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Urbanization is a phenomenon where humans concentrate in high densities and consume more per capita energy than in rural areas, imposing high pressures on biodiversity and ecosystem services. Although Mexico is recognized as a megadiverse country and there is an understanding of ecological and evolutionary processes underlying this high diversity, only some efforts have been devoted to understanding how urban biodiversity has been shaped. Here, we compiled a set of socioeconomic and ecological variables to explore macroecological patterns in urban biodiversity across Mexican municipalities. Specifically, we tested the species-area relationships (SAR) between rural and urban areas across municipalities and evaluated the relative role of different socioeconomic and ecological variables driving urban species richness for terrestrial vertebrates. Finally, we explored the exposure of Mexican municipalities to future urban expansion, the urban heat island (UHI) effect, and climate change. Urban and rural settlements show differences in the shape of SAR models. We found that urban area, size of the network of urban protected areas, the number of ecoregions, and GDP explained the urban total species richness relatively well. Mexican cities in the northeast region may be at a higher risk than others. Based on our analyses, policymakers should identify priority urban conservation sites in cities with high species richness and low urbanization development. These actions would alleviate future urban biodiversity loss in these growing cities., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Velasco et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Although the utility of Ecological Niche Models (ENM) and Species Distribution Models (SDM) has been demonstrated in many ecological applications, their suitability for modelling epidemics or pandemics, such as SARS-Cov-2, has been questioned. In this paper, contrary to this viewpoint, we show that ENMs and SDMs can be created that can describe the evolution of pandemics, both in space and time. As an illustrative use case, we create models for predicting confirmed cases of COVID-19, viewed as our target "species", in Mexico through 2020 and 2021, showing that the models are predictive in both space and time. In order to achieve this, we extend a recently developed Bayesian framework for niche modelling, to include: (i) dynamic, non-equilibrium "species" distributions; (ii) a wider set of habitat variables, including behavioural, socio-economic and socio-demographic variables, as well as standard climatic variables; (iii) distinct models and associated niches for different species characteristics, showing how the niche, as deduced through presence-absence data, can differ from that deduced from abundance data. We show that the niche associated with those places with the highest abundance of cases has been highly conserved throughout the pandemic, while the inferred niche associated with presence of cases has been changing. Finally, we show how causal chains can be inferred and confounding identified by showing that behavioural and social factors are much more predictive than climate and that, further, the latter is confounded by the former.

(1) Background: Chagas disease is the main neglected tropical disease in America. It is estimated that around 6 million people are currently infected with the parasite in Latin America, and 25 million live in endemic areas with active transmission. The disease causes an estimated economic loss of USD 24 billion dollars annually, with a loss of 75,200 working years per year of life; it is responsible for around ~12,000 deaths annually. Although Mexico is an endemic country that recorded 10,186 new cases of Chagas disease during the period of 1990-2017, few studies have evaluated the genetic diversity of genes that could be involved in the prophylaxis and/or diagnosis of the parasite. One of the possible candidates proposed as a vaccine target is the 24 kDa trypomastigote excretory-secretory protein, Tc24, whose protection is linked to the stimulation of T. cruzi -specific CD8 + immune responses. (2) Methods: The aim of the present study was to evaluate the fine-scale genetic diversity and structure of Tc24 in T. cruzi isolates from Mexico, and to compare them with other populations reported in the Americas with the aim to reconsider the potential role of Tc24 as a key candidate for the prophylaxis and improvement of the diagnosis of Chagas disease in Mexico. (3) Results: Of the 25 Mexican isolates analysed, 48% (12) were recovered from humans and 24% (6) recovered from Triatoma barberi and Triatoma dimidiata . Phylogenetic inferences revealed a polytomy in the T. cruzi clade with two defined subgroups, one formed by all sequences of the DTU I and the other formed by DTU II-VI; both subgroups had high branch support. Genetic population analysis detected a single (monomorphic) haplotype of TcI throughout the entire distribution across both Mexico and South America. This information was supported by Nei's pairwise distances, where the sequences of TcI showed no genetic differences. (4) Conclusions: Given that both previous studies and the findings of the present work confirmed that TcI is the only genotype detected from human isolates obtained from various states of Mexico, and that there is no significant genetic variability in any of them, it is possible to propose the development of in silico strategies for the production of antigens that optimise the diagnosis of Chagas disease, such as quantitative ELISA methods that use this region of Tc24.

