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Abstract Since the first studies on bowhead whale singing behaviour, song variations have been consistently reported. However, there has been little discussion regarding variability in bowhead whale singing display and its ecological significance. Unlike the better studied humpback whales, bowhead whales do not appear to share songs at population level, but several studies have reported song sharing within clusters of animals. Over the winter season 2013–2014, in an unstudied wintering ground off Northeast Greenland, 13 song groups sharing similar hierarchical structure and units were identified. Unit types were assessed through multidimensional maps, showing well separated clusters corresponding to manually labelled units, and revealing the presence of unit subtypes. Units presented contrasting levels of variability over their acoustic parameters, suggesting that bowhead whales keep consistency in some units while using a continuum in values of frequency, duration and modulation parameters for other unit types. Those findings emphasise the need to account for variability in song analysis to better understand the behavioural ecology of this endangered species. Additionally, shifting from song toward units or phrase-based analysis, as it has been suggested for humpback whales, offers the opportunity to identify and track similarities in songs over temporal and geographical scales relevant to population monitoring.

Synthetic data promise privacy-preserving data sharing for healthcare research and development. Compared with other privacy-enhancing approaches-such as federated learning-analyses performed on synthetic data can be applied downstream without modification, such that synthetic data can act in place of real data for a wide range of use cases. However, the role that synthetic data might play in all aspects of clinical model development remains unknown. In this work, we used state-of-the-art generators explicitly designed for privacy preservation to create a synthetic version of ever-smokers in the UK Biobank before building prognostic models for lung cancer under several data release assumptions. We demonstrate that synthetic data can be effectively used throughout the medical prognostic modeling pipeline even without eventual access to the real data. Furthermore, we show the implications of different data release approaches on how synthetic biobank data could be deployed within the healthcare system., (© 2024. The Author(s).)

Using passive acoustic monitoring (PAM) and convolutional neural networks (CNN), we monitored the movements of the two endangered Amazon River dolphin species, the boto (Inia geoffrensis) and the tucuxi (Sotalia fluviatilis) from main rivers to floodplain habitats (várzea) in the Mamirauá Reserve (Amazonas, Brazil). We detected dolphin presence in four main areas based on the classification of their echolocation clicks. Using the same method, we automatically detected boat passages to estimate a possible interaction between boat and dolphin presence. Performance of the CNN classifier was high with an average precision of 0.95 and 0.92 for echolocation clicks and boats, respectively. Peaks of acoustic activity were detected synchronously at the river entrance and channel, corresponding to dolphins seasonally entering the várzea. Additionally, the river dolphins were regularly detected inside the flooded forest, suggesting a wide dispersion of their populations inside this large area, traditionally understudied and particularly important for boto females and calves. Boats overlapped with dolphin presence 9% of the time. PAM and recent advances in classification methods bring a new insight of the river dolphins' use of várzea habitats, which will contribute to conservation strategies of these species., (© 2023. The Author(s).)

The COVID-19 pandemic continues to have a devastating impact on Brazil. Brazil's social, health and economic crises are aggravated by strong societal inequities and persisting political disarray. This complex scenario motivates careful study of the clinical, socioeconomic, demographic and structural factors contributing to increased risk of mortality from SARS-CoV-2 in Brazil specifically. We consider the Brazilian SIVEP-Gripe catalog, a very rich respiratory infection dataset which allows us to estimate the importance of several non-laboratorial and socio-geographic factors on COVID-19 mortality. We analyze the catalog using machine learning algorithms to account for likely complex interdependence between metrics. The XGBoost algorithm achieved excellent performance, producing an AUC-ROC of 0.813 (95% CI 0.810-0.817), and outperforming logistic regression. Using our model we found that, in Brazil, socioeconomic, geographical and structural factors are more important than individual comorbidities. Particularly important factors were: The state of residence and its development index; the distance to the hospital (especially for rural and less developed areas); the level of education; hospital funding model and strain. Ethnicity is also confirmed to be more important than comorbidities but less than the aforementioned factors. In conclusion, socioeconomic and structural factors are as important as biological factors in determining the outcome of COVID-19. This has important consequences for policy making, especially on vaccination/non-pharmacological preventative measures, hospital management and healthcare network organization., (© 2021. The Author(s).)

The function of the external ear canal in cetaceans is still under debate and its morphology is largely unknown. Immunohistochemical (IHC) analyses using antibodies specific for nervous tissue (anti-S100, anti-NSE, anti-NF, and anti-PGP 9.5), together with transmission electron microscopy (TEM) and various histological techniques, were carried out to investigate the peripheral nervous system of the ear canals of several species of toothed whales and terrestrial Cetartiodactyla. This study highlights the innervation of the ear canal with the presence of lamellar corpuscles over its entire course, and their absence in all studied terrestrial mammals. Each corpuscle consisted of a central axon, surrounded by lamellae of Schwann receptor cells, surrounded by a thin cellular layer, as shown by IHC and TEM. These findings indicate that the corpuscles are mechanoreceptors that resemble the inner core of Pacinian corpuscles without capsule or outer core, and were labelled as simple lamellar corpuscles. They form part of a sensory system that may represent a unique phylogenetic feature of cetaceans, and an evolutionary adaptation to life in the marine environment. Although the exact function of the ear canal is not fully clear, we provide essential knowledge and a preliminary hypothetical deviation on its function as a unique sensory organ.

