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At least 181 records · Page 10

F-18 FDG PET for assessment of disease activity of large vessel vasculitis: A systematic review and meta-analysis

Background: The aim of this study is to investigate the performance of F-18 fluorodeoxyglucose positron emission tomography (F-18 FDG PET) or positron emission tomography/computed tomography (PET/CT) for the assessment of disease activity in patients with large vessel vasculitis (LVV) through a meta-analysis. Methods: The MEDLINE via PubMed and EMBASE were searched for the studies evaluating the performance of F-18 FDG PET or PET/CT in the assessment of disease activity in patients with LVV. Pooled sensitivity, specificity, diagnostic odds ratios (DORs), and summary receiver-operating characteristic (sROC) curve were estimated across the included studies. Possible publication bias was assessed by Deek’s funnel plot asymmetry tests. Results: A total of 439 PET images from 298 patients pooled from nine studies showed that the pooled sensitivity was 0.88 [95% confidence interval (CI) 0.79-0.93] without heterogeneity (χ{sup 2} = 14.42, P = .07) and the pooled specificity was 0.81 (95% CI 0.64-0.91) with heterogeneity (χ{sup 2} = 63.72, P = .00) for the detection of active LVV. The pooled DOR was 30 (95% CI 8-107). Hierarchical sROC curve indicates that the area under the curve was 0.91 (95% CI 0.89-0.94). There was no significant publication bias (P = .42), and meta-regression analysis revealed that none of the variables was the source of the study heterogeneity. Conclusions: F-18 FDG PET has a good performance for the detection of active disease status in patients with LVV. Revised criteria for the assessment of disease activity incorporated with F-18 FDG PET or PET/CT should be introduced and validated. Further studies are warranted to determine if PET-based treatment of LVV can improve outcomes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

ACC/AATS/AHA/ASE/ASNC/HRS/SCAI/SCCT/SCMR/STS 2019 Appropriate Use Criteria for Multimodality Imaging in the Assessment of Cardiac Structure and Function in Nonvalvular Heart Disease

This document is the second of 2 companion appropriate use criteria (AUC) documents developed by the American College of Cardiology, American Association for Thoracic Surgery, American Heart Association, American Society of Echocardiography, American Society of Nuclear Cardiology, Heart Rhythm Society, Society for Cardiovascular Angiography and Interventions, Society of Cardiovascular Computed Tomography, Society for Cardiovascular Magnetic Resonance, and Society of Thoracic Surgeons. The first document (J Am Coll Cardiol 2017;70:1647-1672) addresses the evaluation and use of multimodality imaging in the diagnosis and management of valvular heart disease, whereas this document addresses this topic with regard to structural (nonvalvular) heart disease. While dealing with different subjects, the 2 documents do share a common structure and feature some clinical overlap. The goal of the companion AUC documents is to provide a comprehensive resource for multimodality imaging in the context of structural and valvular heart disease, encompassing multiple imaging modalities. Using standardized methodology, the clinical scenarios (indications) were developed by a diverse writing group to represent patient presentations encountered in everyday practice and included common applications and anticipated uses. Where appropriate, the scenarios were developed on the basis of the most current American College of Cardiology/American Heart Association Clinical Practice Guidelines. A separate, independent rating panel scored the 102 clinical scenarios in this document on a scale of 1 to 9. Scores of 7 to 9 indicate that a modality is considered appropriate for the clinical scenario presented. Midrange scores of 4 to 6 indicate that a modality may be appropriate for the clinical scenario, and scores of 1 to 3 indicate that a modality is considered rarely appropriate for the clinical scenario. The primary objective of the AUC is to provide a framework for the assessment of these scenarios by practices that will improve and standardize physician decision making. AUC publications reflect an ongoing effort by the American College of Cardiology to critically and systematically create, review, and categorize clinical situations in which diagnostic tests and procedures are utilized by physicians caring for patients with cardiovascular diseases. The process is based on the current understanding of the technical capabilities of the imaging modalities examined.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Design and synthesis of astatinated benzothiazole compounds for their potential use in Targeted Alpha Therapy (TAT) strategies to treat Alzheimer's disease-associated amyloid plaques

