Detection and Exclusion of False-Positive Molecular Formula Assignments via Mass Error Distributions in UHR Mass Spectra of Natural Organic Matter.

Ultrahigh resolution mass spectrometry (UHRMS) routinely detects and identifies thousands of mass peaks in complex mixtures, such as natural organic matter (NOM) and petroleum. The assignment of several chemically plausible molecular formulas (MFs) for a single accurate mass still poses a major problem for the reliable interpretation of NOM composition in a biogeochemical context. Applying sensible chemical rules for MF validation is often insufficient to eliminate multiple assignments (MultiAs)─especially for mass peaks with low abundance or if ample heteroatoms or isotopes are included - and requires manual inspection or expert judgment. Here, we present a new approach based on mass error distributions for the identification of true and false assignments among MultiAs. To this end, we used the mass error in millidalton (mDa), which was superior to the commonly used relative mass error in ppm. We developed an automatic workflow to group MultiAs based on their shared formula units and Kendrick mass defect values and to evaluate the mass error distribution. In this way, the number of valid assignments of chlorinated disinfection byproducts was increased by 8-fold as compared to only applying 37Cl/35Cl isotope ratio filters. Likewise, phosphorus-containing MFs can be differentiated against chlorine-containing MFs with high confidence. Further, false assignments of highly aromatic sulfur-containing MFs ("black sulfur") to sodium adducts in negative ionization mode can be excluded by applying our approach. Overall, MFs for mass peaks that are close to the detection limit or where naturally occurring isotopes are rare (e.g., 15N) or absent (e.g., P and F) can now be validated, substantially increasing the reliability of MF assignments and broadening the applicability of UHRMS analysis to even more complex samples and processes.

A Mitochondrial Basis for Heart Failure Progression.

In health, the human heart is able to match ATP supply and demand perfectly. It requires 6 kg of ATP per day to satisfy demands of external work (mechanical force generation) and internal work (ion movements and basal metabolism). The heart is able to link supply with demand via direct responses to ADP and AMP concentrations but calcium concentrations within myocytes play a key role, signalling both inotropy, chronotropy and matched increases in ATP production. Calcium/calmodulin-dependent protein kinase (CaMKII) is a key adapter to increased workload, facilitating a greater and more rapid calcium concentration change. In the failing heart, this is dysfunctional and ATP supply is impaired. This review aims to examine the mechanisms and pathologies that link increased energy demand to this disrupted situation. We examine the roles of calcium loading, oxidative stress, mitochondrial structural abnormalities and damage-associated molecular patterns.

Genetic factors associated with hidradenitis suppurativa, a literature review.

Background: Hidradenitis suppurativa (HS) is a chronic inflammatory disease characterized by deep-seated, painful lesions most frequently occurring in intertriginous areas of the skin. HS leads to poor quality of life in affected individuals and is difficult to diagnose and treat. Objective: Understanding the genetics associated with familial inheritance may lead to a better understanding of the pathogenesis of this debilitating disease. Methods: Articles published until March 9, 2023, were identified in PubMed using the following search terms: hidradenitis suppurativa and gene* or acne inversa and gene*. Results: The rate of monogenic mutations associated with HS is less than 7%, with the most common genetic mutations reported in sporadic and familial HS cases being in NCSTN and less frequently in PSENEN. Individuals with mutations in the gamma-secretase complex tended to have more severe HS and an early age of onset. Limitations: This study was limited to the case studies available in PubMed, the majority of which used targeted gene panels to detect genetic mutations. Conclusion: Approximately 30% of individuals diagnosed with HS report having a positive family history; however, very few studies demonstrate monogenic familial transmission of HS. The case studies of syndromic HS reported a variety of genetic mutations associated with HS, some of which were familial, while others were sporadic, suggesting that other pathways may be involved in the pathogenesis of HS and other potential mutations that have yet to be evaluated. More research is needed to understand the genetic mutations in HS.

Spatial distribution of settlement of Diadema antillarum around Saba, Dutch Caribbean.

