Risk Of Invasion Research Articles

Global invasion and biosecurity risk from the online trade in ornamental crayfish.

Trade in undomesticated ornamental animals has rapidly expanded beyond brick-and-mortar retail stores to now include growing numbers of internet marketplaces. The growing volume, diversity, and origins of invasive non-native species in trade challenge already weak national biosecurity policies. Despite widespread focus on vertebrates, many knowledge gaps exist regarding the online global trade of ornamental invertebrates. We conducted the first global assessment of the online trade in and associated invasion risk of freshwater crayfishes, which are increasingly popular aquarium animals. We systematically examined e-commerce marketplaces in multiple languages, scrapping information that included species identity, price, quantity, and shipping designation from each crayfish listing. Next, we combined geographic pathways of shipping associated with online trade (introduction risk) and environmental suitability modeling (establishment risk) to estimate global risk of non-native crayfish invasion risk. We identified hundreds of online marketplaces and thousands of sale listings in 33 countries (5 continents) involving 60 species and representing a selling value of ∼US$1.5 million. Invasion risk of non-native crayfish in trade was widespread, with geographic hotspots coinciding with both elevated opportunities for introduction (greater shipping offerings) and establishment. Precise characterization of the online species trade is fundamental to support new and reformed biosecurity policies, build industry partnerships, and design educational campaigns to prevent species invasions through trade. We found that the taxonomy, geography, and economics of the global online ornamental crayfish trade are vast and require greater attention.

Development and Validation of Radiomics-Based Models for Predicting the Parametrial Invasion in Stage IB1 to IIA2 Cervical Cancer.

To develop an early warning system that enables accurate parametrial invasion (PMI) risk prediction in cervical cancer patients with early-stage. We retrospectively collected 218 early-stage cervical cancer patients who were treated in Jingzhou Central Hospital from January 31, 2015, to January 31, 2023, and diagnosed with early stage cervical cancer by pathology. The prediction model training is achieved by randomly dividing 70% of the training queue population, with the remaining 30% used as the testing queue. Then, a prediction model based on machine learning algorithms (including random forest, generalized linear regression, decision tree, support vector machine, and artificial neural network) is constructed to predict the risk of PMI occurrence. Ultimately, the analysis of receiver operating characteristic curve (ROC) and decision curve analysis (DCA) is used to evaluate the predictive ability of various prediction models. We finally included radiomics-based candidate variables that can be used for PMI model. Multivariate logistic regression analysis showed that energy, correlation, sum entropy (SUE), entropy, mean sum (MES), variance of differences (DIV), and inverse difference (IND) were independent risk factors for PMI occurrence. The predictive performance AUC of five types of machine learning ranges from 0.747 to 0.895 in the training set and can also reach a high accuracy of 0.905 in the testing set, indicating that the predictive model has ideal robustness. Our ML-based model incorporating GLCM parameters can predict PMI in cervical cancer patients with stage IB1 to IIA2, particularly the RFM, which could contribute to distinguishing PMI before surgery, especially in assisting decision-making on surgical scope.

A regional One Health approach to the risk of invasion by Anopheles stephensi in Mauritius.