Alzheimer's disease (AD) is a terminal neurodegenerative disease characterized by the buildup of amyloid fibrils, amorphous aggregates and tauopathies. Several treatment modalities, which rely on various biological processes to reduce disease burden, have been largely ineffective at treating Alzheimer's disease. Targeted alpha therapy (TAT) has demonstrated positive results in the treatment of cancer. Benzothiazole derivatives have been successfully shown to target these plaques and are used in several imaging applications. One such derivative, Flutemetamol (Vizamyl TM ) is an FDA approved diagnostic tool for PET imaging of AD-associated plaques. We report the radiolabeling of benzothiazole derivatives with 211 At, a 7.2 h alpha emitting radionuclide, using a copper catalyzed reaction with a boronic acid precursor molecule. In conclusion, our final compound [ 211 At]3'-At-PIB-OMe had a radiochemical yield of 55% and was found to be stable for at least 3 h in phosphate buffered saline.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Fluorescence-labeled liposome accumulation in injured colon of a mouse model of T-cell transfer-mediated inflammatory bowel disease

Drug delivery systems maximize the efficacy of drugs by improving their pharmacokinetic profiles, pharmacodynamic effects, or both and reducing their adverse effects. One of the most advanced, clinically available formulations are liposome-encapsulated drugs. In this study, we aimed to determine if liposomes can selectively deliver compounds in gastrointestinal diseases. Initially, we evaluated the correlation between the diarrhea score and accumulation of fluorescence (FL)-labeled liposome using in vivo imaging systems in various disease states of an inflammatory bowel disease mouse model. The result showed that FL-labeled liposome accumulation and colon tissue weight, which reflect the disease state were highly and positively correlated. Then, to confirm the accumulation of liposomes at injured sites of the colon, we administered both FL-labeled liposomes and luminescence probes for detecting reactive oxygen species (ROS) to the mouse model. The imaging data showed that liposome accumulation tended to coincide with ROS detected sites and the correlation coefficient indicated a significantly positive correlation between liposome accumulation and ROS detection levels. Finally, we evaluated the involvement of macrophages in the uptake mechanism of the liposomes by analyzing the relationship between FL-labeled liposome accumulation and macrophage marker gene expression levels. The result showed that the expression of each macrophage marker gene and liposome accumulation showed a significant positive correlation. Therefore, the macrophages considerably contributed to the uptake mechanism of the liposomes. These data suggest that liposomes could be an attractive delivery tool for enhancing the accumulation of drug candidates through macrophages in injured colonic tissues. This approach is expected to provide new treatment options for patients with colitis.

60 APPLIED LIFE SCIENCES↗

Lipidomic insight into cardiovascular diseases

Highlights: • Update on current lipidomic research in cardiovascular diseases. • Lipidomic research's discovery of novel lipid species correlated with cardiovascular risks. • Potential of lipidomics to identify biomarker lipid molecules that predict future cardiovascular events in young patients. Cardiovascular disease is a primary cause of mortality worldwide. Therefore, it is of major interest to identify sensitive molecular markers that predict cardiovascular events and point to therapeutic strategies that will increase lifespans. Dysregulated lipid metabolism is recognized as an established risk factor in cardiovascular diseases. However, it is still largely unknown which specific lipid molecular species reflect cardiovascular risk. In addition, understanding the whole lipidome signature in vascular pathophysiology is challenging. Recent advancements of mass-spectrometry allow researchers to detect each individual lipid species from unbiased small samples. In this review, we update the current research on lipidomic approaches in cardiovascular diseases.

60 APPLIED LIFE SCIENCES↗

Bioactive peptoids against vector-borne parasitic diseases

Protozoan parasites represent a severe threat to global human health as they are responsible for infection in Malaria, and a range of Neglected Tropical Diseases (NTDs) including Chagas disease, leishmaniasis and African sleeping sickness. Often treatments for protozan parasites are limited in their efficacy and drug resistance is an emerging problem. The current efforts to develop new treatments for the aforementioned diseases have been met with limited success and as such novel compound classes for development are being actively sought. Peptoids are peptidomimetics that have showed promise as antimicrobial agents but their application in the field of vector-borne parasitic diseases is highly underdeveloped. Herein, a library of over 50 peptoids containing a wide variety of chemical functionalities has been prepared and biologically evaluated against a range of protozoan parasitic targets. Selected members of the peptoid library were found to have potent anti-parasitic activity and good selectivity indices (SI). For example, peptoid 29 [NamyNspeNspe)(NhArgNspeNspe)]2 had an IC50 of 0.05 μM against Plasmodium falciparum and a SI > 100.

