Advancing brain tumor detection: harnessing the Swin Transformer's power for accurate classification and performance analysis.

The accurate detection of brain tumors through medical imaging is paramount for precise diagnoses and effective treatment strategies. In this study, we introduce an innovative and robust methodology that capitalizes on the transformative potential of the Swin Transformer architecture for meticulous brain tumor image classification. Our approach handles the classification of brain tumors across four distinct categories: glioma, meningioma, non-tumor, and pituitary, leveraging a dataset comprising 2,870 images. Employing the Swin Transformer architecture, our method intricately integrates a multifaceted pipeline encompassing sophisticated preprocessing, intricate feature extraction mechanisms, and a highly nuanced classification framework. Utilizing 21 matrices for performance evaluation across all four classes, these matrices provide a detailed insight into the model's behavior throughout the learning process, furthermore showcasing a graphical representation of confusion matrix, training and validation loss and accuracy. The standout performance parameter, accuracy, stands at an impressive 97%. This achievement outperforms established models like CNN, DCNN, ViT, and their variants in brain tumor classification. Our methodology's robustness and exceptional accuracy showcase its potential as a pioneering model in this domain, promising substantial advancements in accurate tumor identification and classification, thereby contributing significantly to the landscape of medical image analysis.

Enhanced Regularized Ensemble Encoderdecoder Network for Accurate Brain Tumor Segmentation.

BACKGROUND: Segmenting tumors in MRI scans is a difficult and time-consuming task for radiologists. This is because tumors come in different shapes, sizes, and textures, making them hard to identify visually. OBJECTIVE: This study proposes a new method called the enhanced regularized ensemble encoder-decoder network (EREEDN) for more accurate brain tumor segmentation. METHODS: The EREEDN model first preprocesses the MRI data by normalizing the intensity levels. It then uses a series of autoencoder networks to segment the tumor. These autoencoder networks are trained using back-propagation and gradient descent. To prevent overfitting, the EREEDN model also uses L2 regularization and dropout mechanisms. RESULTS: The EREEDN model was evaluated on the BraTS 2020 dataset. It achieved high performance on various metrics, including accuracy, sensitivity, specificity, and dice coefficient score. The EREEDN model outperformed other methods on the BraTS 2020 dataset. CONCLUSION: The EREEDN model is a promising new method for brain tumor segmentation. It is more accurate and efficient than previous methods. Future studies will focus on improving the performance of the EREEDN model on complex tumors.

Next-Gen brain tumor classification: pioneering with deep learning and fine-tuned conditional generative adversarial networks.

Brain tumor has become one of the fatal causes of death worldwide in recent years, affecting many individuals annually and resulting in loss of lives. Brain tumors are characterized by the abnormal or irregular growth of brain tissues that can spread to nearby tissues and eventually throughout the brain. Although several traditional machine learning and deep learning techniques have been developed for detecting and classifying brain tumors, they do not always provide an accurate and timely diagnosis. This study proposes a conditional generative adversarial network (CGAN) that leverages the fine-tuning of a convolutional neural network (CNN) to achieve more precise detection of brain tumors. The CGAN comprises two parts, a generator and a discriminator, whose outputs are used as inputs for fine-tuning the CNN model. The publicly available dataset of brain tumor MRI images on Kaggle was used to conduct experiments for Datasets 1 and 2. Statistical values such as precision, specificity, sensitivity, F1-score, and accuracy were used to evaluate the results. Compared to existing techniques, our proposed CGAN model achieved an accuracy value of 0.93 for Dataset 1 and 0.97 for Dataset 2.

Advancing Brain Tumor Classification through Fine-Tuned Vision Transformers: A Comparative Study of Pre-Trained Models.

This paper presents a comprehensive study on the classification of brain tumor images using five pre-trained vision transformer (ViT) models, namely R50-ViT-l16, ViT-l16, ViT-l32, ViT-b16, and ViT-b32, employing a fine-tuning approach. The objective of this study is to advance the state-of-the-art in brain tumor classification by harnessing the power of these advanced models. The dataset utilized for experimentation consists of a total of 4855 images in the training set and 857 images in the testing set, encompassing four distinct tumor classes. The performance evaluation of each model is conducted through an extensive analysis encompassing precision, recall, F1-score, accuracy, and confusion matrix metrics. Among the models assessed, ViT-b32 demonstrates exceptional performance, achieving a high accuracy of 98.24% in accurately classifying brain tumor images. Notably, the obtained results outperform existing methodologies, showcasing the efficacy of the proposed approach. The contributions of this research extend beyond conventional methods, as it not only employs cutting-edge ViT models but also surpasses the performance of existing approaches for brain tumor image classification. This study not only demonstrates the potential of ViT models in medical image analysis but also provides a benchmark for future research in the field of brain tumor classification.