The mass mortality event of the herbivorous sea urchin Diadema antillarum in 1983-1984 has been a major contributor to the diminished resilience of coral reefs throughout the Caribbean. The reduction in grazing pressure resulted in algae proliferation, which inhibited coral recruitment after disturbances such as disease, hurricanes, pollution and climatic change induced marine heat waves. Natural recovery of D. antillarum after the 1983-1984 die-off has been slow. However, the few locations with recovered populations exhibit signs of improvement in coral reef health, prompting interest in D. antillarum restoration. Current restoration strategies include translocation of wild individuals, the restocking of juveniles that are either cultured from gametes or collected as settlers and head-started in a nursery, and assisted natural recovery by providing suitable settlement substrate. Both the collection of wild settlers and assisted natural recovery necessitate an understanding of the local, spatiotemporal trends in settlement. In this study, which was carried out on the Dutch Caribbean Island of Saba, artificial turf settlement collectors were deployed at nine locations around the island and monitored from June 2019 till July 2020 (13 months). The primary objective was to identify trends in larval settlement in space and time, to be able to optimize restoration efforts. Additionally, the small size of Saba allowed us to deploy settlement collectors around the island and compare D. antillarum settlement between windward and leeward sides. Our study showed that on Saba, D. antillarum settlement peaked in June and July, following similar seasonal trends observed around other islands in the Northeastern Caribbean. By far the most settlement occurred at the leeward side of the island, suggesting that hydrodynamic forces entrained D. antillarum larvae in the lee of Saba and/or calmer waters facilitated settlement. Limited settlement occurred on the more exposed windward locations. The identified high settlement locations are candidates for settler collection and restoration attempts. Continued monitoring of D. antillarum settlement, especially in light of the 2022 D. antillarum die-off, holds significance as it can provide insights into the potential of natural recovery.

Myths and Methodologies: Standardisation in human physiology research-should we control the controllables?

The premise of research in human physiology is to explore a multifaceted system whilst identifying one or a few outcomes of interest. Therefore, the control of potentially confounding variables requires careful thought regarding the extent of control and complexity of standardisation. One common factor to control prior to testing is diet, as food and fluid provision may deviate from participants' habitual diets, yet a self-report and replication method can be flawed by under-reporting. Researchers may also need to consider standardisation of physical activity, whether it be through familiarisation trials, wash-out periods, or guidance on levels of physical activity to be achieved before trials. In terms of pharmacological agents, the ethical implications of standardisation require researchers to carefully consider how medications, caffeine consumption and oral contraceptive prescriptions may affect the study. For research in females, it should be considered whether standardisation between- or within-participants in regards to menstrual cycle phase is most relevant. The timing of measurements relative to various other daily events is relevant to all physiological research and so it can be important to standardise when measurements are made. This review summarises the areas of standardisation which we hope will be considered useful to anyone involved in human physiology research, including when and how one can apply standardisation to various contexts.

Reward Sensitivity and Noise Contribute to Negative Affective Bias: A Learning Signal Detection Theory Approach in Decision-Making.

In patients with mood disorders, negative affective biases - systematically prioritising and interpreting information negatively - are common. A translational cognitive task testing this bias has shown that depressed patients have a reduced preference for a high reward under ambiguous decision-making conditions. The precise mechanisms underscoring this bias are, however, not yet understood. We therefore developed a set of measures to probe the underlying source of the behavioural bias by testing its relationship to a participant's reward sensitivity, value sensitivity and reward learning rate. One-hundred-forty-eight participants completed three online behavioural tasks: the original ambiguous-cue decision-making task probing negative affective bias, a probabilistic reward learning task probing reward sensitivity and reward learning rate, and a gambling task probing value sensitivity. We modelled the learning task through a dynamic signal detection theory model and the gambling task through an expectation-maximisation prospect theory model. Reward sensitivity from the probabilistic reward task (ß = 0.131, p = 0.024) and setting noise from the probabilistic reward task (ß = -0.187, p = 0.028) both predicted the affective bias score in a logistic regression. Increased negative affective bias, at least on this specific task, may therefore be driven in part by a combination of reduced sensitivity to rewards and more variable responses.

Promoting equality, diversity and inclusion in research and funding: reflections from a digital manufacturing research network.

