Artificial intelligence in parasitic disease control: A paradigm shift in health care.

Parasitic diseases, including malaria, leishmaniasis, and trypanosomiasis, continue to plague populations worldwide, particularly in resource-limited settings and disproportionately affecting vulnerable populations. It has limited the use of conventional health-care delivery and disease control approaches and necessitated exploring innovative strategies. In this direction, artificial intelligence (AI) has emerged as a transformative tool with immense promise in parasitic disease control, offering the potential for enhanced diagnostics, precision drug discovery, predictive modeling, and personalized treatment. Predictive AI algorithms have assisted in understanding parasite transmission patterns and outbreaks by analyzing vast amounts of epidemiological data, environmental factors, and population demographics. This has strengthened public health interventions, resource allocation, and outbreak preparedness strategies, enabling proactive measures to mitigate disease spread. In diagnostics, AI-enabled accurate and rapid identification of parasites by analyzing microscopic images. This capability is particularly valuable in remote regions with limited access to diagnostic facilities. AI-driven computational methods have also assisted in drug discovery for parasitic diseases by identifying novel drug targets and predicting the efficacy and safety of potential drug candidates. This approach has streamlined drug development, leading to more effective and targeted therapies. This article reviews these current developments and their transformative impacts on the health-care sector. It also assessed the hurdles that require attention before these transformations can be realized in real-life scenarios.

Deep tech innovation for parasite diagnosis: New dimensions and opportunities.

By converging advanced science, engineering, and design, deep techs are bringing a great wave of future innovations by mastering challenges and problem complexity across sectors and the field of parasitology is no exception. Remarkable research and advancements can be seen in the field of parasite detection and diagnosis through smartphone applications. Supervised and unsupervised data deep learnings are heavily exploited for the development of automated neural network models for the prediction of parasites, eggs, etc., From microscopic smears and/or sample images with more than 99% accuracy. It is expected that several models will emerge in the future wherein greater attention is being paid to improving the model's accuracy. Invariably, it will increase the chances of adoption across the commercial sectors dealing in health and related applications. However, parasitic life cycle complexity, host range, morphological forms, etc., need to be considered further while developing such models to make the deep tech innovations perfect for bedside and field applications. In this review, the recent development of deep tech innovations focusing on human parasites has been discussed focusing on the present and future dimensions, opportunities, and applications.

Molecular characterization of Giardia intestinalis assemblages in children among the rural and urban population of Pondicherry, India.

Introduction: Giardiasis is one of the greatest public parasitic infections causing diarrheal and also known to be associated with high morbidity and mortality, among the children's particularly in developing countries with less cleanliness practices. Thus, studying genomic variety of Giardia intestinalis aids to improve our perspective related to the variability in the genome of the parasite. Materials and Methods: In this cross-sectional study, 1006 stool samples were collected from the rural (n = 500) and urban settings (n = 506) from the children (<15 years) with and without symptoms and were screened for the presence of G. intestinalis by polymerase chain reaction (PCR) targeting triosephosphate isomerase gene. Further, all PCR-positive amplicons were subjected to restriction fragment length polymorphism using RsaI restriction enzyme. Results: Of the total 1006 stool samples, 500 samples from rural screened by PCR 108 (21%) were found to be positive for assemblage A, 116 (23.2%) belong to assemblage B, and 5 (1%) were mixed assemblages (A + B). Whereas in urban, of the 506 samples screened by PCR, 92 (18.1%) were found to be positive for assemblage A, 93 (18.3%) assemblage B, and 10 (1.9%) were mixed assemblages (A + B). No significant difference was found between the G. intestinalis assemblages with clinical details of symptomatic and asymptomatic in children. Conclusions: This signifies the first study inspection in our location to shed lights and delivers some preliminary data on assemblages and subassemblages. The results suggest that anthroponotic transmission could be a foremost transmission path for giardiasis among the study population.

Climate adaptation impacting parasitic infection.

