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Previous evidence suggests that mindfulness training may improve aspects of psychosocial well-being. Whilst mindfulness is traditionally taught in person, consumers are increasingly turning to mindfulness-based smartphone apps as an alternative delivery medium for training. Despite this growing trend, few studies have explored whether mindfulness delivered via a smartphone app can enhance psychosocial well-being within the general public. The present pilot randomised controlled trial compared the impact of engaging with the self-guided mindfulness meditation (MM) app 'Headspace' (n = 38) for a period of 10 or 30 days, to a wait-list (WL) control (n = 36), using a cohort of adults from the general population. The Satisfaction with Life Scale, Perceived Stress Scale, and Wagnild Resilience Scale were administered online at baseline and after 10 and 30 days of the intervention. Twelve participants (MM n = 9, WL n = 3) were lost to follow-up for unknown reasons. Relative to the WL control, the MM app positively impacted self-reported satisfaction with life, stress, and resilience at day 10, with further improvements emerging at day 30 (Cohen's d = 0.57, 1.42, 0.63 respectively). The rate of improvement was largest at the 10-day assessment point, dropping moderately by day 30. Participants that rated the MM app as easy to engage with experienced the largest self-reported benefits. Moreover, the MM app was able to protect against an unexpected increase in perceived stress that emerged in the control group. This pilot randomised controlled trial shows that self-reported improvements in psychosocial outcomes can be achieved at low cost through short-term engagement with a mindfulness-based smartphone app, and should be followed up with more substantive studies. ISRCTN ISRCTN34618894.

The rapid increase in the number of proteins in sequence databases and the diversity of their functions challenge computational approaches for automated function prediction. Here, we introduce DeepFRI, a Graph Convolutional Network for predicting protein functions by leveraging sequence features extracted from a protein language model and protein structures. It outperforms current leading methods and sequence-based Convolutional Neural Networks and scales to the size of current sequence repositories. Augmenting the training set of experimental structures with homology models allows us to significantly expand the number of predictable functions. DeepFRI has significant de-noising capability, with only a minor drop in performance when experimental structures are replaced by protein models. Class activation mapping allows function predictions at an unprecedented resolution, allowing site-specific annotations at the residue-level in an automated manner. We show the utility and high performance of our method by annotating structures from the PDB and SWISS-MODEL, making several new confident function predictions. DeepFRI is available as a webserver at https://beta.deepfri.flatironinstitute.org/ . The rapid increase in the number of proteins in sequence databases and the diversity of their functions challenge computational approaches for automated function prediction. Here, the authors introduce DeepFRI, a Graph Convolutional Network for predicting protein functions by leveraging sequence features extracted from a protein language model and protein structures.

For the past half-century, structural biologists relied on the notion that similar protein sequences give rise to similar structures and functions. While this assumption has driven research to explore certain parts of the protein universe, it disregards spaces that don’t rely on this assumption. Here we explore areas of the protein universe where similar protein functions can be achieved by different sequences and different structures. We predict ~200,000 structures for diverse protein sequences from 1,003 representative genomes across the microbial tree of life and annotate them functionally on a per-residue basis. Structure prediction is accomplished using the World Community Grid, a large-scale citizen science initiative. The resulting database of structural models is complementary to the AlphaFold database, with regards to domains of life as well as sequence diversity and sequence length. We identify 148 novel folds and describe examples where we map specific functions to structural motifs. We also show that the structural space is continuous and largely saturated, highlighting the need for a shift in focus across all branches of biology, from obtaining structures to putting them into context and from sequence-based to sequence-structure-function based meta-omics analyses. Advances in protein structure prediction have led to a significant influx of protein structure data. Here the authors exploit this data to offer an unbiased overview of complex sequence-structure-function relationships in the protein universe. This work opens up new uses for 3D structure data repositories in meta-omics and other fields of biology.

