bluuebunny/crossref_metadata_2025_split huggingface dataset:
A database with frailty, functional and inertial gait metrics for the research of fall causes in older adults
Authors: García-de-Villa Sara , Neira Guillermo García-Villamil , Álvarez Marta Neira , Huertas-Hoyas Elisabet , Ruiz Luisa Ruiz , del-Ama Antonio J. , Sánchez María Cristina Rodríguez , Jiménez Antonio R. 
Published: August 2023

AbstractThe GSTRIDE database contains information of the health status assessment of 163 elderly adults. We provide socio-demographic data, functional and frailty variables, and the outcomes from tests commonly performed for the evaluation of elder people. The database contains gait parameters estimated from the measurements of an Inertial Measurement Unit (IMU) placed on the foot of volunteers. These parameters include the total walking distance, the number of strides and multiple spatio-temporal gait parameters, such as stride length, stride time, speed, foot angles and clearance, among others. The main processed database is stored, apart from MS Excel, in CSV format to ensure their usability. The database is complemented with the raw IMU recordings in TXT format, in order to let researchers test other algorithms of gait analysis. We include the Python programming codes as a base to reproduce or modify them. The database stores data to study the frailty-related parameters that distinguish faller and non-faller populations, and analyze the gait-related parameters in the frail subjects, which are essential topics for the elderly.
A Dementia mortality rates dataset in Italy (2012–2019)
Authors: Fania Alessandro , Monaco Alfonso , Amoroso Nicola , Bellantuono Loredana , Cazzolla Gatti Roberto , Firza Najada , Lacalamita Antonio , Pantaleo Ester , Tangaro Sabina , Velichevskaya Alena , Bellotti Roberto 
Published: August 2023

AbstractDementia is on the rise in the world population and has been defined by the World Health Organization as a global public health priority. In Italy, according to demographic projections, in 2051 there will be 280 elderly people for every 100 young people, with an increase in all age-related chronic diseases, including dementia. Currently the total number of patients with dementia is estimated to be over 1 million (mainly with Alzheimer’s disease (AD) and Parkinson’s disease (PD)). In-depth studies of the etiology and physiology of dementia are complicated due to the complexity of these diseases and their long duration. In this work we present a dataset on mortality rates (in the form of Standardized Mortality Ratios, SMR) for AD e PD in Italy at provincial level over a period of 8 years (2012–2019). Access to long-term, spatially detailed and ready-to-use data could favor both health monitoring and the research of new treatments and new drugs as well as innovative methodologies for early diagnosis of dementia.
Correlates of estimated lifetime cruciate ligament survival inform potential rupture risk reduction strategies: findings from the Exceptional Aging in Rottweilers Study
Authors: Waters David J. , Fu Rong , Carrillo Andres E. , Chiang Emily C. , Maras Aimee H. , Kengeri Seema S. , Suckow Cheri L. 
Published: August 2023

AbstractCranial cruciate ligament (CCL) rupture is one of the most commonly diagnosed orthopedic conditions of pet dogs, making estimated lifetime cruciate ligament survival an attractive endpoint for studies attempting to define clinical and genetic correlates of rupture risk reduction. Early life experiences contribute significantly to the origins of adult health outcomes, yet our current understanding of modifiable susceptibility factors that drive the high frequency of CCL rupture remains limited. We reasoned that combining lifetime medical history with standardized late-life assessment of lifetime cruciate ligament survival and detailed phenotyping of each dog for selected risk variables would provide a sensitive approach to identify factors that would differentiate between lifelong avoidance versus susceptibility to ligament rupture. Here, we report results of Kaplan–Meier analysis of estimated lifetime cruciate ligament survival and Cox proportional hazards modeling to assess risk variables in a lifetime cohort study of 123 purebred Rottweilers, a breed at high risk for veterinarian-diagnosed CCL rupture. We show that gonad removal during the 24-month developmental period is adversely associated with three measures of susceptibility—increased incidence of CCL rupture, multiplicity (bilateral rupture), and accelerated time to initial CCL failure. Our analysis reveals two other phenotypes—short adult height and the production of offspring (in females)—are associated with significant CCL rupture risk reduction. Together, the results provide clues to an early endocrine influence on lifetime cruciate ligament survival. Further, we identify two distinct clinical syndromes of CCL failure, providing a disease subtyping framework to advance future progress in genetic epidemiology, pathogenesis, and prediction. By conducting an evaluation of estimated lifetime CCL survival in dogs, we show that cruciate ligament survival may be jeopardized by gonad removal during the developmental period. Avoidance of such early environmental adversity may represent an actionable method for the control of canine CCL disease in certain breeds.
The anoikis-related gene signature predicts survival accurately in colon adenocarcinoma
Authors: Hu Gunchu , Li Jian , Zeng Yi , Liu Lixin , Yu Zhuowen , Qi Xiaoyan , Liu Kuijie , Yao Hongliang 
Published: August 2023

