Comparative Analysis of Vectorial Capacity Among Triatoma brasiliensis brasiliensis, Triatoma juazeirensis, and Their Experimental Hybrids

The existence of a natural hybridization zone of members of the Triatoma brasiliensis complex in Pernambuco, a Brazilian state with areas highly infested by Trypanosoma cruzi vectors, raised questions to be studied about the vectorial capacity of these hybrids. Recently, it was demonstrated that experimental hybrids of T. brasiliensis brasiliensis and Triatoma juazeirensis present vectorial competence superior to that of the parental species. The objective of the present study was to compare bionomic aspects related to the vectorial capacity of T. b. brasiliensis, T. juazeirensis, and their experimental hybrids. Feeding and defecation behavior patterns in fifth instar nymphs were comparatively analyzed between four groups, two parental and two hybrids, respectively: T. b. brasiliensis, T. juazeirensis, Hjb (♀ T. juazeirensis × ♂ T. b. brasiliensis), and Hbj (♀ T. b. brasiliensis × ♂ T. juazeirensis). Fifteen newly molted fifth instar nymphs from each of the mentioned groups were previously subjected to a period of fasting for 10 days and individually kept in identified bottles. In the experiment, the insects were placed in a jar containing a mouse immobilized in nylon mesh, in accordance with the guidelines of the animal ethics committee. The following variables were observed: 1-total number of feedings carried out; 2-time to start feeding; 3-duration of feeding and weight acquired; 4-defecations during feeding; 5-defecation within one minute after cessation of feeding; 6-defecation within ten minutes after cessation of feeding; 7-defecation behavior. Specimens from all groups demonstrated voracity, starting their meal immediately after contact with the mouse, and most of the insects defecated immediately after feeding, with 78% of the insects defecating within 30 s. The results obtained suggest that T. brasiliensis, T. juazeirensis, and their experimental hybrids presented bionomic characteristics compatible with the species considered good vectors in the literature. However, T. b. brasiliensis and T. juazeirensis demonstrated even more effective characteristics for T. cruzi transmission regarding their feeding and defecation patterns when compared to their hybrids.

Opportunities and Challenges in Applying AI to Evolutionary Morphology

Artificial intelligence (AI) is poised to revolutionize many aspects of science, including the study of evolutionary morphology. While classical AI methods such as principal component analysis and cluster analysis have been commonplace in the study of evolutionary morphology for decades, recent years have seen increasing application of deep learning to ecology and evolutionary biology. As digitized specimen databases become increasingly prevalent and openly available, AI is offering vast new potential to circumvent long-standing barriers to rapid, big data analysis of phenotypes. Here, we review the current state of AI methods available for the study of evolutionary morphology, which are most developed in the area of data acquisition and processing. We introduce the main available AI techniques, categorizing them into 3 stages based on their order of appearance: (1) machine learning, (2) deep learning, and (3) the most recent advancements in large-scale models and multimodal learning. Next, we present case studies of existing approaches using AI for evolutionary morphology, including image capture and segmentation, feature recognition, morphometrics, and phylogenetics. We then discuss the prospectus for near-term advances in specific areas of inquiry within this field, including the potential of new AI methods that have not yet been applied to the study of morphological evolution. In particular, we note key areas where AI remains underutilized and could be used to enhance studies of evolutionary morphology. This combination of current methods and potential developments has the capacity to transform the evolutionary analysis of the organismal phenotype into evolutionary phenomics, leading to an era of "big data" that aligns the study of phenotypes with genomics and other areas of bioinformatics.

Precision Prediction for Dengue Fever in Singapore: A Machine Learning Approach Incorporating Meteorological Data

OBJECTIVE

This study aimed to improve dengue fever predictions in Singapore using a machine learning model that incorporates meteorological data, addressing the current methodological limitations by examining the intricate relationships between weather changes and dengue transmission.

METHOD

Using weekly dengue case and meteorological data from 2012 to 2022, the data was preprocessed and analyzed using various machine learning algorithms, including General Linear Model (GLM), Support Vector Machine (SVM), Gradient Boosting Machine (GBM), Decision Tree (DT), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) algorithms. Performance metrics such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R-squared (R2) were employed.

RESULTS

From 2012 to 2022, there was a total of 164,333 cases of dengue fever. Singapore witnessed a fluctuating number of dengue cases, peaking notably in 2020 and revealing a strong seasonality between March and July. An analysis of meteorological data points highlighted connections between certain climate variables and dengue fever outbreaks. The correlation analyses suggested significant associations between dengue cases and specific weather factors such as solar radiation, solar energy, and UV index. For disease predictions, the XGBoost model showed the best performance with an MAE = 89.12, RMSE = 156.07, and R2 = 0.83, identifying time as the primary factor, while 19 key predictors showed non-linear associations with dengue transmission. This underscores the significant role of environmental conditions, including cloud cover and rainfall, in dengue propagation.

