Monitoring is a major component of asthma management in children. Regular monitoring allows for diagnosis confirmation, treatment optimization and natural history review. Numerous factors that may affect disease activity and patient wellbeing need to be monitored: response and adherence to treatment, disease control, disease progression, comorbidities, quality of life, medication side-effects, allergen and irritant exposures, diet and more. However, the prioritization of such factors and the selection of relevant assessment tools is an unmet need. Furthermore, rapidly developing technologies promise new opportunities for closer, or even ‘real-time’, monitoring between visits. Following an approach that included needs assessment, evidence appraisal and Delphi consensus, the PeARL Think Tank, in collaboration with major international professional and patient organizations, has developed a set of 24 recommendations on pediatric asthma monitoring, to support healthcare professionals in decision-making and care pathway design.

This article examines the impact of digital health on the management of infectious diseases, focusing on lessons learned during the COVID-19 pandemic. It highlights the rapid expansion of telemedicine and virtual consultations, as well as the crucial role of contact tracing applications in containing the spread of the virus. Additionally, it analyzes the use of big data and predictive analytics to understand and predict the dynamics of the pandemic. Future challenges and opportunities in the implementation of digital health solutions, as well as the importance of public education and awareness, are discussed. In conclusion, the transformative role of digital health in the global response to infectious diseases is acknowledged, emphasizing the need to continue learning and adapting to address future health crises.

Response to Correspondence ALL-2023-01107 “Short-course subcutaneous treatment with PQ Grass strongly improves symptom and medication scores in grass allergy”P.J. de Kam1, S. Zielen2, J.A. Bernstein3, U. Berger4, M. Berger5, M. Cuevas6, D. Cypcar7, A. Fuhr-Horst8, W.A. Greisner9, M. Jandl10, S. Laßmann11, M. Worm12, J. Matz13, E. Sher14, C. Smith15, G.C. Steven16, R. Mösges17,18, M.H. Shamji19,20, L. DuBuske21, F. Borghese1, K. Oluwayi1, T. Zwingers1, M. Seybold1, O. Armfield1, M.D. Heath1, S.J. Hewings1, M.F. Kramer1, M.A. Skinner1Allergy Therapeutics plc, Worthing, United KingdomChildren and Adolescents Dept., Allergology, Pulmonology & Cystic fibrosis, Goethe University, Frankfurt, GermanyBernstein Clinical Research Center, LLC, Cincinnati, OH, United States of AmericaAerobiology and Pollen Research Unit, Dept. Oto-Rhino-Laryngology, Medical University Vienna, Vienna, Austria.Wiener Gesundheitsverbund, Hospital Hietzing, Department of Otorhinolaryngology, Vienna, AustriaClinic and Polyclinic of Otorhinolaryngology, University Clinic Carl Gustav Carus, TU Dresden, GermanyAllergy Partners of Western North Carolina, Asheville, NC, United States of AmericaENT Research- Institut für klinische Studien, Essen, GermanyBluegrass Allergy Research, Lexington, KY, United States of AmericaHamburger Institut für Therapieforschung GmbH, Hamburg, GermanyStudienzentrum Dr. Sabine Laßmann, Saalfeld, GermanyUniversitätsmedizin Berlin, Department of Dermatology and Allergy - Charite Campus Mitte, Berlin, GermanyChesapeake Clinical Research, Inc. White Marsh, MD, United States of AmericaAllergy Partners of New Jersey, Ocean, NJ, United States of AmericaCertified Research Associates, Cortland, NY, United States of AmericaAllergy Asthma & Sinus Center, S.C., Greenfield, WI, United States of AmericaIMSB (Institute of Computational Biology and Medical Statistics), University at Cologne, Cologne, GermanyClinCompetence, Cologne, GermanyImmunomodulation and Tolerance Group, Allergy and Clinical Immunology, Department of National Heart and Lung Institute, Imperial College London, London, United KingdomAsthma UK Centre in Allergic Mechanisms of Asthma, Imperial College London, London, United KingdomDivision of Allergy and Immunology, Department of Internal Medicine, George Washington University Hospital, Washington, DC, United States of America

