bluuebunny/crossref_metadata_2025 huggingface dataset:
Accuracy of Healthcare Professionals’ Estimations of Health Literacy and Numeracy of Patients Visiting Metabolic Bariatric Surgery Clinic
Authors: Allen Calisha , Ghoora Lubnaa , Murki Rajashree , Byworth Chad , Beale Sarah , Mojadady Akifah , Nagri Jameela , Parmar Chetan
Published: July 2024

Introduction

To effectively support patients through their weight loss journey, it is vital that healthcare professionals (HCPs) understand the health literacy skills of their patients and communicate in a way that meets these needs. This is the first study looking at the accuracy of HCPs’ estimations of their patients’ health literacy and numeracy attending a metabolic bariatric surgery (MBS) clinic.

Method

A cross-sectional study was completed at a tertiary-level MBS clinic in London. Patients completed a demographic questionnaire and a validated measure of health literacy and numeracy, the Medical Term Recognition Test (METER) and General Health Numeracy Test–Short Form (GHNT-6), respectively. HCPs provided estimations of their patient’s health literacy and numeracy based on each questionnaire’s scoring categories.

Results

Data was collected for 31 patients. A 80.6% of patients had functional health literacy based on METER. HCPs estimated patients’ health literacy correctly 61.1% of the time; inter-rater agreement was poor (ICC = 0.14; 95% CI =  − 0.19, 0.443; p = 0.202).

A total of 22.6% of patients scored 0 out of 6 on GHNT-6. HCPs estimated health numeracy correctly 13.9% of the time and were more likely to overestimate than underestimate health numeracy. Inter-rater agreement for health numeracy was poor (ICC =  − 0.2; 95% CI =  − 0.49, 0.14; p = 0.878).

Conclusion

There is poor agreement between HCPs’ perception of their patients’ health literacy and numeracy and their assessed ability. HCPs’ understanding of their patient’s health literacy and numeracy skills is vital in ensuring HCPs can support patients through the challenging bariatric surgical pathway, consenting process and post-operative course.

Graphical Abstract
What is needed for improved uptake and adoption of digital aftercare programs by cancer survivors: a mixed methods study applying the COM-B model
Authors: van Deursen Liza , van der Vaart Rosalie , Chavannes Niels H. , Aardoom Jiska J.
Published: July 2024

Introduction

Cancer survivors face physical, lifestyle, psychological, and psychosocial challenges. Despite the availability of aftercare services, survivors still have unmet needs. Digital aftercare programs may offer support, but their use is limited. This study aimed to examine what is needed to improve uptake and adoption of these programs. Additionally, it explored sociodemographic and clinical variables that may influence these needs.

Methods

A mixed-methods approach was used, involving qualitative interviews and a questionnaire. The research was guided by the COM-B model of behaviour, which considers capability, opportunity, and motivation crucial for behaviour. Qualitative analysis was performed using the framework method. Statistical analyses involved descriptive statistics and regression analysis.

Results

Fourteen cancer survivors were interviewed, and 213 participants completed the questionnaire. Findings indicated that most respondents had a positive or neutral attitude towards digital aftercare programs, believing these could address their cancer-related challenges. Still, only a small percentage had experience with them, and most were unaware of their existence. Many expressed a desire to be informed about them. Some were uncertain about their effectiveness. Others were concerned about a lack of reimbursement. No significant influence of the sociodemographic and clinical variables was found.

Conclusion

Cancer survivors are generally positive about digital aftercare programs but are often unaware of their availability. Raising awareness, clarifying their value, and providing support and reimbursement could enhance uptake and adoption.

Implications for Cancer Survivors

The current insights can help improve participation in digital aftercare programs, ultimately fostering health, well-being, and quality of life of cancer survivors.
Cardiac rhabdomyoma: an uncommon culprit in sudden infant death
Authors: Mecklenburg Kori L. , Mitchell Erik K. , Prahlow Joseph A.
Published: July 2024

Sudden death in infants remains a common and poorly understood cause of childhood mortality in the USA. Pediatric cardiac tumors, although rare, may underlie some cases of unexplained sudden infant death. Autopsy is a crucial diagnostic step in these cases, as both gross and microscopic examination of the heart may uncover occult cardiac tumors. Rhabdomyomas are the most common cardiac tumors in childhood and may result in arrythmia and sudden death. We present a case of sudden death in a healthy 5-month-old infant which initially appeared “SIDS-like” until thorough histological analysis revealed an underlying cardiac rhabdomyoma. The case is of particular importance in that the gross examination of the heart was considered completely normal, and the tumor only involved certain portions of the heart microscopically. Had a single random section of myocardium been the only heart section examined microscopically, the diagnosis might have been missed. This case emphasizes the importance of thorough microscopic examination in infant cases, especially in cases where the heart appears grossly normal.
Polymeric Nanostructures Revolutionizing Cervical Cancer: Diagnostics, Therapeutics, and Theranostics
Authors: Dey Bipasa , Kundu Soubarno , Sundara Babitha Kampa
Published: July 2024

