Capuchins can employ several strategies to deal with environmental challenges, such as using stone tools to access encapsulated resources. Nut-cracking is customary in several capuchin populations and can be affected by ecological and cultural factors; however, data on success and efficiency are only known for two wild populations. In this work, using camera traps, we assessed palm nut-cracking success and efficiency in two newly studied wild bearded capuchin populations (Sapajus libidinosus) and compared them with other sites. We tested the hypothesis that the overall success and efficiency of nut-cracking would be similar between sites when processing similar resources, finding partial support for it. Although using hammerstones of different sizes, capuchins had a similar success frequency. However, efficiency (number of strikes to crack a nut) was different, with one population being more efficient. We also tested whether success and efficiency varied between sexes in adults. We predict adult males would be more successful and efficient when cracking hard nuts. We found no differences between the sexes in one site but found sex differences in the other, although also for the low-resistant nut, which was unexpected. Our data add to the knowledge of capuchin nut-cracking behaviour flexibility, variance and potential cultural traits.

The frontal aslant tract (FAT) is a crucial neural pathway of language and speech, but little is known about its connectivity and segmentation differences across populations. In this study, we investigate the probabilistic coverage of the FAT in a large sample of 1065 young adults. Our primary goal was to reveal individual variability and lateralization of FAT and its structure-function correlations in language processing. The study utilized diffusion MRI data from 1065 subjects obtained from the Human Connectome Project. Automated tractography using DSI Studio software was employed to map white matter bundles, and the results were examined to study the population variation of the FAT. Additionally, anatomical dissections were performed to validate the fiber tracking results. The tract-to-region connectome, based on Human Connectome Project-MMP parcellations, was utilized to provide population probability of the tract-to-region connections. Our results showed that the left anterior FAT exhibited the most substantial individual differences, particularly in the superior and middle frontal gyrus, with greater variability in the superior than the inferior region. Furthermore, we found left lateralization in FAT, with a greater difference in coverage in the inferior and posterior portions. Additionally, our analysis revealed a significant positive correlation between the left FAT inferior coverage area and the performance on the oral reading recognition (p = .016) and picture vocabulary (p = .0026) tests. In comparison, fractional anisotropy of the right FAT exhibited marginal significance in its correlation (p = .056) with Picture Vocabulary Test. Our findings, combined with the connectivity patterns of the FAT, allowed us to segment its structure into anterior and posterior segments. We found significant variability in FAT coverage among individuals, with left lateralization observed in both macroscopic shape measures and microscopic diffusion metrics. Our findings also suggested a potential link between the size of the left FAT\'s inferior coverage area and language function tests. These results enhance our understanding of the FAT\'s role in brain connectivity and its potential implications for language and executive functions.

This study aimed to investigate differences in pediatric healthcare utilization in Israel over 10 years by examining differences across populations defined by living environment and ethnicity. Data was obtained from the Clalit Health Care data warehouse, covering over 250,000 children residing in Haifa and Western Galilee districts. The population groups were categorized based on ethnicity (Jewish vs Arab) and residential settings (urban vs rural). Healthcare utilization was consistently higher among Jewish than Arab children, irrespective of the specific dimension analyzed. Additionally, urban-dwelling children exhibited higher usage rates than those residing in rural areas in all investigated dimensions. However, Jewish children showed significantly about 18% lower hospitalization rates than Arab children across all years (P < 0.001). No significant differences in hospitalizations were observed between urban and rural children (RR 0.999, CI (0.987-1.011)). Notably, the study revealed reduced antibiotic consumption and hospitalizations over the years for all populations. Additionally, we found that Arab children and those living in rural areas had reduced access to healthcare, as evidenced by 10-40% fewer physician visits, laboratory tests, and imaging (P < 0.001).    Conclusion: This study highlights the substantial population-based disparities in healthcare utilization among children in Israel despite the equalizing effect of the national health insurance law. Rural and low socioeconomic populations seem to have reduced healthcare access, showing decreased healthcare utilization. Consequently, it is imperative to address these disparities and implement targeted interventions to enhance healthcare access for Arab children and rural communities. The decline in antibiotic usage and hospitalizations suggests positive trends in pediatric health care, necessitating ongoing efforts to ensure equitable access and quality of care for all populations. What is Known: • Healthcare systems worldwide vary in coverage and accessibility, including Israel, which stands out for its diverse population. • Existing research primarily focuses on healthcare utilization among adults, leaving a need for comprehensive data on children\'s healthcare patterns globally. What is New: • Investigating over 250,000 children, this study reveals higher healthcare utilization among Jewish and urban children across all dimensions. • Despite Israel\'s national health insurance law, the study underscores the significant population-based disparities in healthcare utilization.