AbstractColon adenocarcinoma (COAD) is a serious public health problem, the third most common cancer and the second most deadly cancer in the world. About 9.4% of cancer-related deaths in 2020 were due to COAD. Anoikis is a specialized form of programmed cell death that plays an important role in tumor invasion and metastasis. The presence of anti-anoikis factors is associated with tumor aggressiveness and drug resistance. Various bioinformatic methods, such as differential expression analysis, and functional annotation analysis, machine learning, were used in this study. RNA-sequencing and clinical data from COAD patients were obtained from the Gene expression omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Construction of a prognostic nomogram for predicting overall survival (OS) using multivariate analysis and Lasso-Cox regression. Immunohistochemistry (IHC) was our method of validating the expression of seven genes that are linked to anoikis in COAD. We identified seven anoikis-related genes as predictors of COAD survival and prognosis, and confirmed their accuracy in predicting colon adenocarcinoma prognosis by KM survival curves and ROC curves. A seven-gene risk score consisting of NAT1, CDC25C, ATP2A3, MMP3, EEF1A2, PBK, and TIMP1 showed strong prognostic value. Meanwhile, we made a nomogram to predict the survival rate of COAD patients. The immune infiltration assay showed T cells. CD4 memory. Rest and macrophages. M0 has a higher proportion in COAD, and 11 genes related to tumor immunity are important. GDSC2-based drug susceptibility analysis showed that 6 out of 198 drugs were significant in COAD. Anoikis-related genes have potential value in predicting the prognosis of COAD and provide clues for developing new therapeutic strategies for COAD. Immune infiltration and drug susceptibility results provide important clues for finding new personalized treatment options for COAD. These findings also suggest possible mechanisms that may affect prognosis. These results are the starting point for planning individualized treatment and managing patient outcomes.
A pan-cancer analysis of potassium channel tetramerization domain containing 12 in human cancer
Authors: Liu Pan , Liu Zhilan , Luo Qiankun , Fu Qiang , Zhang Xu , Yu Pengfei , Zhou Shuai , Wang Yingying , Zhang Jiali , Chen Song , Zhang Hongwei , Zhu Qinghai , Qin Tao 
Published: August 2023

AbstractAbnormal expression of the potassium channel tetramerization domain containing 12 (KCTD12) is closely related to the occurrence and development of various tumors, but a pan-cancer analysis of KCTD12 has not yet been conducted. We explored the association between KCTD12 and more than 30 human malignancies using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. First, the mRNA and protein levels of KCTD12 were examined and their correlations with tumor stage and survival were explored. Second, we analyzed the infiltration of CD8+ and CD4+ T cells and cancer-associated fibroblasts in tumors and explored the correlation between KCTD12 expression and tumor cell stemness, genomic heterogeneity, and diagnostic specificity. Finally, we explored the molecular mechanisms associated with KCTD12 using KEGG/GO analysis. The results showed that KCTD12 mRNA and protein expression levels decreased in most tumors was significantly associated with the prognosis of tumor patients, and the phosphorylation level of KCTD12 decreased in several tumors, such as S200 and T196, pancreatic adenocarcinoma (PAAD), lung adenocarcinoma (LUAD), and breast invasive cancer (BRCA). The expression of KCTD12 was positively correlated with the degree of cancer-associated fibroblasts infiltration in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), head and neck squamous cell carcinoma (HNSC), PAAD, and stomach adenocarcinoma (STAD). The relationship between KCTD12 expression and CD8+ and CD4+ T cell infiltration was also clarified. KCTD12 showed high diagnostic sensitivity for various types of tumors and may be involved in tumor cell biology by affecting tumor cell stemness, tumor burden, and other characteristics. Finally, we analyzed the molecular functions of KCTD12 and possible KEGG/GO signaling pathways. In this study, we developed a biological marker for diagnosis, prognosis, and immune infiltration of the pan-cancers.
Long-term agro-management strategies shape soil bacterial community structure in dryland wheat systems
Authors: Singh Shikha , Singh Surendra , Lukas Scott B. , Machado Stephen , Nouri Amin , Calderon Francisco , Rieke Elizabeth R. , Cappellazzi Shannon B. 
Published: August 2023

