Sero-prevalence of Toxoplasma gondii before and during the COVID-19 pandemic in Northwestern Iran.

BACKGROUND: Toxoplasma gondii (T. gondii) is a ubiquitous protozoan parasite on our planet that causes toxoplasmosis. This study evaluated the seroprevalence and related risk factors for T. gondii infection in a population referred to healthcare centers in Meshkin-Shahr, Northwest Iran. METHODS: A total of 400 blood samples were randomly collected from the general population and assessed using the anti-Toxoplasma antibodies, Immunoglobulin G and M (IgG and IgM) Enzyme-linked immunosorbent assay (ELISA) Kits in two steps before and during the coronavirus disease 2019 (COVID-19) pandemic, 2019-2020. The results were analyzed through logistic regression via SPSS 26 software. RESULTS: Before the COVID-19 pandemic, anti-toxoplasma antibodies were detected in 39% of individuals (IgG: 38%, IgM: 0.5%, and IgG-IgM: 0.5%). Among the eleven risk factors evaluated, contact with soil and people awareness were significantly associated with T. gondii infection (p < 0.05). However, factors such as females, 20-39 age groups, junior high schools, housewives, rural areas, raw meat or vegetable consumption, vegetable or fruits washed by water, not detergent, and cat owners did not show a significant relationship with seropositivity (p > 0.05). After the outbreak of the COVID-19 pandemic, the overall seroprevalence for anti-T. gondii antibody increased to 49.7% (IgG: 47.7%, IgM: 0.5%, and IgG and IgM: 1.5%). Among these patients, 26% were positive for COVID-19. Additionally, before the COVID-19 pandemic, 40 samples were negative for anti-T. gondii antibodies but later became positive. The crude and adjusted models suggested that toxoplasmosis may be a possible risk factor for increased susceptibility to COVID-19, with an odds ratio (OR) of 1.28 (95% confidence interval (CI), 0.82-1.99; P < 0.05). Conversely, a non-significant protective effect against latent toxoplasmosis was observed in COVID-19-positive individuals (OR = 0.99; 95% CI, 0.51-1.92; P > 0.05), and COVID-19 positivity did not increase the levels of anti-T. gondii IgG antibodies. CONCLUSIONS: The general population in this region had a moderate seroprevalence of T. gondii. The increased number of COVID-19-positive patients with latent toxoplasmosis highlights the need to pay attention to the early diagnosis and proper treatment of toxoplasmosis in these patients and implement preventive programs in these areas for future possible viral infections.

Continuous patient state attention model for addressing irregularity in electronic health records.

BACKGROUND: Irregular time series (ITS) are common in healthcare as patient data is recorded in an electronic health record (EHR) system as per clinical guidelines/requirements but not for research and depends on a patient's health status. Due to irregularity, it is challenging to develop machine learning techniques to uncover vast intelligence hidden in EHR big data, without losing performance on downstream patient outcome prediction tasks. METHODS: In this paper, we propose Perceiver, a cross-attention-based transformer variant that is computationally efficient and can handle long sequences of time series in healthcare. We further develop continuous patient state attention models, using Perceiver and transformer to deal with ITS in EHR. The continuous patient state models utilise neural ordinary differential equations to learn patient health dynamics, i.e., patient health trajectory from observed irregular time steps, which enables them to sample patient state at any time. RESULTS: The proposed models' performance on in-hospital mortality prediction task on PhysioNet-2012 challenge and MIMIC-III datasets is examined. Perceiver model either outperforms or performs at par with baselines, and reduces computations by about nine times when compared to the transformer model, with no significant loss of performance. Experiments to examine irregularity in healthcare reveal that continuous patient state models outperform baselines. Moreover, the predictive uncertainty of the model is used to refer extremely uncertain cases to clinicians, which enhances the model's performance. Code is publicly available and verified at https://codeocean.com/capsule/4587224 . CONCLUSIONS: Perceiver presents a computationally efficient potential alternative for processing long sequences of time series in healthcare, and the continuous patient state attention models outperform the traditional and advanced techniques to handle irregularity in the time series. Moreover, the predictive uncertainty of the model helps in the development of transparent and trustworthy systems, which can be utilised as per the availability of clinicians.