Cervical cancer is the fourth most common cancer among women. Despite recent advancements in diagnostics and therapeutics, this disease is still a formidable challenge to deal with. Conventional methods for detecting human papillomavirus infection and imaging the tissues face major hurdles due to a lack of signal specificity and obscured resolution respectively. Moreover, chemotherapeutics struggle against the development of multidrug resistance and rapid clearance. With their easily tunable properties, polymeric nanostructures present a promising avenue for rapid, specific, and efficient diagnostics and therapeutics. These nanostructures also serve as theranostic agents that integrate imaging modalities with therapeutic approaches concurrently. This review highlights various types of polymeric nanostructures that serve as biosensors for the detection and quantification of cervical cancer biomarkers and act as nanocarriers for transporting fluorophores, photosensitizers, drugs, and radiosensitizers to their target site of action.

Graphical Abstract
Establishment of a nomogram to predict the overall survival of patients with collecting duct renal cell carcinoma
Authors: Jiang Weixing , Zou Zuowei , Wen Li
Published: July 2024

Background

Collecting duct carcinoma (CDC) is a rare histological type of renal cell carcinoma that lacks a prognostic prediction model. In this study, we developed a nomogram to predict the prognosis of CDC patients.

Methods

Data for patients (n = 247) diagnosed with CDC from 2004 to 2015 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database, and the patients were randomized into training (n = 165) and validation (n = 82) cohorts. Survival outcomes were evaluated by the Kaplan–Meier method. Significant variables determined by univariate and multivariate Cox regression analyses were used to construct the nomogram. C-indexes and calibration plots were applied to evaluate the performance of the nomogram.

Results

CDC patients had a median overall survival (OS) of 18.0 months (95% confidence interval: 13.7–22.3); 1-year, 3-year, and 5-year OS rates were 58.7%, 34.2%, and 29.4%, respectively. Independent prognostic factors, including age at diagnosis, tumor size, tumor grade, T stage, N stage, M stage, and surgery information, were identified by multivariate analysis. The nomogram was constructed based on significant factors in the training cohort. The C-indexes were 0.769 (training cohort) and 0.767 (validation cohort). The calibration curves for survival rates showed that the predicted and observed values were consistent.

Conclusions

This study constructed a nomogram to predict prognosis in patients with CDC. The nomogram performed well in predicting the 1-year, 3-year, and 5-year OS, which can help doctors actively monitor and follow up patients.
High-resolution estimates of water availability for the Iberian Peninsula under climate scenarios
Authors: Paredes-Beltran Bolivar , Sordo-Ward Alvaro , Martin-Carrasco Francisco , Garrote Luis
Published: July 2024

Water availability is of paramount importance for sustainable development and environmental planning, specifically in regions such as the Iberian Peninsula, renowned for diverse landscapes and varying climatic conditions. Due to climate change, understanding the potential impacts on water resources becomes essential for effective water management strategies. This research effort aims to assess future potential water availability for the Iberian Peninsula in different climate scenarios, employing cutting-edge water resource modelling techniques integrated within a geographic information system (GIS) framework. In this study, potential water availability is defined as the annual demand for water that can be satisfied at a specific point in the fluvial network with certain reliability. An ensemble of state-of-the-art climate models is utilised to project runoff for the Iberian Peninsula during the mid- and late-twenty-first century periods. These climate projections were subsequently processed using the GIS-based water resource management model, WAAPA, to derive potential water availability under a range of realistic hypotheses. The results indicate that anticipated shifts in precipitation patterns will lead to alterations in hydrological regimes across the region, significantly impacting future water availability. By using GIS-based methodologies, we can facilitate the identification of vulnerable areas susceptible to changes in water availability, offering spatially explicit information along the main rivers of the Iberian Peninsula for decision-makers and stakeholders. High-resolution spatial outputs from this research and detailed water availability estimates serve as valuable input for integrated water resource management and climate change adaptation planning. By combining advanced GIS-based hydrological modelling with climate scenarios, this research presents a robust framework for assessing water resources amidst a changing climate, applicable to other regions struggling with analogous challenges. Ultimately, our study provides vital insights for policymakers and stakeholders, empowering them to make informed decisions and devise adaptive measures to ensure sustainable use of water resources despite uncertain future climatic conditions.
Gentamicin combination treatment is associated with lower mortality in patients with invasive listeriosis: a retrospective analysis
Authors: Sutter Jan P. , Kocheise Lorenz , Kempski Jan , Christner Martin , Wichmann Dominic , Pinnschmidt Hans , Schmiedel Stefan , Lohse Ansgar W. , Huber Samuel , Brehm Thomas Theo
Published: July 2024

Purpose

Listeria monocytogenes causes severe bacterial infections with the highest mortality rate among foodborne pathogens in Europe. Combination treatment with ampicillin and gentamicin is recommended for invasive manifestations. However, evidence to support this treatment approach remains limited due to a lack of randomised controlled trials. To explore this critical issue further, we conducted this retrospective, single-center study.