BACKGROUND: Equal, diverse, and inclusive teams lead to higher productivity, creativity, and greater problem-solving ability resulting in more impactful research. However, there is a gap between equality, diversity, and inclusion (EDI) research and practices to create an inclusive research culture. Research networks are vital to the research ecosystem, creating valuable opportunities for researchers to develop their partnerships with both academics and industrialists, progress their careers, and enable new areas of scientific discovery. A feature of a network is the provision of funding to support feasibility studies - an opportunity to develop new concepts or ideas, as well as to 'fail fast' in a supportive environment. The work of networks can address inequalities through equitable allocation of funding and proactive consideration of inclusion in all of their activities. METHODS: This study proposes a strategy to embed EDI within research network activities and funding review processes. This paper evaluates 21 planned mitigations introduced to address known inequalities within research events and how funding is awarded. EDI data were collected from researchers engaging in a digital manufacturing network activities and funding calls to measure the impact of the proposed method. RESULTS: Quantitative analysis indicates that the network's approach was successful in creating a more ethnically diverse network, engaging with early career researchers, and supporting researchers with care responsibilities. However, more work is required to create a gender balance across the network activities and ensure the representation of academics who declare a disability. Preliminary findings suggest the network's anonymous funding review process has helped address inequalities in funding award rates for women and those with care responsibilities, more data are required to validate these observations and understand the impact of different interventions individually and in combination. CONCLUSIONS: In summary, this study offers compelling evidence regarding the efficacy of a research network's approach in advancing EDI within research and funding. The network hopes that these findings will inform broader efforts to promote EDI in research and funding and that researchers, funders, and other stakeholders will be encouraged to adopt evidence-based strategies for advancing this important goal.

Status and trends in the international wildlife trade in Chameleons with a focus on Tanzania.

Chameleons (family Chamaeleonidae) are a distinctive group of reptiles, mainly found in Africa, which have high local endemism and face significant threats from the international wildlife trade. We review the scale and structure of international chameleon trade, with a focus on collection in and exports from Tanzania; a hotspot of chameleon diversity. Analysis used data from the CITES Trade Database 2000-2019, combined with assessment of online trade, and on-the-ground surveys in Tanzania in 2019. Between 2000 and 2019, 1,128,776 live chameleons from 108 species were reported as exported globally, with 193,093 of these (from 32 species) exported by Tanzania. Both global and Tanzanian chameleon exports declined across the study period, driven by decreased trade in generalist genera. Whilst the proportion of captive-bred individuals increased across time for the generalist taxa, the majority of range-restricted taxa in trade remained largely wild-sourced. For Tanzanian exports, 41% of chameleons were from one of the 23 endemic species, and 10 of the 12 Tanzanian endemic species in trade are categorised as threatened with extinction by IUCN. In terms of online trade, of the 42 Tanzanian species assessed, there was evidence of online sale for 83.3% species, and 69% were actively for sale with prices listed. Prices were on average highest for Trioceros species, followed by Kinyongia, Rieppeleon, Rhampholeon, and Chameleo. Field work in Tanzania provided evidence that the historic harvest of endemic chameleon species has been higher than the quantities of these species reported as exported by Tanzania in their annual trade reports to CITES. However, we found no field evidence for trade in 2020 and 2021, in line with Tanzanian regulations that applied a blanket ban on all exports of live wild animals. Literature evidence, however, suggests that illegal trade continued to Europe from seizures of Tanzanian chameleon species in Austria in 2021.

Making Predictions Using Poorly Identified Mathematical Models.

Many commonly used mathematical models in the field of mathematical biology involve challenges of parameter non-identifiability. Practical non-identifiability, where the quality and quantity of data does not provide sufficiently precise parameter estimates is often encountered, even with relatively simple models. In particular, the situation where some parameters are identifiable and others are not is often encountered. In this work we apply a recent likelihood-based workflow, called Profile-Wise Analysis (PWA), to non-identifiable models for the first time. The PWA workflow addresses identifiability, parameter estimation, and prediction in a unified framework that is simple to implement and interpret. Previous implementations of the workflow have dealt with idealised identifiable problems only. In this study we illustrate how the PWA workflow can be applied to both structurally non-identifiable and practically non-identifiable models in the context of simple population growth models. Dealing with simple mathematical models allows us to present the PWA workflow in a didactic, self-contained document that can be studied together with relatively straightforward Julia code provided on GitHub . Working with simple mathematical models allows the PWA workflow prediction intervals to be compared with gold standard full likelihood prediction intervals. Together, our examples illustrate how the PWA workflow provides us with a systematic way of dealing with non-identifiability, especially compared to other approaches, such as seeking ad hoc parameter combinations, or simply setting parameter values to some arbitrary default value. Importantly, we show that the PWA workflow provides insight into the commonly-encountered situation where some parameters are identifiable and others are not, allowing us to explore how uncertainty in some parameters, and combinations of parameters, regardless of their identifiability status, influences model predictions in a way that is insightful and interpretable.

Indian Ocean temperature anomalies predict long-term global dengue trends.

