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  • Bed elevation uncertainty strongly affects Antarctic ice projections

    What the study found

    The study found that uncertainty in bed topography, meaning the shape and elevation of the ground beneath the Antarctic Ice Sheet, has a large effect on projections of Antarctic ice evolution. The authors report that these uncertainties can change estimates of Antarctica's sea-level contribution by more than 40 cm by 2150 and 1 m by 2300.

    Why the authors say this matters

    The findings indicate that errors in bedrock elevation are a critical but underexplored source of uncertainty in Antarctic ice-sheet projections. The authors conclude that additional observations in critical regions are needed to help reduce these systemic uncertainties.

    What the researchers tested

    The researchers used simulations of Antarctic ice-sheet evolution at both continental and regional scales. They compared the effects of bed topography uncertainties, using error estimates reported in BedMachine Antarctica, with the effects of different climate forcing scenarios.

    What worked and what didn't

    Bed topography uncertainty affected projected sea-level contribution by more than 40 cm in 2150 and 1 m in 2300, according to the simulations. The impact was especially important for grounding line retreat and mass loss in the Amundsen Sea, Ross, and Filchner-Ronne basins, and it was even larger in higher-resolution regional and glacier-scale simulations. The abstract also says that the influence of bedrock uncertainties produced more variation in grounding line positions and mass change than seen in the broader-scale cases.

    What to keep in mind

    The abstract does not describe detailed limitations beyond the use of reported error estimates from BedMachine Antarctica. The findings are based on simulations, so they describe modeled projections rather than direct observations of future ice-sheet change.

    • Uncertainty in Antarctic bed topography can change projected sea-level contribution by more than 40 cm by 2150 and 1 m by 2300.
    • The effect of bed topography uncertainty is described as comparable to the effect of different emission scenarios.
    • The Amundsen Sea, Ross, and Filchner-Ronne basins are highlighted as especially sensitive areas.
    • Higher-resolution regional and glacier-scale simulations show even larger effects from bedrock uncertainty.
    • The authors say more observations are needed in critical regions to reduce systemic uncertainty.

  • Lingual attached gingiva is widest near molars and narrowest near incisors

    What the study found

    The study found that lingual attached gingiva, the band of gum tissue attached on the tongue side of the lower teeth, is widest around the molars and narrowest around the incisors in periodontally sound young adults. The authors also report no significant width differences between males and females.

    Why the authors say this matters

    The authors conclude that lingual attached gingiva has been relatively overlooked compared with buccal attached gingiva, the gum tissue on the cheek side of the teeth. They say the findings suggest this area deserves greater attention in periodontal research.

    What the researchers tested

    The researchers conducted a cross-sectional observational study of 120 people aged 18 to 30 years who were periodontally sound. They located the mucogingival junction, the boundary between attached gum and movable tissue, using rolling probe and visual methods on mandibular teeth and measured width with a UNC-15 periodontal probe.

    What worked and what didn't

    The greatest average width of lingual attached gingiva was reported at the first and second molars, at 5.85 mm ± 1.26 mm, while the narrowest average width was around the incisors, at 1.08 mm ± 0.65 mm. The central incisor had the smallest band at 0.54 mm ± 0.54 mm, and the first molar had the widest band at 5.97 mm ± 1.3 mm; widths ranged from 0 mm to 10 mm, and no significant sex differences were observed.

    What to keep in mind

    The study sample was limited to 120 periodontally sound individuals aged 18 to 30 years, so the findings apply to that group. The abstract does not describe other limitations.

    • Lingual attached gingiva was widest near the first and second molars.
    • The narrowest lingual attached gingiva was found near the incisors.
    • No significant difference in lingual attached gingiva width was seen between males and females.
    • The study included 120 periodontally sound participants aged 18 to 30 years.
    • The authors say lingual attached gingiva has been relatively overlooked in periodontal research.

