bluuebunny/crossref_metadata_2025 huggingface dataset:
RDCorpus: labeled medical records for the timely detection of rare diseases
Authors: Rolando Matias , Raggio Victor , Naya Hugo , Spangenberg Lucia , Cagnina Leticia
Published: August 2024

Rare diseases (RD) are a group of pathologies that individually affect less than 1 in 2000 people but collectively impact around 7% of the world's population. Most of them affect children, are chronic and progressive, and have no specific treatment. RD patients face diagnostic challenges, with an average diagnosis time of 5 years, multiple specialist visits, and invasive procedures. This ‘diagnostic odyssey’ can be detrimental to their health. Machine learning (ML) has the potential to improve healthcare by providing more personalized and accurate patient management, diagnoses, and in some cases, treatments. Leveraging the MIMIC-III database and additional medical notes from different sources such as in-house data, PubMed and chatGPT, we propose a labeled dataset for early RD detection in hospital settings. Applying various supervised ML methods, including logistic regression, decision trees, support vector machine (SVM), deep learning methods (LSTM and CNN), and Transformers (BERT), we validated the use of the proposed resource, achieving 92.7% F-measure and a 96% AUC using SVM. These findings highlight the potential of ML in redirecting RD patients towards more accurate diagnostic pathways and presents a corpus that can be used for future development and refinements.
Minimally Invasive Management of Cervical Spondylodiscitis. A Multicenter Experience
Authors: SEGBEDJI Felix Kouma Kossi , MALLEREAU Charles-Henry , DANNHOFF Guillaume , DEMBOUR Victoria , CEBULA Helene , CERASE Alfonso , MUZII Vitaliano Francesco , ZALAFFI Alessandro , CARANGELO Biagio Roberto , SPATOLA Giorgio , ZAED Ismael , CARDIA Andrea , ROMANO Antonio , CASTELLANI Paola , TARANTINO Francesca , GANAU Mario , TODESCHI Julien , CHIBBARO Salvatore
Published: August 2024

Background
The urgent etiological diagnosis represents the main management objective of cervical spondylodiscitis (CSD) to start as soon as possible antibiotic treatment to prevent neurological deterioration. The present study aimed to evaluate a multicenter experience implementing a minimally invasive surgical approach (MISA) to manage such pathology vs the most complex and aggressive surgical strategies currently used.
Patients and methods Retrospective multicenter study on a prospectively built database of a 70 patients’ series in 5 European tertiary neurosurgical centers. Seventy consecutive patients harboring primary CSD undergoing MISA were included. Formal diagnosis was made in all patients on clinical presentation, imaging findings, and laboratory investigation and confirmed by histopathological and bacteriological analysis of perioperative specimens.
Results
Forty-one patients were men and 29 were women with a mean age of 47.67 years. Severe neck pain was the most common symptom in 45/70 patients. Fifty-one patients presented a single cervical level of spondylodiscitis, 14/70 double level, and 5/70 triple level respectively. The most commonly identified microorganism was Staphylococcus aureus in 49/70 patients. Each patient received a mean of 3 months' antibiotics treatment. With a mean follow-up period of 48 months, all patients showed a complete recovery without neurological deficits. Neither spine instability nor kyphotic deformation was recorded and bony fusion was confirmed radiologically in all patients. No infection recurrence occurred.
Conclusions
MISA treatment of CSD is a valuable management option to identify the microorganism involved and/or to decompress the spinal cord ensuring as much as possible mechanical stability resulting in excellent patient outcomes.
Epidemiology, clinical characteristics and life-threatening risk profile of WPW in children: 30 years population follow up at a single centre in South Wales
Authors: Uzun Orhan , Duman Derya , Sahin Gulhan Tunca , Donmez Yasemin Nuran , Haji Afzal Abubakker Bapputty , Walsh Mark , Corcia Cecilia Gonzalez , O’Callaghan Peter , Leong Fong , Stuart Graham
Published: August 2024

Backgrounds and Aims :
This study aims to assess the epidemiology, clinical presentation, management, and outcomes of pediatric Wolff-Parkinson-White (WPW) syndrome, as well as the incidence of life-threatening events (LTE) in South Wales.
Methods
retrospective review of patients (< 17 years old) diagnosed with WPW syndrome between 1986 and 2019 in South Wales.
Results
The study population consisted of 160 patients, of whom 86 (54%) were male. The prevalence of WPW syndrome was 0.028%. Thirty percent of cases were diagnosed during infancy, while 63% presented after aged 5. Incidental diagnosis occurred in 47 (29,3%) asymptomatic patients. Spontaneous resolution of delta wave was observed in 19 patients (11.9%). Thirteen children (8.1%, 11 males) presented with an LTE, resulting in an estimated LTE risk of 3.8 per 1000 person-years during childhood in South Wales. Acute management was required in 36% (55/154) of patients, with seven experiencing preexcited atrial fibrillation (4.5%). Among children with preexcited atrial fibrillation and rapid ventricular conduction, only three out of seven children experienced aborted sudden cardiac death (1.9%). No deaths directly attributable to isolated WPW and related arrhythmia were recorded.
Conclusions
Asymptomatic WPW in children demonstrated a high propensity for life-threatening events in South Wales, prompting a policy shift towards earlier referral for electrophysiology study (EPS) prior to adolescence. These findings underscores the need for more rigorous risk stratification and closer follow-up of all WPW patients, as asymptomatic cases do not guarantee safety.
Clinical and Imaging Risk Factors for Early Neurological Deterioration and Long-Term Neurological Disability in Patients with Single Subcortical Small Infarction
Authors: feng Xiao , Taiwakuli Meiherinisa , Du junyong , Zhu wenhao , Xu Shabei
Published: August 2024