Antiparasitic↗

Genome-wide fetalization of enhancer architecture in heart disease

Heart disease is associated with re-expression of key transcription factors normally active only during prenatal development of the heart. However, the impact of this reactivation on the regulatory landscape in heart disease is unclear. Here, we use RNA-seq and ChIP-seq targeting a histone modification associated with active transcriptional enhancers to generate genome-wide enhancer maps from left ventricle tissue from up to 26 healthy controls, 18 individuals with idiopathic dilated cardiomyopathy (DCM), and five fetal hearts. Healthy individuals have a highly reproducible epigenomic landscape, consisting of more than 33,000 predicted heart enhancers. In contrast, we observe reproducible disease-associated changes in activity at 6,850 predicted heart enhancers. Combined analysis of adult and fetal samples reveals that the heart disease epigenome and transcriptome both acquire fetal-like characteristics, with 3,400 individual enhancers sharing fetal regulatory properties. We also provide a comprehensive data resource (http://heart.lbl.gov) for the mechanistic exploration of DCM etiology.

60 APPLIED LIFE SCIENCES↗

Alzheimer's disease and alpha-synuclein pathology in the olfactory bulbs of infants, children, teens and adults ≤ 40 years in Metropolitan Mexico City. APOE4 carriers at higher risk of suicide accelerate their olfactory bulb pathology

Highlights: • Air pollution targets olfactory bulbs in young city dwellers. • Olfactory bulb hyperphosphorylated tau and Lewy neurites are present in Mexico City toddlers. • APOE4 carriers accelerate their OB pathology and have 4.7 times higher suicide odds v APOE3. • Olfactory testing may aid in identifying young persons at high risk for neurodegenerative disease. • Early neuroprotective interventions in PM{sub 2.5} and CDNP's exposed individuals ≤ 20 years are critical. There is growing evidence that air pollution is a risk factor for a number of neurodegenerative diseases, most notably Alzheimer's (AD) and Parkinson's (PD). It is generally assumed that the pathology of these diseases arises only later in life and commonly begins within olfactory eloquent pathways prior to the onset of the classical clinical symptoms. The present study demonstrates that chronic exposure to high levels of air pollution results in AD- and PD-related pathology within the olfactory bulbs of children and relatively young adults ages 11 months to 40 years. The olfactory bulbs (OBs) of 179 residents of highly polluted Metropolitan Mexico City (MMC) were evaluated for AD- and alpha-synuclein-related pathology. Even in toddlers, hyperphosphorylated tau (hTau) and Lewy neurites (LN) were identified in the OBs. By the second decade, 84% of the bulbs exhibited hTau (48/57), 68% LNs and vascular amyloid (39/57) and 36% (21/57) diffuse amyloid plaques. OB active endothelial phagocytosis of red blood cell fragments containing combustion-derived nanoparticles (CDNPs) and the neurovascular unit damage were associated with myelinated and unmyelinated axonal damage. OB hTau neurites were associated mostly with pretangle stages 1a and 1b in subjects ≤ 20 years of age, strongly suggesting olfactory deficits could potentially be an early guide of AD pretangle subcortical and cortical hTau. APOE4 versus APOE3 carriers were 6–13 times more likely to exhibit OB vascular amyloid, neuronal amyloid accumulation, alpha-synuclein aggregates, hTau neurofibrillary tangles, and neurites. Remarkably, APOE4 carriers were 4.57 times more likely than non-carriers to die by suicide. The present findings, along with previous data that over a third of clinically healthy MMC teens and young adults exhibit low scores on an odor identification test, support the concept that olfactory testing may aid in identifying young people at high risk for neurodegenerative diseases. Moreover, results strongly support early neuroprotective interventions in fine particulate matter (PM{sub 2.5}) and CDNP's exposed individuals ≤ 20 years of age, and the critical need for air pollution control.

