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  • CDC surveillance databases showed widespread unexplained pauses

    What the study found

    Many U.S. Centers for Disease Control and Prevention (CDC) surveillance databases that had been updated at least monthly were paused or no longer current by late 2025. The authors describe these as “unexplained pauses” in the public evidence base used for health policy.

    Why the authors say this matters

    The authors conclude that real-time federal surveillance informs clinical guidance and public health policy, so long pauses may have compromised evidence for decision making by clinicians, administrators, professional organizations, and policymakers. They also suggest federal databases should have minimum transparency standards, including current update status, a reason if paused, and the next expected update with criteria for resumption.

    What the researchers tested

    The researchers audited the CDC public data catalog on 28 October 2025 to identify database records that had previously been updated at least monthly. They then used each database's stated periodicity, plus a 30-day grace period, to classify databases as current or paused, and they checked whether pauses persisted as of 2 December 2025.

    What worked and what didn't

    Of 1,359 catalog records examined, 82 had been updated at least monthly. Forty-four of those databases were current and 38 were paused; 34 of the paused databases had no data entries within 6 months of the analysis date, while 4 had paused more recently. Among the paused databases, 33 were vaccination-related, 4 of the remaining 5 focused on respiratory diseases, and 1 addressed public health drug overdose deaths; by 2 December 2025, only 1 paused database had been updated.

    What to keep in mind

    The summary provides an audit of CDC catalog records at two points in time and does not explain why the pauses occurred. The available abstract does not describe effects on specific policies or describe any limitations beyond what is implied by the catalog-based approach.

    • The audit examined 1,359 CDC catalog records and focused on 82 that had been updated at least monthly.
    • On 28 October 2025, 44 of those 82 databases were current and 38 were paused.
    • Most paused databases had no data entries within the previous 6 months, and only 1 paused database had been updated by 2 December 2025.
    • Most paused databases were vaccination-related; others mainly concerned respiratory diseases or drug overdose deaths.
    • The authors say unexplained pauses may weaken evidence used for health decision making and public trust.

  • Structured PFAS fingerprinting distinguished overlapping sources

    What the study found

    The study found that a structured framework can separate overlapping per- and polyfluoroalkyl substance, or PFAS, source patterns using only targeted measurements. In the groundwater datasets examined, it resolved distinct mixture types linked to manufacturing era, formulation chemistry, and hydrologic context.

    Why the authors say this matters

    The authors conclude that target-only PFAS datasets can support forensic interpretation when multiple analytical metrics are used together. They present the approach as a possible aid for PFAS investigations where source histories are complex and compound coverage is limited.

    What the researchers tested

    The researchers presented a tiered PFAS fingerprinting framework that combines compound-level concentrations, class- and carbon-number-resolved composition, diagnostic ratios, isomer distributions, precursor-product relationships, multivariate clustering, and geospatial pattern analysis. They demonstrated it with groundwater data collected in 2018 and 2024 from a complex industrial setting with overlapping PFAS inputs.

    What worked and what didn't

    The framework identified sulfonate-rich mixtures consistent with electrochemical fluorination-era inputs, telomer-associated industrial mixtures characterized by fluorotelomer sulfonates and carboxylates, and short-chain-enriched profiles influenced by wastewater-related transport and mixing. Temporal analysis showed changes in precursor abundance and terminal perfluoroalkyl carboxylic acids between sampling events, and diagnostic ratios and isomer patterns added temporal context where they could be measured. Unsupervised clustering also matched compositional similarity and hydraulic connectivity among site domains.

    What to keep in mind

    The abstract does not describe the study's limitations in detail. The framework was demonstrated on groundwater datasets from one complex industrial setting, so the summary here is limited to that example.

    • A tiered PFAS fingerprinting framework was developed for target-only analytical datasets.
    • The approach combined concentrations, composition measures, diagnostic ratios, isomer patterns, precursor-product links, clustering, and geospatial analysis.
    • Groundwater data from 2018 and 2024 showed distinct PFAS mixture archetypes.
    • The identified profiles included electrochemical fluorination-era, telomer-associated, and short-chain-enriched mixtures.
    • Clustering supported similarity and hydraulic connectivity among site domains.

  • Left anterior descending spasm caused a large anterior myocardial infarction

    What the study found

    The study found that isolated spasm of the left anterior descending artery, a major heart artery, caused a large anterior myocardial infarction in a patient whose coronary angiogram showed no obstructive disease. Cardiac magnetic resonance imaging localized the infarct, and optical coherence tomography confirmed epicardial spasm and excluded other causes such as plaque rupture, erosion, thrombus, and spontaneous coronary artery dissection.

