bluuebunny/crossref_metadata_2025_split huggingface dataset:
DNA framework-engineered chimeras platform enables selectively targeted protein degradation
Authors: Zhou Li , Yu Bin , Gao Mengqiu , Chen Rui , Li Zhiyu , Gu Yueqing , Bian Jinlei , Ma Yi 
Published: July 2023

AbstractA challenge in developing proteolysis targeting chimeras (PROTACs) is the establishment of a universal platform applicable in multiple scenarios for precise degradation of proteins of interest (POIs). Inspired by the addressability, programmability, and rigidity of DNA frameworks, we develop covalent DNA framework-based PROTACs (DbTACs), which can be synthesized in high-throughput via facile bioorthogonal chemistry and self-assembly. DNA tetrahedra are employed as templates and the spatial position of each atom is defined. Thus, by precisely locating ligands of POI and E3 ligase on the templates, ligand spacings can be controllably manipulated from 8 Å to 57 Å. We show that DbTACs with the optimal linker length between ligands achieve higher degradation rates and enhanced binding affinity. Bispecific DbTACs (bis-DbTACs) with trivalent ligand assembly enable multi-target depletion while maintaining highly selective degradation of protein subtypes. When employing various types of warheads (small molecules, antibodies, and DNA motifs), DbTACs exhibit robust efficacy in degrading diverse targets, including protein kinases and transcription factors located in different cellular compartments. Overall, utilizing modular DNA frameworks to conjugate substrates offers a universal platform that not only provides insight into general degrader design principles but also presents a promising strategy for guiding drug discovery.
Like-minded sources on Facebook are prevalent but not polarizing
Authors: Nyhan Brendan , Settle Jaime , Thorson Emily , Wojcieszak Magdalena , Barberá Pablo , Chen Annie Y. , Allcott Hunt , Brown Taylor , Crespo-Tenorio Adriana , Dimmery Drew , Freelon Deen , Gentzkow Matthew , González-Bailón Sandra , Guess Andrew M. , Kennedy Edward , Kim Young Mie , Lazer David , Malhotra Neil , Moehler Devra , Pan Jennifer , Thomas Daniel Robert , Tromble Rebekah , Rivera Carlos Velasco , Wilkins Arjun , Xiong Beixian , de Jonge Chad Kiewiet , Franco Annie , Mason Winter , Stroud Natalie Jomini , Tucker Joshua A. 
Published: July 2023

AbstractMany critics raise concerns about the prevalence of ‘echo chambers’ on social media and their potential role in increasing political polarization. However, the lack of available data and the challenges of conducting large-scale field experiments have made it difficult to assess the scope of the problem1,2. Here we present data from 2020 for the entire population of active adult Facebook users in the USA showing that content from ‘like-minded’ sources constitutes the majority of what people see on the platform, although political information and news represent only a small fraction of these exposures. To evaluate a potential response to concerns about the effects of echo chambers, we conducted a multi-wave field experiment on Facebook among 23,377 users for whom we reduced exposure to content from like-minded sources during the 2020 US presidential election by about one-third. We found that the intervention increased their exposure to content from cross-cutting sources and decreased exposure to uncivil language, but had no measurable effects on eight preregistered attitudinal measures such as affective polarization, ideological extremity, candidate evaluations and belief in false claims. These precisely estimated results suggest that although exposure to content from like-minded sources on social media is common, reducing its prevalence during the 2020 US presidential election did not correspondingly reduce polarization in beliefs or attitudes.
A reinforcement learning model for AI-based decision support in skin cancer
Authors: Barata Catarina , Rotemberg Veronica , Codella Noel C. F. , Tschandl Philipp , Rinner Christoph , Akay Bengu Nisa , Apalla Zoe , Argenziano Giuseppe , Halpern Allan , Lallas Aimilios , Longo Caterina , Malvehy Josep , Puig Susana , Rosendahl Cliff , Soyer H. Peter , Zalaudek Iris , Kittler Harald 
Published: July 2023