Brain Tumor Detection and Classification Using Fine-Tuned CNN with ResNet50 and U-Net Model: A Study on TCGA-LGG and TCIA Dataset for MRI Applications.

Nowadays, brain tumors have become a leading cause of mortality worldwide. The brain cells in the tumor grow abnormally and badly affect the surrounding brain cells. These cells could be either cancerous or non-cancerous types, and their symptoms can vary depending on their location, size, and type. Due to its complex and varying structure, detecting and classifying the brain tumor accurately at the initial stages to avoid maximum death loss is challenging. This research proposes an improved fine-tuned model based on CNN with ResNet50 and U-Net to solve this problem. This model works on the publicly available dataset known as TCGA-LGG and TCIA. The dataset consists of 120 patients. The proposed CNN and fine-tuned ResNet50 model are used to detect and classify the tumor or no-tumor images. Furthermore, the U-Net model is integrated for the segmentation of the tumor regions correctly. The model performance evaluation metrics are accuracy, intersection over union, dice similarity coefficient, and similarity index. The results from fine-tuned ResNet50 model are IoU: 0.91, DSC: 0.95, SI: 0.95. In contrast, U-Net with ResNet50 outperforms all other models and correctly classified and segmented the tumor region.

Prevalence and Determinants Influencing the Use of Electronic Cigarette Smoking in Male Students of Taif University.

BACKGROUND AND AIM: Electronic cigarette (e-cigarette) smoking is a significant public health problem in Saudi Arabia, particularly among youth who use it as an alternative to traditional cigarettes. This study aimed to evaluate the prevalence and beliefs towards e-cigarette use among Taif University students in Saudi Arabia. METHODS: A cross-sectional study was conducted among male Taif University students using a self-administered questionnaire. A sample of 319 students was selected through stratified sampling. The questionnaire included questions about socio-demographic characteristics, smoking history, awareness of e-cigarettes, prevalence of e-cigarette use, beliefs towards e-cigarettes, and reasons for e-cigarette use. RESULTS: The study revealed a high prevalence of e-cigarette use among Taif University students, with 40.1% of participants having used e-cigarettes at least once during their lifetime and 43.7% believing that e-cigarettes are less dangerous than traditional cigarettes. Participants studying sciences had 0.76 times the odds of believing that e-cigarettes help smokers to quit compared to participants studying literature. Compared to smokers, ex-smokers had an OR of 34.1 (p<0.001) and non-smokers had an OR of 35.9 (p<0.001) for experimentation of e-cigarettes. Smokers who had friends that tried e-cigarettes had an OR of 6.6 (p<0.001) for trying e-cigarettes, compared to smokers who did not have such friends. CONCLUSION: The study found that 40.1% of participants have used e-cigarettes at least once during their lifetime with a significant proportion of participants unaware of the potential health hazards of e-cigarettes, and many believed that e-cigarettes are less dangerous than traditional cigarettes. These findings emphasize the need for targeted educational interventions to address misconceptions and promote awareness among university students.

Exploring the Power of Deep Learning: Fine-Tuned Vision Transformer for Accurate and Efficient Brain Tumor Detection in MRI Scans.

A brain tumor is a significant health concern that directly or indirectly affects thousands of people worldwide. The early and accurate detection of brain tumors is vital to the successful treatment of brain tumors and the improved quality of life of the patient. There are several imaging techniques used for brain tumor detection. Among these techniques, the most common are MRI and CT scans. To overcome the limitations associated with these traditional techniques, computer-aided analysis of brain images has gained attention in recent years as a promising approach for accurate and reliable brain tumor detection. In this study, we proposed a fine-tuned vision transformer model that uses advanced image processing and deep learning techniques to accurately identify the presence of brain tumors in the input data images. The proposed model FT-ViT involves several stages, including the processing of data, patch processing, concatenation, feature selection and learning, and fine tuning. Upon training the model on the CE-MRI dataset containing 5712 brain tumor images, the model could accurately identify the tumors. The FT-Vit model achieved an accuracy of 98.13%. The proposed method offers high accuracy and can significantly reduce the workload of radiologists, making it a practical approach in medical science. However, further research can be conducted to diagnose more complex and rare types of tumors with more accuracy and reliability.

