Ethiopia has not only one of the largest livestock populations in Africa, but also a substantial growing human population, increasing the risk of zoonotic disease transmission. Anthrax is a priority zoonosis in Ethiopia due to its risks to both human and animal health. Utilising 13 years of retrospective data (2008-2020) from 92 zones, this study investigated the spatio-temporal distribution of livestock anthrax cases in Ethiopia. High variability in annual incidence was observed, with the lowest number of cases (n=2357, 3.73 %) in 2018 followed by the highest number of cases (n=8210, 12.98 %) in 2019. Cattle contributed the majority of cases (n=36,104; 57.09 %) with relatively even distribution across the other species (sheep, goats, camels, and equines). Kruskal-Wallis tests found that incidence of anthrax per 100,000 animals varied significantly by species, year, region and zone, with the largest effect size (0.20) observed between zones. Getis-Ord General G analysis found significant clustering of anthrax cases per 100,000 animals in multiple years for cattle (2013, 2018 and 2019), goats (2009, 2010 and 2012), and sheep (2013, 2015, 2016, and 2019). Getis-Ord Gi* hotspot analysis of data from these years identified zones contributing to these hotspot clusters, but none of the hotspots occurred in multiple species in the same location and year. Cattle hotspots were limited to zones in the Somali region and goat hotspots to neighbouring zones of the Amhara and Oromia regions. Sheep hotspots were not restricted in geographic distribution. Understanding these patterns is vital to coordinating anthrax control and prevention efforts in Ethiopia.
Clostridioides difficile infection (CDI) is one of the most common healthcare-associated infections in the US, and recurrence remains a major clinical challenge, as standard-of-care antibiotics fail to prevent recurrence in up to one-third of cases. Fecal microbiota, live-jslm (RBL) is the first single-dose, microbiota-based product approved by the US Food and Drug Administration and Health Canada for the prevention of recurrent CDI (rCDI) following standard-of-care antibiotics. The RBL clinical development program is the largest to date for any microbiota-based product, encompassing seven studies and enrolling over 1700 participants to evaluate the safety and efficacy of RBL in preventing rCDI. Although the RBL development program consistently evaluated both efficacy and safety outcomes across all studies, this review summarizes the study designs, with a primary focus on the efficacy outcomes. The program consists of randomized controlled trials, open-label cohorts, retrospective analyses, and real-world data, each contributing unique insights across different patient populations and treatment settings. All studies enrolled adults aged ≥ 18 years with rCDI who received antibiotics for their enrolling CDI episode before RBL administration. Most studies administered RBL rectally, except for an open-label study and a retrospective study, which evaluated colonoscopic administration of RBL. Treatment success was evaluated at 8 weeks, and sustained clinical response was evaluated at 6 or 24 months after RBL and/or placebo administration, depending on the study design. Overall, the study designs for all seven studies were consistent, with slight differences between number of CDI episodes (specifically, 2 studies allowed enrollment after the first CDI recurrence), blinding, controls, and administration routes. Efficacy data of RBL reported across all studies consistently demonstrated RBL is efficacious for the prevention of rCDI in a broad adult population. TRIAL REGISTRATION: ClinicalTrials.gov. NCT01925417; NCT02299570; NCT02589847; NCT03244644; NCT03931941; NCT05831189. Antibiotics used to treat bacterial infections can also damage good bacteria in the gut (dysbiosis). When these good bacteria are damaged, a bacterium called Clostridioides difficile can overgrow and release toxins that harm the colon. This can cause severe diarrhea and may become life-threatening. Antibiotics used to treat C. difficile infection contribute to dysbiosis and increase the chance the infection will return. Microbiota-based products are treatments comprising a wide variety of gut microbes. They help restore the natural balance of bacteria in the gut and have been shown to prevent C. difficile infection from returning. RBL, also known as REBYOTA® or fecal microbiota, live-jslm, is one of these microbiota-based products developed to prevent recurrent C. difficile infection in adults. The RBL clinical development program is currently the largest group of studies for any microbiota-based product. More than 1700 people have taken part in these studies to test the safety of RBL and its efficacy in preventing recurrent C. difficile infections. This review summarizes all the RBL studies and results seen so far. Across the different studies, which were similar in design and included a wide range of adult participants, RBL consistently helped prevent C. difficile infections from returning. Overall, the evidence shows RBL is effective for many adults at risk of recurrent C. difficile infection.
