Hasil untuk "Infectious and parasitic diseases"

G. T. Strickland

Part I CLINICAL PRACTICE in the TROPICS. General Principles. Pulmonary Diseases. Cardiovascular Diseases. Gastrointestinal Diseases. Hepatobiliary Diseases. Hematologic Diseases. Urinary Tract Diseases. Dermatologic Diseases. Neurologic Diseases. Opthalmolgic Diseases. Sexually Transmitted Diseases. Malignant Diseases. Surgery. Orthopedics. Maternal and Child Health. Integrated Management of Childhood Illness. Heat-Associated Illness. Traditional Medicine. Health and Nutrition Among. Refugees and Displaced Persons. Environmental and Occupational. Health in the Tropics. Imaging in the Tropics and The. Imaging of Tropical Diseases. Part II VIRAL INFECTIONS. General Principles. Human Immunodeficiency Virus. And AIDS. Human T Cell Lymphotropic Virus. Infections. Viral Infections with Cutaneous Lesions. Viral Respiratory Infections. Enteric Viral Infections. Viral Hepatitis. Viral Febrile Illnesses. Viral Encephalitis. Viral Hemorrhagic Fevers. PART III BACTERIAL INFECTIONS. Section a Infections of the Eye and Throat. Trachoma and Inclusion Conjunctivitis Diphtheria. Section B Respiratory Tract Infections. Q Fever. Psittacosis. Pertussis. Melioidosis. Actinomycoses. Nocardiosis. Section C Gastrointestinal Tract Infections. Shigellosis. Cholera and Other Vibrioses. Diarrhea Caused By Escherichia Coli. Campylobacter Enteritis. Miscellaneous Bacterial Enteritides. Helicobacter PyloriInfections. Section D Sexually Transmitted Infections. Chlamydial Infections. Lymphogranuloma Venereum. Syphilis and the Endemic Treponematoses. Gonococcal Infections. Chancroid. Granuloma Inguinale. Section E Infections Causing Neurological Manifestations. Acute Bacterial Meningitis. Tetanus. Botulism. Section F Infections of Skin and Soft Tissues. Anthrax. Glanders. Gas Gangrene. Pyomyositis. Tropical Phagedenic Ulcer. Section G Febrile Lymphadenitis. Bartonella-Associated Infections. Plague. Tularemia. Pasteurella. Brucellosis. Section H Disseminated Febrile Illnesses. Rickettsial Infections: General. Principles. Typhus. Spotted Fevers. Trench Fever. Scrub Typhus. Ehrlichiosis. Relapsing Fever. Leptospirosis. Lyme Disease. Meningococcal Disease. Typhoid Fever. Nontyphoidal Salmonellosis. Section I Mycobacterial Infections. Tuberculosis. Leprosy. Nontuberculosis Mycobacterial. Part IV the MYCOSES. General Principles. Superficial Mycoses. Subcutaneous Mycoses. Systemic Mycoses. Treatment of Systemic Mycoses. Part V PROTOZOAL INFECTIONS. General Principles. Section a Intestinal and Genital Infections. Amebiasis. Giardiasis. Cryptosporidiosis. Cyclosporiasis. Miscellaneous Intestinal Protozoa. Trichomoniasis. Section B Infections of the Blood and Reticuloendothelial System. Malaria. African Trypanosomiasis. American Trypanosomiasis. Leishmaniasis. Babesiosis. Section C Tissue Infections. Toxoplasmosis. Pneumocystosis. Free-Living Amebic Infections. OtherTissue Protozoa Infections. PART VI HELMINTHIC INFECTIONS. General Principles. Section a Intestinal Nematode Infections. General Principles. Nematodes Limited to the . Intestinal Tract. Intestinal Nematodes That. Migrate Through Lungs. Intestinal Nematodes That. Migrate Through Skin And. Lung. Section B Filarial Infections. Filariasis. Loiasis. Onchocerciasis. Miscellaneous Filarial Infections. Section C Other Tissue Nematode Infections. Dracunculiasis. Trichinosis. Toxocariasis. Gnathostomiasis. Angiostrongyliasis. Cutaneous Larva Migrans. Anisakiasis. Section D Trematode Infections. General Principles. Schistosomiasis. Intestinal Fluke Infections. Liver Fluke Infections. Lung Fluke Infections: Paragonimiasis. Section E Cestode Infections . General Principles. Tapeworm Infections. Larval Cestode Infections. PART VII POISONOUS and TOXIC PLANTS and ANIMALS. Poisonous Plants and Fish. Animals Hazardous to Humans. Pentastomiasis. Injurious Arthropods. PART VIII NUTRITIONAL PROBLEMS and DEFICIENCY DISEASES. General Principles. Protein-Energy Malnutrition. Vitamin Deficiencies. Mineral Deficiencies. Other Nutrition-Related Disorders. PART IX VECTOR TRANSMISSION of DISEASES. General Principles of Infectious . Disease Transmission. Zoonoses. Mollusks Involved in Disease. Transmission. Ticks and Mites in Disease. Transmission. Insects in Disease Transmission. Control of Arthropods of Medical. Importance. PART X TROPICAL DISEASE in a TEMPERATE CLIMATE. General Principles. Establishing a Travel Clinic. Adviceto Travelers. Screening Long Term Travelers. Diarrhea in Travelers. Fever in Travelers. Skin Lesions in Travelers. Eosinophilia in Travelers and Immigrants. Diseases of Immigrants. Global Epidemiology of Infectious Diseases. PART XI LABORATORY DIAGNOSIS of PARASITIC DISEASES. Examination of Stool and Urine Specimens. Examination of Blood, Other Body Fluids, Tissues, And Sputum. Parasitic Immunodiagnosis .