54 ENVIRONMENTAL SCIENCES↗

Projections for temperature-related years of life lost from cardiovascular diseases in the elderly in a Chinese city with typical subtropical climate

Highlights: • First evidence on temperature-related cardiovascular diseases’ YLL in the elderly. • An important dual problem of climate change and aging was investigated. • Adaptation of the population to global warming was taken into consideration. • Heat-related YLL will increase tremendously even considering 30% adaptation. Extreme temperature is an important risk factor for cardiovascular diseases, and the elderly are particularly vulnerable to temperature variation. Global warming and the increasingly aging population are two major global challenges for human health; thus, an urgent need exists to project the temperature-related cardiovascular disease burden regarding both of the aforementioned factors. We aimed to the project temperature-related burden of cardiovascular diseases using years of life lost (YLL) in the elderly in a Chinese city with typical subtropical climate.

54 ENVIRONMENTAL SCIENCES↗

Lung Cancer and Heart Disease Risks Associated With Low-Dose Pulmonary Radiotherapy to COVID-19 Patients With Different Background Risks

The respiratory disease COVID-19 reached global pandemic status in 2020. Excessive inflammation is believed to result in the most severe symptoms and death from this disease. Because treatment options for patients with severe COVID-19 related pulmonary symptoms remain limited, whole-lung low-dose radiation therapy is being evaluated as an anti-inflammatory modality. However, there is concern about the long-term risks associated with low-dose pulmonary irradiation. To help quantify the benefit-risk balance of low-dose radiation therapy for COVID-19, we estimated radiation-induced lifetime risks of both lung cancer and heart disease (major coronary events) for patients of different sexes, treated at ages 50 to 85, with and without other relevant risk factors (cigarette smoking and baseline heart disease risk).

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer’s and coronary disease pathways

Identification of proteins dysregulated by COVID-19 infection is critically important for better understanding of its pathophysiology, building prognostic models, and identifying new targets. Plasma proteomic profiling of 4,301 proteins was performed in two independent datasets and tested for the association for three COVID-19 outcomes (infection, ventilation, and death). We identified 1,449 proteins consistently associated in both datasets with any of these three outcomes. We subsequently created highly accurate models that distinctively predict infection, ventilation, and death. These proteins were enriched in specific biological processes including cytokine signaling, Alzheimer’s disease, and coronary artery disease. Mendelian randomization and gene network analyses identified eight causal proteins and 141 highly connected hub proteins including 35 with known drug targets. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes, reveal their relationship to Alzheimer’s disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.

60 APPLIED LIFE SCIENCES↗

Evaluating disease surveillance strategies for early outbreak detection in contact networks with varying community structure

Disease surveillance systems allow public health agencies to respond to emerging diseases before they become widespread. Developing such systems requires identifying optimal ways to monitor in the context of an epidemic outbreak; this problem is known as sensor selection. Contact networks represent the dynamics of interaction in a population and are used to model how a disease spreads in a population and to explore strategies of sensor selection. We evaluated five sensor selection strategies on their ability to provide an early warning of a COVID-like outbreak in synthetic contact networks encapsulated in four network scenarios. Three of these scenarios assessed different aspects of community structure. The fourth scenario employed a contact network representing the population and interactions of 6.8 million people in New York City, constructed from an agent-based simulation using census and transportation data. This scenario exemplifies how sensor selection strategies may perform in a real-world, urban context. Our findings suggest that the choice of the optimal strategy depends heavily on the community structure of the network. Strategies that select highly connected nodes or maximize network coverage are the optimal surveillance strategy for outbreak detection in many network community structures. However, a naive implementation of these strategies may fail to provide an early warning at all—including in the New York City scenario. Moreover, these methods are impractical for real-world use as they require knowledge of the underlying contact network. Instead, a selection strategy that starts with a set of random nodes and then performs a random walk through a chain of neighbors reliably provides early warnings without requiring prior knowledge of the network. We find this method, called “random chain”, to be the most pragmatic for implementation in a real-world disease surveillance context.