The steady and ongoing change in climatic patterns across the globe is triggering a cascade of climate-adaptive phenomena, both genetic and behavioral in parasites, and influencing the host-pathogen-transmission triangle. Parasite and vector traits are now heavily influenced due to increasing temperature that almost dissolved geospatial boundaries and impacted the basic reproductive number of parasites. As consequence, continents unknown to some parasites are experiencing altered distribution and abundance of new and emerging parasites that are developing into a newer epidemiological model. These are posing a burden to healthcare and higher disease prevalence. This calls for multidisciplinary actions focusing on One Health to improve and innovate in areas of detection, reporting, and medical countermeasures to combat the growing threat of parasite emergence owing to climate adaptations for better public health outcomes.

Balamuthia mandrillaris: An opportunistic, free-living ameba - An updated review.

Balamuthia mandrillaris is an opportunistic, free-living ameba that is pathogenic to humans. It has a worldwide distribution but is mainly detected in warmer regions. Balamuthia infections are rare but have been reported in both immunocompetent and immunocompromised individuals of all ages. B. mandrillaris can enter through wounds on the skin or the nose and cause cutaneous lesions and the usually fatal Balamuthia amebic encephalitis (BAE). Infection usually spreads from the lungs or through nerve fibers, and attacks the central nervous system, forming granulomatous lesions and necrosis in the brain. Balamuthia infection is usually chronic, and patients initially present with nonspecific symptoms, including headache, nausea, myalgia, and low-grade fever. As the disease progresses, the patient becomes paralyzed and comatose, often leading to death. Lack of knowledge of predisposing factors, specific treatment, and standardized detection tools have resulted in a nearly cent percent fatality rate. Although only about 200 cases have been reported worldwide since its characterization in the 1990s, the number of reported cases has increased over the years. BAE is an emerging disease and a major health concern. Few patients have survived Balamuthia infections with antimicrobial treatment that has largely been empirical. Early diagnosis is the key and requires familiarity with the disease and a high degree of suspicion on the part of the diagnostician. There are currently no specific treatment and prevention recommendations. This review highlights our current understanding of B. mandrillaris in terms of its pathogenicity, genomics, and novel diagnostic and therapeutic approaches against BAE infections.

Molecular diagnosis of infectious parasites in the post-COVID-19 era.

The endemicity of several parasitic diseases across the globe and recent evidence of distress among COVID-19 patients with preexisting parasitic infections requires strengthening One Health framework and advanced strategies for parasitic detection. Owing to the greater sensitivity and accuracy, molecular technologies such as conventional polymerase chain reaction (PCR), reverse transcription (RT)-PCR, nested PCR, loop-mediated isothermal amplification (LAMP), and xMAP technology have been extensively studied for parasitic diagnosis. Varieties of genes have been targeted for primer development where 18S rRNA, internal transcribed spacer regions, and mitochondrial DNAs coding for cytochrome, and other enzymes have been widely used. More recent, low-cost sequencing and advances in big data management have resulted in a slow but steady rise of next-generation sequencing-based approaches for parasite diagnosis. However, except for few parasites of global concerns such as Plasmodium and Entamoeba, most of the molecular tools and technologies are yet to witness bench to bedside and field translations. This review looks into some of the advancements in the molecular diagnosis of parasites that have potential relevance to clinical purposes and may pave the way toward disease management in an efficient and timely manner.

Lophomonas blattarum: A new flagellate causing respiratory tract infections.

Lophomonas blattarum is a flagellate protozoan parasite which was originally described as a commensal in the gut of cockroaches. From the 1990s, reports started coming out of peoples Republic of China about its possible role in bronchopulmonary infections, and this was followed by reports from some other parts of the world as well. There had been some skepticism regarding the misidentification of bronchial ciliated epithelial cells as L. blattarum, but recent use of molecular diagnosis has come as an aid in clearing the controversy. This review focuses on the various aspects of the parasite including its biology, epidemiology, clinical manifestations, laboratory diagnosis, and the treatment aspects. Molecular diagnosis has recently been employed and more reports concerning its validation is needed. More basic research concerning the genomic and proteomic analysis is necessary to develop reliable molecular and serological tests for this parasite in future.

Narciclasine improves outcome in sepsis among neonatal rats via inhibition of calprotectin and alleviating inflammatory responses.