Improving Diagnostics with Deep Forest Applied to Electronic Health Records.

An electronic health record (EHR) is a vital high-dimensional part of medical concepts. Discovering implicit correlations in the information of this data set and the research and informative aspects can improve the treatment and management process. The challenge of concern is the data sources' limitations in finding a stable model to relate medical concepts and use these existing connections. This paper presents Patient Forest, a novel end-to-end approach for learning patient representations from tree-structured data for readmission and mortality prediction tasks. By leveraging statistical features, the proposed model is able to provide an accurate and reliable classifier for predicting readmission and mortality. Experiments on MIMIC-III and eICU datasets demonstrate Patient Forest outperforms existing machine learning models, especially when the training data are limited. Additionally, a qualitative evaluation of Patient Forest is conducted by visualising the learnt representations in 2D space using the t-SNE, which further confirms the effectiveness of the proposed model in learning EHR representations.

The sufficient vitamin D and albumin level have a protective effect on COVID-19 infection.

There is limited information regarding the protective factors of SARS-CoV-2 infection. This research is focused on analyzing the role of vitamin D and albumin in the severity, progression, or possible prevention of COVID-19 infection. In this case-control study, 191 patients and 203 healthy individuals were enrolled. Blood samples were taken to test the albumin and vitamin D levels of both groups. Our results show a direct association of vitamin D deficiency with the infection of COVID-19 and severity. According to our findings, 84.4% of patients with COVID-19 in this study had vitamin D deficiency. Moreover, the average level of albumin was significantly decreased in those infected patients who had respiratory symptoms. In the present study, a considerable negative correlation was established between the levels of vitamin D and the severity of COVID-19 infection. This reflects on the immunomodulatory and inhibitory nature of vitamin D to the viral replication.

Cutaneous Leishmaniasis Situation and Predicting the Distribution of Phlebotomus papatasi and P. sergenti as Vectors of Leishmaniasis in Ardabil Province, Iran.

Cutaneous leishmaniosis (CL) is the most common form of leishmaniasis.CL caused by L. major and L. tropica is endemic in 17 provinces of Iran. This study was carried out to elucidate situation of CL in Ardabil province and to predict distribution of Phlebotomus papatasi and Phlebotomus sergenti (Diptera: Psychodidae) as vectors of CL in the region. In this cross-sectional study, data on CL patients were collected from local health centers of Ardabil province, Iran during 2006-2018 to establish a geodatabase using ArcGIS10.3. A total of 20 CL cases were selected randomly and skin samples were collected and analyzed by PCR method. MaxEnt 3.3.3 model was used to determine ecologically suitable niches for the main vectors. A total, 309 CL human cases were reported and the highest incidence rate of disease was occurred in Bilasavar (37/100,000) and Germi (35/100,000). A total of 2,794 sand flies were collected during May to October 2018. The environmentally suitable habitats for P. papatasi and P. sergenti were predicted to be present in northern and central areas of Ardabil province. The most variable that contributed ratio in the modeling were Isothermality and slope factors. Ardabil province is possibly an endemic are for CL. The presence of P. papatasi and P. sergenti justifies local transmission while the vectors of CL are existing in the northern and central areas of the province.

Insights into parasites and COVID-19 co-infections in Iran: a systematic review.

