Enhancing reinforcement learning for de novo molecular design applying self-attention mechanisms.

The drug discovery process can be significantly improved by applying deep reinforcement learning (RL) methods that learn to generate compounds with desired pharmacological properties. Nevertheless, RL-based methods typically condense the evaluation of sampled compounds into a single scalar value, making it difficult for the generative agent to learn the optimal policy. This work combines self-attention mechanisms and RL to generate promising molecules. The idea is to evaluate the relative significance of each atom and functional group in their interaction with the target, and to utilize this information for optimizing the Generator. Therefore, the framework for de novo drug design is composed of a Generator that samples new compounds combined with a Transformer-encoder and a biological affinity Predictor that evaluate the generated structures. Moreover, it takes the advantage of the knowledge encapsulated in the Transformer's attention weights to evaluate each token individually. We compared the performance of two output prediction strategies for the Transformer: standard and masked language model (MLM). The results show that the MLM Transformer is more effective in optimizing the Generator compared with the state-of-the-art works. Additionally, the evaluation models identified the most important regions of each molecule for the biological interaction with the target. As a case study, we generated synthesizable hit compounds that can be putative inhibitors of the enzyme ubiquitin-specific protein 7 (USP7).

ZIF-8 Nanoparticle: A Valuable Tool for Improving Gene Delivery in Sperm-Mediated Gene Transfer.

Metal-organic frameworks (MOFs) are porous materials with unique characteristics that make them well-suited for drug delivery and gene therapy applications. Among the MOFs, zeolitic imidazolate framework-8 (ZIF-8) has emerged as a promising candidate for delivering exogenous DNA into cells. However, the potential of ZIF-8 as a vector for sperm-mediated gene transfer (SMGT) has not yet been thoroughly explored.This investigation aimed to explore the potential of ZIF-8 as a vector for enhancing genetic transfer and transgenesis rates by delivering exogenous DNA into sperm cells. To test this hypothesis, we employed ZIF-8 to deliver a plasmid expressing green fluorescent protein (GFP) into mouse sperm cells and evaluated the efficiency of DNA uptake. Our findings demonstrate that ZIF-8 can efficiently load and deliver exogenous DNA into mouse sperm cells, increasing GFP expression in vitro. These results suggest that ZIF-8 is a valuable tool for enhancing genetic transfer in SMGT, with important implications for developing genetically modified animals for research and commercial purposes. Additionally, our study highlights the potential of ZIF-8 as a novel class of vectors for gene delivery in reproductive biology.Overall, our study provides a foundation for further research into using ZIF-8 and other MOFs as gene delivery systems in reproductive biology and underscores the potential of these materials as promising vectors for gene therapy and drug delivery.

Deep generative model for therapeutic targets using transcriptomic disease-associated data-USP7 case study.

The generation of candidate hit molecules with the potential to be used in cancer treatment is a challenging task. In this context, computational methods based on deep learning have been employed to improve in silico drug design methodologies. Nonetheless, the applied strategies have focused solely on the chemical aspect of the generation of compounds, disregarding the likely biological consequences for the organism's dynamics. Herein, we propose a method to implement targeted molecular generation that employs biological information, namely, disease-associated gene expression data, to conduct the process of identifying interesting hits. When applied to the generation of USP7 putative inhibitors, the framework managed to generate promising compounds, with more than 90% of them containing drug-like properties and essential active groups for the interaction with the target. Hence, this work provides a novel and reliable method for generating new promising compounds focused on the biological context of the disease.

Reinforcing decellularized small intestine submucosa with cellulose acetate nanofibrous and silver nanoparticles as a scaffold for wound healing applications.