Methods

We identified all patients hospitalized with invasive listeriosis at the University Medical Center Hamburg-Eppendorf between 2009 and 2020 and analyzed the effect of gentamicin combination treatment versus monotherapy on 90-day mortality.

Results

In total, 36 patients with invasive listeriosis were included, of which 21 patients received gentamicin combination treatment and 15 received monotherapy. The mean age-adjusted Charlson Comorbidity Index (aaCCI) value was lower in the gentamicin combination treatment group (5.4 vs. 7.4). Neurolisteriosis was more common in the gentamicin group (81% vs. 20%). The 90-day mortality was with significantly lower in the gentamicin combination treatment group (10%) compared to the monotherapy group (60%). Multivariable cox regression analysis, adjusted for a propensity score computed based on neurolisteriosis, aaCCI and sex, revealed a significantly reduced hazard ratio of 0.07 (95% CI: 0.01–0.53, p = 0.01) for 90-day mortality for the gentamicin combination treatment.

Conclusion

This retrospective study highlights the benefit of gentamicin combination treatment in reducing the 90-day mortality rate among patients with invasive listeriosis. The high prevalence of monotherapy in this study cohort raises concerns about the adequacy of antibiotic therapy in clinical practice.
Clinical relevance of Staphylococcus saccharolyticus detection in human samples: a retrospective cohort study
Authors: Michels Ricarda , Papan Cihan , Boutin Sébastien , Alhussein Farah , Becker Sören L. , Nurjadi Dennis , Last Katharina
Published: July 2024

Purpose

To characterize the clinical relevance of S. saccharolyticus and to identify criteria to distinguish between infection and contamination.

Methods

We retrospectively investigated clinical features of patients with S. saccharolyticus detection between June 2009 and July 2021. Based on six criteria, infection was considered likely for patients with a score from 3 to 6 points, infection was considered unlikely for patients with a score from 0 to 2 points. We performed group comparison and logistic regression to identify factors than are associated with likely infection. In addition, whole genome sequencing (WGS) of 22 isolates was performed.

Results

Of 93 patients in total, 44 were assigned to the group “infection likely” and 49 to the group “infection unlikely”. Multiple regression analysis revealed “maximum body temperature during hospital stay” to have the strongest predictive effect on likely infection (adjusted odds ratio 4.40, 95% confidence interval 2.07–9.23). WGS revealed two different clades. Compared to isolates from clade A, isolates from clade B were more frequently associated with implanted medical devices (3/10 vs. 9/12, p = 0.046) and a shorter time to positivity (TTP) (4.5 vs. 3, p = 0.016). Both clades did neither differ significantly in terms of causing a likely infection (clade A 7/10 vs. clade B 5/12, p = 0.23) nor in median length of hospital stay (28 vs. 15.5 days, p = 0.083) and length of stay at the ICU (21 vs. 3.5 days, p = 0.14).

Conclusion

These findings indicate that S. saccharolyticus can cause clinically relevant infections. Differentiation between infection and contamination remains challenging.
Pancreaticoduodenectomy in patients < 75 years versus ≥ 75 years old: a comparative study
Authors: Ergenç Muhammer , Uprak Tevfik Kıvılcım , Özocak Ayşegül Bahar , Karpuz Şakir , Coşkun Mümin , Yeğen Cumhur , Atıcı Ali Emre
Published: July 2024

Objective

This study aimed to compare the postoperative outcomes of < 75-year-old patients and ≥ 75-year-old patients who underwent pancreaticoduodenectomy (PD) for pancreatic head and periampullary region tumors.

Methods

Patients who underwent PD in our hospital between February 2019 and December 2023 were evaluated. Demographics, Eastern Cooperative Oncology Group Performance Status (ECOG-PS) scores, American Society of Anesthesiologists (ASA) scores, comorbidities, hospital stays, complications, and clinicopathological features were analyzed. Patients were divided into < 75 years (Group A) and ≥ 75 years (Group B) groups and compared.

Results

The median age of the entire cohort (n = 155) was 66 years (IQR = 16). There was a significant difference between Group A (n = 128) and Group B (n = 27) regarding the ECOG-PS and ASA scores. There was no significant difference between the groups regarding postoperative complications. The 30-day mortality rate was greater in Group B (p = 0.017). Group B had a cumulative median survival of 10 months, whereas Group A had a median survival of 28 months, with a statistically significant difference (p < 0.001). When age groups were stratified according to ECOG-PS, for ECOG-PS 2–3 Group A, survival was 15 months; for ECOG-PS 2–3 Group B, survival was eight months, and the difference was not statistically significant (p = 0.628).