60 APPLIED LIFE SCIENCES↗

Predicting Kyasanur forest disease in resource-limited settings using event-based surveillance and transfer learning

In recent years, the reports of Kyasanur forest disease (KFD) breaking endemic barriers by spreading to new regions and crossing state boundaries is alarming. Effective disease surveillance and reporting systems are lacking for this emerging zoonosis, hence hindering control and prevention efforts. We compared time-series models using weather data with and without Event-Based Surveillance (EBS) information, i.e., news media reports and internet search trends, to predict monthly KFD cases in humans. We fitted Extreme Gradient Boosting (XGB) and Long Short-Term Memory models at the national and regional levels. We utilized the rich epidemiological data from endemic regions by applying Transfer Learning (TL) techniques to predict KFD cases in new outbreak regions where disease surveillance information was scarce. Overall, the inclusion of EBS data, in addition to the weather data, substantially increased the prediction performance across all models. The XGB method produced the best predictions at the national and regional levels. The TL techniques outperformed baseline models in predicting KFD in new outbreak regions. Novel sources of data and advanced machine-learning approaches, e.g., EBS and TL, show great potential towards increasing disease prediction capabilities in data-scarce scenarios and/or resource-limited settings, for better-informed decisions in the face of emerging zoonotic threats.

60 APPLIED LIFE SCIENCES↗

Climate change, malaria and neglected tropical diseases: a scoping review

Abstract To explore the effects of climate change on malaria and 20 neglected tropical diseases (NTDs), and potential effect amelioration through mitigation and adaptation, we searched for papers published from January 2010 to October 2023. We descriptively synthesised extracted data. We analysed numbers of papers meeting our inclusion criteria by country and national disease burden, healthcare access and quality index (HAQI), as well as by climate vulnerability score. From 42 693 retrieved records, 1543 full-text papers were assessed. Of 511 papers meeting the inclusion criteria, 185 studied malaria, 181 dengue and chikungunya and 53 leishmaniasis; other NTDs were relatively understudied. Mitigation was considered in 174 papers (34%) and adaption strategies in 24 (5%). Amplitude and direction of effects of climate change on malaria and NTDs are likely to vary by disease and location, be non-linear and evolve over time. Available analyses do not allow confident prediction of the overall global impact of climate change on these diseases. For dengue and chikungunya and the group of non-vector-borne NTDs, the literature privileged consideration of current low-burden countries with a high HAQI. No leishmaniasis papers considered outcomes in East Africa. Comprehensive, collaborative and standardised modelling efforts are needed to better understand how climate change will directly and indirectly affect malaria and NTDs.

60 APPLIED LIFE SCIENCES↗

Assessing complexity and dynamics in epidemics: geographical barriers and facilitators of foot-and-mouth disease dissemination

Introduction: Physical and non-physical processes that occur in nature may influence biological processes, such as dissemination of infectious diseases. However, such processes may be hard to detect when they are complex systems. Because complexity is a dynamic and non-linear interaction among numerous elements and structural levels in which specific effects are not necessarily linked to any one specific element, cause-effect connections are rarely or poorly observed. Methods: To test this hypothesis, the complex and dynamic properties of geo-biological data were explored with high-resolution epidemiological data collected in the 2001 Uruguayan foot-and-mouth disease (FMD) epizootic that mainly affected cattle. County-level data on cases, farm density, road density, river density, and the ratio of road (or river) length/county perimeter were analyzed with an open-ended procedure that identified geographical clustering in the first 11 epidemic weeks. Two questions were asked: (i) do geo-referenced epidemiologic data display complex properties? and (ii) can such properties facilitate or prevent disease dissemination? Results: Emergent patterns were detected when complex data structures were analyzed, which were not observed when variables were assessed individually. Complex properties–including data circularity–were demonstrated. The emergent patterns helped identify 11 counties as ‘disseminators’ or ‘facilitators’ (F) and 264 counties as ‘barriers’ (B) of epidemic spread. In the early epidemic phase, F and B counties differed in terms of road density and FMD case density. Focusing on non-biological, geographical data, a second analysis indicated that complex relationships may identify B-like counties even before epidemics occur. Discussion: Geographical barriers and/or promoters of disease dispersal may precede the introduction of emerging pathogens. If corroborated, the analysis of geo-referenced complexity may support anticipatory epidemiological policies.