Anopheles stephensi is an invasive malaria vector in Africa that threatens to put an additional 126 million people at risk of malaria if it continues to spread. The island nation of Mauritius is highly connected to Asia and Africa and is at risk of introduction due to this connectivity. For early detection of An. stephensi, the Vector Biology and Control Division under the Ministry of Health in Mauritius, leveraged a well-established Aedes program, as An. stephensi is known to share Aedes habitats. These efforts triggered multisectoral coordination and cascading benefits of integrated vector and One Health approaches. Beginning June 2021, entomological surveys were conducted at points of entry (seaport, airport) and on ships transporting livestock in collaboration with the Civil Aviation Department, the Mauritian Port Authority and National Veterinary Services. A total of 18, 39, 723 mosquito larval surveys were respectively conducted in the airport, seaport, and other localities in Mauritius while two, 20, and 26 adult mosquito surveys were respectively conducted in the airport, seaport, and twenty-six animal assembly points. Alongside adult mosquito surveys, surveillance of vectors of veterinary importance (e.g.- Culicoides spp.) was also carried out in collaboration with National Parks and Conservation Service and land owners. A total of 8,428 adult mosquitoes were collected and 1,844 larval habitats were positive for mosquitoes. All collected mosquitoes were morphologically identified and 151 Anopheles and 339 Aedes mosquitoes were also molecularly characterized. Mosquito species detected were Aedes albopictus, Anopheles arabiensis, An. coustani, An. merus, Culex quinquefasciatus, Cx. thalassius and Lutzia tigripes. Anopheles stephensi was not detected. The One Health approach was shared with the French Agricultural Research Centre for International Development (CIRAD), strengthening collaboration between Mauritius and Réunion Island on vector surveillance at entry points and insecticide resistance monitoring. The Indian Ocean Commission (IOC) was also alerted to the risk of An. stephensi, leading to regional efforts supporting trainings and development of a response strategy to An. stephensi bringing together stakeholders from Comoros, Madagascar, Mauritius, Réunion Island and Seychelles. Mauritius is a model system showing how existing public health entomology capabilities can be used to enhance vector surveillance and control and create multisectoral networks to respond to any emerging public and veterinary health vector-borne disease threat.

Predicting the potential global distribution of Ixodes pacificus under climate change.

In order to predict the global potential distribution range of Ixodes pacificus (I. pacificus) under different climate scenario models in the future, analyze the major climate factors affecting its distribution, and provide references for the transformation of passive vector surveillance into active vector surveillance, the maximum entropy model (MaxEnt) was used in this study to estimate the global potential distribution range of I. pacificus under historical climate scenarios and different future climate scenarios. The global distribution data of I. pacificus were screened by ENMtools and ArcGIS 10.8 software, and a total of 563 distribution data of I. pacificus were obtained. Maxent 3.4.1 and R 4.0.3 were used to screen climate variables according to the contribution rate of environmental variables, knife cutting method and correlation analysis of variables. R 4.0.3 was used to calculate model regulation frequency doubling and feature combination to adjust MaxEnt parameters. The model results showed that the training omission rate was in good agreement with the theoretical omission rate, and the area under ROC curve (AUC) value of the model was 0.978. Among the included environmental variables, the Tmin2 (minimum temperature in February) and Prec1 (precipitation in January) contributed the most to the model, providing more effective information for the distribution of I. pacificus. MaxEnt model revealed that the distribution range of I. pacificus was dynamically changing. The main potential suitable areas are distributed in North America, South America, Europe, Oceania and Asia. Under the future climate scenario model, the potential suitable areas show a downward trend, but the countries and regions ieeeeeeenvolved in the suitable areas do not change much. Therefore, the invasion risk of the potential suitable area of I. pacificus should be paid attention to.

Invasive alien plants in the Qinghai-Tibetan Plateau (China): Current state and future predictions

Invasive alien plants have received increasing attention due to their worldwide environmental impacts, ecological concerns, and significant economic consequences. The Qinghai-Tibetan Plateau is an important global biodiversity hotspot hosting rich biodiversity and serving as a crucial component of the southwest ecological security barrier, with global conservation value. However, in recent years, invasive plants have been detrimental to the conservation of biodiversity and native ecosystems on the Qinghai-Tibetan Plateau. Here, 197 invasive plant species were recognized from the Qinghai-Tibetan Plateau, encompassing 133 genera across 47 families. We used the maximum entropy model (MaxEnt) method to predict the potential distribution of invasive alien plants on the Qinghai-Tibetan Plateau. Furthermore, potential geographic distribution regions suitable for 43 invasive alien plant species were found to be primarily concentrated in central and eastern Qinghai, southern and eastern Tibet, southwest Xinjiang, and the Qinghai-Tibetan Plateau part of Sichuan, Yunnan, and Gansu in China. Notably, the current potential distribution area for all 43 invasive alien plant species accounts for 29.92 % of the total area, with an increase of 32.72–59.39 % projected by 2050. Moreover, risk screening results confirm the high risk of invasion of most alien plants on the Qinghai-Tibetan Plateau. This study provides a foundation for assessing the risks associated with introducing and managing invasive alien plants in the region. It also offers scientific support for conserving the Qinghai-Tibetan Plateau’s unique biodiversity, ecological originality, and sustainable development during economic growth.