Introduction: This study aims to evaluate the clinical and imaging risk factors for early neurological deterioration (END) and long-term neurological disability in patients with Single subcortical small infarction (SSSI).
Methods: We retrospectively included SSSI patients hospitalized. Outcomes were defined as modified Rankin Scale (mRS) score >2 at follow-up and the occurrence of END during hospitalization. Multivariate logistic regression identified independent predictors of END and long-term outcomes. Stepwise regression analysis was used to develop a predictive model for poor outcomes. The predictive performance of risk factors and the model was assessed using receiver operating characteristic (ROC) curves.
Results: A total of 289 SSSI patients were included. During hospitalization, 18 patients (6.2%) experienced END, and 29 patients (10%) had neurological disability at a median follow-up of 21.4 (16.7–25.2) months. Multivariate analysis showed the National Institutes of Health Stroke Scale (NIHSS) score (OR 1.438, 95% CI 1.182–1.749, P < 0.001), Total cholesterol (TC) (OR 1.545, 95% CI 1.014–2.355, P = 0.043), neutrophil to High density lipoprotein cholesterol ratio (NHR) (OR 1.371, 95% CI 1.074–1.75, P = 0.011), and neutrophil count (OR 1.333, 95% CI 1.025–1.733, P = 0.032) were independently associated with END. Age (OR 1.083, 95% CI 1.008–1.163, P = 0.029), lesion diameter (OR 1.121, 95% CI 1.001–1.255, P = 0.048), NIHSS (OR 1.685, 95% CI 1.33–2.134, P < 0.001), symptomatic intracranial artery stenosis (OR 6.655, 95% CI 1.618–27.38, P = 0.009), lacune grading (OR 3.644, 95% CI 1.468–9.048, P = 0.005), and The degree of brain atrophy (OR 2.232, 95% CI 1.199–4.154, P = 0.011) were independently associated with neurological disability. The predictive model for END (included NIHSS score and NHR level) and long-term neurological disability (included age, NIHSS score, symptomatic intracranial artery stenosis, number of lacunes, and brain atrophy) showed areas under the ROC curve of 0.836 and 0.926, respectively.
Conclusion: High NIHSS, TC, NHR, and neutrophil count are independent risk factors for END. Age, NIHSS, lesion size, symptomatic intracranial artery stenosis, the degree of lacunes and brain atrophy are predictors of neurological disability in SSSI patients.
Stability of cytokine and immunoglobulin concentrations in the general population: prepandemic basal concentrations and intraindividual changes until the COVID-19 pandemic
Authors: Gasull Magda , Pumarega José , Aguilar Ruth , Campi Laura , Prieto-Merino David , Villar-García Judit , Rius Cristina , Bolúmar Francisco , Trasande Leonardo , Dobaño Carlota , Moncunill Gemma , Porta Miquel
Published: August 2024

Background: Evidence on physiological, basal concentrations of cytokines in the general population across sociodemographic groups, and their stability, is scant. No studies have analyzed intraindividual changes in such concentrations from before the COVID-19 pandemic until its outbreak.
Objectives: To investigate: a) prepandemic concentrations of cytokines and immunoglobulins to viral exposures in a general, non-institutionalized population, and their associated sociodemographic variables; b) the intraindividual change in such concentrations between a prepandemic period (2016-17) and the initial pandemic period (2020-21); and c) whether such change was similar in participants who in 2020-21 were SARS-CoV-2 seronegative and seropositive, and between participants who did and did not develop COVID-19.
Methods: We conducted a prospective cohort study in 240 individuals from the general population of Barcelona, Spain. Thirty cytokines and 31 immunoglobulins were measured in paired serum samples collected in 2016-17 and 2020-21 in the same individuals.
Results: The median value of the relative intraindividual change in cytokine concentrations between 2016 and 2020 was <15% for 29 of the 30 cytokines. A substantial number of participants had an intraindividual increase or decrease ≥15% in some cytokines. No major differences in intraindividual changes of cytokine and immunoglobulin levels between 2016 and 2020 were observed between participants participants who did and did not develop COVID-19.
Conclusions: Intraindividual changes in cytokines and immunoglobulins during the four years were moderate, and were not affected by SARS-CoV-2 infection or COVID-19 disease. The findings are novel, and potentially useful in clinical practice and research.
Laboratory based efficacy of Citrus limon mediated Ag-Pd bimetallic nanoparticles against mosquito larvae
Authors: Minal Savy Panamkuttiyiel , Prakash Soam
Published: August 2024