BACKGROUND: The formation of chronic wounds accounts for considerable costs in health care systems. Despite the several benefits of decellularized small intestinal submucosa (SIS) as an appropriate scaffold for different tissue regeneration, it has shortcomings such as lack of antibacterial features and inappropriate mechanical properties for skin tissue regeneration. We aimed to examine the efficacy and safety of decellularized SIS scaffold enhanced with cellulose acetate (CA) and silver (Ag) nanoparticles (NPs) for healing full-thickness wounds. METHODS AND RESULTS: The scaffolds were prepared by decellularizing bovine SIS and electrospinning CA/Ag nanoparticles and characterized using a transmission electron microscope (TEM), scanning electron microscope (SEM), tensile testing, and X-ray diffraction. In vivo evaluations were performed using full-thickness excisions covered with sterile gauze as the control group, SIS, SIS/CA, and SIS/CA/Ag scaffolds on the dorsum of twenty male Wistar rats divided into four groups randomly with 21-days follow-up. All in vivo specimens underwent Masson's trichrome (MT) staining for evaluation of collagen deposition, transforming growth factor-ß (TGF-ß) immunohistochemistry (IHC), and Haematoxylin Eosin (H&E) staining. The IHC and MT data were analyzed with the ImageJ tool by measuring the stained area. The TEM results revealed that Ag nanoparticles are successfully incorporated into CA nanofibers. Assessment of scaffolds hydrophilicity demonstrated that the contact angle of SIS/CA/Ag scaffold was the lowest. The in vivo results indicated that the SIS/CA/Ag scaffold had the most significant wound closure. H&E staining of the in vivo specimens showed the formation of epidermal layers in the SIS/CA/Ag group on day 21. The percentage of the stained area of MT and TGF-ß IHC staining's was highest in the SIS/CA/Ag group. CONCLUSION: The decellularized SIS/CA/Ag scaffolds provided the most significant wound closure compared to other groups and caused the formation of epidermal layers and skin appendages. Additionally, the collagen deposition and expression of TGF-ß increased significantly in SIS/CA/Ag group.

Design, Green Synthesis and in silico Studies of New Substituted Naphtho[1,2-e][1,3]Oxazines as Potential Acetylcholinesterase Inhibitors.

Alzheimer's disease (AD) is a prevalent neurodegenerative condition characterized by progressive cognitive decline and memory impairment resulting from the degeneration and death of brain neurons. Acetylcholinesterase (AChE) inhibitors as the primary pharmacotherapy for numerous neurodegenerative conditions, leveraging their capacity to modulate acetylcholine levels crucial for cognitive function. Recently, oxazines  have brought worthy synthetic interest due to their extensive biological activities including, anti-tubercular, anti-convulsant, and anti-cancer activities. In this study, a series of novel naphtho[1,2-e][1,3]oxazine derivatives has been designed  and synthesized with potential of acetylcholinesterase (AChE) inhibition. The target products have been prepared by a one-pot and three-component condensation reaction of 2-naphthol, aromatic aldehydes, and arylmethanimine in the presence of 3-methyl-1-sulfonic acid imidazolium chloride ([Msim]Cl) as an effective and recyclable catalyst under microwave irradiation solvent-free condition. The molecular docking studies has also been performed to investigate the synthetic compounds in the the AChE active site gorge. The results showed that all these derivatives interact with the enzymes with high affinity in binding pocket. The MM-GBSA studies were performed for all synthesized derivatives and among them, compound 3-(4-Chlorophenyl)-1-phenyl-2,3-dihydro-1H-naphtho[1,2-e][1,3]oxazine 5f, showed the lowest the binding free energy (-48.04 kcal mol-1). In general, oxazine derivatives could be proposed as the strong AChE inhibitors.

Speeding Up Entanglement Generation by Proximity to Higher-Order Exceptional Points.

Entanglement is a key resource for quantum information technologies ranging from quantum sensing to quantum computing. Conventionally, the entanglement between two coupled qubits is established at the timescale of the inverse of the coupling strength. In this Letter, we study two weakly coupled non-Hermitian qubits and observe entanglement generation at a significantly shorter timescale by proximity to a higher-order exceptional point. We establish a non-Hermitian perturbation theory based on constructing a biorthogonal complete basis and further identify the optimal condition to obtain the maximally entangled state. Our study of speeding up entanglement generation in non-Hermitian quantum systems opens new avenues for harnessing coherent nonunitary dissipation for quantum technologies.

Artificial intelligence for prediction of biological activities and generation of molecular hits using stereochemical information.

In this work, we develop a method for generating targeted hit compounds by applying deep reinforcement learning and attention mechanisms to predict binding affinity against a biological target while considering stereochemical information. The novelty of this work is a deep model Predictor that can establish the relationship between chemical structures and their corresponding [Formula: see text] values. We thoroughly study the effect of different molecular descriptors such as ECFP4, ECFP6, SMILES and RDKFingerprint. Also, we demonstrated the importance of attention mechanisms to capture long-range dependencies in molecular sequences. Due to the importance of stereochemical information for the binding mechanism, this information was employed both in the prediction and generation processes. To identify the most promising hits, we apply the self-adaptive multi-objective optimization strategy. Moreover, to ensure the existence of stereochemical information, we consider all the possible enumerated stereoisomers to provide the most appropriate 3D structures. We evaluated this approach against the Ubiquitin-Specific Protease 7 (USP7) by generating putative inhibitors for this target. The predictor with SMILES notations as descriptor plus bidirectional recurrent neural network using attention mechanism has the best performance. Additionally, our methodology identify the regions of the generated molecules that are important for the interaction with the receptor's active site. Also, the obtained results demonstrate that it is possible to discover synthesizable molecules with high biological affinity for the target, containing the indication of their optimal stereochemical conformation.