Comment on “The risk assessment of uveitis after COVID-19 diagnosis”Patrick Wu,1 Chin-Yuan Yii,2 Su-Boon Yong3,4,5College of Medicine, Lake Erie College of Osteopathic Medicine, Bradenton, FL 34211, USADivision of Gastroenterology and Hepatology, Department of Internal Medicine, Landseed International Hospital, Taoyuan, TaiwanDepartment of Allergy and Immunology, China Medical University Children’s Hospital, Taichung, TaiwanDepartment of Medicine, College of Medicine, China Medical University, Taichung, TaiwanCenter for Allergy, Immunology, and Microbiome (A.I.M.), China Medical University Hospital, Taichung, Taiwan.Corresponding authors:Chin-Yuan Yii, MDDivision of Gastroenterology and Hepatology, Department of Internal Medicine, Landseed International Hospital, Taoyuan, TaiwanAddress: No.77, Guangtai Rd., Pingzhen Dist., Taoyuan City 32449, Taiwan Telephone: +886 3 494 1234Email: yiichinyuan@gmail.com2. Su-Boon Yong, MD PhDDepartment of Medicine, College of Medicine, China Medical University, Taichung, TaiwanAddress: No. 2, Yuh-Der Road, Taichung City 404, TaiwanTelephone: 00886-4-22052121Email: yongsuboon@gmail.comFirst author:Patrick Wu, BSCollege of Medicine, Lake Erie College of Osteopathic Medicine, Bradenton, FL 34211, USAAddress: 5000 Lakewood Ranch Blvd, Bradenton, FL 34211, USATelephone: +1(301)3375805Email: PWu36911@med.lecom.eduData availability statement: Not applicable. This letter to the editor does not require data collection.Funding statement: Not applicable. Authorship for letter to the editor did not receive any funding.Conflict of interest disclosure: The authors do not have any conflict of interests to declare.Ethics approval statement: Not applicable.Patient consent statement: Not applicable.Permission to reproduce material from other sources: Not applicable.Clinical trial registration: Not applicable.AbstractSeveral suggestions were made for the study by Hsia et al1 regarding uveitis risk following COVID-19 diagnosis. We recommend the authors align the racial composition of study groups more closely with that of U.S. demographics. In addition, we recommend the study to include possibility of false negatives from PCR testing. Lastly, we suggest the authors to consider cases of self-limiting uveitis and relapses independent of COVID-19.Keywords: uveitis risk, COVID-19, racial composition, PCR testing, self-limiting uveitis, relapsesTo the Editor,We read with great interest the study by Hsia et al1regarding the risk assessment of uveitis after COVID-diagnosis. We appreciate the authors’ attention to detail by eliminating possible confounding variables that may contribute to uveitis development. Furthermore, we were impressed by the robust study design incorporating propensity score matching, long follow-ups, and immense study size of more than 4 million patients using the TriNetX analytics platform.Nevertheless, to enhance this study, we recommend the following considerations.First, this study utilized the US research network, covering about 92 million patients to form a COVID-19 cohort and a non-COVID-19 control group, each with 2 million patients, of which 62.5% and 62.4% were white, respectively. This underrepresents the white population by 13% compared to the 75.5% white representation in the 2022 US census. Future studies should align the racial composition of study groups more closely with national demographics.Second, the authors identified COVID-19 cases based on positive PCR tests or antibody immunoassays. Yet, Binny et al’s study in New Zealand illustrates how PCR test sensitivity fluctuates across the COVID-19 infection timeline, influenced by viral load and patient age.2 The sensitivity of PCR tests peaks at 92.7% between 4 to 5 days post-infection, then drops to 88% from 5 to 14 days, while specificity remains near 100%.2 This indicates a higher likelihood of false negatives and very low false positives in PCR testing. Highlighting this significant limitation in the discussion section would be beneficial.Third, this study excluded those diagnosed with uveitis within 6 months before COVID-19 infection, potentially overlooking undiagnosed, self-limiting cases that may resurface post-infection. 10% of intermediate uveitis cases resolve on their own, and anterior uveitis, while often self-limiting, can cause severe complications.3,4 Moreover, uveitis relapses, as reported in Grunwald et al’s study, could occur independently of COVID-19, leading to misattribution of these cases to COVID-19.5 These aspects represent potential limitations of the study that warrant discussion.In conclusion, the study by Hsia et al1 is a major milestone towards incorporating uveitis assessment among COVID-19 patients in healthcare guidelines. This study has tremendous potential to save numerous patients from glaucoma, cataracts, and permanent vision loss. To improve this study, we recommend authors to adjust study groups so that white patients are adequately represented, discuss the possibility of false negatives from PCR testing, and consider cases of self-limiting uveitis and relapses independent of COVID-19.Acknowledgements: noneReferencesHsia NY, Hsu AY, Wang YH, Li JX, Chen HS, Wei JC, Lin CJ, Tsai YY. The risk assessment of uveitis after COVID-19 diagnosis: A multicenter population-based study. J Med Virol. 2023 Oct;95(10):e29188. doi: 10.1002/jmv.29188. PMID: 37881132.Binny RN, Priest P, French NP, Parry M, Lustig A, Hendy SC, Maclaren OJ, Ridings KM, Steyn N, Vattiato G, Plank MJ. Sensitivity of Reverse Transcription Polymerase Chain Reaction Tests for Severe Acute Respiratory Syndrome Coronavirus 2 Through Time. J Infect Dis. 2022 Dec 28;227(1):9-17. doi: 10.1093/infdis/jiac317. PMID: 35876500; PMCID: PMC9384503.Maggon R. INTERMEDIATE UVEITIS PARS PLANITIS. Med J Armed Forces India. 2001 Jan;57(1):84-5. doi: 10.1016/S0377-1237(01)80106-4. Epub 2011 Jul 21. PMID: 27365593; PMCID: PMC4925061.Islam N, Pavesio C. Uveitis (acute anterior). BMJ Clin Evid. 2010 Apr 8;2010:0705. PMID: 21736765; PMCID: PMC2907596.Grunwald L, Newcomb CW, Daniel E, Kaçmaz RO, Jabs DA, Levy-Clarke GA, Nussenblatt RB, Rosenbaum JT, Suhler EB, Thorne JE, Foster CS, Kempen JH; Systemic Immunosuppressive Therapy for Eye Diseases Cohort Study. Risk of relapse in primary acute anterior uveitis. Ophthalmology. 2011 Oct;118(10):1911-5. doi: 10.1016/j.ophtha.2011.02.044. Epub 2011 Jun 16. PMID: 21680024; PMCID: PMC3179829.