Lydia Dyck, K. Mills

Sazzad Hossain, Saiful Islam, Muhammad Ibrahim et al.

Skin diseases are a major public health concern worldwide, and their detection is often challenging without access to dermatological expertise. In countries like Bangladesh, which is highly populated, the number of qualified skin specialists and diagnostic instruments is insufficient to meet the demand. Due to the lack of proper detection and treatment of skin diseases, that may lead to severe health consequences including death. Common properties of skin diseases are, changing the color, texture, and pattern of skin and in this era of artificial intelligence and machine learning, we are able to detect skin diseases by using image processing and computer vision techniques. In response to this challenge, we develop a publicly available dataset focused on common skin disease detection using machine learning techniques. We focus on five prevalent skin diseases in Bangladesh: Contact Dermatitis, Vitiligo, Eczema, Scabies, and Tinea Ringworm. The dataset consists of 1612 images (of which, 250 are distinct while others are augmented), collected directly from patients at the outpatient department of Faridpur Medical College, Faridpur, Bangladesh. The data comprises of 302, 381, 301, 316, and 312 images of Dermatitis, Eczema, Scabies, Tinea Ringworm, and Vitiligo, respectively. Although the data are collected regionally, the selected diseases are common across many countries especially in South Asia, making the dataset potentially valuable for global applications in machine learning-based dermatology. We also apply several machine learning and deep learning models on the dataset and report classification performance. We expect that this research would garner attention from machine learning and deep learning researchers and practitioners working in the field of automated disease diagnosis.

Alimuddin Zumla, Martin Rao, R. Wallis et al.

Summary Despite extensive global efforts in the fight against killer infectious diseases, they still cause one in four deaths worldwide and are important causes of long-term functional disability arising from tissue damage. The continuing epidemics of tuberculosis, HIV, malaria, and influenza, and the emergence of novel zoonotic pathogens represent major clinical management challenges worldwide. Newer approaches to improving treatment outcomes are needed to reduce the high morbidity and mortality caused by infectious diseases. Recent insights into pathogen–host interactions, pathogenesis, inflammatory pathways, and the host's innate and acquired immune responses are leading to identification and development of a wide range of host-directed therapies with different mechanisms of action. Host-directed therapeutic strategies are now becoming viable adjuncts to standard antimicrobial treatment. Host-directed therapies include commonly used drugs for non-communicable diseases with good safety profiles, immunomodulatory agents, biologics (eg monoclonal antibodies), nutritional products, and cellular therapy using the patient's own immune or bone marrow mesenchymal stromal cells. We discuss clinically relevant examples of progress in identifying host-directed therapies as adjunct treatment options for bacterial, viral, and parasitic infectious diseases.

Cyril Caminade, Diego Ayala, Thibaud de Chevigny et al.