Hypo vs. hyperthyroid eye disease: is there any difference?

BACKGROUND: Thyroid-eye disease (TED) is the most common extra-thyroidal presentation of graves' disease. We performed this study to compare clinical characteristics of TED in hypothyroid vs. hyperthyroid patients. METHODS: This was a retrospective analytical cross-sectional study in which we compared demographics, severity (EUGOGO classification) and activity (clinical activity score) of TED, thyroid disease duration, TED duration and clinical signs between hypothyroid eye disease (Ho-TED) and hyperthyroid eye disease (Hr-TED). To minimize the effect of selection bias and potential confounders, 1:1 propensity score matching (PSM) was also performed. RESULTS: Three hundred and seventy-four patients (341 Hr-TED and 33 Ho-TED) with a female to male ratio of 1.4:1 were identified in our study. Female to male ratio was 1.3:1 in hyperthyroid and 4.5:1 in hypothyroid group (P = 0.005). The duration of thyroid disease was longer in Ho-TED (P = 0.002) while the duration of eye disease was not significantly different between the Hr-TED (mean = 24.33 ± 41.69, median = 8) and Ho-TED (mean = 19.06 ± 33.60, median = 12) (P = 0.923). Most of the patients in hypothyroid group developed eye involvement after thyroid disease (80.0% in hypo vs. 48.1% in hyper, P = 0.003). Severity (P = 0.13) and activity (P = 0.11) was not different between Hr-TED and Ho-TED patients. After PSM analysis, no clinical characteristics were significantly different between the two groups (P > 0.05). CONCLUSION: The results of our study showed several differences between the Hr/Ho TED patients including sex, duration of thyroid disease and pattern of eye involvement. After matching the two groups with statistical methods, no clinical characteristics were different between Hr-TED and Ho-TED patients.

A comparison between bilateral and unilateral thyroid eye disease.

PURPOSE: To compare characteristics of unilateral vs. bilateral thyroid eye disease (TED). METHODS: This retrospective analytical cross-sectional study was conducted on patients with TED who were evaluated at an academic referral center over a 6-year period. We compared demographics, activity (clinical activity score) and severity (EUGOGO classification) of TED, thyroid disease duration, TED duration, the time interval between thyroid and eye involvement, thyroid function status, and clinical signs between bilateral and unilateral TED. RESULTS: Three hundred eighty-three patients including 213 females (55.6%), who had a mean age of 40.23 ± 13.72 years, were enrolled. Active TED was seen in 8.8% of bilateral and none of unilateral cases (P = 0.04). Bilateral TED patients had more severe disease (P = 0.001). The distribution of hyperthyroidism, hypothyroidism, and euthyroidism was significantly different between unilateral and bilateral groups (P = 0.001). Abnormal ocular motility was present in 26.3% versus 2.3% of bilateral and unilateral ones, respectively (P = 0.001). Proptosis was more prevalent in bilateral than unilateral cases (P = 0.001). We did not observe any statistically significant difference between the two groups in others variables. CONCLUSION: Bilateral TED patients present with more severity, activity, movement abnormality, proptosis, and hyperthyroidism.

EFL learners' engagement in online learning context: development and validation of potential measurement inventory.

Research has proved learner engagement is a strong predictor of academic achievement, especially in the online learning environment. The lack of any reliable and valid instrument to measure this construct in the context of online education made the researchers of the current study develop and validate a potential measurement inventory to assess EFL learners' engagement in the online learning environment. For this purpose, a comprehensive review of the related literature and careful investigation of the existing instruments were carried out to find the theoretical constructs for learner engagement which led to the development of a 56-item Likert scale questionnaire. The newly developed questionnaire was piloted with 560 female and male EFL university students selected based on nonprobability convenience sampling. The results of the factor analysis indicated the reduction of items to 48 loaded on three main components, namely behavioral engagement (15 items), emotional engagement (16 items), and cognitive engagement (17 items). The results also revealed that the newly developed questionnaire enjoyed a reliability index of 0.925. The findings of the current study will undoubtedly help teaching practitioners assess EFL learners' engagement in the online learning context and make principled decisions when it comes to learners' engagement.