Stress responses are key for parasite survival and, consequently, also the evolutionary success of these organisms. Despite this importance, our understanding of the molecular pathways dealing with environmental stressors remains limited for parasitic animals. Here, we targeted the molecular pathways dealing with environmental stressors and comparatively investigated antioxidant, heat shock, osmoregulatory, and behaviour-related genes (foraging) in two parasitic flatworm lineages with contrasting species and ecological diversity, Cichlidogyrus and Kapentagyrus (Platyhelminthes: Monogenea), through whole-genome sequencing of 11 species. Using an in silico exon bait capture approach, we assembled the sequences of 48 stress-related genes and report the first foraging (for) gene orthologs in flatworms. We found duplications of heat shock- (hsp) and oxidative stress genes in Cichlidogyrus compared to Kapentagyrus. We also observed positive selection patterns in genes related to mitochondrial protein import (hsp) and behaviour (for) in species of Cichlidogyrus infecting East African cichlids—a host lineage under adaptive radiation—consistent with a potential adaptation linked to a co-radiation of parasites and hosts. Accordingly, this study potentially identifies the first molecular function linked to a flatworm radiation. Additionally, the absence of cytochrome P450, and kappa and sigma-class glutathione S-transferases in monogenean flatworms is reported, genes considered essential for metazoan life.