    Why the authors say this matters

    The authors suggest that coronary artery spasm is an under-recognized cause of myocardial infarction with non-obstructive coronary arteries, or MINOCA, a term for heart attack without a blocked major artery seen on angiography. They also conclude that early cardiac magnetic resonance imaging and intravascular imaging can help identify the cause and guide treatment.

    What the researchers tested

    This was a case report of a 48-year-old woman who presented with angina, dyspnea, hypotension, elevated troponin, anterior T-wave inversion on ECG, and severe regional wall-motion abnormalities on echocardiography. She then underwent angiography, cardiac magnetic resonance imaging, and optical coherence tomography to define the cause of her myocardial infarction.

    What worked and what didn't

    Angiography showed non-obstructive coronary arteries, so it did not identify a blocked vessel. Cardiac magnetic resonance imaging localized a large acute infarct in the left anterior descending artery territory, and optical coherence tomography demonstrated LAD spasm while excluding plaque rupture, erosion, thrombus, and spontaneous coronary artery dissection.

    What to keep in mind

    This is a single case report, so the findings describe one patient rather than a broader group. The abstract does not provide longer-term outcomes, and treatment was limited by vasospasm and hypotension.

    • A 48-year-old woman had an acute anterior myocardial infarction linked to isolated left anterior descending artery spasm.
    • Coronary angiography showed non-obstructive coronary arteries.
    • Cardiac magnetic resonance imaging localized a large infarct in the left anterior descending artery territory.
    • Optical coherence tomography identified LAD spasm and excluded plaque rupture, erosion, thrombus, and spontaneous coronary artery dissection.
    • The authors describe coronary artery spasm as an under-recognized cause of MINOCA.

  • Indexical notation is proposed for representing sound morphology

    What the study found

    The article argues that indexical notation, a type of sign based on a direct causal link, may help represent the lived, changing qualities of sound more effectively than pictographic or symbolic notation. In the case study discussed, this approach was used in an interactive score for a solo performer.

    Why the authors say this matters

    The authors suggest that indexical signs may provide an accessible way for performers to engage with spectral and morphological elements of sound, meaning features related to sound’s frequency content and changing shape. They conclude that this may open new pathways for notation to address experiential phenomena.

    What the researchers tested

    The article explores notation of sound morphology using C. S. Peirce’s concept of indexical signs. It draws on theories outlined by Floris Schuiling and presents a case study of an interactive score called Undersong 1 for solo performer, which avoids symbolic and pictographic notation in favor of indexical causal relationships between performer actions and visual responses.

    What worked and what didn't

    The case study suggests that indexical signs may work as a way to engage performers with spectral and morphological aspects of sound. The abstract states that pictographic and symbolic notation struggle to notate the lived dynamic experience of music, but it does not provide a detailed comparison of outcomes.

    What to keep in mind

    This summary is limited to the abstract, so the article’s full evidence, methods, and any detailed limitations are not available here. The abstract does not describe weaknesses, constraints, or broader testing beyond the single case study.

    • The article explores indexical notation for sound morphology.
    • Pictographic and symbolic notation are described as struggling to capture the lived dynamic experience of music.
    • A case study of the interactive score Undersong 1 is presented.
    • The score uses indexical causal relationships between performer and visual responses.
    • The case study suggests indexical signs may help performers engage with spectral and morphological elements of sound.

  • School-based programs showed some effects for recently arrived immigrant youth

    What the study found

    The review found that about half of the school-based programs it examined had some effects on the outcomes they targeted for recently arrived immigrant adolescents. The programs mainly focused on social-emotional well-being, mental health problems, resilience, social support, or trauma-related symptoms.

    Why the authors say this matters

    The authors conclude that there are some promising findings, but the current literature is too limited to support robust conclusions. They say future research should examine why, how, and for whom programs lead, or do not lead, to intended outcomes, and should develop effective programs that can be implemented with available school resources.

    What the researchers tested

    The researchers conducted a scoping review following PRISMA-ScR guidelines. They searched five databases—Medline, PsycINFO, CINAHL, SCOPUS, and ERIC—for studies published since 2000 on interventions implemented in formal school settings for recently arrived adolescents.

    What worked and what didn't

    The review identified 15 studies that evaluated 17 programs. Around 50% of the programs showed some effects on their intended outcomes, but the abstract does not specify which programs worked best or which outcomes improved most consistently.

    What to keep in mind

    The abstract says the literature has several limitations, but it does not list them in detail. It also does not provide enough information to judge the size, durability, or comparative strength of the effects.