EDNA analysis reveals high invasion risks in nature reserves in Guangdong Province, China

eDNA analysis reveals high invasion risks in nature reserves in Guangdong Province, China

Valve-in-valve transcatheter mitral valve replacement versus redo-surgical mitral valve replacement for degenerated bioprosthetic mitral valves: A systematic review and meta-analysis

Bioprosthetic mitral valve degeneration is traditionally treated with Redo-SMVR, but the latest ViV-TMVR procedure offers a less invasive and lower risk alternative. A systematic literature search was conducted on Cochrane Central, Scopus, and Medline (PubMed interface) electronic databases from inception till 15th April 2024. We used risk ratios (RR) for dichotomous outcomes and mean differences (MD) for continuous outcomes. We included a total of eleven studies with 11,931 patients in the final quantitative and qualitative analysis. When comparing ViV-TMVR with Redo-SMVR, no significant difference was found for 30-day mortality (P = 0.13) and 1-year mortality (P = 0.91), whereas patients in the ViV-TMVR showed significantly reduced incidence of stroke (P < 0.00001), In-hospital mortality (P), bleeding complications (P = 0.003), AKI (P = 0.0006), arrhythmias (P = 0.01), LVOT obstruction (P = 0.04), and PPI (P < 0.00001). Furthermore, no significant difference was observed between either group when comparing vascular complications (P = 0.97), 2-year mortality (P = 0.60) and 3-year mortality. ViV-TMVR was associated with a significant risk of paravalvular leakage (P = 0.008). Although, ViV-TMVR reduces the risk of complications associated with Redo-SMVR, larger studies are imperative to reach conclusive results.

Exploring the Germline Genetics of In Situ and Invasive Cutaneous Melanoma

It is unknown whether germline genetic factors influence in situ melanoma risk differently than invasive melanoma risk. To determine whether differences in risk of in situ melanoma and invasive melanoma are heritable. Three genome-wide association study meta-analyses were conducted of in situ melanoma vs controls, invasive melanoma vs controls, and in situ vs invasive melanoma (case-case) using 4 population-based genetic cohorts: the UK Biobank, the FinnGen cohort, the QSkin Sun and Health Study, and the Queensland Study of Melanoma: Environmental and Genetic Associations (Q-MEGA). Melanoma status was determined using International Statistical Classification of Diseases and Related Health Problems codes from cancer registry data. Data were collected from 1987 to 2022, and data were analyzed from September 2022 to June 2023. In situ and invasive cutaneous melanoma. To test whether in situ and invasive melanoma have independent heritable components, genetic effect estimates were calculated for single-nucleotide variants (SNV; formerly single-nucleotide polymorphisms) throughout the genome for each melanoma. Then, SNV-based heritability was estimated, the genetic correlation between melanoma subtypes was assessed, and polygenic risk scores (PRS) were generated for in situ vs invasive status in Q-MEGA participants. A total of 6 genome-wide significant loci associated with in situ melanoma and 18 loci with invasive melanoma were identified. A strong genetic correlation (genetic r = 0.96; 95% CI, 0.76-1.15) was observed between the 2 classifications. Notably, loci near IRF4, KLF4, and HULC had significantly larger effects for in situ melanoma compared with invasive melanoma, while MC1R had a significantly larger effect on invasive melanoma compared with in situ melanoma. Heritability estimates were consistent for both, with in situ melanoma heritability of 6.7% (95% CI, 4.1-9.3) and invasive melanoma heritability of 4.9% (95% CI, 2.8-7.2). Finally, a PRS, derived from comparing invasive melanoma with in situ melanoma genetic risk, was on average significantly higher in participants with invasive melanoma (odds ratio per 1-SD increase in PRS, 1.43; 95% CI, 1.16-1.77). There is much shared genetic architecture between in situ melanoma and invasive melanoma. Despite indistinguishable heritability estimates between the melanoma classifications, PRS suggest germline genetics may influence whether a person gets in situ melanoma or invasive melanoma. PRS could potentially help stratify populations based on invasive melanoma risk, informing future screening programs without exacerbating the current burden of melanoma overdiagnosis.