Purpose in life is associated consistently with better cognitive outcomes. The association between purpose and neurobiomarkers of brain health has been less robust than the association with cognitive outcomes. This research uses the largest sample to date to test the association between purpose in life and four neurobiomarkers of brain health measured from plasma: The Aβ42/Aβ40 ratio, p-tau181, neurofilament light (NfL), and glial fibrillary acidic protein (GFAP). We further test whether higher purpose is associated with cognitive resilience against neuropathological burden (i.e., better cognitive performance relative to the amount of neuropathology). Data were from the Health and Retirement Study. Participants (N=4193; M  age=68.87, SD = 10.17) reported on their purpose in life and provided venous blood. Biomarkers were assessed using Quanterix's Simoa platforms. Linear regression tested the association between purpose and the four neurobiomarkers. Residual and interaction-based approaches evaluated cognitive resilience. Purpose in life was associated with lower NfL accounting for sociodemographic factors (β=-.06, p<.001). Clinical and behavioral covariates accounted for half of this association, but it persisted (β=-.03, p=.007). Purpose was unrelated to the other three neurobiomarkers. Purpose in life was associated with greater cognitive resilience when tested with the residual approach (β=.12, p<.001) but not the interaction approach (βinteraction=.01, p=.372). In the largest sample to date, individuals with more purpose in life had less neuronal injury, as measured with NfL. Purpose was unrelated to other common neurobiomarkers of brain health.
The only functional impairment data available for all Medicare beneficiaries identify those who qualified for Medicare before age 65 years due to work-related disability. This administrative measure omits impairments arising after age 64 years or affecting nonwork-related activities. Surveys may offer more accurate assessments, but survey data on functional limitations are not routinely available. Claims data may provide a practical, scalable alternative. To describe the development of a survey-based index of functional limitations and a new claims-based model for predicting limitations. Data from respondents to the 2024 Medicare fee-for-service (FFS) Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey were used to create the FFS CAHPS functional limitations index (FCFLI), a measure of the extent to which functional limitations affect overall health and the benchmark for the study's claims-based measure. The FCFLI scores of respondents were linked to Medicare FFS claims from April 2023 to March 2024 to develop a claims-based predictive model (FCFLI-claims). The final model was applied to all FFS beneficiaries enrolled in Medicare Parts A and B during the same period. The FCFLI was derived from beneficiaries' self-rated health and ability to perform 6 basic activities of daily living and 1 instrumental activities of daily living (collectively, I/ADLs). Nine sets of claims-based indicators of functional impairment were used to predict FCFLI scores. Data were collected from 67 596 respondents (53.4% female; mean [SD] age, 75 [8] years). In the FCFLI model, all I/ADL indicators were negatively associated with self-rated health, with the largest effect estimates for difficulty walking (-13.9 points; 95% CI, -14.6 to -13.2 points) and running errands (-11.7 points; 95% CI, -12.7 to -10.8 points). In the FCFLI-claims model, 14 claims indicators had relative importance values that were 5% or greater of the maximum value. The model reliably identified beneficiaries with functional limitations (80.4% positive predictive value). Applied to the 2024 Medicare FFS population, approximately 12% were identified as likely to have functional limitations. Nearly 63% (approximately 2 450 000) of those identified by the algorithm were not identified by Centers for Medicare & Medicaid Services administrative measure of disability, which focuses on limitations that develop before age 65 years. In this cross-sectional study, FCFLI-claims identified beneficiaries likely to have functional limitations who could be prioritized for a survey assessment to verify the algorithm's results. Integrating this information with entitlement data could enhance Centers for Medicare & Medicaid Services' monitoring of functional status, especially among age-eligible beneficiaries.
