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Cities are often hotspots for biological invasions, showing much higher percentages of alien species than non-urbanized settings. The reasons are multiple and are mostly related to two main factors: their heterogeneous, highly disturbed habitats and their many gateways that allow alien species introduction (e.g., airports, roads, train stations, or gardens). In addition to being a sink of biological invasions, cities can also be a source of the spread of alien species into surrounding landscapes, which adds further complexity to this issue. Herein, we are presenting the results of a five-year survey of the alien flora of Montjuïc, the largest urban hill in Barcelona (Spain). In just about 3.4 km2, we recorded up to 247 alien plant taxa, a figure much higher than those of many other Mediterranean cities and which clearly points to the role of Montjuïc as a hotspot for alien plants. The comparison with the alien flora of its surrounding region (coastal Catalonia) suggests that the alien flora of Montjuïc would have become enriched through many immigration episodes from close geographic areas. The hill, however, would have also acted as a source of the spread of alien plants, and indeed, some species have not been detected yet beyond the confines of Montjuïc. This study aims to be a key tool to ensure early detection and also to develop appropriate management and/or eradication actions.

Obstructive sleep apnea (OSA) is a sleep disorder in which repetitive upper airway obstructive events occur during sleep. These events can induce hypoxia, which is a risk factor for multiple cardiovascular and cerebrovascular diseases. OSA is also known to be position-dependent in some patients, which is referred to as positional OSA (pOSA). Screening for pOSA is necessary in order to design more personalized and effective treatment strategies. In this article, we propose analyzing accelerometry signals, recorded with a smartphone, to detect and monitor OSA at home. Our objectives were to: (1) develop an algorithm for detecting thoracic movement associated with disordered breathing events; (2) compare the performance of smartphones as OSA monitoring tools with a type 3 portable sleep monitor; and (3) explore the feasibility of using smartphone accelerometry to retrieve reliable patient sleep position data and assess pOSA. Accelerometry signals were collected through simultaneous overnight acquisition using both devices with 13 subjects. The smartphone tool showed a high degree of concordance compared to the portable device and succeeded in estimating the apnea-hypopnea index (AHI) and classifying the severity level in most subjects. To assess the agreement between the two systems, an event-by-event comparison was performed, which found a sensitivity of 90% and a positive predictive value of 80%. It was also possible to identify pOSA by determining the ratio of events occurring in a specific position versus the time spent in that position during the night. These novel results suggest that smartphones are promising mHealth tools for OSA and pOSA monitoring at home.

Obstructive sleep apnea (OSA) is a prevalent disease, but most patients remain undiagnosed and untreated. Here we propose analyzing smartphone audio signals for screening OSA patients at home. Our objectives were to: (1) develop an algorithm for detecting silence events and classifying them into apneas or hypopneas; (2) evaluate the performance of this system; and (3) compare the information provided with a type 3 portable sleep monitor, based mainly on nasal airflow. Overnight signals were acquired simultaneously by both systems in 13 subjects (3 healthy subjects and 10 OSA patients). The sample entropy of audio signals was used to identify apnea/hypopnea events. The apnea-hypopnea indices predicted by the two systems presented a very high degree of concordance and the smartphone correctly detected and stratified all the OSA patients. An event-by-event comparison demonstrated good agreement between silence events and apnea/hypopnea events in the reference system (Sensitivity = 76%, Positive Predictive Value = 82%). Most apneas were detected (89%), but not so many hypopneas (61%). We observed that many hypopneas were accompanied by snoring, so there was no sound reduction. The apnea/hypopnea classification accuracy was 70%, but most discrepancies resulted from the inability of the nasal cannula of the reference device to record oral breathing. We provided a spectral characterization of oral and nasal breathing to correct this effect, and the classification accuracy increased to 82%. This novel knowledge from acoustic signals may be of great interest for clinical practice to develop new non-invasive techniques for screening and monitoring OSA patients at home.

Poor sleep quality or disturbed sleep is associated with multiple health conditions. Sleep position affects the severity and occurrence of these complications, and positional therapy is one of the less invasive treatments to deal with them. Sleep positions can be self-reported, which is unreliable, or determined by using specific devices, such as polysomnography, polygraphy or cameras, that can be expensive and difficult to employ at home. The aim of this study is to determine how smartphones could be used to monitor and treat sleep position at home. We divided our research into three tasks: (1) develop an Android smartphone application (‘SleepPos’ app) which monitors angle-based high-resolution sleep position and allows to simultaneously apply positional treatment; (2) test the smartphone application at home coupled with a pulse oximeter; and (3) explore the potential of this tool to detect the positional occurrence of desaturation events. The results show how the ‘SleepPos’ app successfully determined the sleep position and revealed positional patterns of occurrence of desaturation events. The ‘SleepPos’ app also succeeded in applying positional therapy and preventing the subjects from sleeping in the supine sleep position. This study demonstrates how smartphones are capable of reliably monitoring high-resolution sleep position and provide useful clinical information about the positional occurrence of desaturation events.