Background and Objectives: The impact of gynaecological cancer and its treatments on sexual intimacy can be profound on female sexuality. However, very few registered clinical trials have addressed sexual intimacy among this cohort. Materials and Methods: This preliminary randomised control trial (RCT) and content analysis assessed the effectiveness of a brief online mindful compassion group intervention adjunct with cannabis suppositories. Eighty-three participants aged between 18 and 50+ years who were at least six months post-cancer treatment were randomly allocated to one of four groups, depending on whether they were already using cannabis suppositories. These included a cannabis-only group (CO), a mindful-compassion group (MC), a combined mindful-compassion and cannabis suppositories group (COCM) and a care-as-usual group (CAU). Measurements of sexual function, sexual self-efficacy, mindful compassion, well-being and quality of life were taken at weeks 0, 4 and 12. Results: Sexual function, including arousal, lubrication and orgasms, improved for both the MC p = 0.002 and COCM p ≤ 0.001 groups; in addition, sexual pain was reduced in the COCM p = 0.008 and CO p ≤ 0.001 groups compared to the CAU and MC groups, where p ≥ 0.05. Feedback suggested that cannabis mediated the effects of mindful compassion and supported well-being, sexual self-efficacy, and quality of life. Participants also voiced a preference for cannabis suppositories when using dilators as part of their treatment and the use of sex toys instead of dilators, suggesting that dilators had negatively impacted their sexuality. Conclusions: These preliminary and exploratory outcomes look promising and provide a foundation for future research to develop varied healthcare options to improve mental health service delivery and quality of life for this cohort.

Background/Objective Loneliness and depression are highly comorbid, and both are associated with social processing deficits. However, there is a paucity of research aimed at differentiating emotional face‐processing deficits that are comorbid to loneliness and depression versus those attributable to loneliness or depression only. Methods 502 participants were recruited and screened for loneliness (UCLA Loneliness Scale) and depression (Beck Depression Inventory). Of those, seventy‐seven took part in a fully crossed 2 (loneliness; low/high) * 2 (depression; low/high) factorial between‐subjects design study to assess individual and comorbid effects of loneliness and depression on a computerized morphed facial emotion processing task. Results Comorbidity was confirmed by a significant positive correlation between loneliness and depression. On the emotion processing task, loneliness was associated with an increased accuracy for sad faces and decreased accuracy for fearful faces and depression with decreased accuracy in identifying happy faces. Comorbid loneliness and depression resulted in an increased misattribution of neutral faces as sad, an effect that was also seen in those who were either only lonely or only depressed. Conclusion This if the first study to tease out comorbid versus independent effects of loneliness and depression on social information processing. To the extent that emotional biases may act as risk factors for detrimental outcomes, our findings highlight the importance of treating both loneliness and depression. Loneliness and depression are highly co‐morbid and both are associated with basic social processing deficits. However, there is a paucity of research aimed at differentiating emotional face processing deficits that are attributable to loneliness versus depression only. Using a novel fully crossed experimental design, the present study aims to tease out individual effects that are due to loneliness versus depression. This will enhance our understanding of loneliness and depression.

The bloom of pelagic Sargassum in the Atlantic Ocean has become increasingly problematic, especially when the algae have beached. A build-up of decaying beached material has damaging effects on coastal ecosystems and tourism industries. While remote sensing offers an effective tool to assess the spatial and temporal patterns of Sargassum over large spatial extents, its use so far has been limited to a broad discrimination of Sargassum species from other macroalgae and floating vegetation. Knowledge on the spatial distribution of decayed material will help to support management strategies and inform targeted removal. In this study, we aim to characterise the spectral response of fresh and decayed Sargassum and identify regions of the spectra that offer the greatest separability for the detection and classification of decayed material. We assessed the spectral response of fresh and decayed Sargassum (1) in situ on the beach and (2) in mesocosm experiments where Sargassum samples were allowed to decay over time. We found a decrease in the magnitude of reflectance, noticeably in the visible region (400–700 nm), for decayed, in contrast to fresh, Sargassum. Separability analyses also showed that most spectral bands with a wavelength > ~540 nm will be capable of discriminating between fresh and decayed material, although the near-infrared region offers the greatest degree of separability. We demonstrate, for the first time, that there are clear differences in the spectral reflectance of fresh and decayed Sargassum with potential application for remote sensing approaches.

Lianas (woody vines) play a key role in tropical forest dynamics because of their strong influence on tree growth, mortality and regeneration. Assessing liana infestation over large areas is critical to understand the factors that drive their spatial distribution and to monitor change over time. However, it currently remains unclear whether satellite-based imagery can be used to detect liana infestation across closed-canopy forests and therefore if satellite-observed changes in liana infestation can be detected over time and in response to climatic conditions. Here, we aim to determine the efficacy of satellite-based remote sensing for the detection of spatial and temporal patterns of liana infestation across a primary and selectively logged aseasonal forest in Sabah, Borneo. We used predicted liana infestation derived from airborne hyperspectral data to train a neural network classification for prediction across four Sentinel-2 satellite-based images from 2016 to 2019. Our results showed that liana infestation was positively related to an increase in Greenness Index (GI), a simple metric relating to the amount of photosynthetically active green leaves. Furthermore, this relationship was observed in different forest types and during (2016), as well as after (2017–2019), an El Niño-induced drought. Using a neural network classification, we assessed liana infestation over time and showed an increase in the percentage of severely (>75%) liana infested pixels from 12.9% ± 0.63 (95% CI) in 2016 to 17.3% ± 2 in 2019. This implies that reports of increasing liana abundance may be more wide-spread than currently assumed. This is the first study to show that liana infestation can be accurately detected across closed-canopy tropical forests using satellite-based imagery. Furthermore, the detection of liana infestation during both dry and wet years and across forest types suggests this method should be broadly applicable across tropical forests. This work therefore advances our ability to explore the drivers responsible for patterns of liana infestation at multiple spatial and temporal scales and to quantify liana-induced impacts on carbon dynamics in tropical forests globally.