While the Greenland and Barents Seas are known habitats for several cetacean and pinniped species there is a lack of long-term monitoring data in this rapidly changing environment. Moreover, little is known of the ambient soundscapes, and increasing off-shore anthropogenic activities can influence the ecosystem and marine life. Baseline acoustic data is needed to better assess current and future soundscape and ecosystem conditions. The analysis of a year of continuous data from three passive acoustic monitoring devices revealed species-dependent seasonal and spatial variation of a large variety of marine mammals in the Greenland and Barents Seas. Sampling rates were 39 and 78 kHz in the respective locations, and all systems were operational at a duty cycle of 2 min on, 30 min off. The research presents a description of cetacean and pinniped acoustic detections along with a variety of unknown low-frequency tonal sounds, and ambient sound level measurements that fall within the scope of the European Marine Strategy Framework (MSFD). The presented data shows the importance of monitoring Arctic underwater biodiversity for assessing the ecological changes under the scope of climate change.

Accurate prediction of survival for cystic fibrosis (CF) patients is instrumental in establishing the optimal timing for referring patients with terminal respiratory failure for lung transplantation (LT). Current practice considers referring patients for LT evaluation once the forced expiratory volume (FEV 1 ) drops below 30% of its predicted nominal value. While FEV 1 is indeed a strong predictor of CF-related mortality, we hypothesized that the survival behavior of CF patients exhibits a lot more heterogeneity. To this end, we developed an algorithmic framework, which we call AutoPrognosis, that leverages the power of machine learning to automate the process of constructing clinical prognostic models, and used it to build a prognostic model for CF using data from a contemporary cohort that involved 99% of the CF population in the UK. AutoPrognosis uses Bayesian optimization techniques to automate the process of configuring ensembles of machine learning pipelines, which involve imputation, feature processing, classification and calibration algorithms. Because it is automated, it can be used by clinical researchers to build prognostic models without the need for in-depth knowledge of machine learning. Our experiments revealed that the accuracy of the model learned by AutoPrognosis is superior to that of existing guidelines and other competing models.

Despite dedicated research has been carried out to adequately map the distribution of the sperm whale in the Mediterranean Sea, unlike other regions of the world, the species population status is still presently uncertain. The analysis of two years of continuous acoustic data provided by the ANTARES neutrino telescope revealed the year-round presence of sperm whales in the Ligurian Sea, probably associated with the availability of cephalopods in the region. The presence of the Ligurian Sea sperm whales was demonstrated through the real-time analysis of audio data streamed from a cabled-to-shore deep-sea observatory that allowed the hourly tracking of their long-range echolocation behaviour on the Internet. Interestingly, the same acoustic analysis indicated that the occurrence of surface shipping noise would apparently not condition the foraging behaviour of the sperm whale in the area, since shipping noise was almost always present when sperm whales were acoustically detected. The continuous presence of the sperm whale in the region confirms the ecological value of the Ligurian sea and the importance of ANTARES to help monitoring its ecosystems.

Recent findings on cephalopods in laboratory conditions showed that exposure to artificial noise had a direct consequence on the statocyst, sensory organs, which are responsible for their equilibrium and movements in the water column. The question remained about the contribution of the consequent near-field particle motion influence from the tank walls, to the triggering of the trauma. Offshore noise controlled exposure experiments (CEE) on common cuttlefish (Sepia officinalis), were conducted at three different depths and distances from the source and particle motion and sound pressure measurements were performed at each location. Scanning electron microscopy (SEM) revealed injuries in statocysts, which severity was quantified and found to be proportional to the distance to the transducer. These findings are the first evidence of cephalopods sensitivity to anthropogenic noise sources in their natural habitat. From the measured received power spectrum of the sweep, it was possible to determine that the animals were exposed at levels ranging from 139 to 142 dB re 1 μPa 2 and from 139 to 141 dB re 1 μPa 2 , at 1/3 octave bands centred at 315 Hz and 400 Hz, respectively. These results could therefore be considered a coherent threshold estimation of noise levels that can trigger acoustic trauma in cephalopods.

Jellyfishes represent a group of species that play an important role in oceans, particularly as a food source for different taxa and as a predator of fish larvae and planktonic prey. The massive introduction of artificial sound sources in the oceans has become a concern to science and society. While we are only beginning to understand that non-hearing specialists like cephalopods can be affected by anthropogenic noises and regulation is underway to measure European water noise levels, we still don't know yet if the impact of sound may be extended to other lower level taxa of the food web. Here we exposed two species of Mediterranean Scyphozoan medusa, Cotylorhiza tuberculata and Rhizostoma pulmo to a sweep of low frequency sounds. Scanning electron microscopy (SEM) revealed injuries in the statocyst sensory epithelium of both species after exposure to sound, that are consistent with the manifestation of a massive acoustic trauma observed in other species. The presence of acoustic trauma in marine species that are not hearing specialists, like medusa, shows the magnitude of the problem of noise pollution and the complexity of the task to determine threshold values that would help building up regulation to prevent permanent damage of the ecosystems.