60 APPLIED LIFE SCIENCES↗

MicroRNAs as biomarkers of diabetic retinopathy and disease progression

Diabetes mellitus, together with its complications, has been increasing in prevalence worldwide. Its complications include cardiovascular disease (e.g., myocardial infarction, stroke), neuropathy, nephropathy, and eye complications (e.g., glaucoma, cataracts, retinopathy, and macular edema). In patients with either type 1 or type 2 diabetes mellitus, diabetic retinopathy is the leading cause of visual impairment or blindness. It is characterized by progressive changes in the retinal microvasculature. The progression from nonproliferative diabetic retinopathy to a more advanced stage of moderate to severe nonproliferative diabetic retinopathy and proliferative diabetic retinopathy occurs very quickly after diagnosis of mild nonproliferative diabetic retinopathy. The etiology of diabetic retinopathy is unclear, and present treatments have limited effectiveness. Currently diabetic retinopathy can only be diagnosed by a trained specialist, which reduces the population that can be examined. A screening biomarker of diabetic retinopathy with high sensitivity and specificity would aid considerably in identifying those individuals in need of clinical assessment and treatment. The majority of the studies reviewed identified specific microRNAs in blood serum/plasma able to distinguish diabetic patients with retinopathy from those without retinopathy and for the progresion of the disease from nonproliferative diabetic retinopathy to proliferative diabetic retinopathy. In addition, certain microRNAs in vitreous humor were dysregulated in proliferative diabetic retinopathy compared to controls. A very high percentage of patients with diabetic retinopathy develop Alzheimer’s disease. Thus, identifying diabetic retinopathy by measurement of suitable biomarkers would also enable better screening and treatment of those individuals at risk of Alzheimer’s disease.

59 BASIC BIOLOGICAL SCIENCES↗

Altered microRNA expression in animal models of Huntington’s disease and potential therapeutic strategies

A review of recent animal models of Huntington’s disease showed many microRNAs had altered expression levels in the striatum and cerebral cortex, and which were mostly downregulated. Among the altered microRNAs were miR-9/9*, miR-29b, miR-124a, miR-132, miR-128, miR-139, miR-122, miR-138, miR-23b, miR-135b, miR-181 (all downregulated) and miR-448 (upregulated), and similar changes had been previously found in Huntington’s disease patients. In the animal cell studies, the altered microRNAs included miR-9, miR-9*, miR-135b, miR-222 (all downregulated) and miR-214 (upregulated). In the animal models, overexpression of miR-155 and miR-196a caused a decrease in mutant huntingtin mRNA and protein level, lowered the mutant huntingtin aggregates in striatum and cortex, and improved performance in behavioral tests. Improved performance in behavioral tests also occurred with overexpression of miR-132 and miR-124. In the animal cell models, overexpression of miR-22 increased the viability of rat primary cortical and striatal neurons infected with mutant huntingtin and decreased huntingtin -enriched foci of ≥ 2 µm. Also, overexpression of miR-22 enhanced the survival of rat primary striatal neurons treated with 3-nitropropionic acid. Exogenous expression of miR-214, miR-146a, miR-150, and miR-125b decreased endogenous expression of huntingtin mRNA and protein in Hdh Q111 /Hdh Q111 cells. Further studies with animal models of Huntington’s disease are warranted to validate these findings and identify specific microRNAs whose overexpression inhibits the production of mutant huntingtin protein and other harmful processes and may provide a more effective means of treating Huntington’s disease in patients and slowing its progression.

59 BASIC BIOLOGICAL SCIENCES↗

Plant Disease Detection: Exploring Applications in Hyperspectral Imaging and Machine Learning for Agriculture

The threat of crop disease on food security and agriculture is projected to escalate, leading to reduced crop yields, global economic loss, and endangered food availability to vulnerable populations. Early identification of plant disease is crucial to combatting the crisis but traditional manual methods for disease detection are laborious and may miss early signs of infection. The proposed solution suggests equipping a drone with a hyperspectral camera to collect images and analyzing the data with neural networks trained to flag and classify infected plants. This approach offers a faster, more accurate, and potentially more cost-effective alternative to current practices. While the expensive and complex nature of hyperspectral imaging (HSI) may be an obstacle to the adoption of the drone, rapidly advancing technologies compounded with rental-based usage may make these tools simpler, cheaper, and more accessible to a wider audience. The research further discusses the potential for automated flight paths and the expansion of disease detection to a broader range of crops.

plant disease detection↗