Explainable deep drug-target representations for binding affinity prediction.

BACKGROUND: Several computational advances have been achieved in the drug discovery field, promoting the identification of novel drug-target interactions and new leads. However, most of these methodologies have been overlooking the importance of providing explanations to the decision-making process of deep learning architectures. In this research study, we explore the reliability of convolutional neural networks (CNNs) at identifying relevant regions for binding, specifically binding sites and motifs, and the significance of the deep representations extracted by providing explanations to the model's decisions based on the identification of the input regions that contributed the most to the prediction. We make use of an end-to-end deep learning architecture to predict binding affinity, where CNNs are exploited in their capacity to automatically identify and extract discriminating deep representations from 1D sequential and structural data. RESULTS: The results demonstrate the effectiveness of the deep representations extracted from CNNs in the prediction of drug-target interactions. CNNs were found to identify and extract features from regions relevant for the interaction, where the weight associated with these spots was in the range of those with the highest positive influence given by the CNNs in the prediction. The end-to-end deep learning model achieved the highest performance both in the prediction of the binding affinity and on the ability to correctly distinguish the interaction strength rank order when compared to baseline approaches. CONCLUSIONS: This research study validates the potential applicability of an end-to-end deep learning architecture in the context of drug discovery beyond the confined space of proteins and ligands with determined 3D structure. Furthermore, it shows the reliability of the deep representations extracted from the CNNs by providing explainability to the decision-making process.

Optimizing blood-brain barrier permeation through deep reinforcement learning for de novo drug design.

MOTIVATION: The process of placing new drugs into the market is time-consuming, expensive and complex. The application of computational methods for designing molecules with bespoke properties can contribute to saving resources throughout this process. However, the fundamental properties to be optimized are often not considered or conflicting with each other. In this work, we propose a novel approach to consider both the biological property and the bioavailability of compounds through a deep reinforcement learning framework for the targeted generation of compounds. We aim to obtain a promising set of selective compounds for the adenosine A2A receptor and, simultaneously, that have the necessary properties in terms of solubility and permeability across the blood-brain barrier to reach the site of action. The cornerstone of the framework is based on a recurrent neural network architecture, the Generator. It seeks to learn the building rules of valid molecules to sample new compounds further. Also, two Predictors are trained to estimate the properties of interest of the new molecules. Finally, the fine-tuning of the Generator was performed with reinforcement learning, integrated with multi-objective optimization and exploratory techniques to ensure that the Generator is adequately biased. RESULTS: The biased Generator can generate an interesting set of molecules, with approximately 85% having the two fundamental properties biased as desired. Thus, this approach has transformed a general molecule generator into a model focused on optimizing specific objectives. Furthermore, the molecules' synthesizability and drug-likeness demonstrate the potential applicability of the de novo drug design in medicinal chemistry. AVAILABILITY AND IMPLEMENTATION: All code is publicly available in the https://github.com/larngroup/De-Novo-Drug-Design. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Topological Quantum State Control through Exceptional-Point Proximity.

We study the quantum evolution of a non-Hermitian qubit realized as a submanifold of a dissipative superconducting transmon circuit. Real-time tuning of the system parameters to encircle an exceptional point results in nonreciprocal quantum state transfer. We further observe chiral geometric phases accumulated under state transport, verifying the quantum coherent nature of the evolution in the complex energy landscape and distinguishing between coherent and incoherent effects associated with exceptional point encircling. Our work demonstrates an entirely new method for control over quantum state vectors, highlighting new facets of quantum bath engineering enabled through dynamical non-Hermitian control.

Decoherence-Induced Exceptional Points in a Dissipative Superconducting Qubit.

Open quantum systems interacting with an environment exhibit dynamics described by the combination of dissipation and coherent Hamiltonian evolution. Taken together, these effects are captured by a Liouvillian superoperator. The degeneracies of the (generically non-Hermitian) Liouvillian are exceptional points, which are associated with critical dynamics as the system approaches steady state. We use a superconducting transmon circuit coupled to an engineered environment to observe two different types of Liouvillian exceptional points that arise either from the interplay of energy loss and decoherence or purely due to decoherence. By dynamically tuning the Liouvillian superoperators in real time we observe a non-Hermiticity-induced chiral state transfer. Our study motivates a new look at open quantum system dynamics from the vantage of Liouvillian exceptional points, enabling applications of non-Hermitian dynamics in the understanding and control of open quantum systems.