Objective: To describe the speech pattern of patients with hereditary Spastic Paraplegia type 4 (SPG4) and correlated it with their clinical data., Methods: Cross-sectional study was carried out in two university hospitals in Brazil. Two groups participated in the study: the case group (n = 28) with a confirmed genetic diagnosis for SPG4 and a control group (n = 17) matched for sex and age. The speech assessment of both groups included: speech task recording, acoustic analysis, and auditory-perceptual analysis. In addition, disease severity was assessed with the Spastic Paraplegia Rating Scale (SPRS)., Results: In the auditory-perceptual analysis, 53.5% (n = 15) of individuals with SPG4 were dysarthric, with mild to moderate changes in the subsystems of phonation and articulation. On acoustic analysis, SPG4 subjects' performances were worse in measurements related to breathing (maximum phonation time) and articulation (speech rate, articulation rate). The articulation variables (speech rate, articulation rate) are related to the age of onset of the first motor symptom., Conclusion: Dysarthria in SPG4 is frequent and mild, and it did not evolve in conjunction with more advanced motor diseases. This data suggest that diagnosed patients should be screened and referred for speech therapy evaluation and those pathophysiological mechanisms of speech involvement may differ from the length-dependent degeneration of the corticospinal tract., Competing Interests: Declaration of Competing Interest The authors declare no conflicts of interest., (Copyright © 2022 HCFMUSP. Published by Elsevier España, S.L.U. All rights reserved.)

Chagas disease, caused by the protozoa Trypanosoma cruzi , is an important yet neglected disease that represents a severe public health problem in the Americas. Although the alteration of natural habitats and climate change can favor the establishment of new transmission cycles for T. cruzi, the compound effect of human-modified landscapes and current climate change on the transmission dynamics of T. cruzi has until now received little attention. A better understanding of the relationship between these factors and T. cruzi presence is an important step towards finding ways to mitigate the future impact of this disease on human communities. Here, we assess how wild and domestic cycles of T. cruzi transmission are related to human-modified landscapes and climate conditions (LUCC-CC). Using a Bayesian datamining framework, we measured the correlations among the presence of T. cruzi transmission cycles (sylvatic, rural, and urban) and historical land use, land cover, and climate for the period 1985 to 2012. We then estimated the potential range changes of T. cruzi transmission cycles under future land-use and -cover change and climate change scenarios for 2050 and 2070 time-horizons, with respect to "green" (RCP 2.6), "business-as-usual" (RCP 4.5), and "worst-case" (RCP 8.5) scenarios, and four general circulation models. Our results show how sylvatic and domestic transmission cycles could have historically interacted through the potential exchange of wild triatomines (insect vectors of T. cruzi ) and mammals carrying T. cruzi , due to the proximity of human settlements (urban and rural) to natural habitats. However, T. cruzi transmission cycles in recent times (i.e., 2011) have undergone a domiciliation process where several triatomines have colonized and adapted to human dwellings and domestic species (e.g., dogs and cats) that can be the main blood sources for these triatomines. Accordingly, Chagas disease could become an emerging health problem in urban areas. Projecting potential future range shifts of T. cruzi transmission cycles under LUCC-CC scenarios we found for RCP 2.6 no expansion of favourable conditions for the presence of T. cruzi transmission cycles. However, for RCP 4.5 and 8.5, a significant range expansion of T. cruzi could be expected. We conclude that if sustainable goals are reached by appropriate changes in socio-economic and development policies we can expect no increase in suitable habitats for T. cruzi transmission cycles.