BACKGROUND: It is well-documented that using immunosuppressive drugs such as corticosteroids or cytokine blockers in treating coronavirus disease 2019 (COVID-19) increases the risk of co-infections. Here we systematically summarized the cases of COVID-19-associated parasitic infections (CAPIs) in Iran. METHODS: From 19 February 2020 to 10 May 2023, all studies on Iranian patients suffering from CAPIs were collected from several databases using a systematic search strategy. RESULTS: Of 540 records, 11 studies remained for data extraction. In this research, most of the studies were related to Lophomonas and Toxoplasma. Of 411 cases of CAPIs, toxoplasmosis (385 [93.7%]) had the highest rate of infection among Iranian patients, followed by blastocystosis (15 [3.6%]), fascioliasis (4 [0.97%]), leishmaniasis (3 [0.7%]), lophomoniasis (3 [0.7%]) and strongyloidiasis (1 [0.2%]). In general, Blastocystis enhanced diarrhoea in patients with COVID-19. Lophomonas, Toxoplasma and Strongyloides increased the severity of COVID-19, but Fasciola decreased its intensity. Patients with a history of cutaneous leishmaniasis showed mild symptoms of COVID-19. Also, patients with a prior history of hydatid cysts were not affected by COVID-19. CONCLUSIONS: Due to the similar symptoms of some parasitic diseases and COVID-19 and immunosuppressive treatment regimens in these patients that may cause the reactivation or recurrence of parasitic infections, early diagnosis and treatment are required.

CliqueFluxNet: Unveiling EHR Insights with Stochastic Edge Fluxing and Maximal Clique Utilisation Using Graph Neural Networks.

Electronic Health Records (EHRs) play a crucial role in shaping predictive are models, yet they encounter challenges such as significant data gaps and class imbalances. Traditional Graph Neural Network (GNN) approaches have limitations in fully leveraging neighbourhood data or demanding intensive computational requirements for regularisation. To address this challenge, we introduce CliqueFluxNet, a novel framework that innovatively constructs a patient similarity graph to maximise cliques, thereby highlighting strong inter-patient connections. At the heart of CliqueFluxNet lies its stochastic edge fluxing strategy - a dynamic process involving random edge addition and removal during training. This strategy aims to enhance the model's generalisability and mitigate overfitting. Our empirical analysis, conducted on MIMIC-III and eICU datasets, focuses on the tasks of mortality and readmission prediction. It demonstrates significant progress in representation learning, particularly in scenarios with limited data availability. Qualitative assessments further underscore CliqueFluxNet's effectiveness in extracting meaningful EHR representations, solidifying its potential for advancing GNN applications in healthcare analytics.

Toxoplasmosis diagnostic techniques: Current developed methods and biosensors.

Toxoplasma gondii infection is a usual worldwide issue since a broad range of vertebrate hosts are infected by this famous parasite. However fetuses and immuno-compromised patients infected by parasite is of specific concern. Developing the easy-to-use, accurate, real time and selective methods for detection of toxoplasma infection has a key role in the treatment and management of patients. In this regard, rapid detection methods with reproducible outcomes during short period are highly interested. In this review, we discussed the recent developed molecular-based laboratory methods for detecting of Toxoplasma infection and also rapid diagnostic methods, especially optic and electrochemical based biosensors with point-of-care features.

Learning Graph Representations With Maximal Cliques.

Non-Euclidean property of graph structures has faced interesting challenges when deep learning methods are applied. Graph convolutional networks (GCNs) can be regarded as one of the successful approaches to classification tasks on graph data, although the structure of this approach limits its performance. In this work, a novel representation learning approach is introduced based on spectral convolutions on graph-structured data in a semisupervised learning setting. Our proposed method, COnvOlving cLiques (COOL), is constructed as a neighborhood aggregation approach for learning node representations using established GCN architectures. This approach relies on aggregating local information by finding maximal cliques. Unlike the existing graph neural networks which follow a traditional neighborhood averaging scheme, COOL allows for aggregation of densely connected neighboring nodes of potentially differing locality. This leads to substantial improvements on multiple transductive node classification tasks.

Major depressive disorder: Biomarkers and biosensors.