A comprehensive review of Coreopsis lanceolata: assessing its invasion risk and ecological impact

A comprehensive review of <i>Coreopsis lanceolata</i>: assessing its invasion risk and ecological impact

Disentangling drivers of annual grass invasion: Abiotic susceptibility vs. fire-induced conversion to cheatgrass dominance in the sagebrush biome

Invasive annual grasses are often facilitated by fire, yet they can become ecologically dominant in susceptible locations even in the absence of fire. We used an extensive vegetation plot database to model susceptibility to the invasive annual grass cheatgrass (Bromus tectorum L.) in the sagebrush biome as a function of climate and soil water availability variables. We built random forest models predicting cheatgrass presence or dominance (>15 % relative cover) under unburned (37,219 plots) and burned conditions (6340 plots). We mapped predicted probability of cheatgrass presence and dominance, conditional on burning. We combined predicted susceptibility with burn probability to quantify the 10-year total risk of cheatgrass dominance. Finally, we identified portions of the landscape (1) at risk of fire-induced conversion to cheatgrass dominance, (2) consistently susceptible to cheatgrass dominance, or (3) consistently resistant to cheatgrass dominance. At the scale of the sagebrush biome, we found that abiotic susceptibility to cheatgrass dominance drives total risk, regardless of fire. At local scales (i.e., individual 30 m pixels), burning increased the probability of cheatgrass dominance by a median of 14 %. Threshold-based analyses indicate that 10–31 % of the sagebrush biome was at risk of fire-induced dominance, with 55 % exhibiting abiotic resistance and 5 % exhibiting abiotic susceptibility to dominance regardless of fire. Burn probability was higher in areas predicted to be susceptible to dominance, illustrating how cheatgrass invasion can cause ecosystem conversions that are then sustained by grass-fire cycles. Disentangling the influence of abiotic conditions and fire contributes to our understanding of the mechanisms driving invasion dynamics, and modeling the probability of dominance can help anticipate where ecological transformations are at risk of occurring. Our approach can facilitate the prioritization of management actions in the sagebrush biome and be used as a framework for modeling invasion risk in other disturbance-prone ecosystems.

Machine learning ensemble model prediction of northward shift in potato cyst nematodes (Globodera rostochiensis and G. pallida) distribution under climate change conditions

Potato cyst nematodes (PCNs) are a significant threat to potato production, having caused substantial damage in many countries. Predicting the future distribution of PCN species is crucial to implementing effective biosecurity strategies, especially given the impact of climate change on pest species invasion and distribution. Machine learning (ML), specifically ensemble models, has emerged as a powerful tool in predicting species distributions due to its ability to learn and make predictions based on complex data sets. Thus, this research utilised advanced machine learning techniques to predict the distribution of PCN species under climate change conditions, providing the initial element for invasion risk assessment. We first used Global Climate Models to generate homogeneous climate predictors to mitigate the variation among predictors. Then, five machine learning models were employed to build two groups of ensembles, single-algorithm ensembles (ESA) and multi-algorithm ensembles (EMA), and compared their performances. In this research, the EMA did not always perform better than the ESA, and the ESA of Artificial Neural Network gave the highest performance while being cost-effective. Prediction results indicated that the distribution range of PCNs would shift northward with a decrease in tropical zones and an increase in northern latitudes. However, the total area of suitable regions will not change significantly, occupying 16–20% of the total land surface (18% under current conditions). This research alerts policymakers and practitioners to the risk of PCNs’ incursion into new regions. Additionally, this ML process offers the capability to track changes in the distribution of various species and provides scientifically grounded evidence for formulating long-term biosecurity plans for their control.