Abstract The risk factors and clinical prediction of cardiovascular disease comorbidities in patients with breast cancer have not been fully clarified. We conducted this retrospective case-control study. The univariable and multivariable cox regression was used to screen the risk factors of cardiovascular comorbidities in breast cancer patients, and construct a clinical prediction model, followed by prediction efficacy test and internal validation. A total of 144 cases were included and divided into two groups based on the low and high expression levels of apoB (n=46 in apoBlow and n=98 in apoBhigh group). Univariable and multivariable cox regression found that apoB, age and HER2 were the key factors responsible for the myocardial ischemia occurrence in breast cancer patients. These factors were used to constructed the clinical prediction model with combination area under curve (AUC) of 0.583, and the decision curve analysis (DCA) suggested that there would be therapeutically clinical net benefit in the model-predicted population in the predicted threshold interval between 0.35 to 0.70. Finally, Kaplan-meier plot indicated HER2(+) category and apoBhigh lead to the most occurrence of myocardial ischemia in breast cancer patients. Moreover, the 3-year disease-free survival (DFS) was not found difference between the apoBlow and apoBhigh subgroups. The clinical prediction model was constructed using three key factors, and it was indicated HER2(+) and apoBhigh lead to the most occurrence of myocardial ischemia in breast cancer patients. This study may be helpful in providing clinical evidence for the early prediction of cardiovascular comorbidities in breast cancer patients.

Integrated multimodal imaging in theranostics nanomaterials offers extensive prospects for precise and noninvasive cancer treatment. Precisely controlling the structural evolution of plasmonic nanoparticles is crucial in the development of photothermal agents. However, previous successes have been limited to static assemblies and single-component structures. Here, an activatable plasmonic theranostics system utilizing self-assembled 1D silver-coated gold nanochains (1D nanochains) is presented for precise tumor diagnosis and effective treatment. The absorbance of the adaptable core-shell chain structure can shift from visible to near-infrared (NIR) regions due to the fusion between nearby Au@Ag nanoparticles induced by elevated H 2O 2 levels in the tumor microenvironment (TME), resulting in the creation of a novel 3D aggregates with strong NIR absorption. With a high photothermal conversion efficiency of 60.2% at 808 nm, nanochains utilizing the TME-activated characteristics show remarkable qualities for photoacoustic imaging and significantly limit tumor growth in vivo. This study may pave the way for precise tumor diagnosis and treatment through customizable, optically tunable adaptive plasmonic nanostructures.

Critical urban infrastructure resilience to extreme events is an essential pillar of cities resilience to these events. The deterioration or destruction of these infrastructure could be limiting factors for cities in the implementation of resilience solutions for the economic and social development sectors. In practice, developing critical urban infrastructure resilience to extreme events plans is a complex task. It requires several information families relating to extreme events impacts on critical urban infrastructure, extreme events impact socioeconomic consequences, Critical urban infrastructure interdependence and critical urban infrastructure vulnerability factors and resilience solutions. In this article, we describe the Badolo Cires (critical infrastructure resilience) model for interdependent critical urban infrastructures resilience modeling and planning. It is a multi-critical infrastructure model to develop and implement resilience plans that integrates extreme events impacts on critical urban infrastructure, extreme events impact socioeconomic consequences, Critical urban infrastructure interdependence and critical urban infrastructure vulnerability factors and resilience solutions, gender, social inclusion and the reduction of greenhouse gas emissions. The Cires model resilience plans are subdivided into resilience subplans to achieve critical urban infrastructure partial resilience configurations. The results of this article are new scientific achievements that could strengthen cities capacities to design, implement, monitor and evaluate critical urban infrastructure resilience actions, that are guided by relevance, efficiency and impact criteria.

A document by Simar P. Singh. Click on the document to view its contents.

Attendance Management System is a software developed for daily student attendance in schools, colleges and institutes. If facilitates to access the attendance information of a particular student in a particular class. The information is sorted by the operators, which will be provided by the teacher for a particular class. This system will also help in evaluating attendance eligibility criteria of a student. The purpose of developing attendance management system is to computerized the tradition way of taking attendance. Another purpose for developing this software is to generate the report automatically at the end of the session or in the between of the session.