Abstract In December 2024, L’Initiative-Expertise France organized a workshop in Musanze, Rwanda, for National Malaria Control and Elimination Programmes (NMC/EPs) representatives from 19 sub-Saharan African countries. The workshop focused on surveillance, modeling, climate forecasting, and innovative control methods to mitigate climate change impacts on malaria. Participants shared challenges, experiences and best practices. Key challenges highlighted include shifts in malaria transmission seasons, disease spread to mid-altitude regions, and infrastructure damage from extreme weather. Additional factors, such as drug and insecticide resistance, the spread of Anopheles stephensi, and changes in vector behaviour, are exacerbating malaria transmission in African cities. Participants stressed the need for collaborative efforts to tackle these evolving threats. This comment reflects the expertise and insights of 19 NMCPs actively managing malaria control and aims at raising awareness, inform policy discussions, and strengthen global partnerships to address the intersection of malaria and climate change.

Jinlong Gao, Jie Cao, Jinmeng Li et al.

Abstract Background The treatment of multidrug-resistant tuberculous meningitis (MDR-TBM) presents significant challenges, as the ability of different anti-tuberculosis (anti-TB) drugs to penetrate the blood-brain barrier varies greatly. The pharmacokinetic characteristics of second-line anti-TB drugs including bedaquiline, cycloserine, moxifloxacin and contezolid remains unclear, particularly in cerebrospinal fluid (CSF). Case presentation We report a case of a 30-year-old female who was diagnosed with MDR-TBM. Therapeutic drug monitoring (TDM) was used to determine whether each anti-TB drug’s peak concentration reached the effective range, and concentrations of each anti-TB drug in plasma and CSF of the patient after 5, 7, 9 and 12 h of medication was detected, the CSF/plasma concentration ratio of each anti-TB drug was also analyzed. Conclusions TDM plays an important role in clinical individualized medication adjustment. Cycloserine, pyrazinamide, contezolid and moxifloxacin may have a high CSF permeability. This study provided valuable reference for the clinical management of MDR-TBM by measuring the plasma and CSF concentrations of anti-TB drugs.

Dmitrii Seletkov, Sophie Starck, Ayhan Can Erdur et al.

Reliable preclinical disease risk assessment is essential to move public healthcare from reactive treatment to proactive identification and prevention. However, image-based risk prediction algorithms often consider one condition at a time and depend on hand-crafted features obtained through segmentation tools. We propose a whole-body self-supervised representation learning method for the preclinical disease risk assessment under a competing risk modeling. This approach outperforms whole-body radiomics in multiple diseases, including cardiovascular disease (CVD), type 2 diabetes (T2D), chronic obstructive pulmonary disease (COPD), and chronic kidney disease (CKD). Simulating a preclinical screening scenario and subsequently combining with cardiac MRI, it sharpens further the prediction for CVD subgroups: ischemic heart disease (IHD), hypertensive diseases (HD), and stroke. The results indicate the translational potential of whole-body representations as a standalone screening modality and as part of a multi-modal framework within clinical workflows for early personalized risk stratification. The code is available at https://github.com/yayapa/WBRLforCR/

Mangsura Kabir Oni, Tabia Tanzin Prama

In Bangladesh, tomatoes are a staple vegetable, prized for their versatility in various culinary applications. However, the cultivation of tomatoes is often hindered by a range of diseases that can significantly reduce crop yields and quality. Early detection of these diseases is crucial for implementing timely interventions and ensuring the sustainability of tomato production. Traditional manual inspection methods, while effective, are labor-intensive and prone to human error. To address these challenges, this research paper sought to develop an automated disease detection system using Convolutional Neural Networks (CNNs). A comprehensive dataset of tomato leaves was collected from the Brahmanbaria district, preprocessed to enhance image quality, and then applied to various deep learning models. Comparative performance analysis was conducted between YOLOv5, MobileNetV2, ResNet18, and our custom CNN model. In our study, the Custom CNN model achieved an impressive accuracy of 95.2%, significantly outperforming the other models, which achieved an accuracy of 77%, 89.38% and 71.88% respectively. While other models showed solid performance, our Custom CNN demonstrated superior results specifically tailored for the task of tomato leaf disease detection. These findings highlight the strong potential of deep learning techniques for improving early disease detection in tomato crops. By leveraging these advanced technologies, farmers can gain valuable insights to detect diseases at an early stage, allowing for more effective management practices. This approach not only promises to boost tomato yields but also contributes to the sustainability and resilience of the agricultural sector, helping to mitigate the impact of plant diseases on crop production.