  • ECORRA outlines five principles for rural cancer equity research

    What the study found

    The study describes the ECORRA program as a national, transdisciplinary effort to understand and reduce inequities in cancer outcomes for people living in rural and remote areas. It says the program is guided by five principles: fit-for-purpose governance, embedded consumer involvement, a genuine rural and remote focus, cross-sector partnerships beyond academia, and place-based engagement.

    Why the authors say this matters

    The authors conclude that ECORRA offers an innovative, principle-driven model for equity-focused health services research to improve cancer outcomes. They present the three flagship projects as examples meant to inform future initiatives aimed at addressing health inequity.

    What the researchers tested

    This is a perspective article about the ECORRA program, a national effort called the Equitable Cancer Outcomes across Rural and Remote Australia program. The abstract says ECORRA brings together researchers, clinicians, consumers, and health policy partners, and that its work is underpinned by co-design, implementation, and health services research frameworks.

    What worked and what didn't

    The abstract states that ECORRA demonstrates an innovative, principle-driven model and identifies five principles as central to its approach. It does not report comparative outcomes, quantitative effects, or specific failures of the projects.

    What to keep in mind

    The available summary does not provide detailed methods, data, or outcome measures. It also does not describe limitations beyond framing the article as a perspective and highlighting three flagship projects.

    • ECORRA is described as a national program focused on cancer inequities in rural and remote areas.
    • Five principles are named: governance, consumer involvement, rural and remote focus, cross-sector partnerships, and place-based engagement.
    • The program brings together researchers, clinicians, consumers, and health policy partners.
    • The authors present ECORRA as an innovative model for equity-focused health services research.
    • No quantitative results or comparative outcome data are reported in the abstract.
  • Text messaging improved FIT completion more than nurse calls

    Text messaging improved FIT completion more than nurse calls

    What the study found

    The study found that automated, behaviorally informed text message reminders were associated with higher fecal immunochemical test (FIT) completion than a nurse-led telephone call reminder. FIT is a stool-based screening test used for colorectal cancer screening.

    Why the authors say this matters

    The authors conclude that automated messaging may offer a scalable, low-cost strategy to promote preventive care and reduce staff burden in underserved populations. The study suggests this could be useful in safety-net settings where screening rates remain suboptimal.

    What the researchers tested

    This quality improvement randomized clinical trial was done at 8 Federally Qualified Health Centers in Brooklyn, New York. Adults with a new FIT order who spoke English, Spanish, or Chinese and had not opted out of text messaging were randomized to 3 automated one-way text reminders on days 2, 5, and 8 or to a single nurse-led telephone call on day 8.

    What worked and what didn't

    FIT completion within 21 days was higher in the text group than in the telephone group: 58.9% versus 49.8%, an absolute difference of 9.0 percentage points. Secondary outcomes at 7 and 14 days were assessed, and post hoc analyses found no evidence of different effectiveness by age, sex, race and ethnicity, or patient portal use.

    What to keep in mind

    The abstract does not describe longer-term follow-up beyond 21 days. It also does not provide detailed limitations beyond the trial setting and the participant eligibility criteria.

    • Automated text reminders were associated with higher FIT completion than a nurse-led phone call.
    • Completion within 21 days was 58.9% in the text group and 49.8% in the telephone group.
    • The trial included 1,275 adults at 8 Federally Qualified Health Centers in Brooklyn, New York.
    • No evidence of different effectiveness was found by age, sex, race and ethnicity, or patient portal use.
    • The authors say automated messaging may reduce staff burden and support preventive care.
  • S2Fin improves multimodal remote sensing classification

    S2Fin improves multimodal remote sensing classification

    What the study found

    The study reports that S2Fin, a spatial-spectral-frequency interaction network, performs strongly on multimodal remote sensing classification. The authors say it shows good robustness and generalization, and that it outperforms state-of-the-art methods in few-sample settings.

    Why the authors say this matters

    The authors suggest the approach matters because multimodal remote sensing images can be difficult to classify when useful structural and detail features are hard to extract, especially when labels are scarce. They present frequency-domain learning as a way to model key and sparse detail features more effectively.