The current study presents data on the eco-friendly biological synthesis of silver and palladium bimetallic nanoparticles (Ag-Pd BNPs) using a 10% aqueous leaf extract of plant Citrus limon. The synthesized Ag-Pd BNPs were characterized using various techniques, including UV-Visible (UV-Vis) and Fourier transform infrared (FT-IR) spectroscopy, Transmission Electron Microscopy (TEM), Scanning Electron Microscopy and Energy Dispersive X-ray Spectroscopy (SEM-EDX), Dynamic light scattering (DLS), and X-ray diffraction (XRD). Subsequently, the larvicidal nanotoxicity of the characterized Ag-Pd BNPs was assessed against I, II, III, and IV instar larvae of Anopheles stephensi and Aedes aegypti mosquitoes, and its impact on the predation efficiency of non-target nymphs of dragonfly and damselfly was evaluated. The results of UV-Vis displayed a maximum absorption at 300 nm ± 40 nm for the leaf extract, while for the synthesized Ag-Pd BNPs no surface plasmon resonance band was observed. FTIR analysis revealed the involvement of surface functional groups from the leaf extract in nanoparticle synthesis. TEM analysis determined a mean particle size of 21 ± 7.22 d nm, while DLS analysis confirmed a Z-average of 1956 d nm. SEM-EDX verified the presence and purity of the Ag-Pd BNPs in the sample, and XRD analysis identified the leaf extract-mediated synthesis with distinct peaks obtained for Ag and Pd. The nanotoxicity bioassay revealed significant larval mortality and the LC50 values were obtained at the time intervals of 24 h, 48 h, and 72 h of exposure for I to IV instars of both mosquito species. The predation efficiency test against the non-target nymphs of dragonfly and damselfly revealed time-dependent predation dynamics, resulting in high predation rates over specific time intervals. In conclusion, this study offers significant scientific insights into the characterization and ecotoxicological properties of Ag-Pd BNPs, demonstrating their potential under vector control while considering their impact on non-target organisms.
Relationship between sleep quality and fear of progression among partients with chronic kidney disease: A cross-sectional survey
Authors: Ye Qi-hui , Sun Tong-xin , Wang Jia-le , Li Xun-liang , Wang De-guang
Published: August 2024

Objectives
The study aims to elucidate the direct correlation between sleep quality and fear of progression (FOP), two significant psychosocial issues that individuals with chronic kidney disease (CKD) encounter.
Methods
A cross-sectional study was conducted among patients with CKD who were recruited from the Second Affiliated Hospital of Anhui Medical University.Clinical and demographic data were collected using a general information questionnaire. The Fear of Progression Questionnaire-Short Form and Pittsburgh Sleep Quality Index were used to measure the level of FOP and evaluate sleep quality over one month. The correlation between sleep quality and FOP was investigated utilizing Pearson correlation and hierarchical regression analysis.
Results
This study comprised 195 people in total, of which 116 (59.5%) suffered from poor sleep quality.Sleep quality and FOP were positively correlated, with higher FOP scores leading to poorer sleep quality. Gender, family financial burden, disease stage, and total FOP score could predict sleep quality. Collectively, these factors combined explained 24.7% of the variation in sleep quality, with FOP independently contributing 6.3% to the explained variance.
Conclusions
Patients with CKD often experience poor sleep quality, an issue that healthcare professionals should take seriously. Interventions focused on reducing FOP could offer a promising approach to enhancing sleep quality.
Trend and Descriptive Epidemiology of Lassa fever in Ebonyi State, 2018 - 2022
Authors: Ezenwa-Ahanene Adanna , Salawu A T , Adebowale Ayo S
Published: August 2024

Background Lassa fever’s emergence in Nigeria has been a public health concern over the years. Ebonyi state is located in the South-Eastern zone of Nigeria where a high burden of Lassa fever has been reported. Assessment of trend and risk factors for Lassa fever are yet to be fully explored in the state. We investigated the trend and descriptive epidemiology of Lassa Fever in Ebonyi state, South-East, Nigeria.
Method This study was analysis of data extracted from Ebonyi State Integrated Disease Surveillance and Response (IDSR) system over a five-year period (2018-2022). A total of 1578 reported Lassa fever cases was captured in the IDSR out of which 300 were laboratory-confirmed. The trend and seasonality of Lassa fever were assessed using an additive time series model to ascertain the quarter of the year when the disease is expected to be at its peak. Lassa fever cases were predicted using the identified fitted model among the linear, quadratic, cubic and exponential models (α0.05).
Results The mean age of the individuals with the reported cases of Lassa fever was 29.4 ± 17.8 years. Lassa fever showed a seasonal trend across the years. The quadratic model provided the best fit for predicting Lassa fever cumulative cases (R2 = 98.4%, P-value <0.05). Projected cases of Lassa fever for the year 2023 were 123 in the 1st quarter, 23 in the 2nd quarter, 42 in the 3rd quarter, and 17 in the 4th quarter. The seasonality index was +70.76, -28.42, -9.09, and -33.2 in the 1st, 2nd, 3rd, and 4th quarters respectively. The reported cases of Lassa fever followed a declining trend (slope= -0.1363). Farmers were 70% less likely to die from Lassa fever compared to those not working (aOR:0.3, CI: 0.17-0.83).
Conclusion: Although the reported Lassa fever cases followed a declining trend in Ebonyi state, there was a seasonality in the trend over the study period. Adequate preparedness to mitigate the spread of the disease during the peak period of the disease is recommended.
Effect of low pressure on flame propagation of hydrogen-kerosene- air mixture
Authors: Liu Jian , Wang Yafen , Hou Lingyun , Pei Xinyan
Published: August 2024