Sepsis is associated with exacerbated inflammatory response which subsequently results in multiple organ dysfunction. Sepsis accounts for high mortality and morbidity among newborns worldwide. Narciclasine is a plant alkaloid which has shown to possess anti-inflammatory properties. In this study we investigated the effect and mechanism of action of narciclasine in neonatal sepsis rat models. The excessive release of S100A8/A9 or calprotectin in neonatal sepsis could be detrimental as it could exacerbate the inflammatory responses. We found that narciclasine significantly reduced the plasma levels of S100A8/A9 and also suppressed its expression in the liver and lung. The systemic and local bacterial load was also reduced in the narciclasine treated rats. The systemic and local production of pro-inflammatory cytokines in plasma and organs (liver and lungs) was significantly reduced in the narciclasine treated rats. The histopathological studies showed that narciclasine prevents the organ damage associated with sepsis and improved the survival of neonatal rats. Sepsis increased the phosphorylated NF-κß p65 protein expression in the liver. Narciclasine suppressed the phosphorylation of NF-κß p65 and the degradation of NF-κß inhibitory protein alpha. It could also suppress the expression of adaptor proteins of the toll like receptor signaling pathway viz., myeloid differentiation factor 88 (MyD88), Interleukin-1 receptor-associated kinase 1 (IRAK1) and TNF receptor associated factor 6 (TRAF6). These results suggest that narciclasine protects against sepsis in neonatal rats through the inhibition of calprotectin, pro-inflammatory cytokines and suppression of NF-κß signaling pathway.

Pondicherry declaration on the identification and detection of Entamoeba histolytica.

Stake holders meet on "Identification and Detection of Entamoeba histolytica" was conducted on July 21, 2019 at Sri Balaji Vidyapeeth Deemed-to-be-University, Pondicherry. This programme was of national importance, since the amoebiasis is being increasingly reported from different parts of India because of poor socioeconomic conditions and sanitation levels. Experts in amoebiasis research across India attended this meeting. This meeting was conducted with an objective to frame the guidelines on the identification and detection of E. histolytica with reference to conventional diagnostic methods and molecular diagnosis targeting appropriate genes of E. histolytica. The recommendations of the panel were released as declaration on the diagnosis of amoebiasis and were circulated to various administrative and scientific bodies in India as reference policy document on the diagnosis of amoebiasis.

Detection of heterogeneous vancomycin-intermediate Staphylococcus aureus: A preliminary report from south India.

Background & objectives: Although there are reports of heterogeneous vancomycin-intermediate Staphylococcus aureus (hVISA) across the globe, there is a lack of reliable data on hVISA in India. The present study was undertaken to determine the rate of hVISA among the methicillin-resistant Staphylococcus aureus (MRSA) isolates, and to compare the brain heart infusion agar with vancomycin 4 µg/ml (BHIV4) method with population analysis profile-area under the curve (PAP-AUC) method for the detection of hVISA and to study the distribution of mobile genetic element that carries methicillin-resistance gene SCCmec (Staphylococcal cassette chromosome mec) types among these isolates. Methods: BHIV4 and PAP-AUC methods were employed to detect hVISA among 500 clinical isolates of MRSA. SCCmec typing of these isolates was performed by multiplex polymerase chain reaction. The clinical presentation, treatment with vancomycin and outcome was documented for patients with hVISA. Results: The rate of hVISA was 12.4 per cent by PAP-AUC method. Sensitivity, specificity, PPV, NPV and kappa agreement of BHIV4 with PAP-AUC was 58.06, 93.15, 54.55, 94.01 per cent and 0.498, respectively. The isolation of hVISA was significantly (P<0.01) higher in patients admitted to intensive care units and wards than in patients attending the outpatient departments. Only 38 per cent of the patients received vancomycin as therapy. Majority of the hVISA isolates carried SCCmec type V or IV. Interpretation & conclusions: The rate of hVISA isolation in our study was 12.4 per cent. The sensitivity of the BHIV4 screening test was low, and was in moderate agreement with PAP-AUC test. SCCmec type V was the predominant type seen in half of the isolates. More studies need to be done in different parts of the country on a large number of isolates to confirm our findings.