Prediction of potential invasion of two weeds of the genus Avena in Asia under climate change based on Maxent

Avena sterilis L. (A. sterilis) and Avena ludoviciana Dur. (A. ludoviciana) are extremely invasive weeds with strong competitive ability and multiple transmission routes. Both species can invade a variety of dryland crops, including wheat, corn, and beans. Asia, as the world's major food-producing continent, will experience significant losses to agricultural production if it is invaded by these weeds on a large scale. This study used the MaxEnt model and ArcGIS to map the distribution of suitable habitats of the two species in Asia under climate change conditions. The constructed model comprised four levels, with a total of 25 index-level indicator factors used to evaluate the invasion risk of the two species. The results showed that the distribution of suitable habitats for both Avena species was highly dependent on precipitation and temperature. Under climate warming conditions, although overall the total suitable area is predicted to decrease compared to the current period, there are still moderately or highly suitable areas. Asian countries need to provide early warning for areas with significant increases in moderate and highly suitable zones for these two species of weeds under the background of climate change. If there is already an invaded area or if the suitability of the original area is increased, this should be closely monitored, and control measures should be taken to prevent further spread and deterioration.

Performance of Supplemental US Screening in Women with Dense Breasts and Varying Breast Cancer Risk: Results from the Breast Cancer Surveillance Consortium.

Background It is unclear whether breast US screening outcomes for women with dense breasts vary with levels of breast cancer risk. Purpose To evaluate US screening outcomes for female patients with dense breasts and different estimated breast cancer risk levels. Materials and Methods This retrospective observational study used data from US screening examinations in female patients with heterogeneously or extremely dense breasts conducted from January 2014 to October 2020 at 24 radiology facilities within three Breast Cancer Surveillance Consortium (BCSC) registries. The primary outcomes were the cancer detection rate, false-positive biopsy recommendation rate, and positive predictive value of biopsies performed (PPV3). Risk classification of participants was performed using established BCSC risk prediction models of estimated 6-year advanced breast cancer risk and 5-year invasive breast cancer risk. Differences in high- versus low- or average-risk categories were assessed using a generalized linear model. Results In total, 34 791 US screening examinations from 26 489 female patients (mean age at screening, 53.9 years ± 9.0 [SD]) were included. The overall cancer detection rate per 1000 examinations was 2.0 (95% CI: 1.6, 2.4) and was higher in patients with high versus low or average risk of 6-year advanced breast cancer (5.5 [95% CI: 3.5, 8.6] vs 1.3 [95% CI: 1.0, 1.8], respectively; P = .003). The overall false-positive biopsy recommendation rate per 1000 examinations was 29.6 (95% CI: 22.6, 38.6) and was higher in patients with high versus low or average 6-year advanced breast cancer risk (37.0 [95% CI: 28.2, 48.4] vs 28.1 [95% CI: 20.9, 37.8], respectively; P = .04). The overall PPV3 was 6.9% (67 of 975; 95% CI: 5.3, 8.9) and was higher in patients with high versus low or average 6-year advanced cancer risk (15.0% [15 of 100; 95% CI: 9.9, 22.2] vs 4.9% [30 of 615; 95% CI: 3.3, 7.2]; P = .01). Similar patterns in outcomes were observed by 5-year invasive breast cancer risk. Conclusion The cancer detection rate and PPV3 of supplemental US screening increased with the estimated risk of advanced and invasive breast cancer. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Helbich and Kapetas in this issue.