Anthropogenic climate change fosters unprecedented temperature challenges, with each year breaking a temperature record. Through evolution by natural selection, species and their populations have adapted to their previously local environments. However, as the average global land temperature has increased by ~2 °C or more, natural selection on many species may not act fast enough with climate change, creating an adaptation lag. To understand potential adaptation lags to recent climate change, we conducted a meta-analysis on the largest set of single-species field transplantation experiments across climates with the broadly-distributed model plant, Arabidopsis thaliana , with a total of 1,600 germplasm and 42 field trials. We developed a Gaussian fitness model dependent on local environment and climate deviations to infer genotype-specific adaptation lag parameters. We estimate a mean thermal adaptation lag over 1.91 °C, suggesting that local populations, on average, are better adapted when transplanted to locations cooler than their home climates. While a less than 2 °C temperature mismatch appears small, its impact on fitness corresponds to a 14% cumulative burden over time, which compounds depending on the future climate emission scenario. Combining climate model projections under different scenarios, we found that by 2025, populations would have lost 30% demographic potential under a moderate emissions scenario. Our discovery of this adaptation lag shows that even this highly adaptable species has not kept pace with recent climate change.
Mustelus whitneyi (humpback smooth-hound shark) is a Critically Endangered demersal species endemic to the southeastern Pacific and exploited by small-scale fisheries in northern Peru. This study evaluated how seasonal and interannual environmental variability, particularly associated with the El Niño-Southern Oscillation (ENSO), influences the spatial distribution of the species. Presence-only data collected between 2015 and 2018 were combined with six oceanographic variables selected from an initial set of eight candidate predictors from the Copernicus Marine Service to develop seasonal species distribution models (SDMs) using Maxent. To account for sampling bias associated with fisheries-dependent records, background selection was informed by a distance-based bias raster. Models performed better than random expectations in all scenarios, although performance varied among seasons and several models exhibited elevated omission rates, indicating lower predictive reliability during specific periods. Bottom potential temperature emerged as the primary environmental predictor, highlighting the importance of subsurface thermal conditions for this demersal species. Predicted suitable habitat showed seasonal and interannual variability. The largest predicted distribution areas were observed during El Niño conditions, particularly in austral spring 2015 and winter 2016, coinciding with warmer bottom waters. In contrast, neutral conditions in 2017 were associated with a contraction of suitable habitat during austral summer, whereas La Niña conditions in 2018 produced more fragmented spatial patterns. Overall, the results suggest that climate-driven environmental variability influences the spatial extent and configuration of the predicted distribution for M. whitneyi. This study provides the first ENSO-phase-specific SDMs for the species and offers a baseline for incorporating environmental variability into fisheries management and conservation planning in the Northern Humboldt Current System.
Zacatecas is in the north-central region of Mexico. Its territorial extension, as well as the unique combination of climatic and physiographic characteristics, favor high biological diversity. However, until now, it has been considered one of the states with lowest herpetofaunal diversity, mainly due to low sampling effort. We provide an updated checklist of the herpetofauna of Zacatecas, including the physiographic provinces and ecoregions where they occur, a summary of their conservation status, and a comparison with neighboring states. Zacatecas has 25 species of native amphibians and 119 native reptiles, with five introduced species (1 frog, 2 lizards, 1 snake and 1 turtle). Of 149 species, four have their type locality in Zacatecas, 16 represent new state records, and 232 records from 79 species are new municipal contributions. More than half of the native herpetofauna (53.5%) of Zacatecas is endemic to Mexico. However, it does not have state endemics, but harbors populations of regional endemics that only inhabit north-central Mexico. Of the native amphibian and reptile species in Zacatecas, 2.8% are listed by IUCN in threatened categories (i.e., Vulnerable, Endangered, Critically Endangered), 13.9% are placed in a protected category by SEMARNAT (i.e., Threatened and in Danger of Extinction), and 33.3% are categorized as high vulnerability by the EVS criteria. Among adjacent states with which it shares a border, Zacatecas is the fourth with the largest territorial extension, the fifth in herpetofauna diversity, and the third with the highest number of country endemic species. Large areas of the state remain underexplored, suggesting that the herpetofauna richness of Zacatecas may increase in the future.