Quantum Jumps in the Non-Hermitian Dynamics of a Superconducting Qubit.

We study the dynamics of a driven non-Hermitian superconducting qubit which is perturbed by quantum jumps between energy levels, a purely quantum effect with no classical correspondence. The quantum jumps mix the qubit states leading to decoherence. We observe that this decoherence rate is enhanced near the exceptional point, owing to the cube-root topology of the non-Hermitian eigenenergies. Together with the effect of non-Hermitian gain or loss, quantum jumps can also lead to a breakdown of adiabatic evolution under the slow-driving limit. Our study shows the critical role of quantum jumps in generalizing the applications of classical non-Hermitian systems to open quantum systems for sensing and control.

Exploring the mediating role of integrative self-knowledge in the relationship between mindfulness and well-being in the context of a mindfulness-based stress reduction program.

Mindfulness-based stress reduction (MBSR) is an effective program for improving well-being. A growing body of studies is exploring the mechanisms mediating its beneficial effects. Integrative self-knowledge (ISK) is the construct of focus in this study. The primary goal of the current study was to investigate the mediating role of ISK in the relationship between improved mindful observing (MO), non-judging inner experience (NJ), and well-being following an MBSR program with an Iranian sample. Participants (n = 118) enrolled in MBSR and completed depression, anxiety, stress (DASS), Bartone Symptoms Checklist (BSC), Five-Facet Mindfulness Questionnaire, and ISK scale before and after the program. Results showed significant reductions in BSC, DASS, and improvements in MO, NJ, and ISK at the end of the program. Mediation analyses revealed that changes in ISK significantly mediated the relationship between changes in MO and NJ and symptoms (MO indirect effect on DASS: ß = 0.11, confidence interval [CI] [0.003, 0.29]; NJ indirect effect on DASS: ß = 0.12, CI [-0.16, 0.45]; MO indirect effect on BSC: ß = 0.08, CI [0.001, 0.27]; NJ indirect effect on BSC: ß = 0.09, CI [0.01, 0.22]). Improvements in MO and NJ may provide a pathway to cultivating ISK in MBSR, which may lead to enhanced well-being.

The effective coping strategies against burnout: Perceptions of Pakistani medical students.

OBJECTIVE: To explore effective coping strategies used by medical students against burnout. METHODS: The mixed method study was conducted at the Al Mizan campus of Riphah International University, Rawalpindi, Pakistan, from March to August 2018, and comprised fourth and fifth year medical students of both genders. Data was collected using the Maslach burnout inventory, which was followed by focus group discussions. Data was analysed using inductive approach. RESULTS: Of the respondents, 34(23.4%) were males and 111(76.5%) were females. Overall, 84 out of 151 (56%) students scored high on emotional exhaustion scale, 35 (23%) scored moderate and 32 (21%) scored low. On the cynicism scale, 93 (63%) out of 147 scored high, 47 (32%) scored moderate and 7 (5%) scored low. On professional efficacy, 42 out of 149 (28%) students scored low,74(50%) moderate and 33(22%) scored high. Seeking emotional support for coping was very common. Parents played the main role in providing support to the students. Turning to religion, acceptance and venting were also common coping strategies. CONCLUSIONS: Emotional exhaustion and cynicism were found in majority of the sample comprising medical students, seeking emotional support was common as a coping strategy.

Investigating expression pattern of eight immune-related genes in pemphigus patients compared with the healthy controls and after rituximab therapy: Potential roles of CTLA4 and FCGR3A genes expression in outcomes of rituximab therapy.

