Timing Of Events Research Articles

Personalized risk assessment of new onset depression in long-term cancer survivors.

e13798 Background: Advances in cancer detection and treatment have improved long-term survival. It is critical to understand the impact that experiencing cancer has on psychological health, given that the prevalence of depression in long-term survivors is higher than in the general population. Our aim was to develop a risk prediction model to identify long-term (5-year) survivors at high risk of developing depression. Methods: We conducted a retrospective study of the SEER-Medicare database beneficiaries with localized breast, prostate, colon, or rectal cancer diagnosed between 2003-2011 who had survived at least 5 years since diagnosis. We required Part D coverage in the breast cohort to account for adjuvant endocrine therapy. Our primary outcome was the cumulative incidence of depression between 5-10 years after diagnosis, which was defined using a claims-based algorithm as a single or recurrent episode of major depressive disorder, recent episode of bipolar I disorder, or dysthymic disorder. For each cancer site, we constructed restricted mean survival time models, a non-parametric method that yields time ratios; a time ratio (TR) < 1 indicates shorter mean time to event (TTE). Results: Our cohort consisted of 80,579 survivors. The cumulative incidence of depression occurring between 5-10 years after diagnosis was 16.9% for breast cancer, 7.8% for prostate cancer, 10.6% for colon cancer, and 8.6% for rectal cancer. The cumulative incidence of new onset depression increased over time and was 7.2% vs. 13.9% among survivors diagnosed before and after 2008, respectively. Compared with patients age < 70 at diagnosis, patients aged 75 and older exhibited 5-10% shorter mean TTE across breast, prostate, and colon cancer. There was no association between Non-Hispanic (NH) Black race or Hispanic ethnicity and depression compared with NH White survivors. Asian survivors were at lower risk of developing depression. Disease specific factors, including stage, grade, hormone receptor status (breast), or PSA (prostate), did not predict depression in long-term survivors. Receipt of treatment in the 3-5 years after initial diagnosis was associated with moderately greater risk for all survivors, with the shortest mean TTE among breast cancer survivors (TR=0.91, 95% CI=0.85-0.97). Across all cohorts, the greatest predictor of depression was a prior history of depression. The incidence of depression in long-term survivors was 42% in patients with a prior history of depression vs. 8% among survivors without a prior history of depression. Conclusions: Diagnoses of depression increased in cancer patients since 2008 and were associated with prior history of depression, advanced age, census tract poverty, and continued treatment 3 years after diagnosis. Treatment type and disease specific factors were not strong predictors of depression.

Dynamic machine learning model to forecast patient availability for clinical trials.

e13641 Background: Patient eligibility is a routine concept in clinical research, comprised of simple or complex set of inclusion or exclusion criteria applied in a specific sequence. Our methodology introduces the concept of ‘availability’ as a narrower term that is closer to the actual number that will be considered for a specific study and who may decide to participate. This specific research develops Machine Learning (ML) model that dynamically predicts likelihood of Multiple Myeloma progression and departure from targeted outcomes to sustain therapy and to indicate potential availability for clinical trials – to reduce screening efforts and improve screening precision of clinical research organizations. Methods: The cohort for training these models was drawn from the ConcertAI Oncology Research database, further enriched by key variables derived from unstructured data sources. Eligible patients for the analysis had a diagnosis of Multiple Myeloma made after Jan 1, 2020. Progressions were labelled using International Myeloma Working Group Criteria. Patients that did not satisfy the criteria were censored. Labels were assigned to patients after initial diagnosis of MM, and the duration between diagnosis to label was computed to build time to event (TTE) models. Over 2000 features were created to build this model, e.g., laboratory values, vitals, biomarkers, medications, ECOG, stage, etc. Variable creation preserved temporality of lab variables and vitals and noted presence of other variables. Several ML methods were employed to build the TTE models, with gradient boosting resulting in the highest c-index (0.8) based on 12 clinically relevant features. A temporal validation of the model was performed on a simulated index date. Results: Cohort used for training the model comprised of N = 4315 patients with average age at diagnosis of 72.3 years, and ~11% of the patients labelled as progressing. Temporal validation was performed on N = 1874 patients, with ~9% progression rate. The area under the curve (AUC) and weighted F1 score for this cohort was 87% and 89% respectively. Conclusions: Patient availability assessments are complex, not supported effectively by existing solutions and often require 100’s of hours from highly trained clinical personnel. An AI model predicting Multiple Myeloma progression built using a large-scale real-world dataset demonstrated 2-4x improvement in forecasting patient availability over other approaches. Integrating these solutions into clinical workflows can improve the effectiveness of research teams; enable more patients to have clinical trials as viable options at the right time; and allow care teams to have forward visibility to choices of standard-of-care and clinical trial alternatives in the best interest of patient outcomes. [Table: see text]