CONCLUSION

In the last decade, meteorological factors have significantly influenced dengue transmission in Singapore. This research, using the XGBoost model, highlights the key predictors like time and cloud cover in understanding dengue's complex dynamics. By employing advanced algorithms, our study offers insights into dengue predictive models and the importance of careful model selection. These results can inform public health strategies, aiming to improve dengue control in Singapore and comparable regions.

High Trypanosoma cruzi prevalence in armadillo (Zaedyus pichiy; Xenarthra: Chlamyphoridae) populations from Mendoza, Argentina

Armadillos are considered important reservoir hosts for Trypanosoma cruzi, the causative agent of Chagas disease. The first report of T. cruzi infection in pichis (Zaedyus pichiy), a small armadillo species endemic to central Argentina and Chile, dates back to 1935. However, more recent reports on T. cruzi in this species are scarce. The objective of this study was to assess T. cruzi infection and parasite load in Z. pichiy from Mendoza Province, an area endemic to human Chagas disease. Blood samples were obtained in 2014-2016 from pichis from Lavalle (low Monte), Malargüe (Patagonian steppe), and San Carlos (ecotone) departments, Mendoza Province, Argentina. The detection and quantification of T. cruzi was performed through qPCR amplification using satellite primers. Of the 265 analyzed samples, 201 (76%) were positive for T. cruzi. Parasite loads varied between < 0.1-55.8 parasite-equivalents/mL (par-eq/mL), with a median of 1.1 par-eq/mL in quantifiable samples. The prevalence was similar in Malargüe and Lavalle (85-94%), but significantly lower in pichis from San Carlos (50%). Animals from Lavalle captured after hibernation had significantly higher parasite loads (median 2.0 par-eq/mL). In Malargüe, T. cruzi infection and parasite loads were significantly lower before than after hibernation in 2016. The high prevalence and low median parasite load suggest a chronic and persistent infection of T. cruzi in pichis. Regional differences and a marked increase in precipitation during 2015-2016 could have influenced annual and seasonal infection rates of this vector-borne disease.

Life History Data of Dipetalogaster maxima (Hemiptera: Reduviidae)

Dipetalogaster maxima (Uhler) is a triatomine species that has been found to be infected by Trypanosoma cruzi Chagas in the habitats of the most important tourist areas of Mexico. Its behavior and vectorial capacity have been scarcely studied, although such information is necessary to reliably estimate the importance of this species as a vector of T. cruzi in its distribution area. This study reports biological parameters related to the vectorial capacity of D. maxima. In particular, the egg-to-adult development time, number of blood meals required to molt, accumulative mortality, time to beginning of feeding, feeding and defecation times, fecundity, and fertility were examined. D. maxima took a median of 211 d to develop from egg to adult, requiring 11 meals in total. Almost two-thirds (63%) of specimens died during the cycle. The time to beginning of feeding was 1 min in all instars. Feeding times varied from 14 to 27 min. Most nymphs (except first-instar) defecated when feeding or immediately thereafter. A mean of 0.7 eggs/♀/day was recorded, with an eclosion rate of 27.3%. Five of the eight studied parameters (mainly defecation delay) suggest the remarkable potential vectorial capacity of D. maxima, so it is necessary to maintain permanent surveillance of domiciliary populations of D. maxima, because they may be infected with T. cruzi.

Benefits and costs of immune memory in Rhodnius prolixus against Trypanosoma cruzi

There is increasing evidence supporting the immune memory in invertebrates, but the studies are relatively neglected in insect vectors other than mosquitoes. Therefore, we tested two hypotheses: 1) Rhodnius prolixus insects possess immune memory against Trypanosoma cruzi, and 2) their immune memory is costly. The Dm28c and Y strains of T. cruzi were used, the former being more infective than the latter. On the one hand, the triatomines subjected to dual challenges with the Dm28c strain did not show significant differences in survival than those of the heterologous challenge groups control-Dm28c and Y-Dm28c. On the other hand, the insects survived longer after a dual Y-Y challenge than after the corresponding heterologous challenge (control-Y). The Y-Y, Dm28c-Y, and naïve groups showed similar survival. There was more prolonged survival following the Y-Y versus Dm28c-Dm28c dual challenge. The Dm28c-Dm28c group exhibited moulting sooner than the control-Dm28c or naïve group. In contrast, there were no differences in the probability of moulting between the Y-Y and naïve groups. The results suggest that triatomines have immune memory against the Y but not the Dm28c strain. Further investigation on triatomine and T. cruzi interaction is needed to determine if infectivity accelerates or delay growth due to innate immune memory.