Hydrogen may play an important role in gas turbine engines for achieving carbon neutrality and performing high-altitude missions. Hydrogen influence on the flame speed of aviation kerosene at low pressures was investigated using a constant-volume bomb. The laminar flame speed of aviation kerosene at atmospheric pressure exhibited a linear relationship with increasing hydrogen mass fraction, with a more pronounced promoting effect under fuel-rich conditions. Hydrogen promotion effects on normalized kerosene laminar flame speed are weaker at low pressures than those at atmospheric pressures. The addition of hydrogen and low pressure suppresses flame instability of aviation kerosene especially under fuel-rich conditions, thereby reducing the promoting effect of turbulence on fuel-rich flame propagation. A scaling law that accounted for the influence of flame stability was successfully constructed to characterize the turbulent flame speed of hydrogen-rich aviation kerosene under different conditions.
Nonlinear Tolerancing: Variation Simulation for Multi-Station Assembly with Compliant Parts
Authors: Lupuleac Sergey , Shinder Julia , Petukhova Margarita , Zaitseva Nadezhda , Churilova Maria
Published: August 2024

Effective modeling of multi-stage assembly processes in aircraft manufacturing that takes into account nonlinear effects is essential due to intricate component interactions and high precision requirements at every assembly stage. This paper introduces an approach for performing nonlinear variation modeling of the multi-station assembly process, specifically addressing the contact interactions between compliant parts. The presented approach accounts for a range of variation sources, including geometrical variations of parts represented as two-dimensional random fields and deviations of part fixations on assembly jigs modeled as random variable distributions.
Specialized numerical methods for solving emerging nonlinear problems make it possible to perform calculations at a speed comparable to linear variation simulations. A case study examining the assembly of the upper skin panel to the wing and subsequent assembly of the wing with fuselage illustrates the application of the proposed approach. This study evaluates the impact of different sources of variation on assembly quality at each station, the propagation of these variations throughout the assembly process, and the analysis of the resultant deviations in the final assemblies. This research demonstrates the capabilities of nonlinear variation simulations in accurate prediction of the assembly variations, thereby enhancing quality control in aerospace manufacturing.
Nanopore adaptive sampling to identify the NLR gene family in melon (Cucumis melo L.)
Authors: Belinchon-Moreno Javier , Berard Aurelie , Canaguier Aurelie , Chovelon Véronique , Cruaud Corinne , Engelen Stéfan , Feriche-Linares Rafael , Le-Clainche Isabelle , Marande William , Rittener-Ruff Vincent , Lagnel Jacques , Hinsinger Damien , Boissot Nathalie , Rampant Patricia Faivre
Published: August 2024

Background Nanopore adaptive sampling (NAS) offers a promising approach for assessing genetic diversity in targeted genomic regions. Here we designed and validated an experiment to enrich a set of resistance genes in several melon cultivars as a proof of concept.Results We showed that, using a single reference, each of the 15 regions we identified in two newly assembled melon genomes (ssp. melo) was also successfully and accurately reconstructed in a third ssp. agrestis cultivar. We obtained fourfold enrichment regardless of the tested samples, but with some variations according to the enriched regions. The accuracy of our assembly was further confirmed by PCR in the agrestis cultivar. We discussed parameters that could influence the enrichment and accuracy of NAS generated assemblies.Conclusions Overall, we demonstrated that NAS is a simple and efficient approach for exploring complex genomic regions. This approach facilitates resistance gene characterization in a large number of individuals, as required when breeding new cultivars suitable for the agroecological transition.
Effects of puffing on the quality of dried pork tendons: Structure and flavor
Authors: Miao Xiaoqing , Huang Jiabo , Li Ya , Dong Xiuping , Sun Na , Jiang Pengfei
Published: August 2024

To improve the portability of dried pork tendons for consumption, we investigated the effects of different puffing temperatures (190 °C - 250 °C) and times (1-7 min) on the quality and flavor of pork tendons. As the temperature and time increased, the expansion ratio of pork tendons exhibited a gradual increase, while the bulk density exhibited a gradual decrease. Moreover, the microstructure of the puffed pork tendons exhibited a uniform porous structure at 230 °C and 250 °C for 6 min. However, further puffing treatment destroyed the spatial structure, causing the void to collapse. Amino acid analysis of puffed pork tendons revealed the presence of 17 free amino acids. In addition, HS-GC-IMS identified 68 volatile organic compounds (VOCs), with the combination of GC-MS analysis indicating that the flavor of pork tendons puffed at 230 °C for 6 min was superior. Our findings provide new insights into the processing of dried pork tendons.
Analysis of factors influencing age and cognitive function in older adults: a cross-sectional study
Authors: Li Xiaomin , He Guixiang
Published: August 2024