Conclusions

With the increasing aging population, patient selection for PD should not be based solely on age. This study demonstrated that PD is safe for patients older than 75 years. In older patients, performance status and the optimization of comorbidities should be considered when deciding on a candidate’s suitability for surgery.
Controlled Twill Surface Structure Endowing Nanofiber Composite Membrane Excellent Electromagnetic Interference Shielding
Authors: Tao Dechang , Wen Xin , Yang Chenguang , Yan Kun , Li Zhiyao , Wang Wenwen , Wang Dong
Published: July 2024

Inspired by the Chinese Knotting weave structure, an electromagnetic interference (EMI) nanofiber composite membrane with a twill surface was prepared. Poly(vinyl alcohol-co-ethylene) (Pva-co-PE) nanofibers and twill nylon fabric were used as the matrix and filter templates, respectively. A Pva-co-PE-MXene/silver nanowire (Pva-co-PE-MXene/AgNW, PMxAg) membrane was successfully prepared using a template method. When the MXene/AgNW content was only 7.4 wt% (PM7.4Ag), the EMI shielding efficiency (SE) of the composite membrane with the oblique twill structure on the surface was 103.9 dB and the surface twill structure improved the EMI by 38.5%. This result was attributed to the pre-interference of the oblique twill structure in the direction of the incident EM wave, which enhanced the probability of the electromagnetic waves randomly colliding with the MXene nanosheets. Simultaneously, the internal reflection and ohmic and resonance losses were enhanced. The PM7.4Ag membrane with the twill structure exhibited both an outstanding tensile strength of 22.8 MPa and EMI SE/t of 3925.2 dB cm−1. Moreover, the PMxAg nanocomposite membranes demonstrated an excellent thermal management performance, hydrophobicity, non-flammability, and performance stability, which was demonstrated by an EMI SE of 97.3% in a high-temperature environment of 140 °C. The successful preparation of surface-twill composite membranes makes it difficult to achieve both a low filler content and a high EMI SE in electromagnetic shielding materials. This strategy provides a new approach for preparing thin membranes with excellent EMI properties.
Control of Online-Appointment Systems When the Booking Status Signals Quality of Service
Authors: Kaluza Isabel , Voigt Guido , Haase Knut , Dietze Antonia
Published: July 2024

We revisit a service provider’s problem to match supply and demand via an online appointment system such as a doctor in the health care sector. We identify in a survey that an extensive set of available appointments leads to significantly less demand because customers infer a lower quality of the service, as part of an observational learning process. We capture the quality inference effect in a multinomial logit framework and present a Markov decision process for solving the problem of releasing available slots of the appointment system to optimality aiming at maximizing the expected profits. We further evaluate several simple decision rules and provide management insights on which rule to apply under different generic scenarios. Different from current literature, offering all available appointments may lead to suboptimal results when accounting for the quality inference effect. The profit-maximizing strategy then is to offer a subset of the available appointments.
Research on the Optimization Method of Project-Based Learning Design for Chinese Teaching Based on Interference-Tolerant Fast Convergence Zeroing Neural Network
Authors: Bai Weihua , Geng Guoli , Fu Xuan
Published: July 2024

The system known as project-based learning, which is applied to specific courses without compromising the coverage of the necessary technical material, uses projects to drive knowledge. The plan and implementation of project-based learning in Chinese teaching as a major project, which embraces undergraduate creativity and places an emphasis on real-world, open-ended projects are discussed in this paper. In this paper, research on optimization method of project-based learning design for Chinese teaching based on optimized interference-tolerant fast convergence zeroing neural network (PBLD-ITFCZNN-BRO). It consists of three stages, import phase, main stage and evaluation stage. In the initial phase, the teacher separated the students to groups before the lecture to make sure that every group poses various traits, with some strong leadership skills and hands-on skills. The second phase of the PBL procedure helped transform what is primarily a passive learning environment (taking notes, listening, and sitting) into a more dynamic, student-centered, and interactive one. Students presented data, articulated their concepts, and then optimized their approaches to problem-solving during the evaluation step. The teachers concluded by summarizing. The performance of the proposed PBLD-ITFCZNN-BRO approach contains 15.26%, 20.42% and 21.27% greater accuracy, and 15.61%, 17.50% and 20.24% greater precision rate, compared with Investigation of Computer Network Technology on New Media Problem-Basis Learning Teaching Mode (CNT-PBLTM), PBL Model Basis application on Deep Learning in Physical Education Classroom Integrating Production with Education (PBL-DL-PEC), Interdisciplinary project-based learning: experiences with reflections from teaching electronic engineering at china (PBL-EEC) techniques, respectively.
Spatiotemporally Explicit Epidemic Model for West Nile Virus Outbreak in Germany: An Inversely Calibrated Approach
Authors: Mbaoma Oliver Chinonso , Thomas Stephanie Margarete , Beierkuhnlein Carl
Published: July 2024