Incidence and Risk Factors of Infections Among Diffuse Large B-cell Lymphoma and Classical Hodgkin's Lymphoma Patients in a Tertiary Care Center in Saudi Arabia: A Retrospective Cohort Study.

INTRODUCTION:  Non-Hodgkin's lymphoma (NHL) ranked fourth among all cancer types in Saudi Arabia, as reported by the Saudi Health Council in 2015. Diffuse large B-cell lymphoma (DLBCL) is the most common histological type of NHL. On the other hand, classical Hodgkin's lymphoma (cHL) ranked sixth and had a modest tendency to affect young men more frequently. Over recent decades, DLBCL patients were treated with cyclophosphamide, doxorubicin hydrochloride, oncovin, and prednisolone (CHOP) alone. Adding rituximab (R) to the standard regimen (CHOP) shows significant improvement in overall survival. However, it also has a considerable effect on the immune system, impacting complement-mediated and antibody-dependent cellular cytotoxicity and causing an immunosuppressive state through modulating T-cell immunity via neutropenia, which can let the infection spread. AIMS AND OBJECTIVES:  This study aims to evaluate the incidence and risk factors associated with infections in DLBCL patients in comparison to patients with cHL treated with doxorubicin hydrochloride (Adriamycin), bleomycin sulfate, vinblastine sulfate, and dacarbazine (ABVD). MATERIALS AND METHODS:  This study is a retrospective case-control study that included 201 patients acquired between January 1st, 2010, and January 1st, 2020. Sixty-seven patients had a diagnosis of cHL and had received ABVD, and 134 had DLBCL and had received rituximab. Clinical data were obtained from the medical records. RESULTS:  During the study period, we enrolled 201 patients, of whom 67 had cHL, and 134 had DLBCL. DLBCL patients had a higher serum lactate dehydrogenase upon diagnosis than cHL (p = 0.005). Both groups have similar response rates with complete remission/partial remission. Compared to cHL, patients with DLBCL were more likely to have advanced disease when they first presented (stage III/IV, DLBCL: 67.3 vs. cHL: 56.5; p = 0.005). DLBCL patients had an increased risk of infection as compared to cHL patients (DLBCL: 32.1 % vs. 16.4%; p = 0.02). However, patients with a poor response to treatment had an increased risk of infection compared to patients with a favorable response regardless of the type of disease (odds ratio: 4.6; p = <0.001). When using multivariate analysis, it is revealed that unfavorable therapeutic response continues to be the only predictor raising the probability of infection in the population (odds ratio: 4.2; p = 0.003). CONCLUSIONS:  Our study explored all potential risk factors for the occurrence of infection in DLBCL patients who received R-CHOP versus cHL. The most reliable predictor of an increased risk of infection during the follow-up period was having an unfavorable response to medication. To assess these results, additional prospective research is required.

Prevalence of Ocular Hypertension and Other Risk Factors of Open-Angle Glaucoma Among Middle-Aged Adults in Al-Baha City, Saudi Arabia.