    • The review covered 15 studies and 17 school-based programs.
    • About 50% of the programs had some effects on intended outcomes.
    • Programs mainly targeted well-being, mental health, resilience, social support, or trauma-related symptoms.
    • The authors say the literature is limited and does not support robust conclusions.
    • Future research should examine why, how, and for whom these programs work.

  • Survey maps graph roles in retrieval-augmented generation

    What the study found

    The survey finds that graphs have a broader role in retrieval-augmented generation, or RAG, than just moving through knowledge graphs. It presents graphs as supporting database construction, algorithms, pipelines, and tasks across graph-structured data.

    Why the authors say this matters

    The authors suggest this broader graph-centered view matters because RAG is used to reduce factual errors and hallucination in large language models, which are AI systems that generate text. They conclude that recognizing these graph functions may help future work in graph learning, database systems, and natural language processing.

    What the researchers tested

    This is a survey article rather than an experimental study. The authors reviewed recent RAG methods and organized them around the functions of graphs in the RAG process, including database construction, algorithms, pipelines, and tasks.

    What worked and what didn't

    The survey reports that prior RAG surveys often limited graphs to knowledge-graph traversal. In contrast, this article highlights commonalities and differences in existing graph-based methods and argues that the broader role of graphs has been underexplored.

    What to keep in mind

    The abstract does not describe new experiments, numerical results, or head-to-head comparisons. It also does not provide specific limitations beyond stating current challenges and future research directions.

    • The survey says graphs have a broader role in RAG than knowledge-graph traversal alone.
    • It organizes graph functions in RAG into database construction, algorithms, pipelines, and tasks.
    • The paper links RAG to reducing factual errors and hallucination in LLMs.
    • The authors say the broader graph-centered view may inform future work in graph learning, database systems, and NLP.
    • No new experiments or quantitative results are described in the abstract.

  • Landslide activity shifted earlier in the year in the European Alps

    What the study found

    The study found four seasonal patterns of landslide occurrence in the European Alps. It also reports a shift toward landslide activity happening earlier in the year, which the authors link to rising air temperatures and changing precipitation patterns.

    Why the authors say this matters

    The authors frame landslides as a major natural hazard in mountain regions that threatens human safety, infrastructure, and ecosystems. The study suggests that understanding how meteorological changes relate to landslide timing may help explain regional impacts of climate change.

    What the researchers tested

    The researchers analyzed instrumental records from 849 seismic stations in the European Alps from 2000 to 2023 using an automated seismic data exploration method. This produced a catalog of 926 seismogenic landslides, and the Alps were divided into 142 massifs based on altitude and slope properties for further analysis.

    What worked and what didn't

    Six massifs had more than 30 landslides each, which allowed the authors to cross-correlate landslide activity with monthly variations in air temperature, precipitation, snow cover, and snow melt before and after 2010. The massifs with the highest landslide counts had lower average air temperatures, higher annual precipitation, and a larger channel steepness index, and the authors report a shift toward earlier-in-the-year activity linked to warming of 0.5°C–2°C and changing precipitation patterns.

    What to keep in mind

    The analysis is limited to the European Alps and to massifs with the highest numbers of detected landslides for detailed comparison. The abstract does not describe additional limitations beyond this scope.

    • The study identified 926 seismogenic landslides in the European Alps from 2000 to 2023.
    • Four seasonal patterns of landslide occurrence were reported.
    • Landslide activity shifted earlier in the year and was linked to rising air temperatures and changing precipitation patterns.
    • The highest-landslide massifs had lower average temperatures, higher annual precipitation, and a larger channel steepness index.
    • Six massifs had more than 30 landslides, enabling before-and-after 2010 comparisons.

  • Reasoning-based LLMs predicted 12-week antidepressant remission

    What the study found

    The study found that reasoning-based large language models could predict 12-week remission in patients with depressive disorder receiving antidepressant monotherapy. The best-performing model was Claude 3.7 Sonnet with 32,000 reasoning tokens and a referencing of deep research prompt.

    Why the authors say this matters

    The authors conclude that these models show promise as interpretable adjunctive tools in depressive disorder treatment planning. They also say prospective validation in real-world clinical settings remains essential.

    What the researchers tested

    The researchers analyzed data from 390 patients in the MAKE Biomarker discovery study who were taking first-step antidepressant monotherapy. They tested three large language models — ChatGPT o1, o3-mini, and Claude 3.7 Sonnet — using prompting strategies including zero-shot chain-of-thought, atom-of-thoughts, and a novel referencing of deep research prompt. Three psychiatrists independently rated the model outputs for clinical validity on 5-point Likert scales.

