University of Rhode Island

Rationale Stable oxygen isotope measurements in silicate clays, such as smectite and kaolinite, provide crucial information for understanding Earth's climate history and environmental changes. Despite a growing interest in the oxygen isotope analysis of silicate clays and clay‐rich sediments, there lacks a consensus on the preparation and standardization of clay mineral samples. To improve the accuracy and interlaboratory comparisons of clay isotope measurements, especially those involving laser fluorination techniques, newly established kaolinite and smectite oxygen isotope standards are much needed. Methods We employed conventional nickel bomb fluorination combined with dual‐inlet isotope ratio mass spectrometry to establish precise δ ¹⁸ O and Δ′ ¹⁷ O values for leached clay reference materials KGa‐1b and SHCa‐1, a kaolinite and a hectorite/smectite, respectively. We further measured leached KGa‐1b and SHCa‐1 pressed into pellets with a lithium fluoride as a binding agent for the laser fluorination method, allowing us to test the reproducibility between methods and utilize a standard laser chamber drift correction scheme. Results The laser fluorination technique yielded highly precise and reproducible δ ¹⁸ O and Δ′ ¹⁷ O measurements for the KGa‐1b and SHCa‐1, aligning with bomb values of δ ¹⁸ O. This confirms the method's reliability and comparability to conventional isotope measurement techniques while also stressing the importance of proper sample preparation and laser chamber drift corrections. Conclusions This study demonstrates that laser fluorination is an effective method for accurately measuring the stable oxygen isotope composition of silicate clays or clay‐rich sediments when corrected with known silicate clay standards. These methods offer a valuable methodology for future research and applications that will significantly improve our understanding of past climate and environmental conditions.

This Viewpoint highlights primary care–based screening for food insecurity as the first social determinant of health topic to be addressed by the US Preventive Services Task Force; the potential benefit of food insecurity screening on access to other preventive services; and several challenges to making a recommendation for food insecurity screening.

Context Lean sports, endurance running, have been at the forefront of disordered eating and body image research, particularly in female populations. Yet, little is known about how athletic men and women differ in body checking behaviors, a known risk factor for body dissatisfaction and disordered eating, across sport type and athletic status. Objective The purpose of this study was to examine gender differences on measures of eating behavior and body checking between full-time collegiate student-athletes and nonathletes. Design Cross-sectional study. Setting NCAA DI collegiate athletics. Participants Two-hundred fifty-nine full-time college students (n = 174 student-athletes, 85 nonathletes) Main Outcome Measures Primary outcomes included self-reported disordered eating behavior and body checking behavior through the EAT-26 and the Body Checking Questionnaire (BCQ) and the Male BCQ (MBCQ). We explored differences based on sport type, team, individual, or nonathlete, and gender identity. Results There was a statistically significant multivariate main effect of gender F(10, 464) = 9.219, p<0.001, 𝜂 2 = 0.166, and a significant multivariate interaction of gender and sport type F(15, 699) = 2.806, p=0.001, 𝜂 2 = 0.057. Follow-up comparisons for team sport athletes showed that women scored significantly higher (p<0.001) on the MBCQ compared to men. Women team sport athletes also scored significantly higher on the MBCQ than women nonathletes (p < 0.001). Conversely, nonathlete men scored significantly higher on the MBCQ than men team and individual sport athletes (p = 0.003 and p = 0.048, respectively). Conclusions Findings suggest that body checking behaviors traditionally studied as masculine occur more frequently in women than men. This effect seems to be driven by women team sport athletes, who reported engaging in more body checking behaviors on the MBCQ than nonathletes. Therefore, assessments based on traditional views of maleness and femaleness may overlook significant risk factors for eating disorders (ED) in college athletes.