Yueheng Jiang, Peng Zhang

Multi-disease diagnosis using multi-modal data like electronic health records and medical imaging is a critical clinical task. Although existing deep learning methods have achieved initial success in this area, a significant gap persists for their real-world application. This gap arises because they often overlook unavoidable practical challenges, such as modality missingness, noise, temporal asynchrony, and evidentiary inconsistency across modalities for different diseases. To overcome these limitations, we propose HGDC-Fuse, a novel framework that constructs a patient-centric multi-modal heterogeneous graph to robustly integrate asynchronous and incomplete multi-modal data. Moreover, we design a heterogeneous graph learning module to aggregate multi-source information, featuring a disease correlation-guided attention layer that resolves the modal inconsistency issue by learning disease-specific modality weights based on disease correlations. On the large-scale MIMIC-IV and MIMIC-CXR datasets, HGDC-Fuse significantly outperforms state-of-the-art methods.

Faika Fairuj Preotee, Shuvashis Sarker, Shamim Rahim Refat et al.

Leaf diseases are harmful conditions that affect the health, appearance and productivity of plants, leading to significant plant loss and negatively impacting farmers' livelihoods. These diseases cause visible symptoms such as lesions, color changes, and texture variations, making it difficult for farmers to manage plant health, especially in large or remote farms where expert knowledge is limited. The main motivation of this study is to provide an efficient and accessible solution for identifying plant leaf diseases in Bangladesh, where agriculture plays a critical role in food security. The objective of our research is to classify 21 distinct leaf diseases across six plants using deep learning models, improving disease detection accuracy while reducing the need for expert involvement. Deep Learning (DL) techniques, including CNN and Transfer Learning (TL) models like VGG16, VGG19, MobileNetV2, InceptionV3, ResNet50V2 and Xception are used. VGG19 and Xception achieve the highest accuracies, with 98.90% and 98.66% respectively. Additionally, Explainable AI (XAI) techniques such as GradCAM, GradCAM++, LayerCAM, ScoreCAM and FasterScoreCAM are used to enhance transparency by highlighting the regions of the models focused on during disease classification. This transparency ensures that farmers can understand the model's predictions and take necessary action. This approach not only improves disease management but also supports farmers in making informed decisions, leading to better plant protection and increased agricultural productivity.

Cody E. FitzGerald, James P. Keener

Chronic Wasting Disease (CWD) is a neurological disease impacting deer, elk, moose, and other cervid populations and is caused by a misfolded protein known as a prion. CWD is difficult to control due to the persistence of prions in the environment. Prions can remain infectious for more than a decade and have been found in soil as well as other environmental vectors, such as ticks and plants. Here, we provide a bifurcation analysis of a mathematical model of CWD spread in a cervid population, and use a modification of the Gillespie algorithm to explore if wolves can be used as an ecological control strategy to limit the spread of the disease in several relevant scenarios. We then analytically compute the probability that the disease spreads given one infected member enters a fully healthy population and the probability of elimination, given a fully susceptible population and remaining prions in the environment. From our analysis, we conclude that wolves can be used as an effective control strategy to limit the spread of CWD in cervid populations, and hunting or other means of lowering the susceptible population are beneficial to controlling the spread of CWD, although it is important to note that inferring biologically relevant parameters from the existing data is an ongoing challenge for this system.

Ruth Zwizwai

Mina Pencheva, Neshka Manchorova_Veleva

From 2019 to the present day, the coronavirus infection COVID-19 continues to be a serious health problem. Scientists and clinicians from all over the world have joined efforts in studying the molecular interaction mechanisms between SARS-CoV-2 and ACE2, including virus-induced changes in ACE2 transcription, expression, and functionalities leading to disruption of basic regulatory pathways for vascular homeostasis, and reprogramming of key proteases, co-receptors and adhesion molecules. Here, we aimed to clarify the mechanisms and signals that would restore the virus-induced imbalance between destructive and protective effects of ACE2. Understanding why only certain individuals are predisposed to infection with SARS-CoV-2, and development of severe pathology is at the center of scientific interest, and the strategies for prevention and therapy.