    What worked and what didn't

    Claude 3.7 Sonnet with 32,000 reasoning tokens and the referencing of deep research prompt achieved the highest performance, with balanced accuracy of 0.6697, sensitivity of 0.7183, and specificity of 0.6210. Medication-specific analysis showed negative predictive values of 0.75 or higher across major antidepressants, suggesting stronger performance for identifying likely nonresponders. Psychiatrists gave favorable mean ratings for correctness, consistency, specificity, helpfulness, and human likeness.

    What to keep in mind

    The study used retrospective data from a single biomarker discovery dataset after excluding patients with uncommon medications or missing biomarker data. The abstract does not describe longer-term follow-up beyond 12 weeks, and it states that prospective real-world validation is still needed.

    • The best model was Claude 3.7 Sonnet with 32,000 reasoning tokens and a referencing of deep research prompt.
    • Balanced accuracy for the top model was 0.6697, with sensitivity of 0.7183 and specificity of 0.6210.
    • Negative predictive values were 0.75 or higher across major antidepressants in medication-specific analysis.
    • Three psychiatrists rated the model outputs favorably on correctness, consistency, specificity, helpfulness, and human likeness.
    • The authors say prospective validation in real-world clinical settings remains essential.

  • Craniofacial fibrous dysplasia osteoblasts show altered bone homeostasis

    What the study found

    The study found that osteoblasts from craniofacial fibrous dysplasia lesions showed higher intracellular cyclic adenosine monophosphate (cAMP), increased proliferation, reduced osteoblastic differentiation, and no mineralization ability. The authors also reported a decreased osteoclastogenic potential, meaning a reduced ability to promote osteoclast formation, in these cells.

    Why the authors say this matters

    The authors suggest that comparing craniofacial and appendicular fibrous dysplasia, that is, lesions in the skull-face region versus the limbs, could help explain why these sites behave differently. They conclude that further study of craniofacial fibrous dysplasia pathogenesis is needed.

    What the researchers tested

    The researchers studied osteoblasts from craniofacial fibrous dysplasia lesions in vitro, meaning in laboratory cell cultures. They examined histology, intracellular cAMP levels, cell proliferation, osteoblastic differentiation, mineralization, and the ability of conditioned medium from these cells to support osteoclast formation.

    What worked and what didn't

    Typical histological features described as an "alphabet soup" appearance were observed in craniofacial fibrous dysplasia lesions. The cells showed increased proliferation, but osteoblastic differentiation and mineralization were decreased or absent. The conditioned medium also showed impaired osteoclast formation, indicating reduced osteoclastogenic potential.

    What to keep in mind

    The abstract does not describe sample size, study duration, or detailed experimental controls. It also does not provide clinical outcome data, so the findings are limited to laboratory observations from craniofacial fibrous dysplasia cells.

    • Craniofacial fibrous dysplasia osteoblasts had higher intracellular cAMP.
    • These cells showed increased proliferation but reduced differentiation and mineralization.
    • Conditioned medium from the cells had impaired osteoclast formation.
    • The study reports typical histological "alphabet soup" features in craniofacial lesions.
    • The authors note shared features with appendicular fibrous dysplasia, but differences in osteoclastic potential.

  • Mosque design in Phoenix is shaped by local context

    What the study found

    The study found that mosque development in Greater Phoenix is shaped by a range of local contextual factors, not just design preferences. It highlights demographic, economic, social, and civic relationships as part of the process from conception to construction.

    Why the authors say this matters

    The authors say this matters because mosques are growing rapidly in U.S. cities, while architects, designers, and planners have limited resources for creating context-sensitive solutions. The study suggests this framework can help address practical community needs rather than focusing only on aesthetics.

    What the researchers tested

    The article used a case study of eight mosques in Greater Phoenix, also described as the Valley of the Sun. It examined mosque construction within a relational regional context and drew on an interdisciplinary framework to understand the urban development process.

    What worked and what didn't

    The findings indicate that interfaith solidarity, relationships with city officials, and architect advocacy played important roles in shaping mosque designs. The article also says that factors such as demographics, economics, and social conditions influenced development from conception to construction.

    What to keep in mind

    The abstract describes a case study of eight mosques in one U.S. region, so the scope is limited to that setting. It does not provide detailed limitations beyond noting that the article shifts attention away from prior work focused mainly on aesthetics.

    • Mosque development in Greater Phoenix is shaped by demographic, economic, social, and civic factors.
    • Interfaith solidarity, city officials, and architect advocacy are identified as important influences.
    • The study uses a case study of eight mosques in the Valley of the Sun.
    • The authors say the work shifts attention from mosque aesthetics to development processes and community needs.
    • The abstract frames the study as an interdisciplinary contextual framework for mosque construction in the U.S.