Traditional methods for estimating juvenile survival in wildlife populations often rely on marking and tracking individual young. However, traditional methods can introduce bias into survival estimates via the capture or handling process and are logistically challenging to implement. Alternatively, researchers studying avian and mammalian species that provide parental care can mark and monitor adults to estimate survival probability of the unmarked offspring. We implemented a field sampling approach using unoccupied aerial vehicles (UAVs, i.e., drones) to estimate detection probabilities and pre‐fledging survival of blue‐winged teal (Spatula discors) by marking and resighting adult females with broods (n = 27). We used a combination of 2 methods to detect marked females, drone‐based VHF radiotelemetry and multispectral imagery, to estimate brood detection and apparent survival using Cormack‐Jolly‐Seber models. We compared between the VHF drone and the camera drone to investigate the ability of the VHF drone to locate marked females and thermal cameras to detect broods. Detections using the camera drone were informed by prior location cues from the VHF drone, meaning that detections were not independent but instead relied on the cues provided by the VHF drone. We monitored marked females and their unmarked broods weekly during the summer of 2023 in Saskatchewan, Canada. Of marked females, 9 suffered complete brood loss (33%), 4 had unknown fates (15%), 14 had at least one duckling survive to 35 days (52%), and we observed that 120 of 230 ducklings survived. Detection probability for sampling with the VHF drone remained constant over time (mean = 0.920), whereas detection probability using the camera drone increased with each sampling occasion (mean = 0.756). Weekly brood survival probability increased with brood age and were similar between survey methods (VHF: mean = 0.907; camera: mean = 0.898). Capitalizing on the interdependence of unmarked juveniles and marked adults, and drone‐based methodology, our approach allowed us to effectively and efficiently estimate juvenile survival for waterfowl. Our approach is applicable to a range of other species as well, where providing more precise and efficient field sampling methods for monitoring vital rates and population dynamics can enhance ecological understanding and resultant management practices.

Aims A hybrid‐three tier system with low grade (LG), high grade‐ G2 (HG‐G2), high grade‐ G3 (HG‐G3) has been proposed in recognition of, and to help address, the clinical heterogeneity within high grade WHO 2004/2022. We assessed interobserver reproducibility amongst international uropathologists using this three‐tier approach. Methods and Results Papillary Ta nonmuscle invasive bladder cancer (NMIBC) specimens ( n = 30) were selected and graded by two uropathologists and assessed using WHO 2004/2022 and WHO 1973 and categorized as LG ( n = 15), HG‐G2 ( n = 8), HG‐G3 ( n = 7), and photographed at 10× and 20× magnification. Images were circulated via Survey Monkey to invited uropathologists who determined: (1) that image was LG or HG, and (2) if HG, assigned to G2 or G3. Model‐based kappa measure of association was used to assess interrater agreement. Eighteen uropathologists:(eight North American, eight European, two other) assessed 60 images with 1076 gradings for analysis. The kappa value amongst Europeans versus North Americans was 0.663 versus 0.647 for 10× images and 0.682 versus 0.623 for 20× images. At 10×, agreement for LG, HG‐G2, and HG‐G3 was 74.6%, 63.6%, and 92.0%, and at 20× was 64.3%, 63.9%, and 95.2% respectively. Conclusion Three‐tier grading of papillary Ta NMIBC had substantial interobserver agreement amongst international uropathologists. The recognition of the HG‐G3 case reached the highest concordance. North American uropathologists had comparable kappa scores (substantial agreement) to Europeans, despite being unaccustomed to separating HG cases into G2 and G3, demonstrating three‐tier grading could be “quickly” adopted by genitourinary experts if endorsed and required by the relevant bodies in their jurisdiction of practice.

This paper proposes a multitasking linear neural network model to analyze both their recycling behaviors and preferences simultaneously. It utilizes latent representations to share information across tasks for improvement in efficiency and accuracy. The model appropriately handles diverse data types commonly found in surveys, including categorical and continuous variables. It creates vector embeddings of consumer demographics and latent representations of individual consumers, enabling a deeper understanding of consumer demographics and their impact on recycling habits. The model's performance is evaluated against traditional methods like linear regression and non-linear neural networks, demonstrating its superior predictive capabilities and efficiency. Furthermore, the model's ability to generate interpretable insights and market segmentations based on demographic inputs and latent representations is showcased, offering valuable theoretical implications for marketing analytics and managerial implications for targeted recycling interventions.