Modeling the risk of aquatic species invasion spread through boater movements and river connections.

Aquatic invasive species (AIS) are one of the greatest threats to the functioning of aquatic ecosystems worldwide. Once an invasive species has been introduced to a new region, many governments develop management strategies to reduce further spread. Nevertheless, managing AIS in a new region is challenging because of the vast areas that need protection and limited resources. Spatial heterogeneity in invasion risk is driven by environmental suitability and propagule pressure, which can be used to prioritize locations for surveillance and intervention activities. To better understand invasion risk across aquatic landscapes, we developed a simulation model to estimate the likelihood of a waterbody becoming invaded with an AIS. The model included waterbodies connected via a multilayer network that included boater movements and hydrological connections. In a case study of Minnesota, we used zebra mussels (Dreissena polymorpha) and starry stonewort (Nitellopsis obtusa) as model species. We simulated the impacts of management scenarios developed by stakeholders and created a decision-support tool available through an online application provided as part of the AIS Explorer dashboard. Our baseline model revealed that 89% of new zebra mussel invasions and 84% of new starry stonewort invasions occurred through boater movements, establishing it as a primary pathway of spread and offering insights beyond risk estimates generated by traditional environmental suitability models alone. Our results highlight the critical role of interventions applied to boater movements to reduce AIS dispersal.

Detecting the distribution of and public attitudes to charismatic alien species based on media coverage

Charismatic species are often reported by the media, providing information for detecting population status and public perception. To identify the number and distribution of free-living Black Swan (Cygnus atratus), a charismatic alien species in Chinese mainland and to detect the public and the media attitudes to the species, we analyzed the reports and emotional tendency from media coverage in 2000–2022 using manual reading, crawler extraction and latent Dirichlet allocation. A total of 6654 Black Swans were reported at 711 sites, including 147 individuals at 30 nature reserves. Successful breeding was reported at one-fourth of the total sites, including five nature reserves. The proportion of positive emotional tendency to Black Swans was overwhelming in the reports and was higher than that to alien species in general, suggesting that the public and the media are unaware of the risk of biological invasion. Effective management of invasive species requires the media clarifies the invasion risk of charismatic alien species. Promoting the unity between the harmfulness of abstract concept of alien species and the charisma of a specific alien species among the public help effective management.

Preoperative prediction of microvascular invasion risk in hepatocellular carcinoma with MRI: peritumoral versus tumor region

ObjectivesTo explore the predictive performance of tumor and multiple peritumoral regions on dynamic contrast-enhanced magnetic resonance imaging (MRI), to identify optimal regions of interest for developing a preoperative predictive model for the grade of microvascular invasion (MVI).MethodsA total of 147 patients who were surgically diagnosed with hepatocellular carcinoma, and had a maximum tumor diameter ≤ 5 cm were recruited and subsequently divided into a training set (n = 117) and a testing set (n = 30) based on the date of surgery. We utilized a pre-trained AlexNet to extract deep learning features from seven different regions of the maximum transverse cross-section of tumors in various MRI sequence images. Subsequently, an extreme gradient boosting (XGBoost) classifier was employed to construct the MVI grade prediction model, with evaluation based on the area under the curve (AUC).ResultsThe XGBoost classifier trained with data from the 20-mm peritumoral region showed superior AUC compared to the tumor region alone. AUC values consistently increased when utilizing data from 5-mm, 10-mm, and 20-mm peritumoral regions. Combining arterial and delayed-phase data yielded the highest predictive performance, with micro- and macro-average AUCs of 0.78 and 0.74, respectively. Integration of clinical data further improved AUCs values to 0.83 and 0.80.ConclusionCompared with those of the tumor region, the deep learning features of the peritumoral region provide more important information for predicting the grade of MVI. Combining the tumor region and the 20-mm peritumoral region resulted in a relatively ideal and accurate region within which the grade of MVI can be predicted.Clinical relevance statementThe 20-mm peritumoral region holds more significance than the tumor region in predicting MVI grade. Deep learning features can indirectly predict MVI by extracting information from the tumor region and directly capturing MVI information from the peritumoral region.Key PointsWe investigated tumor and different peritumoral regions, as well as their fusion.MVI predominantly occurs in the peritumoral region, a superior predictor compared to the tumor region.The peritumoral 20 mm region is reasonable for accurately predicting the three-grade MVI.Graphical