Deathbed experiences and meaning-making: Perspectives of family caregivers of patients who received cancer palliative care.

The deathbed symbolizes a time when the patient is dangerously ill and where death is imminent. The memories of family caregivers during this time can potentially shape their meaning-making of the patient's death and bereavement adjustment. We aimed to understand the experiences of family caregivers at the deathbed of patients receiving palliative care. We also examined caregiver's meaning-making that occurred after the patient's death. In this retrospective qualitative study, family caregivers of cancer patients who received palliative care in Singapore were recruited through purposive sampling. In-person, semi-structured interviews were individually conducted with study participants to understand their experiences from a caregiver's perspective before and after the death of the patient. Thematic content analysis method was conducted. A total of 25 bereaved family caregivers were interviewed, with spouses, adult children, and others comprising one-third each of the sample. Six themes emerged from caregivers' recollected experiences around the patient deathbed: Lasting image of the patient, A time of intense emotions, Healthcare providers prepare caregivers, A time for saying goodbye, Rituals provide comfort, and Impact on family ties. Four themes emerged surrounding post-loss meaning-making: An end to the pain and suffering, "Have I done enough?," Significance in the timing of events, and Gaining strength and personal growth. The deathbed is a salient time for family caregivers as they prepare for patient's death. There are opportunities to provide support to the family based on the study findings.

Lithologies and Chronologic Opportunities of Materials to Be Returned From the Artemis Exploration Zone

AbstractThe Artemis exploration zone is a geologically complex region likely to host some of the oldest and as‐yet‐unstudied materials on the Moon. We review six potential Artemis landing sites (001, 004, 007, 011, 102, and 105) within candidate Artemis III landing regions ”Connecting Ridge,“ “Peak Near Shackleton,” “Leibnitz Beta Plateau,” “de Gerlache Rim,” and “de Gerlache Rim 2.” Kaguya Spectral Profiler mineral data were used to determine the average lithological composition at each landing site. Potentially accessible geologic materials, their ages and significance, and appropriate application of radiometric chronometers are discussed in reference to return samples from each potential landing site. Chronological analyses of return samples from the Artemis exploration zone will enable the anchoring of the lunar impact flux curve, determine the absolute timing of pivotal events in lunar geologic history, and reveal the geological diversity of the differentiated lunar body.

A rapid assessment tool for systemic treatment outcomes in colorectal cancer with deep bidirectional transformers.