Poor sleep quality is a risk factor for multiple mental, cardiovascular, and cerebrovascular diseases. Certain sleep positions or excessive position changes can be related to some diseases and poor sleep quality. Nevertheless, sleep position is usually classified into four discrete values: supine, prone, left and right. An increase in sleep position resolution is necessary to better assess sleep position dynamics and to interpret more accurately intermediate sleep positions. This research aims to study the feasibility of smartphones as sleep position monitors by (1) developing algorithms to retrieve the sleep position angle from smartphone accelerometry; (2) monitoring the sleep position angle in patients with obstructive sleep apnea (OSA); (3) comparing the discretized sleep angle versus the four classic sleep positions obtained by the video-validated polysomnography (PSG); and (4) analyzing the presence of positional OSA (pOSA) related to its sleep angle of occurrence. Results from 19 OSA patients reveal that a higher resolution sleep position would help to better diagnose and treat patients with position-dependent diseases such as pOSA. They also show that smartphones are promising mHealth tools for enhanced position monitoring at hospitals and home, as they can provide sleep position with higher resolution than the gold-standard video-validated PSG.

Epidemiological associations linking between obstructive sleep apnea and poorer solid malignant tumor outcomes have recently emerged. Putative pathways proposed to explain that these associations have included enhanced hypoxia inducible factor (HIF)-1α and vascular endothelial growth factor (VEGF) cell expression in the tumor and altered immune functions via intermittent hypoxia (IH). Here, we examined relationships between HIF-1α and VEGF expression and nocturnal IH in cutaneous melanoma (CM) tumor samples. Prospectively recruited patients with CM tumor samples were included and underwent overnight polygraphy. General clinical features, apnea–hypopnea index (AHI), desaturation index (DI4%), and CM characteristics were recorded. Histochemical assessments of VEGF and HIF-1α were performed, and the percentage of positive cells (0, 75%) was blindly tabulated for VEGF expression, and as 0, 0–5.9, 6.0–10.0, >10.0% for HIF-1α expression, respectively. Cases with HIF-1α expression >6% (high expression) were compared with those 75% of cells was compared with those with

BACKGROUND:Placental growth factor (PlGF) induces angiogenesis and promotes tissue repair, and plasma PlGF levels change markedly during acute myocardial infarction (AMI). Currently, the impact of obstructive sleep apnea (OSA) in patients with AMI is a subject of debate. Our objective was to evaluate the relationships between PlGF levels and both the severity of acute coronary syndrome (ACS) and short-term outcomes after ACS in patients with and without OSA. METHODS:A total of 538 consecutive patients (312 OSA patients and 226 controls) admitted for ACS were included in this study. All patients underwent polygraphy in the first 72 hours after hospital admission. The severity of disease and short-term prognoses were evaluated during the hospitalization period. Plasma PlGF levels were measured using an electrochemiluminescence immunoassay. RESULTS:Patients with OSA were significantly older and more frequently hypertensive and had higher BMIs than those without OSA. After adjusting for age, smoking status, BMI and hypertension, PlGF levels were significantly elevated in patients with OSA compared with patients without OSA (19.9 pg/mL, interquartile range: 16.6-24.5 pg/mL; 18.5 pg/mL, interquartile range: 14.7-22.7 pg/mL; p1, even after adjustment. CONCLUSIONS:The results of this study show that in patients with ACS, elevated plasma levels of PlGF are associated with the presence of OSA and with adverse outcomes during short-term follow-up. TRIAL REGISTRATION:ClinicalTrials.gov NCT01335087.

Aussi bien par son nombre chromosomique (2n=36) que par certaines de ses particularités morphologiques intéressant la souche, la tige, les feuilles et les graines, le M. valentina (Pau) Mateo & Figuerola offre des affinités avec les espèces de la Section Lanceolatae (Fenzl) Graebner. Un étude de la testa des graines au M.E.B. confirme l'appartenance du M. valentina à cette section (présence de papilles dorsales aplaties- linguiformes). Il ne saurait donc être considéré plus longtemps comme une sous-espèce du M. verna L. Les auteurs proposent de le transférer dans le Section Lanceolatae et de créer pour lui une série nouvelle monospécifique: Series Valentinae Çelebioglu, Favarger & J. M. Monts.

IntroductionObstructive sleep apnea (OSA) severity is based on the apnea-hypopnea index (AHI). The AHI is a simplistic measure that is inadequate for capturing disease severity and its consequences in cardiovascular diseases (CVDs). Deleterious effects of OSA have been suggested to influence the prognosis of specific endotypes of patients with acute coronary syndrome (ACS). We aim to identify respiratory polygraphy (RP) patterns that contribute to identifying the risk of recurrent cardiovascular events in patients with ACS.MethodsPost hoc analysis of the ISAACC study, including 723 patients admitted for a first ACS (NCT01335087) in which RP was performed. To identify specific RP patterns, a principal component analysis (PCA) was performed using six RP parameters: AHI, oxygen desaturation index, mean and minimum oxygen saturation (SaO2), average duration of events and percentage of time with SaO2 < 90%. An independent HypnoLaus population-based cohort was used to validate the RP components.ResultsFrom the ISAACC study, PCA showed that two RP components accounted for 70% of the variance in the RP data. These components were validated in the HypnoLaus cohort, with two similar RP components that explained 71.3% of the variance in the RP data. The first component (component 1) was mainly characterized by low mean SaO2 and obstructive respiratory events with severe desaturation, and the second component (component 2) was characterized by high mean SaO2 and long-duration obstructive respiratory events without severe desaturation. In the ISAACC cohort, component 2 was associated with an increased risk of recurrent cardiovascular events in the third tertile with an adjusted hazard ratio (95% CI) of 2.44 (1.07 to 5.56; p-value = 0.03) compared to first tertile. For component 1, no significant association was found for the risk of recurrent cardiovascular events.ConclusionA RP component, mainly characterized by intermittent hypoxemia, is associated with a high risk of recurrent cardiovascular events in patients without previous CVD who have suffered a first ACS.