Although Epstein–Barr virus (EBV) plays a role in Burkitt lymphoma (BL) tumorigenesis, it is unclear if EBV genetic variation impacts clinical outcomes. From 130 publicly available whole‐genome tumor sequences of EBV‐positive BL patients, we used least absolute shrinkage and selection operator (LASSO) regression and Bayesian variable selection models within a Cox proportional hazards framework to select the top EBV variants, putative driver genes, and clinical features associated with patient survival time. These features were incorporated into survival prediction and prognostic subgrouping models. Our model yielded 22 EBV variants, including seven in latent membrane protein 1 (LMP1), as most associated with patient survival time. Using the top EBV variants, driver genes, and clinical features, we defined three prognostic subgroups that demonstrated differential survival rates, laying the foundation for incorporating EBV variants such as those in LMP1 as predictive biomarker candidates in future studies.

Background Persons living with HIV (PWH) remain at risk for hepatitis C virus (HCV) acquisition despite antiretroviral therapy, particularly among those who inject drugs or engage in high-risk sexual behaviors. We evaluated acute HCV incidence and associated risk factors in PWH, incorporating sex-specific differences and the use of Nucleic Acid Testing (NAT) methods, which were not addressed in previous analyses. Methods We assessed NAT-based HCV incidence from 1996-2011 in the ACTG ALLRT cohort, a long-term study of PWH after initiating antiretroviral therapy. Multivariable Poisson regression identified associations with self-reported injection drug use (IDU), and time-varying CD4+ count, HIV RNA level and increased ALT (grade ≥3). No sexual risk factors or non-IDU drug use data were available. Results Among 4,015 PWH (18% women, n=703) with an initial negative HCV antibody result, there were 18,150 person-years (PY) of follow-up. Forty-two participants seroconverted, an incidence of 0.23 per 100 PY (95% CI: 0.17, 0.31). Incidence was lower in females (n=2) versus males (n=40; 0.06 vs 0.27 per 100 PY; p=0.04). Seroconversion was associated with time-updated HIV RNA ≥400 copies/mL (RR 2.7, 95% CI 1.4-5.1, p=0.003), time-updated grade ≥3 ALT (RR 4.7, 95% CI 1.6, 13.4, p=0.005), and IDU (RR 6.3, 95% CI 2.7, 14.4, p<0.001). Conclusions Our analysis showed that IDU history and unsuppressed HIV RNA were associated with HCV acquisition among PWH. Elevated ALT levels are consistent with the biology of acute/recent hepatitis and should trigger HCV RNA testing. These findings emphasize the need for targeted interventions to reduce HCV transmission risk in PWH.

Purpose Chronic kidney disease (CKD) is frequent in bladder cancer patients undergoing radical cystectomy (RC) with ileal conduit. However, the effect of CKD on adverse in-hospital outcomes after ileal conduit RC is not well known. Methods Descriptive analyses, propensity score matching (PSM), and multivariable logistic and Poisson regression models were used to address National Inpatient Sample patients treated with ileal conduit RC between 2006 and 2019. CKD severity was stratified as mild (stage II) vs. moderate (stage III) vs. severe (stage IV/V). Results Of 13,359 patients treated with RC with ileal conduit, 1973 (14.8%) had CKD. Of those, 956 (48.5%), 802 (40.6%), and 215 (10.9%) were classified as mild, moderate, or severe CKD, respectively. CKD rate increased from 4.1 to 21.9% (2006–2019, EAPC: +8.9%, p < 0.001). CKD RC patients exhibited higher rates of adverse in-hospital outcomes in 11 of 15 categories. The absolute differences were largest for overall complications (+ 13.2%), prolonged length of stay (+ 7.0%), blood transfusions (+ 6.0%, all p < 0.001). After detailed multivariable adjustment, CKD was an independent predictor of 11 of 15 adverse in-hospital outcomes’ categories. The detrimental effect of CKD was most pronounced for dialysis (OR 7.09), overall complications (OR 1.84), and neurological complications (OR 1.61, all p < 0.001). Finally, a dose-response effect according to CKD severity on adverse in-hospital outcomes was observed in eight of 15 categories. Conclusions CKD RC patients invariably exhibited higher rates of adverse in-hospital outcomes after RC with ileal conduit. In consequence this patient group should receive particularly strong consideration for preoperative optimization.