Biological Parameters of Two Triatoma protracta Subspecies (Hemiptera: Reduviidae)

In recent years, concerns about Chagas disease in the United States have increased. Triatomine bug (Hemiptera: Reduviidae) populations are the vectors of the parasite Trypanosoma cruzi Chagas (Trypanosomatida: Trypanosomatidae), which causes Chagas disease, although the route of transmission is considered inefficient in United States. However, more studies on triatomine feeding and defecation behavior are needed. In this study, six related biological parameters from two populations of Triatoma protracta protracta (Uhler) and T. p. woodi (Uhler) from Mexican locations near the U.S. border were evaluated. The four population life cycles were less than 6 mo (161-171 d), with 9-10 blood meals needed to molt. Mortality rates were similar (31-38%) among the four populations. Triatoma p. woodi from Hidalgo, Coahuila was the most aggressive one. Feeding times were over 10 min, increasing with instar in all populations. Defecation behaviors varied among populations. High percentages of male and female fourth- and fifth-instar nymphs of T. p. protracta from Imuris and both populations of T. p. woodi defecated immediately after or <1 min of feeding. Lower percentages were observed for T. p. protracta from Jacumé. Because most parameters were similar among the four populations, independent of their subspecies and their geographic origin, we considered that T. p. protracta and T. p. woodi are efficient vectors of T. cruzi. In contrast, defecation patterns were noticeably different among some of the four triatomine populations studied. Our results highlight the importance of studying the biological parameters of local triatomine populations. They also contribute to increasing the knowledge of North American triatomine behavior and defecation patterns.

Biological Parameters of Three Populations of Triatoma dimidiata s. s. (Hemiptera: Reduviidae) From Western Mexico

Chagas disease is a very important vector-borne disease in México, and Triatoma dimidiata sensu stricto (Latreille) is one of the most important vectors of Trypanosoma cruzi Chagas, mainly in southern and central states. In the Pacific Coast states with the highest prevalence of human T. cruzi infection, T. dimidiata s. s. is considered as a secondary vector. However, the vectorial capacity of those populations has not been studied. Therefore, the vector characteristics of three populations of T. dimidiata s. s. in western México were evaluated in this study. The populations were maintained in the laboratory at 27 ± 1°C and 75% ± 5% RH with a 12:12 h (light:dark) regime, fed on rabbits in a fortnight basis. The development times were short (172-238 d), and the number of bloodmeals to molt was low (11). Mortality was moderate (36-45%), the onset of feeding was relatively rapid (0.5-1.7 min), and feedings were extended (>15 min). More than 40% of individuals in most instars defecated in one of three categories: <1 min when feeding (5-37.9%), immediately after feeding (9-28.6%), or in <1 min post feeding (7-25.8%). The median number of laid eggs was high (over 2.5) in the three populations, as were the egg eclosion rates (>86%). Thus, the T. dimidiata s. s. in the three populations are potentially efficient vectors of T. cruzi and could contribute to the high prevalence of infection in human populations in western México.

Chromatic and Morphological Differentiation of Triatoma dimidiata (Hemiptera: Reduviidae) with Land Use Diversity in El Salvador

Chagas disease is caused by the parasite Trypanosoma cruzi, which is transmitted by insect-vectors in the taxonomic subfamily Triatominae and affects approximately 8,000,000 people world-wide. Current mitigation strategies for Chagas focus on insecticides, infrastructure improvements, and management of symptoms, which are largely unsustainable in underserved communities where the disease is widespread. Transmission patterns of vector-borne diseases are known to adaptively respond to habitat change; as such, the objective of our study was to evaluate how the physical characteristics of Triatoma dimidiata would vary in relation to land use in El Salvador. We hypothesized that the color and morphology of T. dimidiata would change with municipal levels of urban and natural green space, natural green space, and agricultural space, as well as municipal diversity, richness, and evenness of land use types. Our results characterize how T. dimidiata color and morphology vary directly with anthropogenic changes to natural and agricultural environments, which are reflective of a highly adaptable population primed to respond to environmental change. Mitigation studies of Chagas disease should exploit the relationships between anthropogenic land use and T. dimidiata morphology to evaluate how the transmission pattern of T. cruzi and Chagas disease symptomology are impacted.