Since the first autochthonous transmission of West Nile Virus was detected in Germany (WNV) in 2018, it has become endemic in several parts of the country and is continuing to spread due to the attainment of a suitable environment for vector occurrence and pathogen transmission. Increasing temperature associated with a changing climate has been identified as a potential driver of mosquito-borne disease in temperate regions. This scenario justifies the need for the development of a spatially and temporarily explicit model that describes the dynamics of WNV transmission in Germany. In this study, we developed a process-based mechanistic epidemic model driven by environmental and epidemiological data. Functional traits of mosquitoes and birds of interest were used to parameterize our compartmental model appropriately. Air temperature, precipitation, and relative humidity were the key climatic forcings used to replicate the fundamental niche responsible for supporting mosquito population and infection transmission risks in the study area. An inverse calibration method was used to optimize our parameter selection. Our model was able to generate spatially and temporally explicit basic reproductive number (R0) maps showing dynamics of the WNV occurrences across Germany, which was strongly associated with the deviation from daily means of climatic forcings, signaling the impact of a changing climate in vector-borne disease dynamics. Epidemiological data for human infections sourced from Robert Koch Institute and animal cases collected from the Animal Diseases Information System (TSIS) of the Friedrich-Loeffler-Institute were used to validate model-simulated transmission rates. From our results, it was evident that West Nile Virus is likely to spread towards the western parts of Germany with the rapid attainment of environmental suitability for vector mosquitoes and amplifying host birds, especially short-distance migratory birds. Locations with high risk of WNV outbreak (Baden-Württemberg, Bavaria, Berlin, Brandenburg, Hamburg, North Rhine-Westphalia, Rhineland-Palatinate, Saarland, Saxony-Anhalt and Saxony) were shown on R0 maps. This study presents a path for developing an early warning system for vector-borne diseases driven by climate change.
Text-to-building: experiments with AI-generated 3D geometry for building design and structure generation
Authors: Bono Giuseppe
Published: July 2024

The paper seeks to investigate novel potentials for building design and structure generation that arise at the intersection of computational design and AI-generated 3D geometries. Although the use of AI technologies is exponentially increasing inside the architectural discipline, the design of spatial building configurations using AI-generated 3D geometries is still limited in its applications and represents an ongoing field of investigation in advanced architectural research. In this regard, several questions still need to be answered: how can we design new building typologies from AI-generated 3D geometries? And how can we use these typologies to shape both the real and the virtual world?

The paper proposes a new approach to architectural design where artificial intelligence is used as the starting point for design exploration, while computational design procedures are employed to convert AI-generated 3D geometries into building elements – such as columns, beams, horizontal and vertical surfaces. The paper starts with a general overview of the current use of artificial intelligence inside the architectural discipline, and then it moves towards the explanation of specific AI generative models for 3D geometry reconstruction and representation. Subsequently, the proposed working pipeline is analysed in more detail – from the creation of 3D geometries using generative AI models to the conversion of such geometries into building elements that can be further designed and optimised using computational design tools and methods. The results shown in the paper are achieved using Shap-E as the main AI model, though the proposed pipeline can be implemented with multiple AI models. The paper ends by showing some of the generated results, finally adding some considerations to the relationship between human and artificial creativity inside the architectural discipline.

The work presented in the paper suggests that the use of computational design tools and methods combined with the tectonics of the latent space opens new opportunities for topological and typological explorations. In a time where traditional architectural typologies are moving towards stagnation due to their inability to satisfy new human needs and ways of living, exploring AI-based working pipelines related to architectural design allows the definition of new design solutions for the generation of new architectural spaces. In doing so, the serendipitous aspect of AI biases is used as an auxiliary force to inform design decisions, promoting the discovery of a new inbuilt dynamism between human and artificial creativity. In a time where AI is everywhere, understanding the measure of such dynamism represents a key aspect for the future of the architectural discipline.
Effect of Uncertainty in Water Vapor Continuum Absorption on CO2 Forcing, Longwave Feedback, and Climate Sensitivity
Authors: Roemer Florian E. , Buehler Stefan A. , Kluft Lukas , Pincus Robert
Published: July 2024

We investigate the effect of uncertainty in water vapor continuum absorption at terrestrial wavenumbers on CO2 forcing , longwave feedback λ, and climate sensitivity at surface temperatures Ts between 270 and 330 K. We calculate this uncertainty using a line‐by‐line radiative‐transfer model and a single‐column atmospheric model, assuming a moist‐adiabatic temperature lapse‐rate and 80% relative humidity in the troposphere, an isothermal stratosphere, and clear skies. Due to the lack of a comprehensive model of continuum uncertainty, we represent continuum uncertainty in two different idealized approaches: In the first, we assume that the total continuum absorption is constrained at reference conditions; in the second, we assume that the total continuum absorption is constrained for all atmospheres in our model. In both approaches, we decrease the self continuum by 10% and adjust the foreign continuum accordingly. We find that continuum uncertainty mainly affects through its effect on λ. In the first approach, continuum uncertainty mainly affects λ through a decrease in the total continuum absorption with Ts; in the second approach, continuum uncertainty affects λ through a vertical redistribution of continuum absorption. In both experiments, the effect of continuum uncertainty on is modest at Ts = 288 K (≈0.02 K) but substantial at Ts ≥ 300 K (up to 0.2 K), because at high Ts, the effects of decreasing the self continuum and increasing the foreign continuum have the same sign. These results highlight the importance of a correct partitioning between self and foreign continuum to accurately determine the temperature dependence of Earth's climate sensitivity.
Cool Roofs Could Be Most Effective at Reducing Outdoor Urban Temperatures in London (United Kingdom) Compared With Other Roof Top and Vegetation Interventions: A Mesoscale Urban Climate Modeling Study
Authors: Brousse O. , Simpson C. , Zonato A. , Martilli A. , Taylor J. , Davies M. , Heaviside C.
Published: July 2024