Despite identifying El Niño events as a factor in dengue dynamics, predicting the oscillation of global dengue epidemics remains challenging. Here, we investigate climate indicators and worldwide dengue incidence from 1990 to 2019 using climate-driven mechanistic models. We identify a distinct indicator, the Indian Ocean basin-wide (IOBW) index, as representing the regional average of sea surface temperature anomalies in the tropical Indian Ocean. IOBW is closely associated with dengue epidemics for both the Northern and Southern hemispheres. The ability of IOBW to predict dengue incidence likely arises as a result of its effect on local temperature anomalies through teleconnections. These findings indicate that the IOBW index can potentially enhance the lead time for dengue forecasts, leading to better-planned and more impactful outbreak responses.

ATR2C ala2 from Arabidopsis-infecting downy mildew requires 4 TIR-NLR immune receptors for full recognition.

Arabidopsis Col-0 RPP2A and RPP2B confer recognition of Arabidopsis downy mildew (Hyaloperonospora arabidopsidis [Hpa]) isolate Cala2, but the identity of the recognized ATR2Cala2 effector was unknown. To reveal ATR2Cala2, an F2 population was generated from a cross between Hpa-Cala2 and Hpa-Noks1. We identified ATR2Cala2 as a non-canonical RxLR-type effector that carries a signal peptide, a dEER motif, and WY domains but no RxLR motif. Recognition of ATR2Cala2 and its effector function were verified by biolistic bombardment, ectopic expression and Hpa infection. ATR2Cala2 is recognized in accession Col-0 but not in Ler-0 in which RPP2A and RPP2B are absent. In ATR2Emoy2 and ATR2Noks1 alleles, a frameshift results in an early stop codon. RPP2A and RPP2B are essential for the recognition of ATR2Cala2. Stable and transient expression of ATR2Cala2 under 35S promoter in Arabidopsis and Nicotiana benthamiana enhances disease susceptibility. Two additional Col-0 TIR-NLR (TNL) genes (RPP2C and RPP2D) adjacent to RPP2A and RPP2B are quantitatively required for full resistance to Hpa-Cala2. We compared RPP2 haplotypes in multiple Arabidopsis accessions and showed that all four genes are present in all ATR2Cala2-recognizing accessions.

Liver fibrosis Assessed Via Non-invasive Tests is Associated With Incident Heart Failure in a General Population Cohort.

BACKGROUND & AIMS: The aim of this study was to determine whether liver fibrosis is associated with heart failure in a general population cohort, and if genetic polymorphisms (PNPLA3 rs738409; TM6SF2 rs58542926), linked to increased risk of liver fibrosis and decreased risk of coronary artery disease, modify this association. METHODS: Using UK Biobank data, we prospectively examined the relationship between noninvasive fibrosis markers (nonalcoholic fatty liver disease [NAFLD] fibrosis score [NFS], Fibrosis-4 [FIB-4] and aspartate transaminase [AST] to platelet ratio index [APRI]) and incident hospitalization/death from heart failure (n = 413,860). Cox-regression estimated hazard ratios (HRs) for incident heart failure. Effects of PNPLA3 and TM6SF2 on the association between liver fibrosis and heart failure were estimated by stratifying for genotype and testing for an interaction between genotype and liver fibrosis using a likelihood ratio test. RESULTS: A total of 12,527 incident cases of heart failure occurred over a median of 10.7 years. Liver fibrosis was associated with an increased risk of hospitalization or death from heart failure (multivariable adjusted high-risk NFS score HR, 1.59; 95% confidence interval [CI],1.47-1.76; P < .0001; FIB-4 HR, 1.69; 95% CI, 1.55-1.84; P < .0001; APRI HR, 1.85; 95% CI, 1.56-2.19; P < .0001; combined fibrosis scores HR, 1.90; 95% CI, 1.44-2.49; P < .0001). These associations persisted for people with metabolic dysfunction-associated steatotic liver disease (MASLD), MASLD with alcohol consumption (Met-ALD), and harmful alcohol consumption. PNPLA3 rs738409 GG and TM6SF2 rs58542926 TT did not attenuate the positive association between fibrosis markers and heart failure. For PNPLA3, a statistically significant interaction was found between PNPLA3 rs738409, FIB-4, APRI score, and heart failure. CONCLUSION: In the general population, serum markers of liver fibrosis are associated with increased hospitalization/death from heart failure. Genetic polymorphisms associated with liver fibrosis were not positively associated with elevated heart failure risk.