Variation in primary care quality across social groups contributes to health inequalities. We examined achievement rates for quality-of-care indicators among patients attending primary care practices in England, comparing rates for patients living in the most and least deprived areas. We analysed electronic health records from 2.2 million patients in 2019/2020, registered with 300 practices contributing to the Clinical Practice Research Datalink (CPRD) Aurum database. Patients were grouped by neighbourhood deprivation using the 2019 Index of Multiple Deprivation. We assessed inequality in 35 quality-of-care indicators from the Quality and Outcomes Framework pay-for-performance scheme for 607 126 patients with a relevant long-term condition, calculating differences in (a) age-sex adjusted achievement rates (overall inequality) and (b) rates further adjusted for common practice fixed effects (within-practice inequality) obtained by logistic regression. Rates were calculated for all patients with relevant conditions (population achievement) and the subset not excluded from the scheme by practices (reported achievement). There was no consistent socioeconomic pattern in reported achievement of individual indicators overall (across all practices), but within-practice reported achievement was significantly lower for patients in more deprived areas for eight indicators. Population achievement was significantly lower for patients in more deprived areas for 13 indicators, reflecting higher exclusion rates. Population achievement was higher in more deprived areas for one indicator. The largest inequalities were for influenza vaccination (chronic obstructive pulmonary disease and stroke) and haemoglobin A1c (HbA1c) control (diabetes). Within the same practice, patients from more deprived areas are less likely to receive recommended care for key quality of care indicators.
Conductive filaments for Material Extrusion Additive Manufacturing (MEX) can enable low-cost fabrication of functional parts with embedded electrical features. However, systematic studies on process-dependent electrical properties like apparent resistivity and repeatability are limited, and the post-printing stability of the electrical response is not commonly addressed. This study evaluates the influence of printing temperature, printing speed and layer height on the apparent resistivity, specimen-to-specimen repeatability and time-dependent drift of a commercial carbon black-filled conductive PLA filament (ProtoPasta). The novelty of the study consists of evaluating not only the initial apparent resistivity, but also the repeatability between specimens and the post-print drift of apparent resistivity over a 0-50 h interval. The filament was investigated using three printing temperatures (210-230 °C), two printing speeds (60-80 mm/s) and three layer heights (0.2-0.4 mm), with three replicates per configuration. Apparent resistivity ranged between 0.156 and 0.205 kΩ·mm at t0 and between 0.162 and 0.222 kΩ·mm at t50. Multifactorial ANOVA and main-effects analyses showed that the printing temperature was the main factor affecting mean apparent resistivity at both t0 and t50. Higher temperature reduced apparent resistivity, most likely due to improved polymer flow, inter-bead/inter-layer bonding and conductive-network continuity. Printing speed had no significant main effect on the mean apparent resistivity or drift within the tested range. Repeatability depended on the parameter configuration and measurement time, with variability increasing after 24 h and then becoming mainly dependent on layer height. Drift analysis showed a significant main effect of layer height and a significant layer height × temperature interaction, with the largest increase at 0.3 mm. These results show that parameter selection for conductive MEX parts should consider both the initial resistivity level and post-print stability over time.