Comprehensive studies comparing impacts of building and street levels interventions on air temperature at metropolitan scales are still lacking despite increased urban heat‐related mortality and morbidity. We therefore model the impact of 9 interventions on air temperatures at 2 m during 2 hot days from the summer 2018 in the Greater London Authority area using the WRF BEP‐BEM climate model. We find that on average cool roofs most effectively reduce temperatures (∼−1.2°C), outperforming green roofs (∼0°C), solar panels (∼−0.5°C) and street level vegetation (∼−0.3°C). Application of air conditioning across London (United Kingdom) increases air temperatures by ∼+0.15°C. A practicable deployment of solar panels could cover its related energetic consumption. Current practicable deployments of green roofs and solar panels are ineffective at large scale reduction of temperatures. We provide a detailed decomposition of the surface energy balance to explain changes in air temperature and guide future decision‐making.
Autotrophic Respiration Is More Sensitive to Nitrogen and Phosphorus Supply Than Heterotrophic Respiration in Semiarid Grassland
Authors: Zhou Junjie , Chen Zhifei , Jian Chunxia , Luo Yang , Niu Furong , Palta Jairo A. , Xu Bingcheng
Published: July 2024

Quantification of autotrophic (Ra) and heterotrophic (Rh) components of soil respiration (Rs) could greatly improve our understanding of terrestrial carbon cycling. Here, we investigated the effect of nitrogen (N) and phosphorus (P) supply on soil respiration rates and its components, and seasonal cumulative soil CO2 efflux in a semiarid grassland. A two‐factor experiment of N (0, 50 and 100 kg N ha−1 yr−1) and P (0, 18 and 36 kg P ha−1 yr−1) supply was conducted on the Loess Plateau in 2018–2021. Our results indicated that the promoting effect of combination of N and P supply on soil respiration and its components was greater than that of N/P supply alone. N and/or P supply increased the cumulative soil CO2 efflux in both non‐growing and growing seasons, and the non‐growing season CO2 efflux accounted for ∼25% of the growing season CO2 efflux. The increase of cumulative CO2 efflux from Ra in response to N and/or P supply was significantly greater than that of Rh in 2018 and 2019, while it shifted to the opposite, that is, a greater increase in Rh than in Ra in 2020 and 2021. Our results suggest that 100 kg N ha−1 yr−1 supply alone is an optimum fertilization scheme to trade‐off grassland productivity and soil CO2 emissions. Our results highlighted that the promoting effects of N and P fertilization on different soil CO2 efflux components could be reversed in a relatively short period (4 years), and this should be considered when nutrient addition is adapted to restore degraded grasslands.
Advances in research on immunocyte iron metabolism, ferroptosis, and their regulatory roles in autoimmune and autoinflammatory diseases
Authors: Zeng Liuting , Yang Kailin , Yu Ganpeng , Hao Wensa , Zhu Xiaofei , Ge Anqi , Chen Junpeng , Sun Lingyun
Published: July 2024

Autoimmune diseases commonly affect various systems, but their etiology and pathogenesis remain unclear. Currently, increasing research has highlighted the role of ferroptosis in immune regulation, with immune cells being a crucial component of the body’s immune system. This review provides an overview and discusses the relationship between ferroptosis, programmed cell death in immune cells, and autoimmune diseases. Additionally, it summarizes the role of various key targets of ferroptosis, such as GPX4 and TFR, in immune cell immune responses. Furthermore, the release of multiple molecules, including damage-associated molecular patterns (DAMPs), following cell death by ferroptosis, is examined, as these molecules further influence the differentiation and function of immune cells, thereby affecting the occurrence and progression of autoimmune diseases. Moreover, immune cells secrete immune factors or their metabolites, which also impact the occurrence of ferroptosis in target organs and tissues involved in autoimmune diseases. Iron chelators, chloroquine and its derivatives, antioxidants, chloroquine derivatives, and calreticulin have been demonstrated to be effective in animal studies for certain autoimmune diseases, exerting anti-inflammatory and immunomodulatory effects. Finally, a brief summary and future perspectives on the research of autoimmune diseases are provided, aiming to guide disease treatment strategies.
A pH-sensitive closed-loop nanomachine to control hyperexcitability at the single neuron level
Authors: Merolla Assunta , Michetti Caterina , Moschetta Matteo , Vacca Francesca , Ciano Lorenzo , Emionite Laura , Astigiano Simonetta , Romei Alessandra , Horenkamp Simone , Berglund Ken , Gross Robert E. , Cesca Fabrizia , Colombo Elisabetta , Benfenati Fabio
Published: July 2024