Pemphigus is a rare group of autoimmune diseases, which its exact molecular pathogenesis and therapeutic biomarkers remained unknown. In this regard the expressions of eight immune-related genes was evalualted in pemphigus patients. Forty-six pemphigus patients, either new case or on minimal therapy, were recruited. The expressions of IL22, IL9, IL21, EBI3, TNFSF13B, FCGR3A, CTLA4, and PDCD1 genes were analyzed at baseline, compared with 32 healthy controls, and their changes were monitored 3 months after rituximab (RTX) therapy through Reverse Transcriptase Real-time PCR (RT-Real-time PCR). Except of IL21, which was similar in both groups, expressions of other genes were significantly lower in patients compared with the controls (P-value <.05). PDCD1, EBI3, IL21, and IL22 genes were significantly overexpressed three months following RTX administration (P-value <.05). Higher prednisolone dosage and PDAI-score were positively correlated with CTLA4 and FCGR3A expressions after 3 months, respectively (P-value = .019 and .048, respectively). Anti-desmoglein 1 (Dsg 1) titer and its positivity at baseline were associated with TNFSF13B expression, FCGR3A expressions, and the PDAI-score. Our results suggest the possible involvement of some gene expressions in pemphigus immunopathogenesis, which could be affected by RTX therapy and also might be used as prognostic biomarkers.

Effects of Life style factors on the symptoms of gastro esophageal reflux disease: A cross sectional study in a Pakistani population.

BACKGROUND &OBJECTIVE: Gastro esophageal reflux disease (GERD) broadly includes the whole spectrum of reflux disease symptoms like heartburn or acid regurgitation to endoscopic, reflux esophagitis or Barrett's esophagus. Our aim therefore was to study the association between Gastroesophageal reflux disease symptoms and various lifestyle factors. METHODS: A descriptive cross-sectional study was carried out in the outpatient department of Darul Sehat Hospital, Zubaida Medical Center and Liaquat National Hospital & Medical College, Karachi, Pakistan from January 2018 to October 2018. The selected candidates were asked to fill a validated GERD questionnaire and they were also asked about their lifestyle factors. Odds ratio and their 95% confidence interval were estimated using binary logistic regression with GERD symptoms as the study outcome. RESULTS: A total of 2000 respondents completed the questionnaire. 69.3% gastroesophageal reflux disease cases were found in participants above 35 years of age while 56.9% subjects were male. The most common lifestyle factors associated with GERD were less exercise time (90.9%) (OR, 6.47; 95% CI, 4.91-8.53), 78.3% participants had habit of eating midnight snacks (OR, 5.08; 95% CI, 4.03-6.40), 87.3% participants reported less interval between dinner and sleep (OR, 6.98; 95% CI, 5.36-9.08). The most important factor relieving GERD symptoms was raising the head of bed during sleep (79.4%) while 43.3% subjects with the habit of post dinner walk reported fewer symptoms of GERD. CONCLUSION: Lifestyle factors particularly less physical activity, late evening meals, inadequate sleep, smoking and post dinner lying were found to be associated with GERD symptoms.

Multiple sclerosis and environmental risk factors: a case-control study in Iran.

Studies have shown an increase in the incidence of MS in Iran. The aim of our study was to evaluate the relationship between environmental exposure and MS in Iran. This case-control study was conducted on 660 MS patients and 421 controls. Many environmental factors are compared between the two groups. Our findings demonstrated that prematurity ([OR = 4.99 (95% CI 1.34-18.68), P = 0.017]), history of measles and mumps ([OR = 1.60 (95% CI 1.05-2.45), P = 0.029; OR = 1.85 (95% CI 1.22-2.78), P = 0.003, respectively]), breast feeding [OR = 2.90 (95% CI 1.49-5.65), P = 0.002], head trauma in childhood ([OR = 8.21 (95% CI 1.56-43.06), P = 0.013]), vaccination in adulthood ([OR = 4.57 (95% CI 1.14-18.41), P = 0.032, respectively]), migraine ([OR = 3.50 (95% CI 1.61-7.59), P = 0.002]), family history of MS, IBD, migraine, and collagen vascular diseases ([OR = 2.73 (95% CI 1.56-4.78), P < 0.001], [OR = 3.14 (95% CI 1.460-6.78), P = 0.004; OR = 3.18 (95% CI 1.83-5.53), P < 0.001; OR = 1.81 (95% CI 1.03-3.20), P = 0.040, respectively]), stressful events ([OR = 32.57 (95% CI 17.21-61.64), P < 0.001]), and microwave exposure ([OR = 3.55 (95% CI 2.24-5.63), P ≤0.001]) were more in the MS group. Sun exposure ([OR = 0.09 (95% CI 0.02-0.38), P = 0.001]), dairy and calcium consumption ([OR = 0.44 (95% CI 0.27-0.71), P = 0.001]), diabetes mellitus ([OR = 0.11 (95% CI 0.01-00.99), P = 0.049], and complete vaccination during childhood appeared to decreased MS risk. Our results investigated many risk factors and protective factors in Iran.