Background Ocular hypertension (OHT), defined by elevated intraocular pressure (IOP) beyond standard levels, is a predominant risk factor for initiating and exacerbating glaucoma, a collection of progressive optic neuropathies responsible for irreversible vision loss. Given the profound implications for vision care, it is imperative to elucidate the interplay between OHT and glaucoma for effective clinical management. Objective The present study aims to measure IOP levels and identify risk factors associated with glaucoma among middle-aged individuals in Al-Baha City, Saudi Arabia. Methods A cross-sectional study was conducted over a six-month span (January-June 2022) in Al-Baha City. The study cohort comprised adults aged 35 and above attending a glaucoma awareness campaign at King Fahad Hospital, Al-Baha. Parameters such as demographics, socioeconomic status, medical and ocular history, and familial history of eye diseases were collated. Initial ophthalmologic assessments and IOP measurements were performed. Statistical analyses utilized Pearson's Chi-square test for nominal variables. Results The study encompassed 111 participants, 84 (75.7%) of whom were male, and 75 (67.6%) were of Saudi nationality. Notably, 102 (91.9%) reported no family history of glaucoma, 91 (81.1%) indicated no past medical history and 81 (73.0%) were not on any chronic medications. The mean IOP for participants' right and left eyes fluctuated between 18.2-21.5 mmHg and 18.9-22.1 mmHg, respectively. Factors such as age, gender, family history of glaucoma, past medical history, use of chronic medications, and history of ophthalmic surgeries demonstrated a statistically significant correlation with IOP (p<0.05). Conclusion This study highlights a higher prevalence of OHT in females, with several risk factors for OHT and glaucoma identified, such as familial history, vascular diseases, diabetes mellitus, and chronic medication use. Notably, our study did not observe a significant association with age or smoking. These findings emphasize the necessity of regular eye examinations and IOP monitoring, especially in high-risk groups.

Impact of COVID-19 Pandemic Lockdown on the Prognosis, Morbidity, and Mortality of Patients Undergoing Elective and Emergency Abdominal Surgery: A Retrospective Cohort Study in a Tertiary Center, Saudi Arabia.

The SARS-CoV-2 pandemic's main concerns are limiting the spread of infectious diseases and upgrading the delivery of health services, infrastructure, and therapeutic provision. The goal of this retrospective cohort study was to evaluate the emergency experience and delay of elective abdominal surgical intervention at King Abdul-Aziz University Hospital from October 2019 to October 2020, with a focus on post-operative morbidity and mortality before and during the COVID-19 pandemic. This study compares two groups of patients with emergent and elective abdominal surgical procedures between two different periods; the population was divided into two groups: the control group, which included 403 surgical patients, and the lockdown group, which included 253 surgical patients. During the lockdown, surgical activity was reduced by 37.2% (p = 0.014), and patients were more likely to require reoperations and blood transfusions during or after surgery (p= 0.002, 0.021, and 0.018, respectively). During the lockdown period, the average length of stay increased from 3.43 to 5.83 days (p = 0.002), and the patients who developed complications (53.9%) were more than those in the control period (46.1%) (p = 0.001). Our tertiary teaching hospital observed a significant decline in the overall number of surgeries performed during the COVID-19 pandemic and lockdown period. During the lockdown, abdominal surgery was performed only on four patients; they were positive for COVID-19. Three of them underwent exploratory laparotomy; two of the three developed shock post-operative; one patient had colon cancer (ASA score 3), one had colon disease (ASA score 2), and two had perforated bowels (ASA scores 2 and 4, respectively). Two out of four deaths occurred after surgery. Our results showed the impact of the COVID-19 lockdown on surgical care as both 30-day mortality and total morbidity have risen considerably.

Modulatory effect of dietary probiotic and prebiotic supplementation on growth, immuno-biochemical alterations, DNA damage, and pathological changes in E. coli-infected broiler chicks.

Avian pathogenic Escherichia coli is one of the principal causes of heavy economic losses to the poultry industry. Little is known about the underlying mechanisms, particularly the potential role of immunoglobulin A and the DNA damage, involving the beneficial effects of dietary supplementation of probiotics and prebiotics in avian colibacillosis. The current study investigated the potential effects of probiotic and prebiotic dietary supplementation on E. coli-infected broiler chicks. A total of 120 1-day-old unsexed Hubbard chicks were divided into six groups: Group 1 was considered as a negative control; Group 2 was supplemented with 1 g/kg feed of Lactobacillus plantarum; Group 3 was supplemented with amylase enzyme; Group 4 served as a positive control infected orally by E. coli O78; Group 5 was supplemented with L. plantarum from 1-day-old chicken and then infected orally with E. coli O78; and Group 6 was supplemented with amylase enzyme from 1-day old chicken and then infected orally with E. coli O78. For all examined groups, the experimental period lasted for 42 days. The E. coli-infected group revealed a decrease in body performance parameters with a significant increase in the liver enzymes and renal function tests. The same group recorded a significant decrease in serum total proteins, albumins, and globulins, and the alteration of immunological parameters, antioxidant enzymes, oxidative stress parameters, and comet assay revealed highly damaged DNA in the liver and the intestine. By histopathological examination, a series of histopathological changes in the liver, the kidney, and the intestine were observed. The infected chick pretreated with probiotics or prebiotics demonstrated an improvement in body performance parameters besides a significant decrease in the hepatic enzymes and renal function tests. We noticed that, in treated groups, there was a significant increase in serum total proteins in the serum albumin and globulin levels, immunological parameters, and antioxidant enzymes. Furthermore, DNA damage and histopathological changes within hepatic, renal, and intestinal tissues were markedly diminished in the treated groups compared with the infected group. We concluded that the adverse effects of E. coli could be modulated through the chemopreventive administration of probiotics and prebiotics.