    What the researchers tested

    The researchers developed the spatial-spectral-frequency interaction network, or S2Fin, for multimodal remote sensing image classification. The model combines pairwise fusion modules across spatial, spectral, and frequency domains, including a high-frequency sparse enhancement transformer, an adaptive frequency channel module, a high-frequency resonance mask, and a spatial-spectral attention fusion module.

    What worked and what didn't

    According to the abstract, the high-frequency sparse enhancement transformer was designed to refine spectral signatures by enhancing discriminative high-frequency components. The adaptive frequency channel module and high-frequency resonance mask were used to combine low-frequency structural information with enhanced details and to amplify modality-consistent regions, and the model performed well across four benchmark datasets. The abstract does not report specific failure cases or components that did not work.

    What to keep in mind

    The summary provided here is limited to the abstract, so only the claims stated there are included. The abstract does not give detailed dataset names, numerical results, or limitations of the method beyond noting the challenge of label-scarce scenarios.

    • S2Fin is a spatial-spectral-frequency interaction network for multimodal remote sensing classification.
    • The authors say the model outperforms state-of-the-art methods in few-sample settings.
    • The network uses pairwise fusion across spatial, spectral, and frequency domains.
    • A high-frequency sparse enhancement transformer is used to refine spectral signatures.
    • The abstract reports good robustness and generalization across four benchmark datasets.

  • Delayed PCL reconstruction linked to more cartilage and meniscal injuries

    What the study found

    The study found that later posterior cruciate ligament reconstruction, especially when surgery was delayed beyond 24 months after injury, was associated with more cartilage and meniscal injuries. Older age was also associated with a higher prevalence of these injuries, and higher body mass index was associated with more patellofemoral cartilage injury.

    Why the authors say this matters

    The authors conclude that delayed posterior cruciate ligament reconstruction, older age, and higher body mass index are important factors related to a higher prevalence of cartilage and meniscal injuries after grade III posterior cruciate ligament injuries. The study suggests these patient and timing factors may help identify people at greater risk of associated joint damage.

    What the researchers tested

    The researchers reviewed 1,003 patients who had primary isolated posterior cruciate ligament reconstruction between August 2016 and July 2024. They used arthroscopic evaluation to confirm cartilage and meniscal injuries, graded cartilage with the International Cartilage Repair Society classification, and performed multivariable logistic regression to identify risk factors.

    What worked and what didn't

    Longer time from injury to surgery, especially more than 24 months, was significantly associated with higher risk of patellofemoral, lateral compartment, and medial compartment cartilage injury, as well as medial meniscal injury, compared with surgery within 3 months. Older age significantly increased the prevalence of all cartilage and meniscal injuries, while increased body mass index was independently associated with a higher incidence of patellofemoral cartilage injury.

    What to keep in mind

    This was a retrospective cohort study, so the abstract does not describe randomized treatment assignment. The summary also does not provide details on other possible limitations beyond the study design and the fact that the findings come from patients who underwent primary isolated posterior cruciate ligament reconstruction.

    • In 1,003 patients, delayed posterior cruciate ligament reconstruction was linked to more concomitant cartilage and meniscal injuries.
    • Surgery delayed beyond 24 months was associated with higher odds of cartilage injury in the patellofemoral, lateral, and medial compartments.
    • Delayed surgery was also associated with a higher risk of medial meniscal injury.
    • Older age was significantly associated with a higher prevalence of all cartilage and meniscal injuries.
    • Higher body mass index was independently associated with more patellofemoral cartilage injury.

  • CSU-PCAST improves medium-range precipitation forecasting

    What the study found

    The study found that CSU-PCAST, a deep learning system for global 6-hour precipitation forecasting, improved several aspects of medium-range precipitation prediction. It showed better short-lead deterministic skill than GEFS, and its probabilistic forecasts were also more reliable in several measures.

    Why the authors say this matters

    The authors state that accurate medium-range precipitation forecasting is important for hydrometeorological risk management and disaster mitigation. The study suggests that improving precipitation intensity, spatial structure, and ensemble reliability at longer lead times remains a useful goal.