Ruth Zwizwai

Safoura Moradkasani, Mina Latifian, Mostafa Salehi-Vaziri et al.

Objectives: Crimean-Congo Hemorrhagic Fever (CCHF) is a tick-borne zoonotic viral disease that could be a public health concern. The overlapping of clinical symptoms of some acute bacterial febrile diseases with CCHF is of importance for clinical diagnosis. This study aimed to molecularly examination of Brucella, Coxiella burnetii, Borrelia, and Ehrlichia infections among individuals suspected of CCHF in Iran. Methods: In this study, 260 serum samples of suspected cases of CCHF with definitively negative laboratory test results for CCHF virus infection, were examined for Brucella spp., Coxiella burnetii, Borrelia spp., and Ehrlichia spp. by Real-time PCR. Results: According to the results, 3.46 % and 3.07 % of the patients were positive for brucellosis and Q fever, respectively. Notably, no cases of borreliosis or ehrlichiosis were detected. Among the positive cases for brucellosis (N = 9), three cases were identified as Brucella abortus infection. Individuals under the age of 43 displayed a significantly higher positivity rate for Q fever (p < 0.01). Furthermore, patients presenting with chills had a 5.81-fold increased likelihood of being infected with Q fever (95 % CI: 1.39–24.26) compared to those without chills. Notably, no other variables demonstrated a statistically significant association with Q fever infection. Discussion and conclusions: The results of this study showed that bacterial infections such as Q fever and brucellosis should be considered as differential diagnoses of CCHF. It is recommended that other bacterial infections that can cause early clinical symptoms similar to CCHF should also be taken into consideration in future studies and serological and molecular investigations of these infections should be tested on a wide scale.

Likui Wang, Lei Guo, Yunguo Liu et al.

Palang Chotsiri, Almahamoudou Mahamar, Halimatou Diawara et al.

Abstract Background Primaquine (PQ) is the prototype 8-aminoquinoline drug, a class which targets gametocytes and hypnozoites. The World Health Organization (WHO) recommends adding a single low dose of primaquine to the standard artemisinin-based combination therapy (ACT) in order to block malaria transmission in regions with low malaria transmission. However, the haemolytic toxicity is a major adverse outcome of primaquine in glucose-6-phosphate dehydrogenase (G6PD)-deficient subjects. This study aimed to characterize the pharmacokinetic properties of primaquine and its major metabolites in G6PD-deficient subjects. Methods A single low-dose of primaquine (0.4–0.5 mg/kg) was administered in twenty-eight African males. Venous and capillary plasma were sampled up to 24 h after the drug administration. Haemoglobin levels were observed up to 28 days after drug administration. Only PQ, carboxy-primaquine (CPQ), and primaquine carbamoyl-glucuronide (PQCG) were present in plasma samples and measured using liquid chromatography mass spectrometry. Drug and metabolites’ pharmacokinetic properties were investigated using nonlinear mixed-effects modelling. Results Population pharmacokinetic properties of PQ, CPQ, and PQCG can be described by one-compartment disposition kinetics with a transit-absorption model. Body weight was implemented as an allometric function on the clearance and volume parameters for all compounds. None of the covariates significantly affected the pharmacokinetic parameters. No significant correlations were detected between the exposures of the measured compounds and the change in haemoglobin or methaemoglobin levels. There was no significant haemoglobin drop in the G6PD-deficient patients after administration of a single low dose of PQ. Conclusions A single low-dose of PQ was haematologically safe in this population of G6PD-normal and G6PD-deficient African males without malaria. Trial registration NCT02535767

Darlyn Buenaño Vera, Byron Oviedo, Washington Chiriboga Casanova et al.