Tamoxifen Increased Parasite Burden and Induced a Series of Histopathological and Immunohistochemical Changes During Chronic Toxoplasmosis in Experimentally Infected Mice.

The global distribution of breast cancer and the opportunistic nature of the parasite have resulted in many patients with breast cancer becoming infected with toxoplasmosis. However, very limited information is available about the potential effects of tamoxifen on chronic toxoplasmosis and its contribution to the reactivation of the latent infection. The present study investigated the potential effects of tamoxifen on chronic toxoplasmosis in animal models (Swiss albino mice). Following induction of chronic toxoplasmosis and treatment with the drug for 14 and 28 days, the anti-parasitic effects of tamoxifen were evaluated by parasitological assessment and counting of Toxoplasma cysts. In addition, the effects of the drug on the parasite load were evaluated and quantitated using TaqMan real-time quantitative PCR followed by investigation of the major histopathological changes and immunohistochemical findings. Interestingly, tamoxifen increased the parasite burden on animals treated with the drug during 14 and 28 days as compared with the control group. The quantification of the DNA concentrations of Toxoplasma P29 gene after the treatment with the drug revealed a higher parasite load in both treated groups vs. control groups. Furthermore, treatment with tamoxifen induced a series of histopathological and immunohistochemical changes in the kidney, liver, brain, and uterus, revealing the exacerbating effect of tamoxifen against chronic toxoplasmosis. These changes were represented by the presence of multiple T. gondii tissue cysts in the lumen of proximal convoluted tubules associated with complete necrosis in their lining epithelium of the kidney section. Meanwhile, liver tissue revealed multiple T. gondii tissue cysts in hepatic parenchyma which altered the structure of hepatocytes. Moreover, clusters of intracellular tachyzoites were observed in the lining epithelium of endometrium associated with severe endometrial necrosis and appeared as diffuse nuclear pyknosis combined with sever mononuclear cellular infiltration. Brain tissues experienced the presence of hemorrhages in pia mater and multiple T. gondii tissue cysts in brain tissue. The severity of the lesions was maximized by increasing the duration of treatment. Collectively, the study concluded novel findings in relation to the potential role of tamoxifen during chronic toxoplasmosis. These findings are very important for combating the disease, particularly in immunocompromised patients which could be life-threatening.

Multi-target potential of Indian phytochemicals against SARS-CoV-2: A docking, molecular dynamics and MM-GBSA approach extended to Omicron B.1.1.529.