Autoimmune encephalitis (AE) is a major cause of acute and subacute neuropsychiatric syndromes. While neuronal autoantibody testing aids diagnosis, results are often delayed or negative in seronegative cases. Cerebrospinal fluid (CSF) cytokine profiling may provide a rapid diagnostic adjunct. In this cross-sectional study, we analysed CSF from 43 AE patients (29 seronegative, 9 N-methyl-d-aspartate receptor antibody-positive, 3 leucine-rich glioma-inactivated 1 (LGI1)-positive, and 2 with rare antibodies) and 34 controls (33 idiopathic intracranial hypertension and 1 viral encephalitis). Cytokine levels (IL-6, IL-7, IL-13, IL-21, CXCL10 and CXCL13) were quantified using a multiplex immunoassay. All measured cytokines were significantly elevated in AE compared with controls (p < .001). CXCL10 and CXCL13 showed the largest differences between AE and controls, with CXCL13 particularly high in LGI1-positive cases. IL-6 correlated positively with IL-13 (r = 0.47, p = .0013) and CXCL13 (r = 0.41, p = .0064), while IL-7 correlated with IL-21 (r = 0.33, p = .029). Cytokine profiles in seronegative AE were comparable to antibody-positive AE, with no statistically significant differences. CSF cytokines-particularly CXCL10, CXCL13, IL-6 and IL-13-are consistently elevated in AE and reflect shared intrathecal immune activation across antibody-positive and seronegative cases. These findings are exploratory, and cytokines are proposed as adjunctive immunological markers rather than standalone diagnostic tools.
Speech brain-computer interfaces (BCIs) can restore rapid communication to people with paralysis, but decoding errors still limit performance. In recent brain-to-text decoding competitions, deep ensemble methods, which combine predictions from multiple independently trained decoders, have delivered striking accuracy improvements and account for the largest gains over baseline approaches. However, these methods have not previously been tested in real-time, require substantial computational resources, and their performance under various clinically relevant constraints remains poorly understood. Here, we present the first closed-loop test of deep ensembles in a participant with bilateral intracortical microelectrode arrays, demonstrating a reduction in word error rate from 33.7% to 26.0% on a large-vocabulary task. Using additional data from three participants, we then assess how these gains depend on baseline error rate, training dataset size, and ensemble size, including the resource-accuracy tradeoffs most relevant for real-world deployment. Finally, we introduce a computationally efficient pseudoensembling approach based on test-time augmentation that improves decoding accuracy while requiring only a single base decoder, greatly reducing the computational burden of ensembling. Together, these results show that the benefits of deep ensembling can be realized in real time and under practical resource constraints, bringing speech BCIs closer to broader clinical adoption.
The persistent presence of a micro-gap at the implant-abutment interface continues to pose biological and mechanical challenges, yet the influence of different connection designs remains insufficiently understood. Therefore, it is of interest to evaluate 100 implant abutment assemblies external hex, internal hex and internal conical using SEM before and after cyclic loading. External hex connections showed the largest micro-gaps, internal hex showed moderate values and internal conical exhibited the smallest and most stable interface. Statistical analysis confirmed significant differences among the designs, with conical connections demonstrating superior resistance to micro-gap enlargement under functional loading. Thus, we show new comparative evidence showing that internal conical connections provide the most stable interface, thereby advancing knowledge on optimal implant-abutment design for improved clinical outcomes.
Anti-Müllerian hormone (AMH) and antral follicle count (AFC) are usually correlated, yet discordance might complicate counseling in elective fertility preservation (EFP). This study evaluated whether discordant ovarian reserve markers affect oocyte yield in healthy women undergoing EFP. This retrospective cohort study included 230 healthy women aged 30-41 years undergoing their first EFP cycle at a university-affiliated tertiary fertility unit. Participants were categorized based on AMH (<1.1 or ≥1.1 ng/mL) and AFC (<7 or ≥7) thresholds. Analyses focused on concordant versus discordant AMH-AFC groups. The primary outcomes were the number of oocytes retrieved and vitrified. Multivariable linear regression assessed independent predictors of oocyte yield. The overall discordance rate was 30.43%. Women in Group 1 - Normal AFC (≥7) with low AMH (<1.1 ng/mL) (n = 67) had significantly fewer retrieved (mean 6.7 ± 4.5) and vitrified oocytes (mean 4.9 ± 3.4) than those in Group 4 - Normal AFC (≥7) with normal AMH (≥1.1 ng/mL) (n = 149; 14.6 ± 8.1 and 10.6 ± 6.8, respectively; P < 0.001), which represented the two largest study groups. AMH was the strongest independent predictor of oocyte yield. Discordance independently contributed additional explanatory value for the number of retrieved oocytes, with discordant patients predicted to achieve fewer oocytes than concordant-normal counterparts. The concordance status did not significantly affect the number of vitrified oocytes. AMH-AFC discordance (specifically low AMH in the presence of normal AFC) is an independent predictor of reduced oocyte yield in EFP but not of the number of vitrified oocytes. Joint interpretation of both markers might facilitate more accurate patient counseling and expectation management.