Purpose Lower urinary tract symptoms (LUTS) associated with bladder outlet obstruction (BOO) are prevalent among men, notwithstanding being self-underreported. We aimed to assess the predictors for BOO during first visit. Methods Data from 1045 analyzed men older than 40 years attending a single urological institution from 2010 to 2021. The men diagnosed with BOO, prostate cancer or any treatment for BOO were excluded. The patients completed the International Prostatic Symptoms Score (IPSS) and were investigated with prostate-specific antigen (PSA), trans-rectal ultrasound to measure prostate volume (PV) and free uroflowmetry. Logistic regression analysis tested the association between parameters and BOO. The area under the curve compared the diagnostic accuracy of predictors. The Youden-index analysis defined the cut-off predicting LUTS. Results Of 1045 patients, the median (IQR) age was 62 (51–69) years. A total of 773 (74%) had moderate LUTS. Both PV (OR: 1.16; 95%CI 1.04–1.3; p = 0.005) and IPSS (OR: 1.06; 95%CI 1.03–1.08; p < 0.001) were associated with BOO after adjusting for age. They showed a predictive accuracy with an AUC of 0.69 (0.60–0.77) and 0.63 (0.59–0.67) for PV and IPSS, respectively. A PV of 43 mL emerged as the cut-off point to define the risk of BOO. Therefore, a 60-year man with a PV ≥ 43 mL showed an 84% (70–90) risk of BOO as compared with 59% (50–68) for a same age man with lower PV. Conclusion Men older than 40 years should be screened for LUTS associated with BOO since they are highly prevalent. User-friendly parameters such as PV and IPSS could guide further investigation of BOO.

Mergers of binary neutron stars emit signals in both the gravitational-wave (GW) and electromagnetic spectra. Famously, the 2017 multi-messenger observation of GW170817 (refs. 1,2) led to scientific discoveries across cosmology³, nuclear physics4, 5–6 and gravity⁷. Central to these results were the sky localization and distance obtained from the GW data, which, in the case of GW170817, helped to identify the associated electromagnetic transient, AT 2017gfo (ref. ⁸), 11 h after the GW signal. Fast analysis of GW data is critical for directing time-sensitive electromagnetic observations. However, owing to challenges arising from the length and complexity of signals, it is often necessary to make approximations that sacrifice accuracy. Here we present a machine-learning framework that performs complete binary neutron star inference in just 1 s without making any such approximations. Our approach enhances multi-messenger observations by providing: (1) accurate localization even before the merger; (2) improved localization precision by around 30% compared to approximate low-latency methods; and (3) detailed information on luminosity distance, inclination and masses, which can be used to prioritize expensive telescope time. Additionally, the flexibility and reduced cost of our method open new opportunities for equation-of-state studies. Finally, we demonstrate that our method scales to long signals, up to an hour in length, thus serving as a blueprint for data analysis for next-generation ground- and space-based detectors.

Background Understanding population structure within species provides information on connections among different populations and how they evolve over time. This knowledge is important for studies ranging from evolutionary biology to large-scale variant-trait association studies. Current approaches to determining population structure include model-based approaches, statistical approaches, and distance-based ancestry inference approaches. Methods In this work, we identify population structure from DNA sequence data using an alignment-free approach. We use the frequencies of short DNA substrings from across the genome (k-mers) with principal component analysis (PCA). K-mer frequencies can be viewed as a summary statistic of a genome and have the advantage of being easily derived from a genome by counting the number of times a k-mer occurred in a sequence. In contrast, most population structure work employing PCA uses multi-locus genotype data (SNPs, microsatellites, or haplotypes). No genetic assumptions must be met to generate k-mers, whereas current population structure approaches often depend on several genetic assumptions and can require careful selection of ancestry informative markers to identify populations. We compare our k-mer based approach to population structure estimated using SNPs with both empirical and simulated data. Results In this work, we show that PCA is able to determine population structure just from the frequency of k-mers found in the genome. The application of PCA and a clustering algorithm to k-mer profiles of genomes provides an easy approach to detecting the number and composition of populations (clusters) present in the dataset. Using simulations, we show that results are at least comparable to population structure estimates using SNPs. When using human genomes from populations identified by the 1000 Genomes Project, the results are better than population structure estimates using SNPs from the same samples, and comparable to those found by a model-based approach using genetic markers from larger numbers of samples. Conclusions This study shows that PCA, together with the clustering algorithm, is able to detect population structure from k-mer frequencies and can separate samples of admixed and non-admixed origin. Using k-mer frequencies to determine population structure has the potential to avoid some challenges of existing methods and may even improve on estimates from small samples.