BACKGROUND: SARS-CoV-2, an emerged strain of corona virus family became almost serious health concern worldwide. Despite vaccines availability, reports suggest the occurrence of SARS-CoV-2 infection even in a vaccinated population. With frequent evolution and expected multiple COVID-19 waves, improved preventive, diagnostic, and treatment measures are required. In recent times, phytochemicals have gained attention due to their therapeutic characteristics and are suggested as alternative and complementary treatments for infectious diseases. This present study aimed to identify potential inhibitors against reported protein targets of SARS-CoV-2. METHODOLOGY: We computationally investigated potential SARS-CoV-2 protein targets from the literature and collected druggable phytochemicals from Indian Medicinal Plants, Phytochemistry and Therapeutics (IMPPAT) database. Further, we implemented a systematic workflow of molecular docking, dynamic simulations and generalized born surface area free-energy calculations (MM-GBSA). RESULTS: Extensive literature search and assessment of 1508 articles identifies 13 potential SARS-CoV-2 protein targets. We screened 501 druggable phytochemicals with proven biological activities. Analysis of 6513(501 *13) docked phytochemicals complex, 26 were efficient against SARS-CoV-2. Amongst, 4,8-dihydroxysesamin and arboreal from Gmelina arborea were ranked potential against most of the targets with binding energy ranging between - 10.7 to - 8.2 kcal/mol. Additionally, comparative docking with known drugs such as arbidol (-6.6 to -5.1 kcal/mol), favipiravir (-5.5 to -4.5 kcal/mol), hydroxychloroquine (-6.5 to -5.1 kcal/mol), and remedesivir (-8.0 to -5.3 kcal/mol) revealed equal/less affinity than 4,8-dihydroxysesamin and arboreal. Interestingly, the nucleocapsid target was found commonly inhibited by 4,8-dihydroxysesamin and arboreal. Molecular dynamic simulation and Molecular mechanics generalized born surface area (MM-GBSA)calculations reflect that both the compounds possess high inhibiting potential against SARS-CoV-2 including the recently emerged Omicron variant (B.1.1.529). CONCLUSION: Overall our study imparts the usage of phytochemicals as antiviral agents for SARS-CoV-2 infection. Additional in vitro and in vivo testing of these phytochemicals is required to confirm their potency.

Differences in Transporters Rather than Drug Targets Are the Principal Determinants of the Different Innate Sensitivities of Trypanosoma congolense and Trypanozoon Subgenus Trypanosomes to Diamidines and Melaminophenyl Arsenicals.

The animal trypanosomiases are infections in a wide range of (domesticated) animals with any species of African trypanosome, such as Trypanosoma brucei, T. evansi, T. congolense, T. equiperdum and T. vivax. Symptoms differ between host and infective species and stage of infection and are treated with a small set of decades-old trypanocides. A complication is that not all trypanosome species are equally sensitive to all drugs and the reasons are at best partially understood. Here, we investigate whether drug transporters, mostly identified in T. b. brucei, determine the different drug sensitivities. We report that homologues of the aminopurine transporter TbAT1 and the aquaporin TbAQP2 are absent in T. congolense, while their introduction greatly sensitises this species to diamidine (pentamidine, diminazene) and melaminophenyl (melarsomine) drugs. Accumulation of these drugs in the transgenic lines was much more rapid. T. congolense is also inherently less sensitive to suramin than T. brucei, despite accumulating it faster. Expression of a proposed suramin transporter, located in T. brucei lysosomes, in T. congolense, did not alter its suramin sensitivity. We conclude that for several of the most important classes of trypanocides the presence of specific transporters, rather than drug targets, is the determining factor of drug efficacy.

Antitrypanosomal and Antileishmanial Activity of Chalcones and Flavanones from Polygonum salicifolium.

Trypanosomiasis and leishmaniasis are a group of neglected parasitic diseases caused by several species of parasites belonging to the family Trypansomatida. The present study investigated the antitrypanosomal and antileishmanial activity of chalcones and flavanones from Polygonum salicifolium, which grows in the wetlands of Iraq. The phytochemical evaluation of the plant yielded two chalcones, 2',4'-dimethoxy-6'-hydroxychalcone and 2',5'-dimethoxy-4',6'-dihydroxychalcone, and two flavanones, 5,7-dimethoxyflavanone and 5,8-dimethoxy-7-hydroxyflavanone. The chalcones showed a good antitrypanosomal and antileishmanial activity while the flavanones were inactive. The EC50 values for 2',4'-dimethoxy-6'-hydroxychalcone against Trypanosoma brucei brucei (0.5 µg/mL), T. congolense (2.5 µg/mL), and Leishmania mexicana (5.2 µg/mL) indicated it was the most active of the compounds. None of the compounds displayed any toxicity against a human cell line, even at 100 µg/mL, or cross-resistance with first line clinical trypanocides, such as diamidines and melaminophenyl arsenicals. Taken together, our study provides significant data in relation to the activity of chalcones and flavanones from P. salicifolium against both parasites in vitro. Further future research is suggested in order to investigate the mode of action of the extracted chalcones against the parasites.

Positively selected modifications in the pore of TbAQP2 allow pentamidine to enter Trypanosoma brucei.