AbstractSoil microbes play a crucial role in soil organic matter decomposition and nutrient cycling and are influenced by management practices. Therefore, quantifying the impacts of various agricultural management practices on soil microbiomes and their activity is crucial for making informed management decisions. This study aimed to assess the impact of various management systems on soil bacterial abundance and diversity, soil enzyme activities and carbon mineralization potential in wheat-based systems. To accomplish this, soil samples from 0 to 15 cm depth were collected from ongoing long-term field trials in eastern Oregon region under wheat (Triticum aestivum L.)-fallow (WF), WF with different tillage (WT), wheat-pea (Pisum sativum L.) (WP), WF under different crop residue management (CR) and natural undisturbed/unmanaged grassland pasture (GP). These trials consisted of an array of treatments like tillage intensities, nitrogen rates, organic amendments, and seasonal residue burning. This study was a part of the Soil Health Institute’s North American Project to Evaluate Soil Health measurements (NAPESHM). Bacterial community structure was determined using amplicon sequencing of the V4 region of 16SrRNA genes and followed the protocols of the Earth Microbiome Project. In addition, extracellular enzyme activities, and carbon mineralization potential (1d-CO2) were measured. Among different trials, 1d-CO2 in WT, WP, and CR studies averaged 53%, 51% and 87% lower than GP systems, respectively. Enzyme activities were significantly greater in GP compared to the other managements and followed similar trend as respiration. We observed higher evenness in GP and higher richness in spring residue burning treatment of CR study. Our results indicated that species evenness is perhaps a better indicator of soil health in comparison to other indices in dryland wheat systems.
How AI can learn from the law: putting humans in the loop only on appeal
Authors: Cohen I. Glenn , Babic Boris , Gerke Sara , Xia Qiong , Evgeniou Theodoros , Wertenbroch Klaus 
Published: August 2023

AbstractWhile the literature on putting a “human in the loop” in artificial intelligence (AI) and machine learning (ML) has grown significantly, limited attention has been paid to how human expertise ought to be combined with AI/ML judgments. This design question arises because of the ubiquity and quantity of algorithmic decisions being made today in the face of widespread public reluctance to forgo human expert judgment. To resolve this conflict, we propose that human expert judges be included via appeals processes for review of algorithmic decisions. Thus, the human intervenes only in a limited number of cases and only after an initial AI/ML judgment has been made. Based on an analogy with appellate processes in judiciary decision-making, we argue that this is, in many respects, a more efficient way to divide the labor between a human and a machine. Human reviewers can add more nuanced clinical, moral, or legal reasoning, and they can consider case-specific information that is not easily quantified and, as such, not available to the AI/ML at an initial stage. In doing so, the human can serve as a crucial error correction check on the AI/ML, while retaining much of the efficiency of AI/ML’s use in the decision-making process. In this paper, we develop these widely applicable arguments while focusing primarily on examples from the use of AI/ML in medicine, including organ allocation, fertility care, and hospital readmission.
Integration of pre-trained protein language models into geometric deep learning networks
Authors: Wu Fang , Wu Lirong , Radev Dragomir , Xu Jinbo , Li Stan Z. 
Published: August 2023

AbstractGeometric deep learning has recently achieved great success in non-Euclidean domains, and learning on 3D structures of large biomolecules is emerging as a distinct research area. However, its efficacy is largely constrained due to the limited quantity of structural data. Meanwhile, protein language models trained on substantial 1D sequences have shown burgeoning capabilities with scale in a broad range of applications. Several preceding studies consider combining these different protein modalities to promote the representation power of geometric neural networks but fail to present a comprehensive understanding of their benefits. In this work, we integrate the knowledge learned by well-trained protein language models into several state-of-the-art geometric networks and evaluate a variety of protein representation learning benchmarks, including protein-protein interface prediction, model quality assessment, protein-protein rigid-body docking, and binding affinity prediction. Our findings show an overall improvement of 20% over baselines. Strong evidence indicates that the incorporation of protein language models’ knowledge enhances geometric networks’ capacity by a significant margin and can be generalized to complex tasks.
Role of interneuron subtypes in controlling trial-by-trial output variability in the neocortex
Authors: Guo Lihao , Kumar Arvind 
Published: August 2023