Permafrost thaw resulting from climate warming is threatening to release carbon from high latitude peatlands. The aim of this research was to determine subsidence rates linked to permafrost thaw in sub-Arctic peatlands in Sweden using historical orthophotographic (orthophotos), Unoccupied Aerial Vehicle (UAV), and Interferometric Synthetic Aperture Radar (InSAR) data. The orthophotos showed that the permafrost palsa on the study sites have been contracting in their areal extent, with the greatest rates of loss between 2002 and 2008. The surface motion estimated from differential digital elevation models from the UAV data showed high levels of subsidence (maximum of −25 cm between 2017 and 2020) around the edges of the raised palsa plateaus. The InSAR data analysis showed that raised palsa areas had the greatest subsidence rates, with maximum subsidence rates of 1.5 cm between 2017 and 2020; however, all wetland vegetation types showed subsidence. We suggest that the difference in spatial units associated with each sensor explains parts of the variation in the subsidence levels recorded. We conclude that InSAR was able to identify the areas most at risk of subsidence and that it can be used to investigate subsidence over large spatial extents, whereas UAV data can be used to better understand the dynamics of permafrost degradation at a local level. These findings underpin a monitoring approach for these peatlands.

Trichomonas vaginalis , the causative agent of the venereal disease trichomoniasis, infects men and women globally and is associated with serious outcomes during pregnancy, increased risk of HIV-1 infection, and cancers of the human reproductive tract. Species of trichomonad parasitize a range of hosts in addition to humans, including birds, livestock, and pets. Genetic analysis of trichomonads recovered from columbid birds has provided evidence that they undergo frequent host-switching, and that a spillover event from columbids likely gave rise to T. vaginalis in humans. Here we describe a comparative genomics study of seven trichomonad species, generating chromosome-scale reference genomes for T. vaginalis and its avian sister species Trichomonas stableri , and assemblies of five other species that infect birds and mammals. Human-infecting trichomonad lineages have undergone recent and convergent genome size expansions compared to their avian sister species, a result of extensive repeat expansions specifically of multicopy gene families and transposable elements, with genetic drift likely a driver due to relaxed selection. Trichomonads are thought to have independently host-switched twice from birds to mammals/humans. We identify gene functions implicated in the transition, including host tissue adherence and phagocytosis, extracellular vesicle formation, and CAZyme virulence factors, which are all associated with pathogenesis phenotypes. The sexually transmitted human parasite Trichomonas vaginalis belongs to a clade of host-switching trichomonads that parasitize mammals, birds, livestock, and pets. Here the authors describe a chromosome-scale genome for T. vaginalis and assemblies of other bird and mammal-infecting species, identifying gene functions implicated in the spillover of trichomonads from birds to humans.

Sexual intimacy is a basic human need that is associated with quality of life whereby its absence can significantly impact both interpersonal and personal wellbeing. This systematic review aimed to provide an up-to-date evaluation of the available literature on mindfulness treatments for sexual functioning in women diagnosed with cancer. Electronic searches including PubMed, PsycINFO, Web of Science and registered clinical trials yielded 10 studies that met the inclusion criteria. The results showed that treatment intervention designs varied and included mixed methods, randomised clinical trials, single arm non-randomised trials and those with the absence of any control. Furthermore, both brief and longer-term mindfulness interventions were trialled across different sexual domains. Whilst inconclusive, mindfulness-based interventions appear to support sexual function and quality of life in both early- and post-cancer survivors. However, in some instances, there were outcome inconsistencies in sexual desire, arousal and orgasm. This review has identified a current shortage in research on the effectiveness of mindfulness-based treatments for supporting sexual functioning in women with cancer; and so far, no research has been conducted in palliative care. This unmet need in supporting sexual functioning in women with cancer, including palliative care, carries important implications for both psychosexual and oncological healthcare services as sexual intimacy does not end with cancer diagnosis or prognosis.