Background Cognitive impairment in the elderly continues to be a serious problem, and existing studies have mostly focused on the elderly as a whole and used multiple linear regression to study the influencing factors, without subdividing them by age, which is a limitation that does not allow us to propose targeted strategies. Therefore, the decision tree and multiple linear regression model were jointly applied in this study to study the cognitive function status and influencing factors of elderly people in different age groups, with other age groups as the research subjects.
Methods Data from the China Health and Aging Tracking Survey (CHARLS) 2020 were used to select older adults aged 60-89 as the study subjects, and SPSS 26.0 was used to analyze the data. The factors affecting cognitive function in older adults of different ages were analyzed using the one-way analysis, linear regression model, and decision tree model.
Results High level of education, good memory status, and living in towns and cities were protective factors for cognitive function in older adults of all ages. Depression and unsocialization were risk factors for cognitive function in 60-79-year-olds, but not in 80-89-year-olds.Women as a protective factor for cognitive function in 60-69-year-olds, but not in 70-89-year-olds. Disability was a risk factor for cognitive function in 70-79-year-olds, not a factor influencing cognitive function in 60-69 and 80-89-year-olds. Low life satisfaction and lack of pension insurance were risk factors for cognitive function in 80- to 89-year-olds, but not in 60- to 79-year-olds.
Conclusion The cognitive condition of older adults deteriorates with age, and there are commonalities and differences in the effects of various factors on the cognitive function of older adults in different age groups. In practice, individualized intervention models should be developed for different age groups to reduce the incidence of cognitive dysfunction in various age groups.
Flecainide enhances blood-brain barrier function: Novel mode of action of sodium channel blocking in experimental autoimmune encephalomyelitis (EAE)
Authors: Sindi Mustafa , Dobelmann Vera , Ricci Rebekka , Klees Diana , Hecker Christina , Müntefering Thomas , Issberner Andrea , Gruchot Joel , Hartung Hans-Peter , Ruck Tobias , Kurz Thomas , Stark Holger , Küry Patrick , Engelhardt Britta , Lyck Ruth , Meuth Sven G. , Dietrich Michael , Albrecht Philipp
Published: August 2024

Introduction
Multiple Sclerosis (MS), an autoimmune disorder, is characterized by severe neuroinflammation, leading to demyelination and neuronal damage in the CNS, resulting in significant clinical impairment. MS progression involves complex pathological processes like immune cell invasion and cytokine-mediated recruitment to the CNS. Experimental autoimmune encephalomyelitis (EAE), a model for MS, has been crucial for identifying effective treatments. Recent studies have shown that sodium channel (Nav) blockers and monoamine oxidase- (MAO) B inhibitors can alleviate symptoms of EAE and optic neuritis (ON), but their mode of action remains partially unclear.
Methods
To evaluate the effects and understand the action mechanism of Nav blockers and MAO-B inhibitors (rasagiline ,safinamide, flecainide and phenytoin) in neurological conditions, various techniques were used, including optical coherence tomography (OCT), optomotor response measurement (OMR), flow cytometry, histological evaluations, Evans blue assay, blood-brain barrier (BBB) permeability assay and gene expression analyses.
Results
The study found that the primary therapeutic effect comes from inhibiting the Nav 1.5 sodium channel, not MAO-B inhibition. Flecainide, a Nav 1.5 channel blocker, significantly reduced EAE disability scores, mitigated neurodegeneration, preserved visual function, and restricted immune cell migration into the CNS. Importantly, blocking the Nav 1.5 channel had an effect on the BBB, limiting lymphocyte entry into the CNS.
Discussion/Conclusion
This research highlights sodium channel blockers' potential in treating neuroinflammatory diseases like MS. The findings demonstrate reduced disease progression and neuroprotection, suggesting a novel therapeutic approach. Crucially, it reveals for the first time that Nav 1.5 channel blockade leads to neuroprotection primarily by affecting the BBB, a key factor in controlling immune cell migration, thus addressing a critical aspect of MS pathology.
Using a K-mer Based Approach with Machine Learning Classifiers for Enhancer Identification and Classification
Authors: Pillai Cyril , Benton Mary Lauren
Published: August 2024

Background
Enhancers are genetic elements that modulate the level of gene expression in cells; because they are essential for cellular function, enhancer dysfunction is associated with many complex diseases including many types of cancers. Furthermore, current research highlights the challenge of enhancer identification due to variability in enhancer definitions and identification approaches. Developing a machine learning pipeline to distinguish enhancers from other DNA elements would greatly aid the ability to study enhancers and their role in disease. In this project, we developed a random forest machine learning model to distinguish between human liver enhancer sequences with low versus high levels of support across eight different enhancer identification methods.
Results
Enhancers were classified as “shared” if they had support from multiple methods and “unique” otherwise; the threshold for the number of methods that made an enhancer region “shared” or “unique” was adjusted as an independent variable. We also extracted a set of random sequences from the human genome to evaluate potential differences between shared/unique enhancer regions and genomic background. Our machine learning model used the frequency of k length sequence (k-mer) patterns as features to classify the shared versus unique enhancer regions. We hypothesized that the distribution of k-mer frequencies would correlate with transcription factor binding sites on the enhancer and distinguish them from other types of DNA sequence.
Conclusions
The final shared vs random models perform with 93.8–99.9% accuracy, the final unique vs random models perform with 93.4–99.8% accuracy, but the final shared model performs with only 56.8–61.4% accuracy. These results indicate that the k-mer frequency distributions for shared and unique enhancers are not significantly different although shared/unique sequences differ from the genomic background.
Genetic associations with human longevity are enriched for oncogenic genes
Authors: Park Junyoung , Peña-Tauber Andrés , Talozzi Lia , Greicius Michael , Guen Yann Le
Published: August 2024