Given the significant impact of mosquito-borne flaviviruses (MBFVs) on both human and animal health, predicting their dynamics and understanding their transmission cycle is of the utmost importance. Usually, predictions about the distribution of priority pathogens, such as Dengue, Yellow fever, West Nile Virus and St. Louis encephalitis, relate abiotic elements to simple biotic components, such as a single causal agent. Furthermore, focusing on single pathogens neglects the possibility of interactions and the existence of common elements in the transmission cycles of multiple pathogens. A necessary, but not sufficient, condition that a mosquito be a vector of a MBFV is that it co-occurs with hosts of the pathogen. We therefore use a recently developed modeling framework, based on co-occurrence data, to infer potential biotic interactions between those mosquito and mammal species which have previously been identified as vectors or confirmed positives of at least one of the considered MBFVs. We thus create models for predicting the relative importance of mosquito species as potential vectors for each pathogen, and also for all pathogens together, using the known vectors to validate the models. We infer that various mosquito species are likely to be significant vectors, even though they have not currently been identified as such, and are likely to harbor multiple pathogens, again validating the predictions with known results. Besides the above "niche-based" viewpoint we also consider an assemblage-based analysis, wherein we use a community-identification algorithm to identify those mosquito and/or mammal species that form assemblages by dint of their significant degree of co-occurrence. The most cohesive assemblage includes important primary vectors, such as A. aegypti , A. albopictus , C. quinquefasciatus , C. pipiens and mammals with abundant populations that are well-adapted to human environments, such as the white-tailed deer ( Odocoileus virginianus ), peccary ( Tayassu pecari ), opossum ( Didelphis marsupialis ) and bats ( Artibeus lituratus and Sturnira lilium ). Our results suggest that this assemblage has an important role in the transmission dynamics of this viral group viewed as a complex multi-pathogen-vector-host system. By including biotic risk factors our approach also modifies the geographical risk profiles of the spatial distribution of MBFVs in Mexico relative to a consideration of only abiotic niche variables.

Objectives: Hereditary spastic paraplegias (HSP) are a group of genetic diseases characterized by lower limb spasticity with or without additional neurological features. Swallowing dysfunction is poorly studied in HSP and its presence can lead to significant respiratory and nutritional complications. The aim of this study was to evaluate the frequency and clinical characteristics of dysphagia in different types of HSP., Methods: A two-center cross-sectional prevalence study was performed. Genetically confirmed HSP patients were evaluated using the Northwestern Dysphagia Patient Check Sheet and the Functional Oral Intake Scale. In addition, self-perception of dysphagia was assessed by the Eat Assessment Tool-10 and the Swallowing Disturbance Questionnaire., Results: Thirty-six patients with spastic paraplegia type 4 (SPG4), five with SPG11, four with SPG5, four with cerebrotendinous xanthomatosis (CTX), three with SPG7, and two with SPG3A were evaluated. Mild to moderate oropharyngeal dysphagia was present in 3/5 (60%) of SPG11 and 2/4 (50%) of CTX patients. A single SPG4 (2%) and a single SPG7 (33%) patient had mild oropharyngeal dysphagia. All other evaluated patients presented with normal or functional swallowing., Conclusions: Clinically significant oropharyngeal dysphagia was only present in complicated forms of HSP Patients with SPG11 and CTX had the highest risks for dysphagia, suggesting that surveillance of swallowing function should be part of the management of patients with these disorders.

The mechanisms driving phenotypic evolution have been of interest to biologists since Darwin. Ecological release-wherein adaptive evolution occurs following relaxation of constraining selective pressures-and environmental filtering-wherein exaptive traits allow colonization of a new area-have been studied in several insular cases. Anolis lizards, which may exist in solitude or sympatry with multiple congeners, are an excellent system for evaluating whether ecological release and environmental filtering are associated with phenotypic shifts across phylogenetic and geographical scales. Insular solitary Anolis exhibit phenotypic differentiation in body size and sexual size dimorphism-SSD-through exaptive and adaptive evolution, respectively. But, the generality of these effects has not yet been addressed. Here, we analyse the evolution of body size and SSD relative to sympatry in mainland Anolis. We found that mainland species co-occurring with few congeners exhibit uniform body size and greater SSD relative to other random mainland assemblages, consistent with the insular solitary pattern. The locations of evolutionary shifts for both traits do not coincide with evolutionary transitions to decreased levels of sympatry. These results are consistent with exaptive environmental filtering but not adaptive ecological release. Future studies should be conducted at local scales to evaluate the role of these factors in the evolution of solitary existence in mainland and island species.