Depressive disorders belong to highly heterogeneous psychiatric diseases. Loss of in interest in previously enjoyed activities and a depressed mood are the main characteristics of major depressive disorder (MDD). Moreover, due to significant heterogeneity in clinical presentation and lack of applicable biomarkers, diagnosis and treatment remains challenging. Identification of relevant biomarkers would allow for improved disease classification and more personalized treatment strategies. Herein, we review the current state of these biomarkers and then discuss diagnostic techniques of aimed to specifically target these analytes using state of the art biosensor technology.

The role of genetics and gender specific differences in neurodegenerative disorders: Insights from molecular and immune landscape.

Neurodegenerative disorders (NDDs) are the most common neurological disorders with high prevalence and have significant socioeconomic implications. Understanding the underlying cellular and molecular mechanisms associated with the immune system can be effective in disease etiology, leading to more effective therapeutic approaches for both females and males. The central nervous system (CNS) actively participates in immune responses, both within and outside the CNS. Immune system activation is a common feature in NDDs. Gender-specific factors play a significant role in the prevalence, progression, and manifestation of NDDs. Neuroinflammation, in both inflammatory neurological and neurodegenerative conditions, is defined by the triggering of microglia and astrocyte cell activation. This results in the secretion of pro-inflammatory cytokines and chemokines. Numerous studies have documented the role of neuroinflammation in neurological diseases, highlighting the involvement of immune signaling pathways in disease development. Converging evidence support immune system involvement during neurodegeneration in NDDs. In this review, we summarize emerging evidence that reveals gender-dependent differences in immune responses related to NDDs. Also, we highlight sex differences in immune responses and discuss how these sex-specific influences can increase the risk of NDDs. Understanding the role of gender-specific factors can aid in developing targeted therapeutic strategies and improving patient outcomes. Ultimately, the better understanding of these mechanisms contributed to sex-dependent immune response in NDDs, can be critically usful in targeting of immune signaling cascades in such disorders. In this regard, sex-related immune responses in NDDs may be promising and effective targets in therapeutic strategies.

One-pot synthesis of polyhydroquinoline-1,2,3-triazole hybrids in deep eutectic solvent as anti-leishmanial agents and molecular modeling studies.

The novel hybrids with 1,2,3-triazole and polyhydroquinoline scaffolds were successfully synthesized by multicomponent reaction of propargyloxybenzaldehyde, 1,3-cyclohexadione, ethylacetoacetate and ammonium acetate followed through click reaction in the presence of deep eutectic solvent ChCl/ZnCl2 as an efficient catalyst. Their anti-leishmanial activity was evaluated against amastigote and promastigote forms of L. tropica, L. major, and two different species of L. infantum. Furthermore, to determine the cytotoxicity of the hybrids, they were evaluated against the murine macrophage cell line J774.A1. Based on the results, three hybrids showed the highest antileishmanial activity. However, they revealed low cytotoxicity. Hybrid 6j was the most potent compound against both the forms of all leishmanial types, with IC50 = 13.5 and 11.9 µg/mL for L. major, 37.5 and 25 µg/mL for L. tropica, 17.5 and 20 µg/mL for L. infantum (MCAN/IR//96/LON49) and 35.5 and 30 µg/mL for L. infantum (MCAN/ES/98/LIM-877), respectively. Finally, molecular docking and molecular dynamics simulations were also performed to identify possible mechanism antileishmanial activity.Communicated by Ramaswamy H. Sarma.

DyVGRNN: DYnamic mixture Variational Graph Recurrent Neural Networks.