Epilepsy affects 1% of the general population and 30% of patients are resistant to antiepileptic drugs. Although optogenetics is an efficient antiepileptic strategy, the difficulty of illuminating deep brain areas poses translational challenges. Thus, the search of alternative light sources is strongly needed. Here, we develop pH-sensitive inhibitory luminopsin (pHIL), a closed-loop chemo-optogenetic nanomachine composed of a luciferase-based light generator, a fluorescent sensor of intracellular pH (E2GFP), and an optogenetic actuator (halorhodopsin) for silencing neuronal activity. Stimulated by coelenterazine, pHIL experiences bioluminescence resonance energy transfer between luciferase and E2GFP which, under conditions of acidic pH, activates halorhodopsin. In primary neurons, pHIL senses the intracellular pH drop associated with hyperactivity and optogenetically aborts paroxysmal activity elicited by the administration of convulsants. The expression of pHIL in hippocampal pyramidal neurons is effective in decreasing duration and increasing latency of pilocarpine-induced tonic-clonic seizures upon in vivo coelenterazine administration, without affecting higher brain functions. The same treatment is effective in markedly decreasing seizure manifestations in a murine model of genetic epilepsy. The results indicate that pHIL represents a potentially promising closed-loop chemo-optogenetic strategy to treat drug-refractory epilepsy.
Steady motion of 80-nm-size skyrmions in a 100-nm-wide track
Authors: Song Dongsheng , Wang Weiwei , Zhang Shuisen , Liu Yizhou , Wang Ning , Zheng Fengshan , Tian Mingliang , Dunin-Borkowski Rafal E. , Zang Jiadong , Du Haifeng
Published: July 2024

The current-driven movement of magnetic skyrmions along a nanostripe is essential for the advancement and functionality of a new category of spintronic devices resembling racetracks. Despite extensive research into skyrmion dynamics, experimental verification of current-induced motion of ultra-small skyrmions within an ultrathin nanostripe is still pending. Here, we unveil the motion of individual 80 nm-size skyrmions in an FeGe track with an ultrathin width of 100 nm. The skyrmions can move steadily along the track over a broad range of current densities by using controlled pulse durations of as low as 2 ns. The potential landscape, arising from the magnetic edge twists in such a geometrically confined system, introduces skyrmion inertia and ensures efficient motion with a vanishing skyrmion Hall angle. Our results showcase the steady motion of skyrmions in an ultrathin track, offering a practical pathway for implementing skyrmion-based spintronic devices.
Structure-based out-of-distribution (OOD) materials property prediction: a benchmark study
Authors: Omee Sadman Sadeed , Fu Nihang , Dong Rongzhi , Hu Ming , Hu Jianjun
Published: July 2024

In real-world materials research, machine learning (ML) models are usually expected to predict and discover novel exceptional materials that deviate from the known materials. It is thus a pressing question to provide an objective evaluation of ML model performances in property prediction of out-of-distribution (OOD) materials that are different from the training set. Traditional performance evaluation of materials property prediction models through the random splitting of the dataset frequently results in artificially high-performance assessments due to the inherent redundancy of typical material datasets. Here we present a comprehensive benchmark study of structure-based graph neural networks (GNNs) for extrapolative OOD materials property prediction. We formulate five different categories of OOD ML problems for three benchmark datasets from the MatBench study. Our extensive experiments show that current state-of-the-art GNN algorithms significantly underperform for the OOD property prediction tasks on average compared to their baselines in the MatBench study, demonstrating a crucial generalization gap in realistic material prediction tasks. We further examine the latent physical spaces of these GNN models and identify the sources of CGCNN, ALIGNN, and DeeperGATGNN’s significantly more robust OOD performance than those of the current best models in the MatBench study (coGN and coNGN) as a case study for the perovskites dataset, and provide insights to improve their performance.
A skin-specific α-Synuclein seeding amplification assay for diagnosing Parkinson’s disease
Authors: Kuang Yaoyun , Mao Hengxu , Gan Tingting , Guo Wenyuan , Dai Wei , Huang Weimeng , Wu Zhuohua , Li Hongyan , Huang Xiaoyun , Yang Xinling , Xu Ping-Yi
Published: July 2024

The seeding amplification assay (SAA) has recently emerged as a valuable tool for detecting α-synuclein (αSyn) aggregates in various clinically accessible biospecimens. Despite its efficiency and specificity, optimal tissue-specific conditions for distinguishing Parkinson’s disease (PD) from non-PD outside the brain remain underexplored. This study systematically evaluated 150 reaction conditions to identify the one with the highest discriminatory potential between PD and non-synucleinopathy controls using skin samples, resulting in a modified SAA. The streamlined SAA achieved an overall sensitivity of 92.46% and specificity of 93.33% on biopsy skin samples from 332 PD patients and 285 controls within 24 h. Inter-laboratory reproducibility demonstrated a Cohen’s kappa value of 0.87 (95% CI 0.69–1.00), indicating nearly perfect agreement. Additionally, αSyn seeds in the skin were stable at −80 °C but were vulnerable to short-term exposure to non-ultra-low temperatures and grinding. This study thoroughly investigated procedures for sample preprocessing, seed amplification, and storage, introducing a well-structured experimental framework for PD diagnosis using skin samples.
Global evaluation of current and future threats to drylands and their vertebrate biodiversity
Authors: Lewin Amir , Murali Gopal , Rachmilevitch Shimon , Roll Uri
Published: July 2024