e15567 Background: Retrospective investigations involving cancer treatment encounter the challenge of manually reviewing voluminous imaging reports to identify the best responses and the timing of disease progression. Here, we employed natural language processing, specifically deep bidirectional transformers, to automate the extraction of treatment response data. Methods: Data were sourced from the Yonsei Cancer Data Library database, focusing on patients with stage II-IV colorectal cancer at the Yonsei Cancer Center from Jan 1, 2010, to Dec 31, 2020. Imaging reports from 6,574 patients were gathered, amounting to 97,119 CT readings. Among these, 9,000 CT reports corresponding to 2,859 patients were randomly subjected to multilabel manual labeling by four radiology experts, based on the RECIST version 1.1 classification (CR/NED, PR, SD, PD). The pretrained BERT-base-uncased model was employed and fine-tuned for the downstream tasks of multilabel classification. 6,765 reports were used for training, while the remaining 1,000 reports were divided equally between the validation and test sets. Additionally, an algorithm for integrating and extracting treatment response data was also implemented. Clinical data were meticulously collected for 47 patients with stage IV early-onset colorectal cancer (EOCRC) receiving palliative first-line chemotherapy. The primary objective was to evaluate the model’s accuracy in predicting the timing of disease progression events within a ±30-day window. Secondary objectives focused on the model’s ability to identify the best response and its timing within a ±45-day window. Results: The evaluation of the classification accuracy across 1,000 individual CT reports, categorized as CR/NED (319), PR (86), SD (272), and PD (298), revealed accuracy with an AUROC of 0.956 and an F1 score of 0.823. All EOCRC patients were initially diagnosed with stage IV disease, and 45 out of 47 (95.7%) underwent metastasectomy either before initiating chemotherapy or during the first-line chemotherapy treatment. In clinical evaluation, the model demonstrated 72.3% (95% Confidence Interval [CI], 59.5-85.1) accuracy in predicting the day of disease progression within a ±30-day window. It achieved 55.3% (95% CI, 41.1-69.5) accuracy in predicting the best response category and its timing within ±45-days. Notably, the model was more accurate in predicting CR/NED at 72% compared to SD and PR, which had accuracy of 27.3% and 15.4%, respectively. Conclusions: Our model demonstrated high performance in classifying CT reports, which is expected to provide rapid insights into patient progress and improve clinical decision-making. However, the complexity involved in integrating and extracting data result in slight constraints in performance. This emphasizes the need for further research into multimodal large language models that can integrate a wider variety of clinical data.

Trends and Climate‐Sensitivity of Phenology in China's Natural and Planted Forests

AbstractForest is the largest carbon sink on land, and the timing of forest phenology profoundly influences carbon uptake. However, disparities in the timing and sensitivity of forest phenology, particularly between planted forests (PF) and natural forests (NF), have yet to be determined. In this study, we analyzed the phenological trends and the climate‐sensitivities of China's NF and PF from 2000 to 2022 using field survey data and satellite data. We found that the start of the growing season (start of the season (SOS)) in NF and PF advanced significantly by 0.07 and 0.08 days yr−1, while the end of the growing season (end of the season (EOS)) in both NF and PF delayed by 0.06 days yr−1. Moreover, precipitation and air temperature jointly influenced the timing of phenological events. The pre‐season precipitation delayed the EOS by 0.009 days mm−1 and 0.006 days mm−1 in NF and PF. Moreover, the SOS was more sensitive to precipitation in PF than in NF in arid areas (i.e., pre‐season precipitation <100 mm). Air temperature significantly advanced the SOS by 0.74 and 0.95 days °C−1 in NF and PF and delayed the EOS by 0.89 and 0.71 days °C−1 in NF and PF. Additionally, the sensitivities of SOS and EOS to air temperature significantly differed between NF and PF. Our findings demonstrate a significant phenological discrepancy between PF and NF. The results suggest that NF and PF responded differently to climate variability, implying forest origin should be considered in the projection of carbon sequestration capability under changing climate.

Utility of the NLR and the ratio of NLR after and before adverse events for identifying irAEs and bacterial infections in patients with cancer during PD-(L)1 inhibitors treatment.