Although graph representation learning has been studied extensively in static graph settings, dynamic graphs are less investigated in this context. This paper proposes a novel integrated variational framework called DYnamic mixture Variational Graph Recurrent Neural Networks (DyVGRNN), which consists of extra latent random variables in structural and temporal modelling. Our proposed framework comprises an integration of Variational Graph Auto-Encoder (VGAE) and Graph Recurrent Neural Network (GRNN) by exploiting a novel attention mechanism. The Gaussian Mixture Model (GMM) and the VGAE framework are combined in DyVGRNN to model the multimodal nature of data, which enhances performance. To consider the significance of time steps, our proposed method incorporates an attention-based module. The experimental results demonstrate that our method greatly outperforms state-of-the-art dynamic graph representation learning methods in terms of link prediction and clustering.2.

Berberine improves inhibitory avoidance memory impairment of Toxoplasma gondii-infected rat model of ketamine-induced schizophrenia.

BACKGROUND: Memory impairment caused by Toxoplasma gondii infection has been documented. Berberine (BRB) is well known for its enhancing effects on memory and has shown promising results. However, the impact of BRB on T. gondii infection and schizophrenia-induced consolidation and reconsolidation memory impairment is still unclear. Here; we examined the effect of BRB on the inhibitory avoidance (IA) memory consolidation and reconsolidation impairment induced by T. gondii infection, and ketamine (Ket) as a pharmacological model of schizophrenia. Also; the brain-derived neurotrophic factor (BDNF) levels in the medial prefrontal cortex (mPFC) and hippocampus were analyzed. METHODS: Rats were infected with T. gondii RH strain or received Ket (30 mg/kg/day) intraperitoneally (i.p) for at least five consecutive days (as the model of schizophrenia). Then followed by oral administration with BRB (25 mg/kg/day) for five days. Finally, the IA memory retention test was examined 48 post-conditioning, and BDNF was measured. RESULTS: Results indicated IA memory impairment in T. gondii-infected animals since lower step-through latency (STL) was observed than in control animals. We found significant (P = 0.01, P = 0.001) elevations in STL and a significant decrease (P = 0.001) in total time spent in the dark area following BRB administration in infected and Ket-treated rats, indicating improvement (increased STL) in consolidation and reconsolidation memory. Moreover, BDNF levels were reduced (P = 0.01) in the hippocampus and mPFC regions of both T. gondii- infected and Ket-induced groups, which remarkably enhanced after BRB treatment. Furthermore; we found that BRB administration notably increased the mPFC BDNF levels in mPFC (P < 0.01) and hippocampus (P = 0.001) in the Ket-treated and rats infected with T. gondii. CONCLUSION: Taken together; BRB may be a valuable preclinical treatment for improving memory impairment through BDNF expression in PFC and hippocampus, therefore; BRB is suggested for memory disturbances induced by T. gondii infection.

In vitro Evaluation of the Potent Antileishmanial Activity of Ferula tabasensis Alone or in Combination with Shark Cartilage Extract Against the Standard Iranian Strain of Leishmania major (MRHO/IR/75/ER).

Background: The available drugs for the treatment of leishmaniasis are highly toxic and extremely expensive, with low efficiency; therefore, the development of effective therapeutic compounds is essential. Objectives: The present study aimed to explore the antileishmanial effects of ethyl acetate extract, methanol extract, and fractions 1-4 (F1-F4) of Ferula tabasensis, alone or in combination with shark cartilage extract (ShCE), on L. major in vitro. Methods: In this study, ethyl acetate, methanol, and n-hexane extracts were extracted from the aerial roots of F. tabasensis by the maceration method. The silica gel column chromatography was used to separate n-hexane extracts at varying polarities (F1-F4 fractions). Subsequently, the effects of extracts and fractions against promastigotes were assessed by the parasite counting method microscopic inhibition test and MTT assay. Besides, their effects on the infected macrophage cells and the number of amastigotes were investigated. Cytotoxicity was evaluated in non-infected J774A.1 macrophage cells. Finally, apoptosis induction of promastigotes, including infected and non-infected macrophages, was evaluated. Results: The results indicated the highly potent activity of F. tabasensis extracts and F1-F4 fractions, alone or in combination with ShCE, against L. major promastigotes and amastigotes in a dose-dependent manner (P < 0.05). The F1 fraction and methanol extract showed markedly higher toxicity compared to the other extracts and fractions, with 50% inhibitory concentrations (IC50/72h) of 2.4 ± 0.29 and 2.9 ± 0.55 µg/mL against promastigotes and 1.79 ± 0.27 µg/mL and 1.39 ± 0.27 µg/mL against amastigotes (P < 0.001). Moreover, they had a high selectivity index (SI) due to the low toxicity of macrophages (P < 0.0001). The results of flow cytometry indicated that the percentages of apoptotic promastigote cells in contact with IC50 concentrations of F1 and methanol extract alone after 72 h were 43.83 and 43.93%, as well as 78.4%, and 65.45% for their combination with ShCE, respectively.Also, apoptosis of infected macrophages induced by F1 and methanol extracts was estimated at 68.5% and 83.7%, respectively. Conclusions: In this study, the F1 fraction and methanol extract of F. tabasensis showed potent efficacy against L. major, associated with low toxicity and apoptosis induction. Therefore, they can be promising therapeutic candidates in future animal and even human studies.

