to the control group. The results suggest that the ALP group may have a higher SOD level than the CUR and nanomicelle-CUR groups.

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📋 Title: How can nanomicelle-curcumin modulate aluminum phosphide-induced neurotoxicity?: Role of SIRT1/FOXO3 signaling pathway

📥 Link: https://www.aimspress.com/article/doi/10.3934/Neuroscience.2023005

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🩻 We aimed to predict Montreal Cognitive Assessment (MoCA) scores in Parkinson’s disease patients at year 4 using handcrafted radiomics (RF), deep (DF), and clinical (CF) features at year 0 (baseline) applied to hybrid machine learning systems (HMLSs)

📖 PDF file of this article is available in NAIRG channel

📋Title: Prediction of Cognitive Decline in Parkinson’s Disease Using Clinical and DAT SPECT Imaging Features, and Hybrid Machine Learning Systems


📥 Link :
https://www.mdpi.com/2075-4418/13/10/1691

📎 doi: https://doi.org/10.3390/diagnostics13101691

📎 Journal name:
Diagnostics 2023, 13(10), 1691;

📎 Authors:
Mahdi Hosseinzadeh
Arman Gorji
Ali Fathi Jouzdani
Seyed Masoud Rezaeijo
Arman Rahmim
Mohammad R. Salmanpour

📎 Result:
For the sole usage of RFs and DFs, ANOVA and MLP resulted in averaged accuracies of 59 ± 3% and 65 ± 4% for 5-fold cross-validation, respectively, with hold-out testing accuracies of 59 ± 1% and 56 ± 2%, respectively. For sole CFs, a higher performance of 77 ± 8% for 5-fold cross-validation and a hold-out testing performance of 82 + 2% were obtained from ANOVA and ETC. RF+DF obtained a performance of 64 ± 7%, with a hold-out testing performance of 59 ± 2% through ANOVA and XGBC. Usage of CF+RF, CF+DF

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📋 Title :
Prediction of Cognitive Decline in Parkinson’s Disease Using Clinical and DAT SPECT Imaging Features, and Hybrid Machine Learning Systems

📥 Link:
https://www.mdpi.com/2075-4418/13/10/1691#

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🎊🎉Happy New Year 🎉🎊

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#Conferences

🩻Although the use of hand-crafted radiomics features (RF) has shown significant promise to improve diagnostic, prognostic, and treatment response assessments, employing deep features (DF) extracted from deep learning (DL) algorithms merits significant investigation in lung cancer disease. We aimed to employ RFs vs. DFs to predict recurrence-free survival (RFS) and overall survival (OS) using machine learning (ML) techniques in lung cancer.


📋 Title:

PET-CT Fusion Based Outcome Prediction in Lung Cancer using Deep and Handcrafted Radiomics Features and Machine Learning


📥 Link :
https://jnm.snmjournals.org/content/64/supplement_1/P1196.abstract

📎 Journal name:
Journal of Nuclear Medicine June 2023, 64 (supplement 1) P1196;

📎 Authors:

Arman Gorji
Ali Fathi Jouzdani
Nima Sanati
Mahdi Hosseinzadeh
Ali Mahboubisarighieh
Seyed Masoud Rezaeijo
Mehdi Maghsudi
Sara Moore
Leung Bonnie
Carlos Uribe
Cheryl Ho
Arman Rahmim
Mohammad R Salmanpour

📎 Result:
In RF framework, SR+ANOVA+MLP and VSMWLS+ANOVA+MLP resulted in MAEs of 506.7± 6.1 and 264.0±6.8 days to predict approximate death (OS) and approximate recurrence time (RFS) while we arrived at the lowest MSEs of 430.3±10.2 and 250.5±10.2 using DF supplied to LP_SR+ANOVA+MLP and CT+MRMR+ HistGB, respectively. In predictions of time to events such as OS and RFS, Wavelet+PCA+RadSF and NSCT_SR+PCA+RadSF linked with DFs obtained c-indexes of 0.59±0.03 and 0.61±0.01, while the highest c-indexes of 0.64 ±0.03 and 0.61±0.05 were obtained by RFs followed by CBF+PCA+RadSF and VSMWLS+PCA+RadSF, respectively.

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