    What the researchers tested

    The researchers developed CSU-PCAST using ERA5 atmospheric and surface variables at 0.25° spatial resolution, IMERG precipitation labels, and 57 prognostic atmospheric and surface variables plus static geographical fields. The model uses a patch-based Swin Transformer backbone, periodically padded residual convolutions, stochastic noise conditioning, time embeddings, and a dual-branch decoder for precipitation and non-precipitation variables; during inference it is initialized from operational GFS analyses and generates 30 autoregressive ensemble members to 15 days.

    What worked and what didn't

    Evaluation over 2023, using IMERG as the precipitation reference, showed higher CSI and lower RMSE for CSU-PCAST during the first several forecast days. The model also reduced GEFS wet bias for light precipitation and dry bias at the 10 and 20 mm thresholds, and it achieved lower CRPS, higher Brier Skill Scores for several thresholds, and improved ensemble reliability; however, both systems remained underdispersive. A Sanba extreme precipitation case study also showed improved spatial structure and exceedance-probability guidance, while regional precipitation totals, high-end intensity, and ensemble calibration still needed improvement.

    What to keep in mind

    The abstract reports that both CSU-PCAST and GEFS remained underdispersive, meaning the ensemble spread was still too small. It also notes that regional precipitation totals, high-end intensity, and ensemble calibration remain areas for further improvement.

    • CSU-PCAST is a deep learning ensemble framework for global 6-hour precipitation forecasting.
    • It was trained with ERA5 variables, IMERG precipitation labels, and 57 prognostic atmospheric and surface variables plus static geographical fields.
    • The model improved short-lead deterministic skill relative to GEFS, with higher CSI and lower RMSE during the first several forecast days.
    • It reduced GEFS wet bias for light precipitation and dry bias at the 10 and 20 mm thresholds.
    • Probabilistic verification showed lower CRPS, higher Brier Skill Scores for several thresholds, and improved ensemble reliability.
    • Both systems remained underdispersive, and some areas such as regional totals, high-end intensity, and calibration still need improvement.

  • Culture and institutions shape goodwill impairment under IFRS

    What the study found

    The study found that goodwill impairment losses under IFRS are linked to both cultural differences and institutional quality across countries. It also found that stronger institutional quality is associated with larger impairment amounts and that firms in stronger institutional settings report impairments that more closely reflect underlying economic conditions.

    Why the authors say this matters

    The authors conclude that goodwill impairment under IFRS is not only an accounting issue but is also shaped by the institutional and cultural environment in which firms operate. They say that revising accounting standards alone is not enough for comparable reporting, and that consistent enforcement across jurisdictions remains essential.

    What the researchers tested

    The researchers analyzed 2,466 companies from 17 IFRS-adopting countries, using 14,898 firm-year observations from 2007 to 2013. They estimated a pooled Tobit model with year and industry fixed effects, using Hofstede's cultural dimensions and validated institutional quality measures from Alshehabi et al. (2021).

    What worked and what didn't

    Goodwill impairment losses were associated with firm-level economic factors and managerial reporting incentives. Power distance and individualism had direct effects in the predicted direction, while uncertainty avoidance was positively associated with impairment, which the authors interpret as consistent with income smoothing. Institutional quality, especially quality of legality and equity market development, was positively associated with impairment magnitude, and moderation analyses showed that stronger institutions reduced the sensitivity of impairment to goodwill carrying values.

    What to keep in mind

    The study used firm-level data rather than cash-generating-unit-level data. The sample period was limited by the availability of the validated institutional measures, and the authors note that their results provide a pre-2014 enforcement baseline for future research on later regulatory changes.

    • Goodwill impairment losses under IFRS were associated with both culture and institutional quality.
    • Power distance and individualism showed direct effects on impairment amounts in the predicted direction.
    • Uncertainty avoidance was positively associated with impairment, which the authors link to income smoothing.
    • Higher institutional quality, especially legality and equity market development, was associated with larger impairment magnitude.
    • Stronger institutional environments were linked to impairment reports that more closely reflected economic conditions.