Post column infusion of an internal standard into LC-FT-ICR MS enables semi-quantitative comparison of dissolved organic matter in original samples.

Ultrahigh resolution mass spectrometry hyphenated with liquid chromatography (LC) is an emerging tool to explore the isomeric composition of dissolved organic matter (DOM). However, matrix effects limit the potential for semi-quantitative comparison of DOM molecule abundances across samples. We introduce a post-column infused internal standard (PCI-IS) for reversed-phase LC-FT-ICR MS measurements of DOM and systematically evaluate matrix effects, detector linearity and the precision of mass peak intensities. Matrix effects for model compounds spiked into freshwater DOM samples ranging from a headwater stream to a major river were reduced by 5-10% for PCI-IS corrected mass peak intensities as compared to raw (i.e., untransformed) intensities. A linear regression of PCI-IS corrected DOM mass peak intensities across a typical DOM concentration range (2-15 mg dissolved organic carbon L-1) in original, non-extracted freshwater samples demonstrates excellent linearity of the detector response (r2 > 0.9 for 98% of detected molecular formulas across retention times). Importantly, PCI-IS could compensate for 80% of matrix effects across an environmental gradient of DOM composition from groundwater to surface water. This enabled studying the ionization efficiency of DOM isomers and linking the observed differences to the biogeochemical sources. With PCI-IS original, non-extracted DOM samples can be analysed by LC-FT-ICR MS without carbon load adjustment, and mass peak intensities can be reliably used to semi-quantitatively compare isomer abundances between compositionally similar DOM samples.

Prospective validation of clinical deterioration predictive models prior to intensive care unit transfer among patients admitted to acute care cardiology wards.

Objective. Very few predictive models have been externally validated in a prospective cohort following the implementation of an artificial intelligence analytic system. This type of real-world validation is critically important due to the risk of data drift, or changes in data definitions or clinical practices over time, that could impact model performance in contemporaneous real-world cohorts. In this work, we report the model performance of a predictive analytics tool developed before COVID-19 and demonstrate model performance during the COVID-19 pandemic.Approach. The analytic system (CoMETⓇ, Nihon Kohden Digital Health Solutions LLC, Irvine, CA) was implemented in a randomized controlled trial that enrolled 10 422 patient visits in a 1:1 display-on display-off design. The CoMET scores were calculated for all patients but only displayed in the display-on arm. Only the control/display-off group is reported here because the scores could not alter care patterns.Main results.Of the 5184 visits in the display-off arm, 311 experienced clinical deterioration and care escalation, resulting in transfer to the intensive care unit, primarily due to respiratory distress. The model performance of CoMET was assessed based on areas under the receiver operating characteristic curve, which ranged from 0.725 to 0.737.Significance.The models were well-calibrated, and there were dynamic increases in the model scores in the hours preceding the clinical deterioration events. A hypothetical alerting strategy based on a rise in score and duration of the rise would have had good performance, with a positive predictive value more than 10-fold the event rate. We conclude that predictive statistical models developed five years before study initiation had good model performance despite the passage of time and the impact of the COVID-19 pandemic.

Anticoagulation in COVID-19 patients - An updated systematic review and meta-analysis.

BACKGROUND: Thromboembolic events are common complications of COVID-19. Clinical study results on safety and efficacy of anticoagulation in COVID-19 are controversial. MATERIAL AND METHODS: This report is the second update of our systematic review with meta-analysis on randomized controlled trials (RCTs) comparing standard thromboprophylaxis, intermediate or therapeutic dose anticoagulation or no anticoagulation in COVID-19 in- and outpatients. We searched eligible studies up to 5 October 2023. Certainty of evidence was assessed using GRADE. RESULTS: For this update we included fourteen new RCTs and a total of 27 RCTs with 16,789 patients. Certainty of evidence ranged from very low to high depending on outcome and comparison. Standard thromboprophylaxis with low dose anticoagulation may have little or no effect for COVID-19 outpatients compared to no anticoagulation. In inpatients with moderate or severe COVID-19, intermediate dose anticoagulation may decrease any thrombotic events or death, but may increase major bleeding compared to standard thromboprophylaxis. Therapeutic dose anticoagulation decreases thrombotic events or deaths in inpatients with moderate COVID-19, but probably has little or no effect in patients with severe COVID-19 compared to standard thromboprophylaxis with low or intermediate dose anticoagulation. With therapeutic dose anticoagulation, the risk of major bleeding probably increases regardless of COVID-19 severity. We are uncertain on the effect of thromboprophylaxis with low dose anticoagulation compared to no anticoagulation in the post-discharge setting. CONCLUSIONS: Hospitalized, moderately-ill COVID-19 patients may benefit from intermediate or therapeutic dose anticoagulation, while critically ill patients may not. Risk of major bleeding must be considered.