ABSTRACT

Wetland ecosystems are vital for both biodiversity and communities that depend on them. The Ligawasan Marsh in the Southern Philippines is one of the most threatened wetlands in the country. Apart from growing anthropogenic developments (e.g. natural gas extraction and industrialisation), marshes face warfare-driven threats that have hindered research and conservation efforts in the area for many decades. Our study is the first to investigate the patterns of physicochemical parameters, the impact of land-use changes on the environmental status of the marshland, and the contribution of surrounding towns. We found a strong negative correlation between dissolved oxygen (DO) and indicators of pollution such as biochemical oxygen demand (BOD), chemical oxygen demand (COD), and heavy metals. Interestingly, we observed elevated levels of phosphate and mercury at all sampling sites within the Ligawasan Marsh. Our landscape-level modelling showed that these elevated levels are associated with expanding croplands and urbanisation. Furthermore, we utilised our newly developed Marshland Impact Area (MARia) Index. We found that the potential impact contribution of cropland and urbanisation from surrounding towns of the Ligawasan Marsh varied significantly, suggesting the importance of implementing local policies to reduce land use change impacts. With the current limited knowledge and beyond safe pollution levels in the Ligawasan Marsh, it is crucial to implement collaborative and science-based governance to integrate conservation initiatives with the priorities of global targets, such as the Kunming-Montreal Global Biodiversity Framework, for a comprehensive and sustainable approach to Ligawasan Marsh conservation.

To understand the exhumation history of the Alpine foreland, it is important to accurately reconstruct its time-temperature evolution. This is often done employing thermokinematic models. One problem of many current approaches is that they are limited to 2-D and do not consider structural or kinematic uncertainties. In this work, we combine 3-D kinematic forward modeling with a systematic random sampling approach to automatically generate an ensemble of kinematic models in the range of assigned geometric uncertainties. Using Markov chain Monte Carlo, each randomly generated model will be assessed in regards to how well they fit the available thermochronology data. This is done to obtain an updated set of modeling parameters with reduced uncertainty. The resulting, more robust model can then be used to re-interpret the thermochronological data and find alternative drivers of cooling for certain samples.We apply this approach to a simple synthetic model to test the methodology, and then to the Eastern Alps triangle zone in the Bavarian Subalpine Molasse. Results show that it is possible to translate low-temperature thermochronology data into a likelihood function to obtain a 3-D kinematic model with updated, more probable parameters. The thermochronological data by itself, however, may not be informative enough to reduce the parameter uncertainty. The method is useful, however, to study alternative mechanisms of exhumation for the thermochronological samples that are not respected by the modeling, even when uncertainty is considered.

A document by Hongze Zhao. Click on the document to view its contents.

This study addresses the modeling of deep-seated landslides, focusing on the El Forn landslide in Andorra, using remote sensing and data-driven approaches to create risk maps. A temperature-based model is adjusted with data from an instrumented borehole to determine material properties and conditions. The calibrated model is compared to Interferometric Synthetic Aperture Radar (InSAR) data, using the data for spatial analysis and creating a correlation map through kriging. This map leads to a physics-informed risk map indicating areas of instability. An uncertainty analysis of the model highlights its limitations but underscores the utility of such maps for policy and planning in areas prone to landslides. This approach provides a novel tool for assessing landslide risks, combining in-situ and remote sensing data for effective risk management.

Solar energetic particles (SEPs) can cause severe damage to astronauts and sensitive equipment in space, and can disrupt communications on Earth. A lack of thorough understanding the eruption processes of solar activities and the subsequent acceleration and transport processes of energetic particles makes it difficult for physics-based models to forecast the occurrence of an SEP event and its intensity. Therefore, in order to provide an advance warning for astronauts to seek shelter in a timely manner, we apply neural networks to forecast the intensity of SEP events. The neural network uses a time series of past and current electron and proton flux in 5-minute intervals to predict future proton flux 30 minutes or 1 hour ahead. In addition to regular neural networks, we also use recurrent neural networks (RNNs), which are designed to handle time series data. For each model, we consider two approaches: a single model trained on all data, and the ensemble of models where the particular model is selected dynamically for each input using the predicted behavior of the input data. Overall, our results indicate that a single RNN model forecasts proton flux of each event with less error. Furthermore, the RNN model incurs less error in predicting proton flux, but a larger lag, than the forecasting matrix method proposed by Posner (2007). When advance and extended warnings are incorporated, the RNN model can improve SEP event prediction scores.