Response of spontaneous plant communities to microhabitats in a riparian corridor in Beijing, China

With the increasing urban environmental problems, spontaneous vegetation has been gradually emphasized for high ecological value, whose distribution has been reported as strongly influenced by fine-scale environmental factors. As one of the major zones for urban spontaneous vegetation distribution, urban riparian corridors are well suited for research on the response of spontaneous plants to microhabitats. Taking the Wenyu River-North Canal in Beijing as the study site, we measured six microhabitat factors, including the level of maintenance and visitor activity, canopy density, litter thickness, and distance to water and road, to investigate their effects on spontaneous plant assemblages. The results showed that spontaneous plants respond significantly to fine-scale habitat variation, and were more responsive to human disturbance than other factors. Compared with diversity indicators, the functional trait compositions were more significantly correlated with microhabitat factors. Under lower maintenance of plants, the spontaneous communities had a higher invasion risk for plants. Thick litter can impede the occurrence of invasive species while favoring the growth of native ones. Our findings are important for furthering understanding of the spontaneous plant community establishment, and can serve as a good reference for the maintenance and management of spontaneous plants in urban riparian corridors.

Briganti's 2012 nomogram is an independent predictor of prostate cancer progression in EAU intermediate-risk class: results from 527 patients treated with robotic surgery.

The study aimed to test if Briganti's 2012 nomogram could be associated with the risk of prostate cancer (PCa) progression in European Association of Urology (EAU) intermediate-risk patients treated with robotic surgery. From January 2013 to December 2021, 527 consecutive patients belonging to the EAU intermediate-risk class were selected. Briganti's 2012 nomogram, which predicts the risk of pelvic lymph node invasion (PLNI), was assessed as a continuous and dichotomous variable that categorized up to the median of 3.0%. Disease progression defined as biochemical recurrence and/or metastatic progression was evaluated by Cox proportional hazards (univariate and multivariate analysis). After a median follow-up of 95.0 months (95% confidence interval [CI]: 78.5-111.4), PCa progression occurred in 108 (20.5%) patients who were more likely to present with an unfavorable nomogram risk score, independently by the occurrence of unfavorable pathology including tumor upgrading and upstaging as well as PLNI. Accordingly, as Briganti's 2012 risk score increased, patients were more likely to experience disease progression (hazard ratio [HR] = 1.060; 95% CI: 1.021-1.100; P = 0.002); moreover, it also remained significant when dichotomized above a risk score of 3.0% (HR = 2.052; 95% CI: 1.298-3.243; P < 0.0001) after adjustment for clinical factors. In the studied risk population, PCa progression was independently predicted by Briganti's 2012 nomogram. Specifically, we found that patients were more likely to experience disease progression as their risk score increased. Because of the significant association between risk score and tumor behavior, the nomogram can further stratify intermediate-risk PCa patients, who represent a heterogeneous risk category for which different treatment paradigms exist.

Coronary microvascular dysfunction and left heart filling pressures in patients with type 2 diabetes.