AbstractTrial-by-trial variability is a ubiquitous property of neuronal activity in vivo which shapes the stimulus response. Computational models have revealed how local network structure and feedforward inputs shape the trial-by-trial variability. However, the role of input statistics and different interneuron subtypes in this process is less understood. To address this, we investigate the dynamics of stimulus response in a cortical microcircuit model with one excitatory and three inhibitory interneuron populations (PV, SST, VIP). Our findings demonstrate that the balance of inputs to different neuron populations and input covariances are the primary determinants of output trial-by-trial variability. The effect of input covariances is contingent on the input balances. In general, the network exhibits smaller output trial-by-trial variability in a PV-dominated regime than in an SST-dominated regime. Importantly, our work reveals mechanisms by which output trial-by-trial variability can be controlled in a context, state, and task-dependent manner.
Experimental evidence of Förster energy transfer enhancement in the near field through engineered metamaterial surface waves
Authors: Lezhennikova Kseniia , Rustomji Kaizad , Kuhlmey Boris T. , Antonakakis Tryfon , Jomin Pierre , Glybovski Stanislav , de Sterke C. Martijn , Wenger Jérôme , Abdeddaim Redha , Enoch Stefan 
Published: August 2023

AbstractPlasmonics has been demonstrated to provide fine tuning of the emission properties of single quantum sources (brightness, polarization, directivity, spectrum, lifetime…). However, significantly less is known about the role of surface plasmons in mediating subwavelength Förster resonant energy transfer (FRET) when a second emitter is introduced. Here, we report microwave experiments showing that excitation of surface waves on a dedicated metasurface can strongly mediate FRET in the near-field regime. This work paves the way for metasurfaces engineered to control dipole-dipole energy transfer with applications in lighting sources, photovoltaics, quantum information processing and biophysics.
High-harmonic generation in CdTe with ultra-low pump intensity and high photon flux
Authors: Long Zhe , Yang Hang , Tian Kan , He Linzhen , Qin Rui , Chen Zi-Yu , Wang Qi Jie , Liang Houkun 
Published: August 2023

AbstractAn ultra-low pump intensity and high photon flux have been long pursuits of high harmonic generation (HHG) in solids. However, there is lack of a criterion to identify a pristine solid material exhibiting such characteristics. Here, we report systematic investigation into HHG from a cadmium telluride (CdTe) bulk crystal with a flat band dispersion near the Fermi level which leads to a large density of states. The measured pump intensity for the 31st harmonics (229 nm) is only 75 GW/cm2, one order of magnitude lower than that of other pristine crystals including two-dimensional materials reported so far. A comparative measurement shows CdTe has two-to-three orders of magnitude stronger HHG than silicon does, and high HHG yields in the ultraviolet region compared to GaSe. A high photon flux of ~ 6 × 1012 photons/s (5th−8th) with a robust long-time sustainability is obtained. This work offers a route towards compact vacuum ultraviolet laser sources.
Joint optimization of land carbon uptake and albedo can help achieve moderate instantaneous and long-term cooling effects
Authors: Graf Alexander , Wohlfahrt Georg , Aranda-Barranco Sergio , Arriga Nicola , Brümmer Christian , Ceschia Eric , Ciais Philippe , Desai Ankur R. , Di Lonardo Sara , Gharun Mana , Grünwald Thomas , Hörtnagl Lukas , Kasak Kuno , Klosterhalfen Anne , Knohl Alexander , Kowalska Natalia , Leuchner Michael , Lindroth Anders , Mauder Matthias , Migliavacca Mirco , Morel Alexandra C. , Pfennig Andreas , Poorter Hendrik , Terán Christian Poppe , Reitz Oliver , Rebmann Corinna , Sanchez-Azofeifa Arturo , Schmidt Marius , Šigut Ladislav , Tomelleri Enrico , Yu Ke , Varlagin Andrej , Vereecken Harry 
Published: August 2023