Previously, African American race/ethnicity predisposed to higher rate of adverse in-hospital outcomes after radical cystectomy (RC). We tested whether this association applies to contemporary RC patients. Patients were identified within the National Inpatient Sample (NIS 2000–2019). Multivariable logistic and Poisson regression models were fitted. Of 19,370 RC patients, 1,089 (5.6%) were African American, while 18,281 (94.4%) were Caucasian. Relative to Caucasians, African Americans were younger (median age 66 vs. 70 years; p < 0.001), more frequently female (33.8 vs. 18.5%; p < 0.001) and more frequently in the lowest income quartile (46.8 vs. 18.6%; p < 0.001). Relative to Caucasians, after RC, African Americans exhibited higher rates of postoperative complications (61.3 vs. 58.3%; multivariable odds ratio [MOR] 1.2; p = 0.009). Specifically, African Americans exhibited higher rates of blood transfusions (30.2 vs. 24.1%; MOR 1.3; p < 0.001), gastrointestinal (26.7 vs. 24.1%; MOR 1.2; p = 0.003), and infectious (6.2 vs. 4.2%; MOR 1.5; p = 0.001) complications, as well as deep vein thrombosis (3.1 vs. 1.7%; MOR 1.9; p < 0.001). Additionally, after RC, African Americans exhibited higher rates of critical care therapy use (CCT; 13.9 vs. 12.2%; MOR 1.3; p = 0.002) and in-hospital mortality (2.8 vs. 1.7%; MOR 1.8; p = 0.002). Finally, African Americans exhibited higher rates of length of stay ≥ 75th percentile (40.9 vs. 31.2%; MOR 1.6; p < 0.001). In contemporary RC patients, African American race/ethnicity predisposes to less favorable in-hospital outcomes, including higher in-hospital mortality and longer hospital stay. Unfortunately, these race/ethnicity disadvantages have not been improved upon relative to the previous report.

Aims The aim of study was to generate quantitative data on the abundance of drug‐metabolizing enzymes and transporters (DMETs) in inflamed and non‐inflamed Crohn's disease (CD) ileum and colon, for incorporation into physiologically based pharmacokinetic (PBPK) models, enabling prediction of oral drugs' pharmacokinetics (PK) perturbation in CD patients. Methods Homogenate fractions were processed from 13 inflamed (six ileum and seven colon) and seven non‐inflamed (two ileum and five colon) CD and 10 healthy (five ileum and five colon) tissues from deceased subjects by calcium chelation elution, and protein abundances determined by liquid chromatography–tandem mass spectrometry (LC–MS/MS)‐based proteomics and compared with healthy values. PBPK simulation was applied to predict the potential effect of altered DMET profiles on the PK of oral drugs. Results All investigated proteins showed trends for reduced expression in inflamed and non‐inflamed CD samples relative to healthy individuals. Significant downregulation (P < 0.05) was observed for CYP3A4, AOX1, NAT1 and several SULTs in inflamed ileum as well as UGT1A10, NAT1, BCRP and several SULTs in inflamed and non‐inflamed colon. Inter‐individual variability was generally higher in CD, with exceptions, for most targets (up to 146%CV in inflamed ileum and up to 169% in histologically normal colon tissues). Integration of abundance data into a verified PBPK model of CD showed a considerable (≥2‐fold; CD predicted relative to healthy predicted) change in systemic drug exposure for 10 drugs examined. Conclusions CD inflammation significantly suppresses the expression of intestinal DMETs, which, together with changes in other system parameters, can alter the fate of drugs taken orally in these patients. Virtual patients within a PBPK framework, informed by the measured DMET ranges in the intestine, may serve as a guide for dose adjustment in the absence of dedicated clinical studies.