During a survey of endophytic fungi associated with medicinal plants in Iran, three novel species of the genus Xenodidymella including X. euphorbiae, X. hamanae and X. kopetdagensis were isolated from asymptomatic tissues of Euphorbia kopetdaghi Prokh and Thymus transcaspicus Klokov. Species delimitation was conducted using a combination of morphological characterisation and multilocus phylogenetic analyses based on the ITS rDNA, partial beta-tubulin (tub2), and RNA polymerase II second largest subunit (rpb2) gene regions. Both Bayesian inference and Maximum Likelihood phylogenetic analyses revealed that each new species formed distinct, well-supported clades, clearly separated from previously known taxa. In addition, Xenodidymella camporesii is reported for the first time from healthy roots of Salvia sclarea L., representing a novel host record. These findings suggest a potential endophytic lifestyle for Xenodidymella species, contrasting with their traditionally known roles as pathogens or saprobes. This study contributes to the taxonomic expansion of the genus and underscores the rich, yet underexplored fungal diversity of Iran's arid and semi-arid ecosystems.
HPV-associated cancers in men represent a growing public health concern in Latin America, yet evidence on burden remains limited. We analyzed national data in Peru (2015-2019) to estimate outpatient consultations, hospitalization, and death rates for HPV-associated cancers and applied site-specific attributable fractions to derive HPV-attributable burden. Rates were age-standardized (ASR) to the WHO World Standard Population. Sensitivity analysis excluded mortality data for 2015-2016 to account for improvements in cause‑of‑death completeness. Between 2015 and 2019, 5,996 outpatient consultations for HPV-associated cancers in men were recorded (ASR: 8.2 per 100,000), mainly due to head and neck (56.3%) and penile (30.4%) cancers. A total of 1,136 hospitalizations were identified (ASR: 1.6 per 100,000), with head and neck and penile cancers accounting for 46.3% and 45.9% of total hospitalizations, respectively. Rates increased with age, reaching 38.0 outpatient consultations and 7.5 hospitalizations per 100,000 among men ≥60 years, but were also present among younger (<30 years) and middle-aged (30-59 years) men. Applying attributable fractions, 2,056 outpatient consultations (ASR: 2.8) and 402 hospitalizations (ASR: 0.6) were HPV-attributable, with penile cancer contributing the largest share. A total of 859 deaths from HPV-associated cancers were recorded (ASR: 1.2), of which 208 were HPV-attributable (ASR: 0.3), predominantly among men aged ≥60 years (77.2%). Sensitivity analysis had minimal impact on mortality estimates. HPV‑attributable cancers impose a substantial and preventable burden on Peruvian men. Strengthening universal HPV vaccination, ensuring high coverage, expanding multi‑age catch‑up strategies, and improving access to early diagnosis and treatment are essential to reduce future burden.