e14620 Background: Identifying immune-related adverse events (irAEs) or bacterial infections in cancer patients undergoing treatment with PD-(L)1 inhibitors can be challenging. This study aimed to assess the effectiveness of the neutrophil-to-lymphocyte ratio (NLR) in distinguishing between irAEs and bacterial infections in cancer patients receiving PD-(L)1 inhibitors. Methods: We conducted a retrospective analysis of cancer patients who received at least one dose of PD-(L)1 inhibitors at Affiliated Cancer Hospital of Zhengzhou University from 2018 to 2023. We compared the changes in peripheral blood cell counts before and after the occurrence of adverse events, as well as the ratio of the NLR at the time of adverse events (post-NLR) to the NLR before adverse events (pre-NLR). Bacterial infections were diagnosed based on clear etiology and/or controlled adverse events through the use of antibiotics without systemic glucocorticoid administration during treatment. irAEs were diagnosed based on clinicolaboratory criteria, or the improvement of immune system disorders after withdrawal of PD-(L)1 inhibitors or systemic glucocorticoid administration, excluding bacterial infection. Data were collected from microbiology, radiography, serology, and physician notes. Results: Among the 4173 patients who were administered PD-(L)1 inhibitors, 217 individuals experienced a total of 249 irAEs, while 256 patients were diagnosed with 257 bacterial infections. When comparing pre-infection levels with those after bacterial infection, it was observed that the NLR increased significantly. Similarly, in the group experiencing irAEs, the NLR also showed a significant increase after the occurrence of the irAEs. Notably, the NLR was significantly higher in patients with bacterial infections compared to those with irAEs [11.08 (6.63, 19.29) vs 2.78 (1.92, 4.31), P < 0.001]. Furthermore, the post-NLR/pre-NLR ratio was higher in the bacterial infection group than in the irAEs group [2.86 (1.56, 6.20) vs 1.16 (0.82, 1.76), P < 0.001]. Appraising the potential of NLR and the post-NLR/pre-NLR ratio in identifying irAEs and bacterial infections in cancer patients, the receiver operating characteristic (ROC) curve analysis was performed. The area under the curve (AUC) was 0.91 for NLR and 0.81 for the post-NLR/pre-NLR ratio, respectively. Using a cut-off value of 4.56 for NLR and 1.96 for the post-NLR/pre-NLR ratio yielded the highest sensitivity and specificity. Conclusions: The NLR along with the post-NLR/pre-NLR ratio could serve as valuable diagnostic indicators for irAEs and bacterial infections in cancer patients undergoing treatment with PD-(L)1 inhibitors.

Ohio River basin snow ablation and the role of rain‐on‐snow

AbstractSnow cover ablation within the Ohio River Basin (ORB) plays an important role in regional hydroclimatology, while also representing a potential hazard during large and rapid events. Rain‐on‐snow ablation is a particular challenge, where runoff rates are typically enhanced due to the dual inputs of snowmelt and liquid precipitation. Here, we present a 40‐year climatology of snow ablation events frequency, intensity, and timing for the ORB using a 4‐km gridded snow‐water‐equivalent dataset, focusing on the relative proportion of events caused by rain‐on‐snow and changes over time. Spatial patterns of snow ablation frequency and intensity mirror that of seasonal snowfall totals, with higher (lower) values in the northern and eastern (southern) portions of the basin. Rain‐on‐snow events represent approximately 40% of all ablation events within the basin and result in approximately 24%–25% more snow‐water‐equivalent loss than non‐rain‐on‐snow events, plus an additional 3–12 mm of liquid precipitation per event on average. Peak frequency of ablation and rain‐on‐snow events occurs in late winter and early spring, similar to that of the surrounding region. Over time, the frequency of ablation and rain‐on‐snow events has decreased in the northern and eastern portions of the basin, in some cases by as much as 30%. Trends in event magnitudes were more isolated but decreased across portions of central IN, northern KY, eastern OH and northern WV. Additionally, the magnitude of precipitation during rain‐on‐snow events has increased across the region, extending from northern KY into western PA by over 100% in many cases. Broadly, we find tendencies towards fewer events with less snow loss but more liquid precipitation that suggest complicated impacts to the hydroclimatology warranting further investigation.

Seismic Swell Effect Correction Using GVF-Based Guideline

Swells in marine seismic data disrupt the continuity of the reflection events and make interpretation difficult. The swell effect removal process consists of sea-bottom detection and correction, which removes the swell effect by shifting the detected sea-bottom signal to the known or estimated seafloor location. The quality of correction depends on the accuracy of the sea-bottom detection. Since general sea-bottom signal detection techniques have been applied directly after pre-processing, many mispick scenarios exist due to the characteristics of the data, and additional processes are needed. This study proposes a method for accurately detecting sea-bottom reflection signals using the guideline. The errors are caused by mistaking other reflection events as sea-bottom signals. The guideline can improve detection accuracy by providing rough event times of sea-bottom reflection. The guideline was extracted from the gradient vector flow (GVF) technique, a segmentation method in image processing. In the GVF data, the seafloor signals are smoothed, and the energy is focused on the sea bottom. The threshold method detected sea-bottom signals in the range after the guideline. The detected signals were shifted to estimated seafloor locations to attenuate the swell effect. The GVF-based guideline (GVF-GL) method was applied to field data acquired by the airgun and chirp sources with different frequencies. The sea-bottom location was successfully detected, and the continuity of the sea-bottom and subsurface signals in the section was improved.