The impact of COVID-19 on diagnostic biomarkers in neuropsychiatric and neuroimmunological diseases: a review.

Coronavirus disease 2019 (COVID-19) is an infectious respiratory disease, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Evidence-based emerging reports of neurological manifestations show that SARS-CoV-2 can attack the nervous system. However, little is known about the biomarkers in disease in neuropsychiatric and neuroimmunological disorders. One of the important keys in the management of COVID-19 is an accurate diagnosis. Biomarkers could provide valuable information in the early detection of disease etiology, diagnosis, further treatment, and prognosis. Moreover, ongoing investigations on hematologic, biochemical, and immunologic biomarkers in nonsevere, severe, or fatal forms of COVID-19 patients provide an urgent need for the identification of clinical and laboratory predictors. In addition, several cytokines acting through mechanisms to emerge immune response against SARS-CoV-2 infection are known to play a major role in neuroinflammation. Considering the neuroinvasive potential of SARS-CoV-2, which can be capable of triggering a cytokine storm, the current evidence on inflammation in psychiatry and neurodegenerative by emerging neuroinflammation is discussed in this review. We also highlighted the hematologic, biochemical, and immunologic biomarkers in COVID-19 diagnosis. COVID-19 prognostic biomarkers in patients with neuropsychiatric and neuroimmunological diseases are also explained.

Can anti-parasitic drugs help control COVID-19?

Novel COVID-19 is a public health emergency that poses a serious threat to people worldwide. Given the virus spreading so quickly, novel antiviral medications are desperately needed. Repurposing existing drugs is the first strategy. Anti-parasitic drugs were among the first to be considered as a potential treatment option for this disease. Even though many papers have discussed the efficacy of various anti-parasitic drugs in treating COVID-19 separately, so far, no single study comprehensively discussed these drugs. This study reviews some anti-parasitic recommended drugs to treat COVID-19, in terms of function and in vitro as well as clinical results. Finally, we briefly review the advanced techniques, such as artificial intelligence, that have been used to find effective drugs for the treatment of COVID-19.

Seroprevalence of Human Toxocariasis in Children (5-15-Year-Old) Using ELISA Method in Ardabil District, North-West of Iran.

Background: Toxocariasis is a worldwide-distributed helminth parasitic infection. This study aimed to evaluate the seroprevalence of human toxocariasis in children living in Ardabil Province, North-West of Iran. Methods: A seroepidemiological study to evaluate human toxocariasis among urban and rural populations of Ardabil County, North-West of Iran using ELISA test was carried out from 2019 to 2020. The study population was 472 children (185 females and 287 males) aged between 5 and 15 yr old. Immunoglobulin G antibodies against Toxocara spp. were analyzed by ELISA test. Results: Of the 472 collected serum samples, 66 (14.0%) were positive for antibodies against human toxocariasis. The highest prevalence of infection was observed in children with age groups of 5-6 years. Data demonstrate higher seroprevalence among males (15.3%) than females (11.8%). Rural areas prevalence was significantly higher (24.4%) than the urban area (8.65%). The rate of the diseases was 22.8% in children having history of contact with dog. Conclusion: Toxocariasis is prevalent in the children of Ardabil region. The present study can increase the awareness of the population about the risk of zoonotic diseases as well as the anthelmintic treatment of dogs by veterinarians and, more importantly, the control of stray dogs.