Background and Objectives Elderspeak is communication that sounds like babytalk and is a common form of communication often used in dementia care. The purpose of this research was to develop and validate the Iowa Coding for Elderspeak (ICodE) scheme, as a means of standardizing the coding of elderspeak across studies. Research Design and Methods The ICodE categorizes communicative interactions by nursing staff into five states that encompass who is speaking, who is being addressed, and in what manner. ICodE also captures different attributes of elderspeak, such as vocabulary usage and prosodic modifications. Intra-rater and inter-rater reliability were evaluated for each communication state. Convergent validity was evaluated by comparing the use of elderspeak to ratings of emotional tone by 31 community-dwelling older adults and to the occurrence of rejection of care during 88 observations of hospital dementia care. Results Inter-rater and intra-rater reliability were excellent for each communication state with confidence intervals ranging from moderate to excellent. Convergent validity with the emotional tone ratings was established for 10 of the 11 elderspeak attributes, indicating that older adults perceive these attributes as more patronizing and/or less respectful than neutral speech. Convergent validity with rejection of care was established for eight of the attributes, suggesting that these aspects of elderspeak were also negatively perceived by individuals living with dementia. Discussion and Implications The ICodE is an evidence-based coding scheme that can reliably and validly document the use of elderspeak by nursing staff and that will facilitate uniformity in elderspeak research going forward.

Bots (i.e., automated software programs that perform a variety of tasks) and fraudulent responders pose a growing threat to psychological research. Bots and fraudulent responders affect data integrity, and cost researchers and organizations resources (e.g., time and money). Bot and fraud detection tactics (BFDTs) are methods used to identify and eliminate bots and fraudulent responders while simultaneously retaining real and verified human participants. This study describes our team’s experience with bots and fraudulent responders during an online experience sampling study with trauma-exposed sexual minority cisgender women and transgender and/or nonbinary people. We employed and tested an array of BFDTs, as well as the timing and duration of BFDT deployment (i.e., how long we used them to identify bots and fraudulent responders) to create a preliminary protocol for eliminating bots. The baseline survey received 24,053 responses. After applying our BFDT protocols, we eliminated 99.75% of respondents that were likely bots or fraudulent responders. Executing BFDTs generated a final sample size of 59. Analyses showed that some BFDTs seemed to be more effective than others, some BFDTs afforded higher confidence than others, protocols that were changed periodically (i.e., the order of BFDTs) were more effective than protocols that did not change, an bots and fraudulent responders introduced significant bias in the data collected. This study highlights the need for further research to validate the preliminary strategies developed and tested in this pilot, proof-of-concept study aimed at mitigating the impact of bots and fraudulent responders in online psychological research.

Objective: Philip Morris International’s Smoke-Free Future (SFF) campaign pledged to replace conventional cigarettes with smoke-free alternatives, promoting smokers’ health and combating smoking-related misinformation. Method: We interviewed 25 college students to assess their perceived credibility of SFF messages and interest in smoke-free products. Results: Nearly half couldn’t identify a tobacco company as the message source, speculating it came from public health entities. Many overlooked profit motives, instead seeing SFF as genuinely supportive of smoking cessation and being aligned with public health. About a third found the message credible, citing factors like lay narrators and language/images signifying science. Most expressed interest in smoke-free products, driven by curiosity and misunderstanding of their health implications. Conclusion: Our study underscores concern that recent tobacco corporate communications may influence young people’s interest in these products, even without explicit promotion, necessitating better education about industry tactics to disguise their identity with health and science initiatives, while undermining tobacco control efforts.