Human lifespan is shaped by both genetic and environmental exposures and their interaction. To enable precision health, it is essential to understand how genetic variants contribute to earlier death or prolonged survival. In this study, we tested the association of common genetic variants and the burden of rare non-synonymous variants in a survival analysis, using age-at-death (N = 35,551, median [min, max] = 72.4 [40.9, 85.2]), and last-known-age (N = 358,282, median [min, max] = 71.9 [52.6, 88.7]), in European ancestry participants of the UK Biobank. The associations we identified seemed predominantly driven by cancer, likely due to the age range of the cohort. Common variant analysis highlighted three longevity-associated loci: APOE, ZSCAN23, and MUC5B. We identified six genes whose burden of loss-of-function variants is significantly associated with reduced lifespan: TET2, ATM, BRCA2, CKMT1B, BRCA1 and ASXL1. Additionally, in eight genes, the burden of pathogenic missense variants was associated with reduced lifespan: DNMT3A, SF3B1, CHL1, TET2, PTEN, SOX21, TP53 and SRSF2. Most of these genes have previously been linked to oncogenic-related pathways and some are linked to and are known to harbor somatic variants that predispose to clonal hematopoiesis. A direction-agnostic (SKAT-O) approach additionally identified significant associations with C1orf52, TERT, IDH2, and RLIM, highlighting a link between telomerase function and longevity as well as identifying additional oncogenic genes.
Our results emphasize the importance of understanding genetic factors driving the most prevalent causes of mortality at a population level, highlighting the potential of early genetic testing to identify germline and somatic variants increasing one’s susceptibility to cancer and/or early death.
Associations of demographic, health, and risk-taking behaviors with tattooing in a population-based cross-sectional study of ~18,000 US adults
Authors: McCarty Rachel D , Trabert Britton , Millar Morgan M , Kriebel David , Grieshober Laurie , Barnard Mollie E , Collin Lindsay J , Lawson-Michod Katherine A , Gibson Brody , Gilreath Jeffrey A , Shami Paul J , Doherty Jennifer A
Published: August 2024

Background
Little is known about current characteristics of individuals with tattoos. We quantified the prevalence of tattooing and associations of demographic, health, and risk-behavior factors with tattooing.
Methods
We computed adjusted prevalence ratios (PR) of tattooing in a population-based analysis of > 18,000 Utah adults from the 2020–2021 Behavioral Risk Factor Surveillance System survey.
Results
The prevalence of tattooing was 26% among women and 22% among men, with the highest prevalence among women ages 25–29 (45%). Tattoo prevalence was higher among younger individuals, individuals with a lower education level, and those without religious affiliation. Tattoo prevalence was higher among indviduals with current tobacco (women: PR = 2.89 [95% confidence interval (CI): 2.60, 3.20]; men: 3.39 [2.98, 3.86]), e-cigarette (women: 2.44 [2.21, 2.69]; men: 2.64 [2.37, 2.94]), and heavy alcohol use (women: 2.16 [1.93, 2.43]; men: 1.89 [1.63, 2.19]). Tattoo prevalence was lower among individuals receiving a flu (women: 0.84 [0.76, 0.92]; men: 0.75 [0.67, 0.84]) or COVID-19 vaccine (women: 0.65 [0.54, 0.79]; men: 0.75 [0.61, 0.92]).
Conclusions
Several risk-taking behaviors were associated with tattooing. Tattoo studios/conventions may present opportunities for partnership with tobacco cessation, alcohol reduction, and vaccination public health initiatives.
The Role of Green Networks for Environmental Innovation in European Regions
Authors: Fabrizi Andrea , Fiorelli Cristiana , Meliciani Valentina
Published: August 2024

This paper investigates the role of green research networks in green innovation capabilities (proxied by green patents) in European regions. Our hypothesis is based on the idea that cross-border collaboration facilitates the diffusion of knowledge, thereby favouring the green innovation of the regions belonging to the network. We exploit information contained in the European Framework Programmes by looking at the role of intra and extra-regional collaborations and at the diversity of institutional partners. We find that both intra and extra regional collaborations matter for green innovation, although external knowledge appears to be more relevant. We also find a positive effect of both firms and universities and a non-linear effect of network heterogeneity. We discuss the implications of the results for green innovation policies.
Atomic short-range order in SiGeSn alloys
Authors: LIU Jifeng , Liu Shang , Chen Shunda , Jin Xiaochen , Bae Jin-Hee , Bikmukhametov Ilias , Jaeger David , Concepcion Omar , Covian Alejandra , Wang Xiaoxin , Cline Cory , Akey Austin , Vogl Lilian , Zhao Haochen , Zeng Yuping , Minor Andrew , Yu Shui-Qing , Buca Dan , Li Tianshu
Published: August 2024

Neighborhood at atomic scale is important for the properties of advanced alloys. The preference or avoidance between neighboring atomic species is known as chemical short-range order (SRO). While SRO in metallic medium/high entropy alloys has garnered substantial attention recently, understanding SRO in semiconductor alloys remains underdeveloped. Motivated by theoretically predicted SRO and its dramatic impact on band structure, here we perform statistical analyses of atom probe tomography data to quantify SRO in SixGe1-x-ySny alloys (x<12 at.%, y<16 at.%). Leveraging a side-by-side experiment-theory comparison at the same spatial scale enabled by machine-learning neuroevolution potentials of first-principles accuracy, we reveal, for the first time, a notable SRO favoring Si-Si 1st nearest neighbors even at dilute Si and Sn compositions. The SRO can be tuned by varying precursors, offering a new degree of freedom for band engineering beyond composition and strain, and enabling new phase-change materials based on SRO transitions for Si electronics/photonics.
A secreted Botrytis cinerea stage-specific effector promotes virulence by targeting the plant ROS-generating machinery
Authors: Sharon Amir , Bi kai , Wang Ziyao , Nie Xiaofei , Liang Yong , Zhu Wenjun
Published: August 2024