Mutations in the Trypanosoma brucei aquaporin AQP2 are associated with resistance to pentamidine and melarsoprol. We show that TbAQP2 but not TbAQP3 was positively selected for increased pore size from a common ancestor aquaporin. We demonstrate that TbAQP2's unique architecture permits pentamidine permeation through its central pore and show how specific mutations in highly conserved motifs affect drug permeation. Introduction of key TbAQP2 amino acids into TbAQP3 renders the latter permeable to pentamidine. Molecular dynamics demonstrates that permeation by dicationic pentamidine is energetically favourable in TbAQP2, driven by the membrane potential, although aquaporins are normally strictly impermeable for ionic species. We also identify the structural determinants that make pentamidine a permeant although most other diamidine drugs are excluded. Our results have wide-ranging implications for optimising antitrypanosomal drugs and averting cross-resistance. Moreover, these new insights in aquaporin permeation may allow the pharmacological exploitation of other members of this ubiquitous gene family.

African sleeping sickness is a potentially deadly illness caused by the parasite Trypanosoma brucei. The disease is treatable, but many of the current treatments are old and are becoming increasingly ineffective. For instance, resistance is growing against pentamidine, a drug used in the early stages in the disease, as well as against melarsoprol, which is deployed when the infection has progressed to the brain. Usually, cases resistant to pentamidine are also resistant to melarsoprol, but it is still unclear why, as the drugs are chemically unrelated. Studies have shown that changes in a water channel called aquaglyceroporin 2 (TbAQP2) contribute to drug resistance in African sleeping sickness; this suggests that it plays a role in allowing drugs to kill the parasite. This molecular 'drain pipe' extends through the surface of T. brucei, and should allow only water and a molecule called glycerol in and out of the cell. In particular, the channel should be too narrow to allow pentamidine or melarsoprol to pass through. One possibility is that, in T. brucei, the TbAQP2 channel is abnormally wide compared to other members of its family. Alternatively, pentamidine and melarsoprol may only bind to TbAQP2, and then 'hitch a ride' when the protein is taken into the parasite as part of the natural cycle of surface protein replacement. Alghamdi et al. aimed to tease out these hypotheses. Computer models of the structure of the protein were paired with engineered changes in the key areas of the channel to show that, in T. brucei, TbAQP2 provides a much broader gateway into the cell than observed for similar proteins. In addition, genetic analysis showed that this version of TbAQP2 has been actively selected for during the evolution process of T. brucei. This suggests that the parasite somehow benefits from this wider aquaglyceroporin variant. This is a new resistance mechanism, and it is possible that aquaglyceroporins are also larger than expected in other infectious microbes. The work by Alghamdi et al. therefore provides insight into how other germs may become resistant to drugs.

Cloning and functional complementation of ten Schistosoma mansoni phosphodiesterases expressed in the mammalian host stages.

Only a single drug against schistosomiasis is currently available and new drug development is urgently required but very few drug targets have been validated and characterised. However, regulatory systems including cyclic nucleotide metabolism are emerging as primary candidates for drug discovery. Here, we report the cloning of ten cyclic nucleotide phosphodiesterase (PDE) genes of S. mansoni, out of a total of 11 identified in its genome. We classify these PDEs by homology to human PDEs. Male worms displayed higher expression levels for all PDEs, in mature and juvenile worms, and schistosomula. Several functional complementation approaches were used to characterise these genes. We constructed a Trypanosoma brucei cell line in which expression of a cAMP-degrading PDE complements the deletion of TbrPDEB1/B2. Inhibitor screens of these cells expressing only either SmPDE4A, TbrPDEB1 or TbrPDEB2, identified highly potent inhibitors of the S. mansoni enzyme that elevated the cellular cAMP concentration. We further expressed most of the cloned SmPDEs in two pde1Δ/pde2Δ strains of Saccharomyces cerevisiae and some also in a specialised strain of Schizosacharomyces pombe. Five PDEs, SmPDE1, SmPDE4A, SmPDE8, SmPDE9A and SmPDE11 successfully complemented the S. cerevisiae strains, and SmPDE7var also complemented to a lesser degree, in liquid culture. SmPDE4A, SmPDE8 and SmPDE11 were further assessed in S. pombe for hydrolysis of cAMP and cGMP; SmPDE11 displayed considerable preferrence for cGMP over cAMP. These results and tools enable the pursuit of a rigorous drug discovery program based on inhibitors of S. mansoni PDEs.