AbstractWe investigated whether human preferences hold the potential to improve diagnostic artificial intelligence (AI)-based decision support using skin cancer diagnosis as a use case. We utilized nonuniform rewards and penalties based on expert-generated tables, balancing the benefits and harms of various diagnostic errors, which were applied using reinforcement learning. Compared with supervised learning, the reinforcement learning model improved the sensitivity for melanoma from 61.4% to 79.5% (95% confidence interval (CI): 73.5–85.6%) and for basal cell carcinoma from 79.4% to 87.1% (95% CI: 80.3–93.9%). AI overconfidence was also reduced while simultaneously maintaining accuracy. Reinforcement learning increased the rate of correct diagnoses made by dermatologists by 12.0% (95% CI: 8.8–15.1%) and improved the rate of optimal management decisions from 57.4% to 65.3% (95% CI: 61.7–68.9%). We further demonstrated that the reward-adjusted reinforcement learning model and a threshold-based model outperformed naïve supervised learning in various clinical scenarios. Our findings suggest the potential for incorporating human preferences into image-based diagnostic algorithms.
A pipeline to further enhance quality, integrity and reusability of the NCCID clinical data
Authors: Breger Anna , Selby Ian , Roberts Michael , Babar Judith , Gkrania-Klotsas Effrossyni , Preller Jacobus , Escudero Sánchez Lorena ,   AIX-COVNET Collaboration, Dittmer Sören , Thorpe Matthew , Gilbey Julian , Korhonen Anna , Jefferson Emily , Langs Georg , Yang Guang , Xing Xiaodan , Nan Yang , Li Ming , Prosch Helmut , Jan Stanczuk  , Tang Jing , Teare Philip , Patel Mishal , Wassink Marcel , Holzer Markus , Solares Eduardo González , Walton Nicholas , Liò Pietro , Shadbahr Tolou , Rudd James H. F. , Aston John A. D. , Weir-McCall Jonathan R. , Sala Evis , Schönlieb Carola-Bibiane 
Published: July 2023

AbstractThe National COVID-19 Chest Imaging Database (NCCID) is a centralized UK database of thoracic imaging and corresponding clinical data. It is made available by the National Health Service Artificial Intelligence (NHS AI) Lab to support the development of machine learning tools focused on Coronavirus Disease 2019 (COVID-19). A bespoke cleaning pipeline for NCCID, developed by the NHSx, was introduced in 2021. We present an extension to the original cleaning pipeline for the clinical data of the database. It has been adjusted to correct additional systematic inconsistencies in the raw data such as patient sex, oxygen levels and date values. The most important changes will be discussed in this paper, whilst the code and further explanations are made publicly available on GitLab. The suggested cleaning will allow global users to work with more consistent data for the development of machine learning tools without being an expert. In addition, it highlights some of the challenges when working with clinical multi-center data and includes recommendations for similar future initiatives.
Cardiac defibrillator implantation in patients with syncope and inducible ventricular arrhythmia: insights from the German Device Registry
Authors: Kahle Ann-Kathrin , Senges Jochen , Hochadel Matthias , Brachmann Johannes , Thomas Dierk , Straube Florian , Bonaventura Klaus , Larbig Robert , Werner Nikos , Butter Christian , Alken Fares-Alexander , Meyer Christian 
Published: July 2023

AbstractHistory of syncope is an independent predictor for sudden cardiac death. Programmed stimulation may be considered for risk stratification, but data remain sparse among different populations. Here, we analyzed the prognostic value of inducible ventricular arrhythmia (VA) regarding clinical outcome in patients with syncope undergoing defibrillator implantation. Among 4196 patients enrolled in the prospective, multi-center German Device Registry, patients with syncope and inducible VA (n = 285, 6.8%) vs. those with a secondary preventive indication (n = 1885, 45.2%), defined as previously documented sustained ventricular tachycardia or ventricular fibrillation, serving as a control group were studied regarding demographics, device implantation and post-procedural adverse events. Patients with syncope and inducible VA (64.9 ± 14.4 years, 81.1% male) presented less frequently with congestive heart failure (15.1% vs. 29.1%; p < 0.001) and any structural heart disease (84.9% vs. 89.3%; p = 0.030) than patients with a secondary preventive indication (65.0 ± 13.8 years, 81.0% male). Whereas dilated cardiomyopathy (16.8% vs. 23.8%; p = 0.009) was less common, hypertrophic cardiomyopathy (5.6% vs. 2.8%; p = 0.010) and Brugada syndrome (2.1% vs. 0.3%; p < 0.001) were present more often. During 1-year-follow-up, mortality (5.1% vs. 8.9%; p = 0.036) and the rate of major adverse cardiac or cerebrovascular events (5.8% vs. 10.0%; p = 0.027) were lower in patients with syncope and inducible VA. Among patients with inducible VA, post-procedural adverse events including rehospitalization (27.6% vs. 21.7%; p = 0.37) did not differ between those with vs. without syncope. Taken together, patients with syncope and inducible VA have better clinical outcomes than patients with a secondary preventive defibrillator indication, but comparable outcomes to patients without syncope, which underlines the relevance of VA inducibility, potentially irrespective of a syncope.
Industrial washing conditions as factor that influence the cellulose structure and mechanical strength of bed linens
Authors: Jasińska Izabela 
Published: July 2023