An event-based distributed least square linear equation solver employing network flow

In this article, we study a distributed, second-order, event-triggered network flow for solving linear algebraic equations described by the form z=Hy in the sense of least squares. An undirected graph is utilized to describe the distributed computation network. In the network, each node broadcasts its dynamic states to its neighbors in an asynchronous fashion, and updates the flow at the isolated event times. We construct a specific trigger function to determine the event times, in which an exponential decay function is introduced as a comparison term. We show that if the linear algebraic equation has a unique least squares solution, all nodes states converge to this unique solution exponentially fast, when the applied network is connected and the decay rate of the comparison term satisfies certain bounds determined jointly by the topology and the linear equations information. We obtain a strictly positive lower bound on the time interval between consecutive events for time t∈[0,∞), and therefore the event-triggered system does not exhibit Zeno behavior. We provide numerical examples to verify the effectiveness of the proposed event-based network flow. In addition, we illustrate the importance of the strictly positive inter-event time interval, in comparison with the case that the inter-event time interval may converge to zero when time t goes to infinity.

TDK részvétel motivációi a Debreceni Egyetem Tehetséggondozó Programjában résztvevő hallgatók körében

Recognition and support of outstanding students are among the most important tasks of higher education, as they can thereby be motivated to pursue a career in academia. In our study, we examined the willingness of members of the Talent Management Program (DETEP) at the University of Debrecen to participate and present at scientific student conferences. Our research was based on a questionnaire survey. The sample consisted of respondents who had previously participated in local TDK conferences (n=128). Based on our results, we can conclude that students who have participated three or more times in TDK events are considering a future career in academia. Respondents who have participated only once mainly participate for the purpose of the competition According to the results between achieving the ranking and the experience of participating in the TDK, participation is experienced as a positive experience if they manage to achieve a ranking at the local conference. Additionally, achieving a ranking also affects the feeling of gaining an advantage during studies and faculty recognition among the respondents.

Radial Variations in Solar Type III Radio Bursts

Type III radio bursts are generated by electron beams accelerated at reconnection sites in the corona. This study, utilizing data from the Parker Solar Probe’s first 17 encounters, closely examines these bursts down to 13 solar radii. A focal point of our analysis is the near-radial alignment (within 5°) of the Parker Solar Probe, STEREO-A, and Wind spacecraft relative to the Sun. This alignment, facilitating simultaneous observations of 52 and 27 bursts by STEREO-A and Wind respectively, allows for a detailed differentiation of radial and longitudinal burst variations. Our observations reveal no significant radial variations in electron beam speeds, radio fluxes, or exponential decay times for events below 50 solar radii. In contrast, closer to the Sun we noted a decrease in beam speeds and radio fluxes. This suggests potential effects of radio beaming or alterations in radio source sizes in this region. Importantly, our results underscore the necessity of considering spacecraft distance in multispacecraft observations for accurate radio burst analysis. A critical threshold of 50 solar radii emerges, beyond which beaming effects and changes in beam speeds and radio fluxes become significant. Furthermore, the consistent decay times across varying radial distances point toward a stable trend extending from 13 solar radii into the inner heliosphere. Our statistical results provide valuable insights into the propagation mechanisms of type III radio bursts, particularly highlighting the role of scattering near the radio source when the frequency aligns with the local electron plasma frequency.

A User - Friendly Signal-Processing App For Harmonics

Harmonics, especially the 3^rd,5^th, and 7^th components, are significant disturbances in power systems, occurring simultaneously and at varying time intervals. Measurements of these components depend on factors such as fundamental frequency deviation, event duration, amplitude values, and noise levels. Accurate detection and measurement are crucial for effective harmonic mitigation and preventive strategies. This study introduces a harmonic signal analysis application utilizing methods like FFT, STFT, CWT, EMD, and HHT, with individual user interfaces for in-phase and time-variant harmonic signals. The application provides results for amplitude, frequency, event time intervals, and noise effects simultaneously. Test results at a 60 dB signal-to-noise ratio (SNR) reveal that FFT achieves precise frequency and amplitude results due to its high resolution, whereas other methods offering time-frequency domain results exhibit lower resolution. EMD, in particular, demonstrates high errors in frequency and amplitude responses, reducing four frequency components to three. HHT, utilizing EMD results, yields higher accuracy with minimal errors compared to other methods. This application, combined with test results, facilitates signal synthesis and comparative analysis in time and time-frequency domains.