AbstractBoth carbon dioxide uptake and albedo of the land surface affect global climate. However, climate change mitigation by increasing carbon uptake can cause a warming trade-off by decreasing albedo, with most research focusing on afforestation and its interaction with snow. Here, we present carbon uptake and albedo observations from 176 globally distributed flux stations. We demonstrate a gradual decline in maximum achievable annual albedo as carbon uptake increases, even within subgroups of non-forest and snow-free ecosystems. Based on a paired-site permutation approach, we quantify the likely impact of land use on carbon uptake and albedo. Shifting to the maximum attainable carbon uptake at each site would likely cause moderate net global warming for the first approximately 20 years, followed by a strong cooling effect. A balanced policy co-optimizing carbon uptake and albedo is possible that avoids warming on any timescale, but results in a weaker long-term cooling effect.
Higher vegetation sensitivity to meteorological drought in autumn than spring across European biomes
Authors: Jin Hongxiao , Vicente-Serrano Sergio M. , Tian Feng , Cai Zhanzhang , Conradt Tobias , Boincean Boris , Murphy Conor , Farizo Begoña Alvarez , Grainger Sam , López-Moreno Juan I. , Eklundh Lars 
Published: August 2023

AbstractEurope has experienced severe drought events in recent decades, posing challenges to understand vegetation responses due to diverse vegetation distribution, varying growth stages, different drought characteristics, and concurrent hydroclimatic factors. To analyze vegetation response to meteorological drought, we employed multiple vegetation indicators across European biomes. Our findings reveal that vegetation sensitivity to drought increases as the canopy develops throughout the year, with sensitivities from −0.01 in spring to 0.28 in autumn and drought-susceptible areas from 18.5 to 57.8% in Europe. Soil water shortage exacerbates vegetation-drought sensitivity temporally, while its spatial impact is limited. Vegetation-drought sensitivity strongly correlates with vapor pressure deficit and partially with atmospheric CO2concentration. These results highlight the spatiotemporal variations in vegetation-drought sensitivities and the influence of hydroclimatic factors. The findings enhance our understanding of vegetation response to drought and the impact of concurrent hydroclimatic factors, providing valuable sub-seasonal information for water management and drought preparedness.
Exercise ameliorates skeletal muscle insulin resistance by modulating GRK4-mediated D1R expression
Authors: Tao Yu , Luo Wenbin , Chen Yue , Chen Caiyu , Chen Shengnan , Li Xiaoping , Chen Ken , Zeng Chunyu 
Published: August 2023

Abstract
Exercise has been recommended as a nonpharmaceutical therapy to treat insulin resistance (IR). Previous studies showed that dopamine D1-like receptor agonists, such as fenoldopam, could improve peripheral insulin sensitivity, while antipsychotics, which are dopamine receptor antagonists, increased susceptibility to Type 2 diabetes mellitus (T2DM). Meanwhile, exercise has been proved to stimulate dopamine receptors. However, whether the dopamine D1 receptor (D1R) is involved in exercise-mediated amelioration of IR remains unclear. We found that the D1-like receptor antagonist, SCH23390, reduced the effect of exercise on lowering blood glucose and insulin in insulin-resistant mice and inhibited the contraction-induced glucose uptake in C2C12 myotubes. Similarly, the opposite was true for the D1-like receptor agonist, fenoldopam. Furthermore, the expression of D1R was decreased in skeletal muscles from streptozotocin (STZ)- and high-fat intake-induced T2DM mice, accompanied by increased D1R phosphorylation, which was reversed by exercise. A screening study showed that G protein-coupled receptor kinase 4 (GRK4) may be the candidate kinase for the regulation of D1R function, because, in addition to the increased GRK4 expression in skeletal muscles of T2DM mice, GRK4 transgenic T2DM mice exhibited lower insulin sensitivity, accompanied by higher D1R phosphorylation than control mice, whereas the AAV9-shGRK4 mice were much more sensitive to insulin than AAV9-null mice. Mechanistically, the up-regulation of GRK4 expression caused by increased reactive oxygen species (ROS) in IR was ascribed to the enhanced expression of c-Myc, a transcriptional factor of GRK4. Taken together, the present study shows that exercise, via regulation of ROS/c-Myc/GRK4 pathway, ameliorates D1R dysfunction and improves insulin sensitivity.