Necrotrophic plant pathogens are assumed to exploit the plant hypersensitive response (HR), but the molecular mechanism underlying this exploitation remains largely unclear. Here, we report the discovery and characterization of BcCELP1, an early infection-specific, cell death-inducing effector required for plant colonization by the phytopathogenic fungus Botrytis cinerea. We demonstrate that BcCELP1 is necessary during the initial stage of plant colonization, and that it interacts with the host scaffold protein NbRACK1, promoting NbRACK1’s interaction with the reduced nicotinamide adenine dinucleotide phosphate oxidase NbRBOHB, and thereby contributing to excessive ROS production. We further show that BcCELP1 is produced and specifically leveraged during plant invasion to facilitate the formation of necrotic tissue patches, which serve as foci for subsequent fungal spread. Misregulation of bccelp1 disrupts pathogen development, resulting in reduced disease symptoms. Collectively, these findings reveal an unsuspected sophisticated strategy employed by a necrotrophic pathogen, whereby a fungal effector activates the host ROS-generating machinery in a stage-specific manner to promote effective invasion.
The far-reaching distributional effects of global warming:
Evidence from half a century of climate and inequality data
Authors: Castells-Quintana David , McDermott Thomas
Published: August 2024

Climate change is already impacting several development outcomes, including economic growth, human health and mortality, agricultural productivity and even conflict. Moreover, the impact of climate change is expected to be unevenly distributed across locations and population groups. In particular, the worst effects of climate change are expected to be felt in low-income countries. Similarly, within countries, the most vulnerable to these effects are typically low-income regions and households. While the literature to date has provided evidence of the between-countries inequality-increasing effect of global warming, evidence for inequality within countries remains limited. In this paper, we empirically explore the connection between climate change and long-run distributional dynamics within countries. To do so, we first build a global panel dataset combining gridded data on climate variables with gridded population data, and country-level data on a range of inequality measures and development outcomes. We use these data to test climate effects on several dimensions of inequality, including the (interpersonal) distribution of income, using traditional Gini coefficients, indices of concentration of both income and wealth, proxies of inequality in the spatial distribution of economic activity within countries, and measures of inequality in life expectancy. Our evidence shows a clear positive and statistically significant relationship between higher temperatures and increases in different measures and dimensions of inequality. The role of higher temperatures is robust to a wide range of controls, different specifications and estimation techniques. We complement our country-level analysis with an exploratory analysis at the subnational level for selected countries (US, Russia and Spain).
CORRELATION OF ORAL HEALTH LITERACY AND GINGIVAL STATUS AMONG ELDERLY IN YOGYAKARTA: A CROSS-SECTIONAL STUDY
Authors: Rodestawati Budi , Vega Christia Aye Waindy , Nur'aini Bekti , Widita Elastria
Published: August 2024

Background: The aging population is growing faster in several countries around the world, including Indonesia. Oral health literacy as a personal-behavioral component has been studied and is regarded an important determinant of health as well as a causative factor for oral health disorders, which are subsequently thought to have an impact on oral health-related quality of life.
Objective: The purpose of this study was to investigate the association between oral health literacy and oral health status among elderly in Yogyakarta.
Method: This cross-sectional study included 193 respondents aged ?60 years in Yogyakarta City. The data collection was done using interviewer-administered questionnaires (socio-demography data, health history, health behavior, and oral health literacy) and clinical examination. The Modified Gingival Index is used to determine gingival health status during a clinical examination of the oral cavity.
Result: The results of this study indicated that there was a significant relationship between oral health literacy and Modified Gingival Index (p=0.01). Understanding participants' oral health literacy levels was critical for developing successful health education materials and intervention programs that enhance oral health.
Conclusion: Elderly people with higher oral health literacy have better oral health outcomes.
HYPERTILING — a high performance Python library for the generation and visualization of hyperbolic lattices
Authors: Schrauth Manuel , Thurn Yanick , Goth Florian , Portela Jefferson , Herdt Dietmar , Dusel Felix
Published: August 2024

HYPERTILING is a high-performance Python library for the generation and visualization of regular hyperbolic lattices embedded in the Poincaré disk model. Using highly optimized, efficient algorithms, hyperbolic tilings with millions of vertices can be created in a matter of minutes on a single workstation computer. Facilities including computation of adjacent vertices, dynamic lattice manipulation, refinements, as well as powerful plotting and animation capabilities are provided to support advanced uses of hyperbolic graphs. In this manuscript, we present a comprehensive exploration of the package, encompassing its mathematical foundations, usage examples, applications, and a detailed description of its implementation.
Codebase release 1.3 for HYPERTILING
Authors: Schrauth Manuel , Thurn Yanick , Goth Florian , Portela Jefferson , Herdt Dietmar , Dusel Felix
Published: August 2024

HYPERTILING is a high-performance Python library for the generation and visualization of regular hyperbolic lattices embedded in the Poincaré disk model. Using highly optimized, efficient algorithms, hyperbolic tilings with millions of vertices can be created in a matter of minutes on a single workstation computer. Facilities including computation of adjacent vertices, dynamic lattice manipulation, refinements, as well as powerful plotting and animation capabilities are provided to support advanced uses of hyperbolic graphs. In this manuscript, we present a comprehensive exploration of the package, encompassing its mathematical foundations, usage examples, applications, and a detailed description of its implementation.
Prediksi Jumlah Calon Siswa Baru Menggunakan Metode Double Exponential Smoothing Brown (Studi Kasus: SMK Ma’arif NU 1 Purwokerto Tahun Pelajaran 2024/2025)
Authors: Nurohmah Siti , Kartika Dwiani Listya , Muhassanah Nuraini , Yuniarti Dwi Ariani Finda
Published: August 2024