Background: Little is known about the cognitive profile of Hereditary Spastic Paraplegias (HSP), where most scientific attention has been given to motor features related to corticospinal tract degeneration. Objectives: We aimed to perform a broad characterization of the cognitive functions of patients with pure and complicated HSP as well as to determine the frequency of abnormal cognitive performances in the studied subtypes. Methods: A two-center cross-sectional case-control study was performed. All individuals underwent cognitive assessment through screening tests (Mini Mental State Examination-MEEM and Montreal Cognitive Assessment-MOCA) and tests to assess specific cognitive functions (Verbal fluency with phonological restriction-FAS; Verbal categorical fluency-FAS-cat and Rey's Verbal Auditory Learning Test -RAVLT). Results: Fifty four patients with genetically confirmed HSP diagnosis, 36 with spastic paraplegia type 4 (SPG4), 5 SPG11, 4 SPG5, 4 cerebrotendinous xanthomatosis (CTX), 3 SPG7 and 2 SPG3A, and 10 healthy, unrelated control subjects, with similar age, sex, and education participated in the study. SPG4 patients had worse performances in MOCA, FAS, FAS-cat, and RAVLT when compared to controls. Most SPG4 patients presented cognitive changes not compatible with dementia, performing poorly in memory, attention and executive functions. SPG5 patients scored lower in executive functions and memory, and SPG7 patients performed poorly on memory tasks. All evaluated cognitive functions were markedly altered in CTX and SPG11 patients. Conclusions: Cognitive abnormalities are frequent in HSP, being more severe in complicated forms. However, cognitive impairments of pure HSPs might impact patients' lives, decreasing families' socioeconomic status and contributing to the overall disease burden.

The modeling of ecological data that include both abiotic and biotic factors is fundamental to our understanding of ecosystems. Repositories of biodiversity data, such as GBIF, iDigBio, Atlas of Living Australia, and SNIB (Mexico's National System of Biodiversity Information), contain a great deal of information that can lead to knowledge discovery about ecosystems. However, there is a lack of tools with which to efficiently extract such knowledge. In this paper, we present SPECIES, an open, web-based platform designed to extract implicit information contained in large scale sets of ecological data. SPECIES is based on a tested methodology, wherein the correlations of variables of arbitrary type and spatial resolution, both biotic and abiotic, discrete and continuous, may be explored from both niche and network perspectives. In distinction to other modeling systems, SPECIES is a full stack exploratory tool that integrates the three basic components: data (which is incrementally growing), a statistical modeling and analysis engine, and an interactive visualization front end. Combined, these components provide a powerful tool that may guide ecologists toward new insights. SPECIES is optimized to support fast hypothesis prototyping and testing, analyzing thousands of biotic and abiotic variables, and presenting descriptive results to the user at different levels of detail. SPECIES is an open-access platform available online (http://species.conabio.gob.mx), that is, powerful, flexible, and easy to use. It allows for the exploration and incorporation of ecological data and its subsequent integration into predictive models for both potential ecological niche and geographic distribution. It also provides an ecosystemic, network-based analysis that may guide the researcher in identifying relations between different biota, such as the relation between disease vectors and potential disease hosts., Competing Interests: None declared.

Arboviruses are often maintained in complex cycles involving vertebrates such as mammals or birds and blood-feeding mosquitoes. However, the role of wildlife hosts in their emergence or re-emergence in human populations has received little attention. The recent emergence of Zika virus in America, and previous occurrences of chikungunya and dengue, forces us to confront a potential new disease-emergence phenomenon. Using a spatial data mining framework to identify potential biotic interactions, based on the degree of co-occurrence between different species, we identified those mammal species with the highest potential for establishing mammal-vector interactions, considering as principal vector Aedes aegypti. Seven of the top ten identified mammal species with highest potential were bats, with two of them having previously been confirmed as positive hosts for dengue in Mexico. We hope that this will raise interest of Mexican public health authorities and academic institutions to assess the role of wild hosts in the maintenance and spread of arboviruses.