Visceral Leishmaniasis in Ardabil Province, Northwest of Iran: A Retrospective Epidemiological, Clinical and Paraclinical Study (1985-2018).

Background: We aimed to investigate the epidemiological, clinical and paraclinical aspects of Visceral Leishmaniasis in Ardabil Province, from 1986 to 2018. Methods: The disease has been diagnosed by a serological validate test as Direct Agglutination Test, parasitological methods, and clinical manifestations. The data were collected and then analyzed. Results: Overall, 2824 out of 69007cases (4.1%) had anti-Leishmania antibodies at titers≥1:3200. The majority of VL cases belonged to Meshkin-Shahr, and then Germi County. The percentages of both male and female cases were 52.8 % and 46.6%, respectively. Approximately 78.1% of cases were less than 5 yr old. The high incidence rate of the disease was recorded in the years 1987 and 2003. 48.6%, 3.2%, and 1.9% of the patients had low titer (1:3200), high titer (1:102400), and suspicious titer (1:1600), respectively. Out of 1200 bone marrow aspiration, 23% were positive, and 77% were negative. Fever, paleness, and hepatosplenomegaly were the main symptoms in patients. Moreover, abdominal swelling, edema, weight loss, lymphadenopathy and jaundice were some other symptoms in the patients. Among biochemistry factors, the levels of aspartate aminotransferase, alanine aminotransferase, lactate dehydrogenase, triglyceride and cholesterol have been increased. The death rate was estimated to be 2.8%, mainly related to the Ardabil and Germi cases. Conclusion: Kala-Azar is still one of the most important infectious diseases in Ardabil Province, and is responsible for considerable death rate in infants. More attention should be done to parasite control and early diagnosis.

Synergistic Anti-Leishmanial Activities of Morphine and Imiquimod on Leishmania infantum (MCAN/ES/98/LIM-877).

BACKGROUND: This study was performed to evaluate in vitro and in vivo Leishmanicidal potential of morphine (Mph), imiquimod (IQ), and their combination. METHODS: Leishmania infantum promastigote and amastigote assays were performed at the presence of 0.015-150µM Mph, 0.04-416µM IQ, and their combination. The inhibition effects of these drugs on promastigotes were evaluated after 24, 48, and 72h. The cytotoxic effects of the drugs were evaluated by MTT as well as flow cytometry after 72h. We explored the therapeutic effects of Mph and IQ in BALB/c mice at the end of the treatment using parasite load determination and cytokine assay. One group of mice received Mph for three weeks before infection. RESULTS: The results of promastigote and amastigote assays showed the cytotoxic effects of the drugs at low concentrations. The cytotoxic effects were higher on promastigotes than amastigotes (p< 0.05). There was a negative correlation between drug concentration and amastigote/promastigote viability. Imiquimod alone or combined with Mph showed remarkable cytotoxic effects at all concentrations (p< 0.05). Flow cytometry results revealed apoptosis in the parasite following exposure to the drug combinations. Accordingly, the reduction of parasite loads in the spleen and liver was observed (p< 0.05) with simultaneous increases in IFN-γ and IL-4. We believe that the in vivo leishmanicidal effect was mediated by Mph through IL-4 and by IQ through both IL-4 and IFN-γ. CONCLUSION: Results pointed out the promising effects of Mph and IQ at low concentrations, especially when combined.