AbstractIt is crucial for companies providing rental and maintenance services to hotels and hospitals to tackle the problem of decreased physical longevity caused by frequent laundering procedures in the industrial textile sector. Proper maintenance of bed linens is vital as they undergo multiple rigorous preservation techniques, such as being treated with chlorine to remove tough stains and sanitize the fabrics. The mechanical strength of fabric made of 100% cotton fibre products greatly relies on the degree of polymerization of cellulose-cotton fibre material. The study evaluated the washing performance of five cotton fabrics. Two weaving pattern variations were used and the fabrics were composed either of 100% cotton or a blend of 50% cotton and 50% polyester fibres. The washing methods included commercial and chlorine-based laboratory washing. 100% cotton fabrics, especially in plain weave show higher tensile strength falls then blended ones. The pure cotton fabric loss much more of its initial strength after only few chlorine-based washings than after hundred commercial ones. Limiting viscosity number values drop in half after hundred commercial washings for cotton fibres taken from tested woven fabrics. In comparison, decline of this parameter after only ten chlorine-based washings is more than 80% of their initial values. Performing the maintenance process without free chlorine, while still retaining its high effectiveness, can notably augment the frequency of maintenance procedures and preserve the mechanical durability of cotton fabrics over a longer time span. This leads to a reduction in textile waste residues.
Association between high-sensitivity C-reactive protein and coronary atherosclerosis in a general middle-aged population
Authors: Cederström Sofia , Lundman Pia , Alfredsson Joakim , Hagström Emil , Ravn-Fischer Annica , Söderberg Stefan , Yndigegn Troels , Tornvall Per , Jernberg Tomas 
Published: July 2023

AbstractDespite abundant knowledge about the relationship between inflammation and coronary atherosclerosis, it is still unknown whether systemic inflammation measured as high-sensitivity C-reactive protein (hsCRP) is associated with coronary atherosclerosis in a general population. This study aimed to examine the association between hsCRP and coronary computed tomography angiography (CCTA)-detected coronary atherosclerosis in a population-based cohort. Out of 30,154 randomly invited men and women aged 50 to 64 years in the Swedish Cardiopulmonary Bioimage Study (SCAPIS), 25,408 had a technically acceptable CCTA and analysed hsCRP. Coronary atherosclerosis was defined as presence of plaque of any degree in any of 18 coronary segments. HsCRP values were categorised in four groups. Compared with hsCRP below the detection limit, elevated hsCRP (≥ 2.3 mg/L) was weakly associated with any coronary atherosclerosis (OR 1.15, 95% CI 1.07–1.24), coronary diameter stenosis ≥ 50% (OR 1.27, 95% CI 1.09–1.47), ≥ 4 segments involved (OR 1.13, 95% CI 1.01–1.26 ) and severe atherosclerosis (OR 1.33, 95% CI 1.05–1.69) after adjustment for age, sex and traditional risk factors. The associations were attenuated after further adjustment for body mass index (BMI), although elevated hsCRP still associated with noncalcified plaques (OR 1.16, 95% CI 1.02–1.32), proposed to be more vulnerable. In conclusion, the additional value of hsCRP to traditional risk factors in detection of coronary atherosclerosis is low. The association to high-risk noncalcified plaques, although unlikely through a causal pathway, could explain the relationship between hsCRP and clinical coronary events in numerous studies.
Transition of deformation modes from bending to auxetic compression in origami-based metamaterials for head protection from impact
Authors: Tomita Sunao , Shimanuki Kento , Oyama Shin , Nishigaki Hidekazu , Nakagawa Toshiaki , Tsutsui Masakazu , Emura Youhei , Chino Masahiko , Tanaka Hirokazu , Itou Yoshinobu , Umemoto Kazuhiko 
Published: July 2023