During the COVID-19 pandemic, the bidirectional relationship between policy and data reliability has been a challenge for researchers of the local municipal health services. Policy decisions on population specific test locations and selective registration of negative test results led to population differences in data quality. This hampered the calculation of reliable population specific infection rates needed to develop proper data driven public health policy.

Objective: Age and years of education are strong predictors of cognitive performance in several versions of the Edinburgh Cognitive and Behavioral ALS Screen (ECAS) and cutoffs for the Swedish and Polish versions are not established yet. Here we evaluated the performance of healthy subjects on the national versions of the Swedish and Polish ECAS and compared cognitive performance on three European translations of the ECAS. Methods: The ECAS performances of healthy subjects from Sweden (n = 111), Poland (n = 124) and Germany (n = 86) were compared. Based on the test results on the national versions of ECAS, age- and education-adjusted cutoffs were compared for the German, Swedish and Polish versions, respectively. Results: Age and years of education correlated with performance in the ECAS. Swedish subjects under the age of 60 years and Swedish subjects with low education level scored significantly higher in memory than the respective German and Polish subgroups. German and Polish subjects over 60 years of age performed significantly better in language than the respective Swedish subgroup. The Polish cohort in total had lower executive scores compared to the Swedish cohort, and lower than the German subjects in the higher education subgroup. Conclusions: The results highlight the importance of establishing age- and education-adjusted ECAS cutoffs not only in general, but also for seemingly similar populations of different origins. The results should be taken into account when comparing cognition data across patient populations including in drug trials where an ECAS test result is being used as an inclusion criterium or outcome measure.

Forensic DNA Phenotyping (FDP) can reveal the appearance of an unknown individual by predicting the ancestry, phenotype (i.e., hair, eye, skin color), and age from DNA obtained at the crime scene. The HIrisPlex system has been developed to simultaneously predict eye and hair color. However, the prediction accuracy of the system needs to be assessed for the tested population before implementing FDP in casework. In this study, we evaluated the performance of the HIrisPlex system on 149 individuals from the Turkish population. We applied the single-based extension (SNaPshot chemistry) method and used the HIrisPlex online tool to test the prediction of the eye and hair colors. The accuracy of the HIrisPlex system was assessed through the calculation of the area under the receiver characteristic operating curves (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). The results showed that the proposed method successfully predicted the eye and hair color, especially for blue (100%) and brown (95.60%) eye and black (95.23) and brown (98.94) hair colors. As observed in previous studies, the system failed to predict intermediate eye color, representing 25% in our cohort. The majority of incorrect predictions were observed for blond hair color (40.7%). Previous HIrisPlex studies have also noted difficulties with these phenotypes. Our study shows that the HIrisPlex system can be applied to forensic casework in Turkey with careful interpretation of the data, particularly intermediate eye color and blond hair color.