Many essential inhaled medicines recommended in guidelines are delivered to the lung via pressurized metered-dose inhalers (pMDIs). Global environmental legislation will lead to phasing out of hydrofluoroalkane propellants currently used in pMDIs, owing to their global warming potential (GWP). Furthermore, the European Chemicals Agency is reviewing proposed legislation to ban per- and polyfluoroalkyl substances (PFAS) on the basis of chemical structure, which could also impact pMDI availability. Here, we estimated pMDI use as a proportion of all inhaler use in 60 countries, spanning six geographical regions, to understand the relevance of any pMDI restrictions to patients and prescribers. pMDI use as a percentage of total inhaler use during 2022 was calculated by country and geographical region using inhaler sales data (a surrogate of use) from the IQVIA Quarterly MIDAS database; inhaler use for the 10-year period from 2013 to 2022 was also evaluated for these regions. Data were compared by individual inhalations. The total patient population living with asthma and/or chronic lower respiratory disease was calculated on the basis of Eurostat (the statistical office of the European Union [EU]) 2019 data and available disease prevalence statistics. Maintenance pMDI utilization was estimated by adjusting for ratio of maintenance pMDI use to total inhaler use. Across all countries analyzed, pMDIs accounted for the largest proportion of inhaler use in 2022 (77.3%). In 51 out of 55 countries with available country-level data, pMDIs represented > 50% of total inhaler use. After adjusting for pMDI usage, an estimated 8.1 million EU patients received a maintenance pMDI in 2022, with the greatest proportion in Germany and France. pMDIs are vital inhalers for most patients in Europe and around the world. While transitioning to near-zero or low-GWP inhalers, it is essential to avoid unintended consequences from the proposed PFAS ban by safeguarding patient access to this essential device option.
Modeling disease-specific survival (DSS) is essential for evaluating the risk of death due to the disease itself, offering valuable insights into disease progression, identifying high-risk subgroups, and informing treatment decisions. The National Cancer Database (NCDB), one of the largest cancer registries in the United States, has the potential to be a valuable resource for assessing DSS in the general cancer population. However, the NCDB does not record cause-of-death information due to practical limitations. In contrast, randomized cancer clinical trials provide detailed documentation of the cause of death. To bridge this gap, a framework is developed to leverage cause-of-death information from clinical trials to infer DSS in the NCDB population through a proportional cause ratio model. This model accommodates both temporal variation and patient-level characteristics influencing the distribution of causes of death. To account for population heterogeneity between trial participants and registry patients, information transfer is restricted to the cause-of-death mechanism rather than the overall survival distribution. Estimation procedures are established, and the asymptotic properties of the resulting estimators are rigorously derived. Extensive simulation studies demonstrate the validity of the proposed estimators and associated inference under both the proportional cause ratio model and the proportional hazards model for DSS. The proposed method is applied to our motivating study in which cause of death information from the National Surgical Adjuvant Breast and Bowel Project (NSABP B-06 trial) is transferred to the NCDB to infer breast cancer-specific survival based on demographics of the patient, clinical characteristics, and treatments received.
Citizen satisfaction with public services is a fundamental indicator of government effectiveness and democratic legitimacy in Latin America. However, there is little empirical evidence on regional gaps in countries with high territorial heterogeneity such as Peru. The objective of this study was to determine the differences in levels of citizen satisfaction with public services between the country's coastal, mountain, and jungle regions. A secondary analysis was conducted of the 2024 National Household Survey, corresponding to the Governance, Democracy, and Transparency Module (n = 33,691), evaluating 21 public services using the Citizen Satisfaction Index. Student's t-tests were applied for comparisons between urban and rural areas, one-factor ANOVA with Bonferroni post-hoc tests for comparisons between geographic domains, and principal component analysis to explore the dimensional structure. The results revealed statistically significant differences between the eight geographic domains (F = 89.57, p < .001, η² = .022); although this effect size is small, indicating that geographic domain accounts for 2.2% of the variance in satisfaction, the patterns are consistent and policy-relevant. The North Coast (M = 3.09) and Amazon (M = 3.13) showed the lowest satisfaction rates, while the Southern Highlands (M = 3.29) even surpassed Metropolitan Lima. Social programs (51.9%) and the Public Prosecutor's Office (56.4%) obtained the lowest national satisfaction ratings, with the largest regional gaps. Rural areas reported higher satisfaction with public transportation (+7.0%) and public education (+3.5%) than urban areas. A four-dimensional factor structure was identified that explains 46.7% of the variance. It is concluded that territorial gaps are consistent with structural differences in regional institutional capacity, requiring territorially differentiated public policies to reduce inequalities in the provision of state services.