Patients with type 2 diabetes (T2D) have a high prevalence of diastolic dysfunction and heart failure with preserved ejection fraction (HFpEF), which in turn leads to an increased risk of hospitalization and death. However, the factors of risk and their relative importance in leading to higher left ventricular filling pressures are still disputed. We sought to clarify the associations of a wide range of invasive and non-invasive risk factors with cardiac filling pressures in high-risk T2D patients. Patients with T2D at high risk of cardiovascular events were prospectively enrolled in this study. Participants were thoroughly phenotyped including right heart catheterization at rest and during exercise, echocardiography, urinary excretion of albumin (UACR), and quantification of their myocardial blood flow rate (MFR) using cardiac 82Rb-PET/CT. Of the 37 patients included in the study, 22 (59%) patients met invasive criteria for HFpEF. Only 2 out of 39 variables emerged as independent factors associated with left ventricular filling pressure as assessed by pulmonary capillary wedge pressure (PCWP) at rest; history of hypertension (coefficient: 2.6mmHg [0.3; 5.0], P=0.030) and MFR (P=0.026). We found a significant inverse association between MFR and PCWP with a coefficient of -2.3mmHg (-4.3; -0.3) in PCWP per integer change of MFR. The MFR ranged from 1.18 to 3.68 in our study, which corresponds to a difference in PCWP of approximately 6mmHg between patients with the lowest compared to the highest MFR. During exercise, only 2 variables emerged as borderline independent factors associated with PCWP: myocardial flow reserve (coefficient: -4.4 [-9.6; 0.8], P=0.091) and beta-blockers use (coefficient: 6.1 [-0.1; 12.4], P=0.053). In patients with type 2 diabetes without known HFpEF but risk factors for cardiovascular disease, myocardial blood flow rate was independently associated with PCWP at rest across the range from normal to abnormal left heart filling pressures. A clinically significant difference of 6mmHg in PWCP was attributable to differences in MFR in patients with the lowest compared with the highest MFR values. This suggests that strategies than attenuate microvascular dysfunction could slow progression of increased left ventricular left heart filling pressures in patients at increased risk.

Risk of invasion and disease transmission by the Australasian freshwater snail Orientogalba viridis (Lymnaeidae): a field and experimental study

BackgroundBiological invasions pose risks to the normal functioning of ecosystems by altering the structure and composition of several communities. Molluscs stand out as an extensively studied group given their long history of introduction by either natural or anthropogenic dispersal events. An alien population of the lymnaeid species Orientogalba viridis was first sighted in 2009 in southern Spain. In its native range (Australasian), this species is one of the main intermediate hosts of Fasciola hepatica, a major worldwide trematode parasite largely affecting humans, domestic animals and wildlife.MethodsWe collected field populations of O. viridis from its native (Malaysia) and invaded (Spain) ranges. We performed detailed morphoanatomical drawings of the species and screened for natural infection of parasites. Individuals were molecularly characterized using ITS2 for comparison with existing sequences in a fine phylogeography study. We founded experimental populations at two different conditions (tropical, 26 °C and temperate, 21 °C) to study the life-history traits of exposed and non-exposed individuals to different F. hepatica isolates.ResultsWe found a 9% natural prevalence of trematode infection (98% similarity with a sequence of Hypoderaeum conoideum [Echinostomatidae]) in the Spanish field population. The haplotypes of O. viridis found in our study from Spain clustered with Australian haplotypes. Experimental infection with F. hepatica was successful in both experimental conditions but higher in tropical (87% prevalence) than in temperate (73%). Overall lifespan, however, was higher in temperate conditions (mean 32.5 ± 7.4 weeks versus 23.3 ± 6.5) and survivorship remained above 70% during the first 20 weeks. In parasite-exposed populations, life expectancy dropped from an overall 37.75 weeks to 11.35 weeks but still doubled the time for initial cercariae shedding. Cercariae shedding started at day 23 post-exposure and peaked between days 53 and 67 with an average of 106 metacercariae per snail.ConclusionsWhether O. viridis will succeed in Europe is unknown, but the odds are for a scenario in which a major snail host of F. hepatica occupy all available habitats of potential transmission foci, ravelling the epidemiology of fasciolosis. This research provides a comprehensive understanding of O. viridis biology, interactions with parasites and potential implications for disease transmission dynamics, offering valuable insights for further research and surveillance.Graphical