Spatio-temporal characterization of drought variability in data-scarce regions using global precipitation data: a case study in Cauto river basin, Cuba.

Drought is considered the most severe water-related disaster in the Cauto river basin, which is the longest river and the main agricultural producer in Cuba. Better understanding of drought characteristics is crucial to drought management. Given the sparsity of ground-based precipitation observations in the Cauto, this study aims at using gridded global precipitation to analyze the spatio-temporal variations of drought in this river basin. Firstly, the monthly Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) was calibrated with the gauged precipitation using the Thiessen polygon-based method and linear least squares regression equations. Then, the gridded standardized precipitation index (SPI) with time scales of 3, 6, 9months and drought characteristics, namely, drought frequency, duration and intensity were calculated using the calibrated CHIRPS. Finally, the spatio-temporal analysis was performed to investigate the variations of drought in the Cauto river basin in time and space. The obtained results show that the calibrated CHIRPS is highly consistent with the gauged observations and is capable of determining the magnitude, time, and spatial extent of drought events in the Cauto river basin. The trend analysis by the Mann-Kendall test reveals that although the trend is not statistically significant, the SPI tends to decrease with time in the dry season, which indicates the more severe drought. The spatial analysis indicates that the lower altitude area of the Cauto river basin is suffered from longer drought duration and higher drought intensity than the upper one. This study expresses the importance of open global precipitation data sources in monitoring and quantifying drought characteristics in data-scarce regions.

Time Reparametrization and Event Location for Discontinuous Differential Algebraic Equations

In this paper, we consider numerical methods for the event location of differential algebraic equations. The event corresponds to cross a discontinuity surface, beyond which another differential algebraic equation holds. The methods are based on a particular change of the independent variable time, called time reparametrization or time transformation, reducing the equation to another equation where the event time is known in advance. From a numerical point of view, these methods never cross the discontinuity surface and reach it in a fixed number of steps. The methods works also for differential algebraic equations of index higher than one.

Genome-wide investigation of exogenous female hormones, genetic variation, and venous thromboembolism risk

BackgroundIncreased risk of venous thromboembolism (VTE) is a life-threatening side effect for users of oral contraceptives (OCs) or hormone therapy (HT). ObjectivesTo investigate the potential for genetic predisposition to VTE in OC or HT users, we conducted a gene-by-environment case-only meta-analysis of genome-wide association studies (GWAS). MethodsUse or nonuse of OCs (7 studies) or HT (8 studies) at the time of the VTE event was determined by pharmacy records or self-report. A synergy index (SI) was modeled for each variant in each study and submultiplicative/supramultiplicative gene-by-environment interactions were estimated. The SI parameters were first meta-analyzed across OC and HT studies and subsequently meta-analyzed to obtain an overall estimate. The primary analysis was agnostic GWAS and interrogated all imputed genotypes using a P value threshold of <5.0 × 10−8; secondary analyses were candidate-based. ResultsThe VTE case-only OC meta-analysis included 2895 OC users and 6607 nonusers; the case-only HT meta-analysis included 2434 HT users and 12 793 nonusers. In primary GWAS meta-analyses, no variant reached genome-wide significance, but the smallest P value approached statistical significance: rs9386463 (P = 5.03 × 10−8). We tested associations for 138 candidate variants and identified 2 that exceeded statistical significance (0.05/138 = 3.62 × 10−4): F5 rs6025 (P = 1.87 × 10−5; SI, 1.29; previously observed) and F11 rs2036914 (P = 2.0 × 10−4; SI, 0.91; new observation). ConclusionThe candidate variant approach to identify submultiplictive/supramultiplicative associations between genetic variation and OC and HT use identified a new association with common genetic variation in F11, while the agnostic interrogations did not yield new discoveries.