The number of new students registering at SMK Ma'arif NU 1 Purwokerto from 2010 to 2023 has increased and decreased. This fluctuating pattern is a problem faced in determining strategies to attract new students to register. Large fluctuations in student numbers can cause instability in school revenues, which affects all operational aspects and will impact the school's reputation in the eyes of the community and prospective students. In this regard, it is necessary to take action, namely forecasting the number of new students registering for the 2024/2025 academic year. The aim of this research is to determine the prediction of the number of prospective new students at SMK Ma'arif NU 1 Purwokerto using theDouble Exponential Smoothing Brown in the 2024/2025 academic year. From the research results, it was obtained that the number of new students in the 2024/2025 academic year was based on overall data on students who registered with the best α parameter α = 0.2 with a value ofMAD = 6,02, MSE = 68,37, andMAP= 20.23%, namely 42 students. The forecast for the number of new students registering at SMK Ma'arif NU 1 Purwokerto based on overall data from the school has increased from the previous year. Value resultsMAPshows that the forecasting that has been carried out falls into the category of adequate forecasting method capabilities so that it can be used to predict the number of new students enrolling at SMK Ma'arif NU 1 Purwoketo and the predicted value for the following year can be known.Keywords: predictions, forecasting, new students, Double Exponential Smoothing Brown
Self-attention transformer model for pan evaporation prediction: a case study in Australia
Authors: Abed Mustafa , Imteaz Monzur Alam , Huang Yuk Feng , Ahmed Ali Najah
Published: August 2024

In drought-prone regions like Australia, accurately assessing evaporation rates is essential for effectively managing and maximising the use of precious water resources and reservoirs. Current estimates show that evaporation reduces Australia's open water lake capacity by about 40% annually. With climate change, this water loss is expected to become an even greater concern. This study investigates a transformer-based neural network (TNN) to estimate monthly evaporation in three Australian locations. The models were trained and tested using monthly weather data spanning from 2009 to 2022. Input parameters were chosen based on Pearson's correlation coefficient values to identify the most impactful combinations. The developed TNN model was compared with two widely used empirical methods, namely Thornthwaite and Stephens and Stewart. The TNN model's impressive accuracy in evaporation prediction, attributed to its unique self-attention mechanism, suggests its promising potential for future use in evaporation forecasting. Additionally, the study revealed an intriguing result: Despite using the same input datasets, the TNN model surpassed traditional methods, achieving an average improvement of 18% in prediction accuracy. The TNN prediction model accurately predicts water loss (average R² = 0.970), supports irrigation management and agricultural planning and offers financial benefits to farming and related industries.
Impact of projected climate variability on agricultural water demand of key crops in drought-prone central India region
Authors: Vishwakarma Ankur , Choudhary Mahendra Kumar , Chauhan Mrityunjay Singh
Published: August 2024

Water scarcity predominantly affects agriculture production. It is mandatory to save future water to prevent its shortage due to variations in climate. Variation in climate is a significant factor responsible for frequent droughts over the Bundelkhand region in central India. It is necessary to obtain early warning studies in this region to manage and arrange future agricultural water. Out of best Regional Climate Models (RCMs) under the Coordinated Regional Downscaling Experiment (CORDEX) and their driving Coupled Model Intercomparison Project Phase 5 (CMIP5), General Circulation Models (GCMs) for India, the most effective model has been found based on the observed multiscale data for the region. The daily projected data (2021–2100) of best GCM, Earth System Model, ESM-2M have been used to evaluate the future water requirements for major rabi and hot weather crops grown in the region. The climate change effect is seen in the majority, especially in the upper Bundelkhand part. Most of the crops will need more water than the present condition, especially from 2071 to 2100. The findings will also help researchers and policymakers to utilize the future projected data to propose suitable water management strategies for agriculture.
Assessing the influence of land use/land cover dynamics and climate change on water resources in Upper Blue Nile, Ethiopia
Authors: Tikuye Birhan Getachew , Ray Ram L. , Gebeyehu Kindie , Teshome Menberu
Published: August 2024

This study evaluates the impact of climate and land use changes on Lake Tana Basin's hydrology, using datasets on land use, weather patterns, topography, soil characteristics, and discharge. Future climate data were obtained from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase Five (CMIP5) and generated using the Weather Generator (LARS-WG) tool from the Long Ashton Research Station with five distinct GCMs. Land use changes were projected using the Markov chain model based on cellular automata (CA). The Soil and Water Assessment Tool (SWAT) model was used to assess changes in hydrological elements between reference and future periods, with calibration and validation ensured by the Integrated Parameter Estimation and Uncertainty Analysis Tool (IPEAT). Projections indicate a 4.9 °C increase in ensemble mean annual temperature and a 16% rise in precipitation by the end of the 21st century under Representative Concentration Pathway (RCP) 8.5. Additionally, average annual hydrological components, including water yield, soil water, percolation, lateral flow, runoff, and actual and potential evapotranspiration, are expected to increase due to combined climate and land use changes. Therefore, it is crucial to fully understand these cumulative impacts before formulating and implementing water resource management strategies in the basin.