Long-read single-cell RNA sequencing provides an opportunity to understand human health and disease at a level difficult to resolve with bulk or short-read methods. This approach enables isoform-level investigation of cellular diversity and disease mechanisms and definition of cell-types, rather than using genes alone. Using a modified, microfluidic-free PIPseq workflow and computational pipeline adapted for Oxford Nanopore long-read sequencing, we generated the largest long-read single-cell dataset of human peripheral blood mononuclear cells (PBMCs) from a single donor to date, the first with sufficient cell numbers to detect megakaryocytes. This study profiled isoform usage across immune cells, integrating marker expression and isoform discovery. We identified 126 novel isoforms from known and new genes, several with distinct cell-type-specific patterns, and characterized marker gene isoform expression across cell-types. Non-canonical protein-coding variants of GZMB and CD3G were enriched in unexpected cell-types, including megakaryocytes and monocyte-derived populations. We also discovered novel transcripts from CMC1 and LYAR with cell-type-specific signatures that were also the predominantly expressed transcript within the gene. This study expands the versatility of long-read single-cell studies to not only relay changes in isoform signatures, but to position them within the functional context of the biology they impact. These results demonstrate the power of long-read single-cell sequencing for mapping the isoform landscape-the isonome-across tissues and disease contexts.
Polygenic risk scores (PRS) for breast cancer are increasingly used for risk stratification to inform screening and prevention. However, for PRSs to be equitable and clinically useful, they need to perform well across diverse populations. While PRS performance is known to be ancestry-dependent, it is not well understood how environmental context, such as that of socioeconomic status (SES), affects PRS transferability. Here, we assess whether SES, measured via self-reported household income, modifies breast cancer PRS performance and, if so, whether socioeconomic context contributes predictive information beyond genetic risk alone. We used the US-based All of Us biobank to evaluate how SES impacts breast cancer PRS performance. First, we quantified changes in breast cancer PRS performance by modeling a commonly-cited polygenic score for breast cancer previously described by Mavaddat et al. with SES. We then reestimated the genetic effect sizes of the 3,820 variants from Mavaddat et al. in All of Us with and without income as a covariate. Because social determinants of health affect breast cancer detection and outcomes, we stratified analyses by socially defined populations on the basis of self-identified race and ethnicity. We further stratified individuals whose self-identified race is White ("White") into three SES groups (high, middle, low) based on self-reported income and re-estimated genetic effect sizes to create SES-specific PRSs. We then applied these PRSs to White participants, the largest group in the study, and to Black or African American ("Black") and Hispanic or Latino ("Hispanic") participants, groups underrepresented in breast cancer research. Model discrimination between cases and controls was measured by area under the curve (AUC). We analyzed 163,715 women from the All of Us biobank, which included 8,833 breast cancer cases (6,619 White, 1,178 Black, and 1,036 Hispanic), with relative income available for a subset of these cases (5,525 White, 848 Black, and 566 Hispanic). The ancestry-dependent performance of the breast cancer PRS described in Mavaddat et al. was replicated in All of Us. In Black individuals, this PRS (AUC and 95% CI: 0.576 [0.571, 0.582]) produced a similar increase in AUC as relative income (AUC: 0.573 [0.568, 0.577]) when added to an age-only model. Incorporating income with PRS, age, and genetic PCs 1-3 improved AUC by 0.007 in White Americans and 0.018 in Black Americans (both p < 10 -11 ), while attenuating the contribution of PRS in the full model. PRS performance also varied among SES categories. Notably, PRSs with variant effect sizes that were recalibrated in low-SES White participants performed best in low-SES White participants (AUC: 0.605 [0.583, 0.628]) and Black Americans (AUC: 0.588 [0.586, 0.591]), both better than performance in high-SES White Americans (AUC: 0.579 [0.577, 0.580]) and middle-SES White Americans (AUC: 0.578 [0.569, 0.586]). Socioeconomic context, measured by income, significantly impacts the transferability of a PRS for breast cancer within and among groups defined by self-identified race and ethnicity. Accounting for SES improves PRS performance, most notably in Black Americans and low-SES White individuals.