Adenoviral pVII proteins are multifunctional, highly basic, histone-like proteins that can bind to and transport the viral genome into the host cell nucleus. Despite the identification of several nuclear localization signals (NLSs) in the pVII protein of human adenovirus 5 (HAdV5), the mechanistic details of nuclear transport are largely unknown. Here we provide a full characterization of the nuclear import of precursor (Pre-) pVII protein from an ancient siadenovirus, frog siadenovirus 1 (FrAdV1) using a combination of structural, functional and biochemical approaches. Two strong NLSs (termed NLSa and NLSd) interact with importin (IMP)b and IMPa respectively, and are the main drivers of nuclear import. A weaker NLS (termed NLSb) also contributes, together with an additional signal (NLSc) which we found to be important for nucleolar targeting. Expression of Pre-pVII wild-type and NLS defective derivatives in the presence of selective inhibitors of different nuclear import pathways revealed that, unlike its human counterpart, FrAdV1 Pre-pVII nuclear import is dependent on IMPa/b and IMPb1. Clearly, AdVs evolved to maximise the nuclear import pathways for the pVII proteins, whose subcellular localization is the result of a complex process. Therefore, our results pave the way for an evolutionary comparison of the interaction of different AdVs with the host cell nuclear transport machinery.

AbstractThis essay charts a course beyond the stereotypical image of Vikings as mere raiders. It navigates the vast distances traversed by the Northmen – a broader term encompassing Scandinavians and their neighbours – during the 9th-11th centuries. While acknowledging the scholarly debate surrounding the term "Viking," the focus here is on their remarkable journeys as explorers and settlers.Despite limitations in source reliability, the essay employs a modern navigational tool to estimate the staggering distances covered by these intrepid seafarers. We encounter the pioneering Irish monks (Papar) who likely reached Iceland first, followed by Northmen settlers like Ingolfr, whose saga unfolds across hundreds of nautical miles. Eirík the Red emerges as a bold adventurer, leading the first Norse settlement in the icy embrace of Greenland.The essay then delves into the exploration of North America (Vínland), crediting Leif Eiríksson with its discovery and detailing subsequent expeditions undertaken by Thorvald and Thorfinn Karlsefni. Compelling figures like Gudrid, who traversed a distance exceeding the breadth of the entire North American continent in her lifetime, showcase the immense scale of these voyages.The essay culminates by highlighting Auðun's remarkable odyssey, exceeding a staggering 9,413 miles, which even included a polar bear as a royal gift! By unveiling the Northmen's incredible feats of navigation and exploration, this essay offers a more nuanced perspective on these historical adventurers. It concludes by calling for further investigation into the specific locations mentioned in sagas to gain a richer understanding of their journeys and daily lives, forever etching their stories onto the map of human exploration.

Background: Children treated for cancer are at risk of developing iron toxicity due to receiving red cell transfusions and myelosuppressive chemotherapy. Transfusions administered during prolonged episodes of marrow suppression may increase exposure to toxic, reactive forms of iron and thereby increase risk of extrahepatic iron accumulation and long-term organ damage. Objective: This study aimed to evaluate the severity and organ distribution of clinically significant iron overload through measurement of hepatic, cardiac, pancreatic, and pituitary iron deposition in an at-risk cohort of children and young adults treated for cancer. Methods: This retrospective study evaluated patients treated for any type of cancer who underwent an MRI due to clinical concern for evaluation of iron overload (n=103, 73 post-treatment). Data regarding cancer type and treatment, MRI and laboratory results, and treatment for iron overload were analyzed. Results: Over half (53%) of this sample had moderate or greater hepatic siderosis, 80% had pancreatic siderosis, and nearly half (45%) had pituitary siderosis and/or volume loss. Pancreatic iron was associated with both cardiac (p=0.0043) and pituitary iron (p=0.0101). Patients treated for acute myeloid leukemia or high-risk acute lymphoblastic leukemia had higher liver iron concentration (LIC) compared to other cancer types (median LIC 8.5 vs. 2.9 mg/g DLW, p=0.0011). Conclusion: Pediatric cancer patients are at risk for transfusional iron overload, with significant exposure to toxic forms of iron indicated by extrahepatic iron deposition (pancreas, heart and pituitary). Further studies should examine the effect of exposure to reactive iron on long-term outcomes and develop management recommendations.