AbstractFor the protection of the human head by energy absorption structures, a soft mechanical response upon contact with the head is required to mitigate the effect of impact, while a hard mechanical response for highly efficient energy absorption is required to stop the movement of the head. This study realized the opposite mechanical properties during head protection by transitioning the deformation mode from bending to auxetic compression. First, non-linear finite element (FE) models were constructed to numerically reproduce the bending behavior. The calculated force responses agreed well with forces in bending tests. Using the FE models, the EA structures with proper transition of deformation modes were designed and installed in the seat headrests of real vehicles. Head protection was evaluated by dynamic loading in sled testing, in which the force on the head of the crash test dummy was measured. The head injury criterion improved from 274 to 155, indicating the superior performance of the tested structures compared to that achieved by energy absorption structures based on steel plates. Moreover, the deformation of auxetic structures prevented neck bending by holding the head. These findings present new possibilities for effectively protecting the human body by mitigating impact, facilitating energy absorption, and ensuring head stability.
Theory of localization-hindered thermalization in nonlinear multimode photonics
Authors: Ramos Alba Y. , Shi Cheng , Fernández-Alcázar Lucas J. , Christodoulides Demetrios N. , Kottos Tsampikos 
Published: July 2023

AbstractOur society’s appetite for ultra-high bandwidth communication networks and high-power optical sources, together with recent breakthroughs in mode multiplexing/demultiplexing schemes, forced the photonics community to reconsider the deployment of nonlinear multimode systems. These developments pose fundamental challenges stemming from the complexity of nonlinear mode-mode mixing by which they exchange energy in the process towards an equilibrium Rayleigh-Jeans (RJ) distribution. Here we develop a universal one-parameter scaling theory for the relaxation rates of out-of-equilibrium excitations towards their RJ thermal state. The theory predicts an exponential suppression of the rates with increasing disorder due to the formation of stable localization clusters resisting the nonlinear mode-mode interactions that tend to separate them. For low optical temperatures, the rates experience a crossover from linear to nonlinear temperature dependence which reflects a disorder-induced reorganization of the low frequency eigenmodes. Our theory will guide the design of nonlinear multimode photonic networks with tailored relaxation-scales.
Significantly improved thermoelectric performance of SnSe originating from collaborative adjustment between valence and conduction bands, mass fluctuations, and local strain
Authors: Wang Shuai , Yuan Hang , Li Chunhui , Liu HongQuan , Gu Yi-jie , Wang YanFang 
Published: July 2023

In this investigation, environmentally friendly, low cost, and easy to synthesize InSn and VSn co-doped SnSe was designed, which achieves 1.3 of ZT at 773K via quality fluctuation, local strain and dual regulation of valence and conduction band.
Biometric privacy protection: What is this thing called privacy?
Authors: Mordini Emilio 
Published: July 2023

AbstractWe are at the wake of an epochal revolution, the Information Revolution. The Information Revolution has been accompanied by the rise of a new commodity, digital data, which is changing the world including methods for human recognition. Biometric systems are the recognition technology of the new age. So, privacy scholars tend to frame biometric privacy protection chiefly in terms of biometric data protection. The author argues that this is a misleading perspective. Biometric data protection is an extremely relevant legal and commercial issue but has little to do with privacy. The notion of privacy, understood as a personal intimate sphere, is hardly related to what is contained in this private realm (data or whatever else), rather it is related to the very existence of a secluded space. Privacy relies on having the possibility to hide rather than in hiding anything. What really matters is the existence of a private sphere rather than what is inside. This also holds true for biometric privacy. Biometric privacy protection should focus on bodily and psychological integrity, preventing those technology conditions and operating practices that may lead to turn biometric recognition into a humiliating experience for the individual.
Multi‐objective digital circuit block optimisation based on cell mapping in an industrial electronic design automation flow
Authors: Cao Linan , Bale Simon J. , Trefzer Martin A. 
Published: July 2023

AbstractModern electronic design automation (EDA) tools can handle the complexity of state‐of‐the‐art electronic systems by decomposing them into smaller blocks or cells, introducing different levels of abstraction and staged design flows. However, throughout each independently optimised design step, overheads and inefficiencies can accumulate in the resulting overall design. Performing design‐specific optimisation from a more global viewpoint requires more time due to the larger search space but has the potential to provide solutions with improved performanc. In this work, a fully‐automated, multi‐objective (MO) EDA flow is introduced to address this issue. It specifically tunes drive strength mapping, prior to physical implementation, through MO population‐based search algorithms. Designs are evaluated with respect to their power, performance and area (PPA). The proposed approach is aimed at digital circuit optimisation at the block level, where it is capable of expanding the design space and offers a set of trade‐off solutions for different case‐specific utilisation. We have applied the proposed multi‐objective electronic design automation flow (MOEDA) framework to ISCAS‐85 and EPFL benchmark circuits by using a commercial 65 nm standard cell library. The experimental results demonstrate how the MOEDA flow enhances the solutions initially generated by the standard digital flow and how simultaneously a significant improvement in PPA metrics is achieved.
Psychische Vorerkrankungen und Depressivität in der 2. Welle
der SARS-CoV-2-Pandemie in Deutschland – Die Rolle pandemieassoziierter
Stressoren
Authors: Markert Jenny , Niemann Jana , Starke Dagmar , Frese Thomas , Meyer Gabriele , Mikolajczyk Rafael , Schildmann Jan , Steckelberg Anke , Knöchelmann Anja 
Published: July 2023