  • Full-resolution MSRE model matches benchmark and experimental trends

    What the study found

    The study found that a full-resolution multiphysics model of the Molten Salt Reactor Experiment can agree well with benchmark data and reproduce major experimental flow trends. The authors also report that it can capture three-dimensional flow structures that axisymmetric models do not represent.

    Why the authors say this matters

    The authors conclude that high-fidelity simulation techniques may help support reactor start-up procedures and digital-twin applications. They also suggest the model can be used to infer missing design data from experimental observations when some design parameters are uncertain.

    What the researchers tested

    The researchers built a full-resolution model of the Molten Salt Reactor Experiment, resolving the entire reactor vessel and internal structures without porous-media or axisymmetric approximations. They coupled Monte Carlo neutron-photon transport, a method for simulating particle behavior, with conjugate heat transfer and turbulent flow simulation on unstructured meshes, and iterated the model to convergence with temperature and density feedback.

    What worked and what didn't

    The predicted effective multiplication factor and power fractions showed good agreement with benchmark data. Velocity profiles in the volute, annulus, and core passages were compatible with experimental measurements and previous simulations within known uncertainties, and the model reproduced major experimental flow trends in the lower plenum. Some discrepancies remained, mainly due to input uncertainties and limitations of Reynolds-averaged Navier-Stokes (RANS) turbulence models under strong adverse pressure gradients.

    What to keep in mind

    The abstract notes that some inputs and operating conditions were uncertain, which affects interpretation of the comparisons. It also says the current discrepancies point to possible future extensions to large-eddy simulation (LES) turbulence modeling, but no further limitations are described in the available summary.

    • The model resolved the entire MSRE vessel and internal structures without porous-media or axisymmetric approximations.
    • Predicted effective multiplication factor and power fractions agreed well with benchmark data.
    • Velocity profiles in several reactor passages were compatible with experimental measurements and previous simulations within known uncertainties.
    • The model reproduced major lower-plenum flow trends and revealed three-dimensional structures missed by axisymmetric surrogates.
    • Remaining discrepancies were attributed mainly to input uncertainties and RANS-model limits under strong adverse pressure gradients.

  • Human influence on ozone may have been detectable by 1957

    What the study found

    The study found that human-caused ozone depletion was likely detectable as early as 1957 in the tropical upper stratosphere, a high layer of the atmosphere above the tropics. It also found that the earliest ozone loss was primarily caused by human-made carbon tetrachloride, a solvent, rather than by chlorofluorocarbons alone.

    Why the authors say this matters

    The authors conclude that a clear human influence on the stratospheric ozone layer began nearly 70 years ago, before substantial emissions of chlorofluorocarbons from spray cans or air conditioning. They also say the findings highlight the importance of considering both internal variability, or natural noise, and the forced response, or human-driven signal, in detection studies.

    What the researchers tested

    The researchers carried out a thought experiment to ask when human-induced ozone depletion could first have been detected if accurate stratospheric ozone observations had been available from 1950 onward. They used a combination of observational reasoning and modeling to examine where and when the signal would have emerged.

    What worked and what didn't

    The tropical upper stratosphere appears to have been the earliest place where the human signal could be identified because its internal variability was low. Even though ozone losses there were smaller than at higher latitudes, the lower noise made detection possible earlier.

    What to keep in mind

    This was a thought experiment, not a reconstruction from actual ozone observations beginning in 1950. The abstract does not describe additional limitations beyond the assumptions of the detection study.

    • Human-caused ozone depletion was likely identifiable by 1957 in the tropical upper stratosphere.
    • Low internal variability in the tropical upper stratosphere helped make the human signal detectable early.
    • Early ozone loss was described as being mainly driven by human-made carbon tetrachloride, a solvent.
    • The authors say a clear human influence on the ozone layer began nearly 70 years ago.
    • The study emphasizes the need to consider both natural noise and human-driven signal in detection studies.