This paper presents a new method for solving a classification problem; the  BireyselValue method assumes that the individual traits of a class help to classify an observation based on similarity measures. The method involves three stages to solve the classification problem:  the building stage, the training stage, and the prediction stage. The first two stages accomplish two key steps: firstly, five parameters are used to transform any observation of size \(n\) variables into six variables; secondly, subsets of the individual traits of each class are created. As a result, the parameters, the subsets of the individual traits, and a scaled version of the training dataset are saved as a predictive model. Ultimately, the prediction stage uses the elements in the predictive model to transform the observations that are to be classified and of size \(n\) into the size of six variables and to perform similarity measures between the observation and the individual traits of class to make the final prediction. The experimental results obtained on 6 multiclass datasets from different domains showed that the proposed method is efficient at solving classification problems. Moreover, the method can potentially be used for purposes other than solving a classification problem.Keywords: BireyselValue Method, Classification, Prediction, Dimension Reduction

Vaccination against high-risk human papillomaviruses (HPV) is currently the main mechanism for reducing cervical cancer in Spain. The objective of this study is to investigate the prevalence and distribution of HPV types within a population of 30,947 subjects with suspicion of HPV infection and/or with a genital lesion diagnostic from 2007 to 2022. Samples were analysed by polymerase chain reaction (PCR), restriction fragment length polymorphism (RFLP) analysis and/or DNA sequencing. An overall HPV prevalence of 29.2% and 49 different types were verified, of which HPV 16, 53, 31, 66, 6, 58, 61, 33, 18 and 84 were the most common. HPV 6, 16, 31 and 33 were more prevalent in younger populations, while HPV 18, 53, 58, 61, 70 and 83 presented higher frequencies in older ages. High-risk HPVs had a frequency of 47.3% in positive samples, which was higher in atypical squamous or glandular cells (73.7%), low-degree squamous intraepithelial lesions (67.0%) and high-degree squamous intraepithelial lesions (87.1%). A reduction tendency of high-risk HPVs was observed during the studied period, indicating the effectiveness of the vaccination program. By determining the HPV distribution in Spain, this study presents baseline information that can be applied for assessing prophylactic and therapeutic strategies.

Warm airmass intrusions (WAIs) from the mid-latitudes significantly impact the Arctic water budget. Here, we combine water vapor isotopes measurements from the MOSAiC expedition, with a Lagrangian-based process attribution diagnostic to track moisture origin and transformation in the central Arctic Ocean during two WAIs, under contrasting sea-ice concentrations (SIC). During winter with high SIC, two moisture states emerge: the local in-Arctic moisture, for which the isotope signal is influenced by kinetic processes in ice-cloud formation, is rapidly overprinted by low-latitude moisture advected poleward during WAI. In summer under low SIC, moisture is supplied through evaporation from land and ocean, with moisture distillation via liquid-cloud formation. The isotopic composition reflects the influence of higher humidity at the evaporation sites. Given the projected increase of frequency and duration of WAIs, our study contributes to assess process changes in the Arctic water cycle.

Precipitation changes under global warming are widely studied. However, the direct radiative effect of CO2 on precipitation changes, independent from CO2-induced SST changes, has received less attention. Mechanistic understanding of the CO2 direct effect is therefore important and necessary. Utilizing multiple global atmospheric models, we identify robust summer precipitation changes across North America in response to the direct CO2 forcing. We find that spatial distribution of CO2 forcing at land surface is primarily shaped by climatological distribution of water vapor and clouds. This, coupled with changes in convection and moisture supply resulting from CO2-induced circulation changes, largely determines North America hydroclimate changes. In central North America, increasing CO2 decreases summertime precipitation by warming the surface and inducing dry advection into the region to reduce moisture supply. Meanwhile, for the southwest and the east, CO2-induced northward shift of subtropical highs generates wet advections to mitigate the drying effect from surface warming.

Mouse models to explore the biological and organismic roleof DNA polymerase betaRobert W. Sobol1,*1Department of Pathology and Laboratory Medicine, Warren Alpert Medical School & Legorreta Cancer Center, Brown University, Providence, RI 02912Running title : DNA polymerase beta mouse modelsKeywords : DNA polymerase beta, base excision repair, mouse, mouse models, transgenic, knock-out, knock-in, CRISPR/Cas9*Address correspondence to :Robert W. Sobol, Ph.D.Department of Pathology and Laboratory MedicineWarrant Alpert Medical School & Legorreta Cancer CenterBrown University, Providence, RI 02912rwsobol@brown.edu