ZusammenfassungDie 2. Welle der SARS-CoV-2-Pandemie war durch einschneidende Maßnahmen
gekennzeichnet. Aus vorherigen Pandemien sowie der 1. Welle ist bekannt, dass
dabei gerade Personen mit einer psychischen Vorbelastung vulnerabel für
einen schlechten psychischen Gesundheitszustand sein können. Der Beitrag
untersucht daher den Zusammenhang zwischen psychischen Störungen vor
Pandemiebeginn (PSV) und Depressivität in der 2. Welle, unter
Berücksichtigung allgemeiner Stressbelastungen, Belastung durch
Isolation, der subjektiven Sinnhaftigkeit politischer Maßnahmen und
erlebten Einschränkung sowie Angst vor den Pandemiefolgen und
Veränderung der Arbeits- und Einkommensituation. Grundlage der
Querschnittsanalyse bilden Daten von 812 Befragten der Health Related Beliefs
and Health Care Experiences in Germany-Studie (HeReCa). Der Zusammenhang
zwischen PSV und Depressivität wurde mittels für Bildung und
Alter gewichteter logistischer Regression adjustiert für genannte
Kovariablen sowie soziodemographische Charakteristiken untersucht. Personen mit
PSV gaben signifikant häufiger stärkere Depressivität an
als Personen ohne (OR: 25,1; 95-% KI: 11,0-57,3). Dieser Zusammenhang
verringerte sich zum Teil u.a. durch die Hinzunahme erhöhter allgemeiner
Stressbelastungen und Belastung durch Isolation. Fehlende Partnerschaft,
geringes Haushaltseinkommen und männliches Geschlecht waren dabei mit
der stärkeren Depressivität assoziiert, änderten den
Zusammenhang von PSV und Depressivität jedoch nur marginal. Insgesamt
wurde deutlich, dass während der 2. Welle der Pandemie Personen mit PSV
zur stärkeren Depressivität neigten als Personen ohne PSV. Die
Versorgung von psychischen Erkrankungen sollte daher auch in pandemischen Zeiten
gewährleistet sein und durch E-Mental-Health oder professionelle Hilfen
zur Stressbewältigung ergänzt werden.
Toward an extreme-scale electronic structure system
Authors: Galvez Vallejo Jorge L. , Snowdon Calum , Stocks Ryan , Kazemian Fazeleh , Yan Yu Fiona Chuo , Seidl Christopher , Seeger Zoe , Alkan Melisa , Poole David , Westheimer Bryce M. , Basha Mehaboob , De La Pierre Marco , Rendell Alistair , Izgorodina Ekaterina I. , Gordon Mark S. , Barca Giuseppe M. J. 
Published: July 2023

Electronic structure calculations have the potential to predict key matter transformations for applications of strategic technological importance, from drug discovery to material science and catalysis. However, a predictive physicochemical characterization of these processes often requires accurate quantum chemical modeling of complex molecular systems with hundreds to thousands of atoms. Due to the computationally demanding nature of electronic structure calculations and the complexity of modern high-performance computing hardware, quantum chemistry software has historically failed to operate at such large molecular scales with accuracy and speed that are useful in practice. In this paper, novel algorithms and software are presented that enable extreme-scale quantum chemistry capabilities with particular emphasis on exascale calculations. This includes the development and application of the multi-Graphics Processing Unit (GPU) library LibCChem 2.0 as part of the General Atomic and Molecular Electronic Structure System package and of the standalone Extreme-scale Electronic Structure System (EXESS), designed from the ground up for scaling on thousands of GPUs to perform high-performance accurate quantum chemistry calculations at unprecedented speed and molecular scales. Among various results, we report that the EXESS implementation enables Hartree–Fock/cc-pVDZ plus RI-MP2/cc-pVDZ/cc-pVDZ-RIFIT calculations on an ionic liquid system with 623 016 electrons and 146 592 atoms in less than 45 min using 27 600 GPUs on the Summit supercomputer with a 94.6% parallel efficiency.