Validation of risk prediction models in independent data provides a more rigorous assessment of model performance than internal assessment, for example, done by cross-validation in the data used for model development. However, several differences between the populations that gave rise to the training and the validation data can lead to seemingly poor performance of a risk model. In this paper we formalize the notions of \"similarity\" or \"relatedness\" of the training and validation data, and define reproducibility and transportability. We address the impact of different distributions of model predictors and differences in verifying the disease status or outcome on measures of calibration, accuracy and discrimination of a model. When individual level information from both the training and validation data sets is available, we propose and study weighted versions of the validation metrics that adjust for differences in the risk factor distributions and in outcome verification between the training and validation data to provide a more comprehensive assessment of model performance. We provide conditions on the risk model and the populations that gave rise to the training and validation data that ensure a model\'s reproducibility or transportability, and show how to check these conditions using weighted and unweighted performance measures. We illustrate the method by developing and validating a model that predicts the risk of developing prostate cancer using data from two large prostate cancer screening trials.

Rapidly mutating Y chromosomal short tandem repeat markers (RM Y-STRs) -characterized by at least one mutation per 100 generations- are suitable for differentiating both related and unrelated males. The recently introduced multiplex method RMplex allows for the efficient analysis of 30 Y-STRs with increased mutation rates, including all 26 currently known RM Y-STRs. While currently available RM Y-STR mutation rates were established mostly from European individuals, here we applied RMplex to DNA samples of 178 genetically confirmed father-son pairs from East Asia. For several Y-STRs, we found significantly higher mutation rates in Japanese compared to previous estimates. The consequent father-son differentiation rate based on RMplex was significantly higher (52%) in Japanese than previously reported for Europeans (42%), and much higher than with Yfiler Plus in both sample sets (14% and 13%, respectively). Further analysis suggests that the higher mutation and relative differentiation rates in Japanese can in part be explained by on average longer Y-STR alleles relative to Europeans. Moreover, we show that the most striking difference, which was found in DYS712, could be linked to a Y-SNP haplogroup (O1b2-P49) that is common in Japanese and rare in other populations. We encourage the forensic Y-STR community to generate more RMplex data from more population samples of sufficiently large sample size in combination with Y-SNP data to further investigate population effects on mutation and relative differentiation rates. Until more RMplex data from more populations become available, caution shall be placed when applying RM Y-STR mutation rate estimates established in one population, such as Europeans, to forensic casework involving male suspects of paternal origin from other populations, such as non-Europeans.

During the COVID-19 pandemic, the bidirectional relationship between policy and data reliability has been a challenge for researchers of the local municipal health services. Policy decisions on population specific test locations and selective registration of negative test results led to population differences in data quality. This hampered the calculation of reliable population specific infection rates needed to develop proper data driven public health policy.

The 24-h rest and activity behaviors (i.e., physical activity, sedentary behaviors and sleep) are fundamental human behaviors essential to health and well-being. Functional principal component analysis (fPCA) is a flexible approach for characterizing rest-activity rhythms and does not rely on a priori assumptions about the activity shape. The objective of our study is to apply fPCA to a nationally representative sample of American adults to characterize variations in the 24-h rest-activity pattern, determine how the pattern differs according to demographic, socioeconomic and work characteristics, and examine its associations with general health status.
The current analysis used data from adults 25 or older in the National Health and Nutrition Examination Survey (NHANES, 2011-2014). Using 7-day 24-h actigraphy recordings, we applied fPCA to derive profiles for overall, weekday and weekend rest-activity patterns. We examined the association between each rest-activity profile in relation to age, gender, race/ethnicity, education, income and working status using multiple linear regression. We also used multiple logistic regression to determine the relationship between each rest-activity profile and the likelihood of reporting poor or fair health.
We identified four distinct profiles (i.e., high amplitude, early rise, prolonged activity window, biphasic pattern) that together accounted for 86.8% of total variation in the study sample. We identified numerous associations between each rest-activity profile and multiple sociodemographic characteristics. We also found evidence suggesting the associations differed between weekdays and weekends. Finally, we reported that the rest-activity profiles were associated with self-rated health.
Our study provided evidence suggesting that rest-activity patterns in human populations are shaped by multiple demographic, socioeconomic and work factors, and are correlated with health status.