The early identification of diseases in cocoa pods is an important task to guarantee the production of high-quality cocoa. The use of artificial intelligence techniques such as machine learning, computer vision and deep learning are promising solutions to help identify and classify diseases in cocoa pods. In this paper we introduce the development and evaluation of a deep learning computational model applied to the identification of diseases in cocoa pods, focusing on "monilia" and "black pod" diseases. An exhaustive review of state-of-the-art of computational models was carried out, based on scientific articles related to the identification of plant diseases using computer vision and deep learning techniques. As a result of the search, EfficientDet-Lite4, an efficient and lightweight model for object detection, was selected. A dataset, including images of both healthy and diseased cocoa pods, has been utilized to train the model to detect and pinpoint disease manifestations with considerable accuracy. Significant enhancements in the model training and evaluation demonstrate the capability of recognizing and classifying diseases through image analysis. Furthermore, the functionalities of the model were integrated into an Android native mobile with an user-friendly interface, allowing to younger or inexperienced farmers a fast and accuracy identification of health status of cocoa pods

Tagesu Abdisa Serbessa, Yosef Gemechu Geleta, Ifa Obsa Terfa

Poultry and swine production play an important role in countries' socioeconomic development by providing proteins that support food and nutrition security. However, several infectious and non-infectious diseases hinder the production of swine and poultry. Therefore, this review aim to provide highlight of the common disease and health management of poultry and swine. Poultry production has suffered from different pathogenic microorganisms that cause devastating economic losses in poultry industries worldwide. Poultry can be infected with common diseases like endoparasites, ectoparasites, infectious bronchitis, Marek's disease, fowl cholera, salmonellosis, infectious coryza, fowl pox, avian encephalomyelitis, etc. Health management is a system of preventive medicine that considers the whole poultry farms and the total influences, including social, with respect to relationships with others in the flock, psychological, and environmental factors that affect health. Swine production can be destructed by the influence of infectious diseases, which include Mycoplasma Hyopneumoniae, Actinobacillus pleuropneumoniae, Porcine Reproductive and Respiratory Syndrome Virus, Trichinella spp., Toxoplasma gondii, Salmonella spp., Campylobacter, and Leprospira. This all causes respiratory problems, leg problems, reproductive disorders, gastrointestinal problems, claw and skin problems, parasitic infections, and piglet mortality. Endoparasites and ectoparasites are regarded as the most significant constraints for welfare and health, as well as economic loss, in swine production, particularly during the post-weaning period. However, health management of swine production can reduce the effect of disease and optimize their productivity. Herd health management practices include vaccination, genetic improvement, and observation for all animals’ clinical signs, record keeping, detection and treatment of injury, sanitation, disease, pest control, and animal handlers. Generally, disease has a great risk to the health of poultry and swine animals that causes a decrement in their production. Therefore, the health management on poultry and swine farms should have to be strictly measured and further studies need to be conducted to solve the major problem of economic loss of production.

A. Kirichenko, E. Bryushkova, A. Shabalina et al.

Intro: Deoxyribozymes (Dz) are short synthetic DNA oligonucleotides that catalyze the cleavage of a phosphodiester bond between nucleotides in the presence of divalent metal ions. The use of DNAzymes in the in vitro diagnostics increases the specificity and versatility of the analysis. Methods: We took the well-studied Dz 10-23 with high catalytic activity as the basis of our system. The biosensor is divided into two fragments according to the binary probe principle (Dz1 and Dz2), which consist of target RNA binding sites, a fluorescent substrate (Fsub), and half of the Dz 10-23 catalytic center sequence. Assembly of the Dz 10-23 active center with subsequent Fsub cleavage and registration of a fluorescent signal is possible only if the target RNA is present in the sample. Findings: To assess the diagnostic potential of the biosensor, we measured FAM fluorescence in a solution containing synthetic RNA 35 nucleotides long (nip35) corresponding to the NiV target sequence, Fsub labeled with the FAM-BHQ1 and Dz_NiV pair. A mixture of Dz_NiV and Fsub was used as a control. The detection limit of the target RNA reached 5 nM, the signal development time was 30 minutes at a temperature of 37 C ̊. Discussion: The specificity of Dz_NiV was evaluated in the presence of synthetic RNAs from six other RNA viruses of similar length: Hendra, Machupo, Sabia, Junin, Guanarito, and SARS-CoV. A fluorescent signal was recorded only in the presence of nip35 in the reaction mixture. The efficiency of Dz_NiV on a long fragment was tested using a plasmid with a cloned target sequence. The site is about 700 b.p. was amplified by PCR, followed by transcription. Conclusion: It was developed the highly specific biosensor Dz_NiV for the detection of Nipah virus RNA with a sensitivity limit of 5 nM at 37 C ̊.