Background: To evaluate the role of adipose tissue function on the association of fatty liver (FL) with impaired fasting glucose (IFG) or newly diagnosed type 2 diabetes mellitus (nT2D)., Methods: In 1264 subjects, computed tomography was used to evaluate FL and elevated visceral adipose tissue (VAT). Fasting plasma glucose, <5.6, 5.6-6.9 and ≥7 mmol/l, were used to defined normoglycemic (NG), IFG or nT2D, respectively. Elevated free fatty acids, low serum adiponectin levels and adipose tissue insulin resistance (Adipo-IR), were used as markers of adipose tissue dysfunction., Results: Compared to NG subjects, those with IFG or nT2D had higher prevalence of FL and elevated VAT. FL was found to be independently associated with IFG and nT2D. Adipo-IR increased the association between FL and IFG [OR: 2.46 (95% I.C.: 1.73-3.49) to 5.42 (3.11-9.41)], whereas low adiponectin levels had a higher effect on the FL and nT2D association [OR: 4.26 (2.18-8.34) to 8.53 (2.96-24.55)]., Conclusion: Fatty liver was independently associated with IFG and nT2D. Our results indicate for the first time, that adipose tissue dysfunction increases these associations.

Zoonoses are an important class of infectious diseases. An important element determining the impact of a zoonosis on domestic animal and human health is host range. Although for particular zoonoses some host species have been identified, until recently there have been no methods to predict those species most likely to be hosts or their relative importance. Complex inference networks infer potential biotic interactions between species using their degree of geographic co-occurrence, and have been posited as a potential tool for predicting disease hosts. Here we present the results of an interdisciplinary, empirical study to validate a model based on such networks for predicting hosts of Leishmania (L.) mexicana in Mexico. Using systematic sampling to validate the model predictions we identified 22 new species of host (34% of all species collected) with the probability to be a host strongly dependent on the probability of co-occurrence of vector and host. The results confirm that Leishmania (L.) mexicana is a generalist parasite but with a much wider host range than was previously thought. These results substantially change the geographic risk profile for Leishmaniasis and provide insights for the design of more efficient surveillance measures and a better understanding of potential dispersal scenarios., Competing Interests: The authors have declared that no competing interests exist.

Leishmania (Leishmania) mexicana causes cutaneous leishmaniasis, an endemic zoonosis affecting a growing number of patients in the southeastern states of Mexico. Some foci are found in shade-grown cocoa and coffee plantations, or near perennial forests that provide rich breeding grounds for the sand fly vectors, but also harbor a variety of bat species that live off the abundant fruits provided by these shade-giving trees. The close proximity between sand flies and bats makes their interaction feasible, yet bats infected with Leishmania (L.) mexicana have not been reported. Here we analyzed 420 bats from six states of Mexico that had reported patients with leishmaniasis. Tissues of bats, including skin, heart, liver and/or spleen were screened by PCR for Leishmania (L.) mexicana DNA. We found that 41 bats (9.77%), belonging to 13 species, showed positive PCR results in various tissues. The infected tissues showed no evidence of macroscopic lesions. Of the infected bats, 12 species were frugivorous, insectivorous or nectarivorous, and only one species was sanguivorous (Desmodus rotundus), and most of them belonged to the family Phyllostomidae. The eco-region where most of the infected bats were caught is the Gulf Coastal Plain of Chiapas and Tabasco. Through experimental infections of two Tadarida brasiliensis bats in captivity, we show that this species can harbor viable, infective Leishmania (L.) mexicana parasites that are capable of infecting BALB/c mice. We conclude that various species of bats belonging to the family Phyllostomidae are possible reservoir hosts for Leishmania (L.) mexicana, if it can be shown that such bats are infective for the sand fly vector. Further studies are needed to determine how these bats become infected, how long the parasite remains viable inside these potential hosts and whether they are infective to sand flies to fully evaluate their impact on disease epidemiology.