U-Pb calcite ages date oblique rifting of the Arctic–North Atlantic gateway

Abstract Miocene breakup of Svalbard from Greenland formed a deep oceanic gateway that enabled circulation between the Arctic and Atlantic Oceans, significantly changing the global climate. However, the timing of events remains unclear. An excellent opportunity to constrain this timing is found onshore western Svalbard, where the Sarsbukta fault forms the eastern margin of the Eocene–Oligocene Forlandsundet basin. Here, we present new results from U-Pb dating of calcite precipitated in fault-related veins to constrain the timing of Sarsbukta fault deformation and the evolution of the basin. Our oldest calcite age is Permo-Triassic, suggesting long-lived deformation along the fault. A cluster of ages between 41 and 33 Ma overlaps with fossil-based depositional ages from parts of the Forlandsundet basin. These data indicate that onshore transtension partly pre-dated the well-established Chron 13 (magnetic polarity time scale; 35.5–33.7 Ma) reorganization of spreading ridges in the North Atlantic. Our youngest age of 13 Ma indicates that faulting persisted long after the preserved basin fill was deposited. If seafloor spreading marked the end of extension of continental crust, Molloy Ridge spreading during Chron 5 (19.6–9.8 Ma) may have initiated after 13 Ma.

The relative contribution of acoustic signals versus movement cues in group coordination and collective decision-making.

To benefit from group living, individuals need to maintain cohesion and coordinate their activities. Effective communication thus becomes critical, facilitating rapid coordination of behaviours and reducing consensus costs when group members have differing needs and information. In many bird and mammal species, collective decisions rely on acoustic signals in some contexts but on movement cues in others. Yet, to date, there is no clear conceptual framework that predicts when decisions should evolve to be based on acoustic signals versus movement cues. Here, we first review how acoustic signals and movement cues are used for coordinating activities. We then outline how information masking, discrimination ability (Weber's Law) and encoding limitations, as well as trade-offs between these, can identify which types of collective behaviours likely rely on acoustic signals or movement cues. Specifically, our framework proposes that behaviours involving the timing of events or expression of specific actions should rely more on acoustic signals, whereas decisions involving complex choices with multiple options (e.g. direction and destination) should generally use movement cues because sounds are more vulnerable to information masking and Weber's Law effects. We then discuss potential future avenues of enquiry, including multimodal communication and collective decision-making by mixed-species animal groups. This article is part of the theme issue 'The power of sound: unravelling how acoustic communication shapes group dynamic'.

Exploring home fall events among infants and toddlers using social media information: an infodemiology study in China

BackgroundPractical interventions of fall prevention are challenging for infants and toddlers. This study aimed to explore specific details of falls that occurred at home for kids 0–3 years old using...

Dynamics and timing of diversification events of ciliated eukaryotes from a large phylogenomic perspective

Ciliophora, an exceptionally diverse lineage of unicellular eukaryotes, exhibits a remarkable range of species richness across classes in the ciliate Tree of Life. In this study, we have acquired transcriptome and genome data from 40 representative species in seven ciliate classes. Utilizing 247 genes and 105 taxa, we devised a comprehensive phylogenomic tree for Ciliophora, encompassing over 60 % of orders and constituting the most extensive dataset of ciliate species to date. We established a robust phylogenetic framework that encompasses ambiguous taxa and the major classes within the phylum. Our findings support the monophyly of each of two subphyla (Postciliodesmatophora and Intramacronucleata), along with three subclades (Protocruzia, CONTHREEP, and SAPML) nested within Intramacronucleata, and elucidate evolutionary positions among the major classes within the phylum. Drawing on the robust ciliate Tree of Life and three constraints, we estimated the radiation of Ciliophora around 1175 Ma during the middle of the Proterozoic Eon, and most of the ciliate classes diverged from their sister lineage during the latter half of this period. Additionally, based on the time-calibrated tree and species richness pattern, we investigated net diversification rates of Ciliophora and its classes. The global net diversification rate for Ciliophora was estimated at 0.004979 species/Ma. Heterogeneity in net diversification rates was evident at the class level, with faster rates observed in Oligohymenophorea and Spirotrichea than other classes within the subclades CONTHREEP and SAPML, respectively. Notably, our analysis suggests that variations in net diversification rates, rather than clade ages, appear to contribute to the differences in species richness in Ciliophora at the class level.