Drylands are often overlooked in broad conservation frameworks and development priorities and face increasing threats from human activities. Here we evaluated the formal degree of protection of global drylands, their land vertebrate biodiversity and current threats, and projected human-induced land-use changes to drylands under different future climate change and socioeconomic scenarios. Overall, drylands have lower protected-area coverage (12%) compared to non-drylands (21%). Consequently, most dryland vertebrates including many endemic and narrow-ranging species are inadequately protected (0–2% range coverage). Dryland vertebrates are threatened by varied anthropogenic factors—including agricultural and infrastructure development (that is, artificial structures, surfaces, roads and industrial sites). Alarmingly, by 2100 drylands are projected to experience some degree of land conversion in 95–100% of their current natural habitat due to urban, agricultural and alternative energy expansion. This loss of undisturbed dryland regions is expected across different socioeconomic pathways, even under optimistic scenarios characterized by progressive climate policies and moderate socioeconomic trends.
AI-based differential diagnosis of dementia etiologies on multimodal data
Authors: Xue Chonghua , Kowshik Sahana S. , Lteif Diala , Puducheri Shreyas , Jasodanand Varuna H. , Zhou Olivia T. , Walia Anika S. , Guney Osman B. , Zhang J. Diana , Poésy Serena , Kaliaev Artem , Andreu-Arasa V. Carlota , Dwyer Brigid C. , Farris Chad W. , Hao Honglin , Kedar Sachin , Mian Asim Z. , Murman Daniel L. , O’Shea Sarah A. , Paul Aaron B. , Rohatgi Saurabh , Saint-Hilaire Marie-Helene , Sartor Emmett A. , Setty Bindu N. , Small Juan E. , Swaminathan Arun , Taraschenko Olga , Yuan Jing , Zhou Yan , Zhu Shuhan , Karjadi Cody , Alvin Ang Ting Fang , Bargal Sarah A. , Plummer Bryan A. , Poston Kathleen L. , Ahangaran Meysam , Au Rhoda , Kolachalama Vijaya B.
Published: July 2024

Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an artificial intelligence (AI) model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a microaveraged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the microaveraged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in clinical settings and drug trials. Further prospective studies are needed to confirm its ability to improve patient care.
Fake views removal and popularity on YouTube
Authors: Castaldo Maria , Frasca Paolo , Venturini Tommaso , Gargiulo Floriana
Published: July 2024

This paper analyses how YouTube authenticates engagement metrics and, more specifically, how the platform corrects view counts by removing “fake views” (i.e., views considered artificial or illegitimate by the platform). Working with one and a half years of data extracted from a thousand French YouTube channels, we show the massive extent of the corrections done by YouTube, which concern the large majority of the channels and over 78% of the videos in our corpus. Our analysis shows that corrections are not done continuously as videos collect new views, but instead occur in batches, generally around 5 p.m. every day. More significantly, most corrections occur relatively late in the life of the videos, after they have reached most of their audience, and the delay in correction is not independent of the final popularity of videos: videos corrected later in their life are more popular on average than those corrected earlier. We discuss the probable causes of this phenomenon and its possible negative consequences on content diffusion. By inflating view counts, fake views could make videos appear more popular than they are and unwarrantedly encourage their recommendation, thus potentially altering the public debate on the platform. This could have implications on the spread of online misinformation, but their in-depth exploration requires first-hand information on view corrections, which YouTube does not provide through its API. This paper presents a series of experimental techniques to work around this limitation, offering a practical contribution to the study of online attention cycles (as described in the “Data and methods” section). At the same time, this paper is also a call for greater transparency by YouTube and other online platforms about information with crucial implications for the quality of online debate.
Leveraging AI techniques for predicting spatial distribution and determinants of carbon emission in China's Yangtze River Delta
Authors: Zhang Wen , Yuan Weijun , Xuan Wei , Lu Yanfei , Huang Zhaoxu
Published: July 2024

This study focuses on the prediction and management of carbon emissions (CE) under the backdrop of global warming, with a particular emphasis on developing spatial planning strategies for urban clusters. In this context, we integrate artificial intelligence technologies to devise an optimized spatial analysis method based on the attributes of multi-source, urban-level spatio-temporal big data on CE. This method enhances both the accuracy and interpretability of CE data processing. Our objectives are to accurately analyze the current status of CE, predict the future spatial distribution of urban CE in the Yangtze River Delta (YRD), and identify key driving factors. We aim to provide pragmatic recommendations for sustainable urban carbon management planning. The findings indicate that: (1) the algorithm designed by us demonstrates excellent fitting capabilities in the analysis of CE data in the YRD, achieving a fitting accuracy of 0.93; (2) it is predicted that from 2025 to 2030, areas with higher CE in the YRD will be primarily concentrated in the 'Provincial Capital Belt' and the 'Heavy Industry Belt'; (3) the economic foundation has been identified as the most significant factor influencing CE in the YRD; (4) projections suggest that CE in the YRD are likely to peak by 2030.