Objective: To analyze the participation of fatty liver (FL) in the association of metabolic syndrome (MS) with type 2 diabetes and coronary artery calcification (CAC)., Research Design and Methods: A total of 765 subjects (52% women) aged 30 to 75 years without clinical atherosclerosis were included in this study. MS was defined in accordance with the Adult Treatment Panel III (ATPIII) guidelines, while FL and CAC were identified by computed tomography., Results: There were increasing frequencies of type 2 diabetes and CAC in all three groups: control, MS without FL, and MS plus FL. Multivariable-adjusted logistic regression analyses showed that FL increased the association of MS with type 2 diabetes in both women [odds ratio 10.6 (95% CI 3.4-33.7)] and men [12.1 (4.1-36.1)]. In women, FL also increased the association of MS with CAC [2.34 (1.07-5.12)]., Conclusions: FL increases the association of MS with type 2 diabetes and subclinical atherosclerosis.

Background: Climate change is increasingly being implicated in species' range shifts throughout the world, including those of important vector and reservoir species for infectious diseases. In North America (México, United States, and Canada), leishmaniasis is a vector-borne disease that is autochthonous in México and Texas and has begun to expand its range northward. Further expansion to the north may be facilitated by climate change as more habitat becomes suitable for vector and reservoir species for leishmaniasis., Methods and Findings: The analysis began with the construction of ecological niche models using a maximum entropy algorithm for the distribution of two sand fly vector species (Lutzomyia anthophora and L. diabolica), three confirmed rodent reservoir species (Neotoma albigula, N. floridana, and N. micropus), and one potential rodent reservoir species (N. mexicana) for leishmaniasis in northern México and the United States. As input, these models used species' occurrence records with topographic and climatic parameters as explanatory variables. Models were tested for their ability to predict correctly both a specified fraction of occurrence points set aside for this purpose and occurrence points from an independently derived data set. These models were refined to obtain predicted species' geographical distributions under increasingly strict assumptions about the ability of a species to disperse to suitable habitat and to persist in it, as modulated by its ecological suitability. Models successful at predictions were fitted to the extreme A2 and relatively conservative B2 projected climate scenarios for 2020, 2050, and 2080 using publicly available interpolated climate data from the Third Intergovernmental Panel on Climate Change Assessment Report. Further analyses included estimation of the projected human population that could potentially be exposed to leishmaniasis in 2020, 2050, and 2080 under the A2 and B2 scenarios. All confirmed vector and reservoir species will see an expansion of their potential range towards the north. Thus, leishmaniasis has the potential to expand northwards from México and the southern United States. In the eastern United States its spread is predicted to be limited by the range of L. diabolica; further west, L. anthophora may play the same role. In the east it may even reach the southern boundary of Canada. The risk of spread is greater for the A2 scenario than for the B2 scenario. Even in the latter case, with restrictive (contiguous) models for dispersal of vector and reservoir species, and limiting vector and reservoir species occupancy to only the top 10% of their potential suitable habitat, the expected number of human individuals exposed to leishmaniasis by 2080 will at least double its present value., Conclusions: These models predict that climate change will exacerbate the ecological risk of human exposure to leishmaniasis in areas outside its present range in the United States and, possibly, in parts of southern Canada. This prediction suggests the adoption of measures such as surveillance for leishmaniasis north of Texas as disease cases spread northwards. Potential vector and reservoir control strategies-besides direct intervention in disease cases-should also be further investigated.

Networks offer a powerful tool for understanding and visualizing inter-species ecological and evolutionary interactions. Previously considered examples, such as trophic networks, are just representations of experimentally observed direct interactions. However, species interactions are so rich and complex it is not feasible to directly observe more than a small fraction. In this paper, using data mining techniques, we show how potential interactions can be inferred from geographic data, rather than by direct observation. An important application area for this methodology is that of emerging diseases, where, often, little is known about inter-species interactions, such as between vectors and reservoirs. Here, we show how using geographic data, biotic interaction networks that model statistical dependencies between species distributions can be used to infer and understand inter-species interactions. Furthermore, we show how such networks can be used to build prediction models. For example, for predicting the most important reservoirs of a disease, or the degree of disease risk associated with a geographical area. We illustrate the general methodology by considering an important emerging disease--Leishmaniasis. This data mining methodology allows for the use of geographic data to construct inferential biotic interaction networks which can then be used to build prediction models with a wide range of applications in ecology, biodiversity and emerging diseases.