Utilization of bis-MPA Dendrimers for the Calibration of Ion Mobility Collision Cross Section Calculations.

Ion mobility-mass spectrometry (IM-MS) has become increasingly popular with the rapid expansion of available techniques and instrumentation. To enable accuracy, standardization, and repeatability of IM-MS measurements, the community requires reliable and well-defined reference materials for calibration and tuning of the equipment. To address this need, synthetic dendrimers of high chemical and structural purity were tested on three ion mobility platforms as potential calibrants. First, synthesized dendrimers were characterized by drift tube ion mobility (DTIMS), using an Agilent 6560 IM-qTOF-MS to assess their drift tube collision cross section (DTCCS) values. Then, assessment of obtained CCS values on trapped ion mobility (TIMS) and traveling wave ion mobility (TWIMS) ion mobility platforms were compared to those found by DTIMS. Across all three systems, dendrimers were found to have high potential for m/z and ion mobility calibration in the CCS range of 160-1700 Å2. To further validate their use as calibrants, drift tube calculated CCS values for dendrimers were utilized to calibrate calculations of CCS for known standards including Agilent Tuning mix, the CCS Major mix from Waters, and SPLASH LIPIDOMIX. Additionally, structures of sodiated dendrimers were computated along with theoretical CCS values which showed good agreement with the experimental CCS values. On the basis of the results presented, we recommend the use of dendrimers as alternatives and/or complementary compounds to commonly used calibrants for ion mobility platforms.

Opportunities for incorporating intersectionality into biomedical informatics.

Many approaches in biomedical informatics (BMI) rely on the ability to define, gather, and manipulate biomedical data to support health through a cyclical research-practice lifecycle. Researchers within this field are often fortunate to work closely with healthcare and public health systems to influence data generation and capture and have access to a vast amount of biomedical data. Many informaticists also have the expertise to engage with stakeholders, develop new methods and applications, and influence policy. However, research and policy that explicitly seeks to address the systemic drivers of health would more effectively support health. Intersectionality is a theoretical framework that can facilitate such research. It holds that individual human experiences reflect larger socio-structural level systems of privilege and oppression, and cannot be truly understood if these systems are examined in isolation. Intersectionality explicitly accounts for the interrelated nature of systems of privilege and oppression, providing a lens through which to examine and challenge inequities. In this paper, we propose intersectionality as an intervention into how we conduct BMI research. We begin by discussing intersectionality's history and core principles as they apply to BMI. We then elaborate on the potential for intersectionality to stimulate BMI research. Specifically, we posit that our efforts in BMI to improve health should address intersectionality's five key considerations: (1) systems of privilege and oppression that shape health; (2) the interrelated nature of upstream health drivers; (3) the nuances of health outcomes within groups; (4) the problematic and power-laden nature of categories that we assign to people in research and in society; and (5) research to inform and support social change.

Human movement and environmental barriers shape the emergence of dengue.

Understanding how emerging infectious diseases spread within and between countries is essential to contain future pandemics. Spread to new areas requires connectivity between one or more sources and a suitable local environment, but how these two factors interact at different stages of disease emergence remains largely unknown. Further, no analytical framework exists to examine their roles. Here we develop a dynamic modelling approach for infectious diseases that explicitly models both connectivity via human movement and environmental suitability interactions. We apply it to better understand recently observed (1995-2019) patterns as well as predict past unobserved (1983-2000) and future (2020-2039) spread of dengue in Mexico and Brazil. We find that these models can accurately reconstruct long-term spread pathways, determine historical origins, and identify specific routes of invasion. We find early dengue invasion is more heavily influenced by environmental factors, resulting in patchy non-contiguous spread, while short and long-distance connectivity becomes more important in later stages. Our results have immediate practical applications for forecasting and containing the spread of dengue and emergence of new serotypes. Given current and future trends in human mobility, climate, and zoonotic spillover, understanding the interplay between connectivity and environmental suitability will be increasingly necessary to contain emerging and re-emerging pathogens.