bluuebunny/crossref_metadata_2025_split huggingface dataset:
Non-cell-autonomous cancer progression from chromosomal instability
Authors: Li Jun , Hubisz Melissa J. , Earlie Ethan M. , Duran Mercedes A. , Hong Christy , Varela Austin A. , Lettera Emanuele , Deyell Matthew , Tavora Bernardo , Havel Jonathan J. , Phyu Su M. , Amin Amit Dipak , Budre Karolina , Kamiya Erina , Cavallo Julie-Ann , Garris Christopher , Powell Simon , Reis-Filho Jorge S. , Wen Hannah , Bettigole Sarah , Khan Atif J. , Izar Benjamin , Parkes Eileen E. , Laughney Ashley M. , Bakhoum Samuel F. 
Published: August 2023

AbstractChromosomal instability (CIN) is a driver of cancer metastasis1–4, yet the extent to which this effect depends on the immune system remains unknown. Using ContactTracing—a newly developed, validated and benchmarked tool to infer the nature and conditional dependence of cell–cell interactions from single-cell transcriptomic data—we show that CIN-induced chronic activation of the cGAS–STING pathway promotes downstream signal re-wiring in cancer cells, leading to a pro-metastatic tumour microenvironment. This re-wiring is manifested by type I interferon tachyphylaxis selectively downstream of STING and a corresponding increase in cancer cell-derived endoplasmic reticulum (ER) stress response. Reversal of CIN, depletion of cancer cell STING or inhibition of ER stress response signalling abrogates CIN-dependent effects on the tumour microenvironment and suppresses metastasis in immune competent, but not severely immune compromised, settings. Treatment with STING inhibitors reduces CIN-driven metastasis in melanoma, breast and colorectal cancers in a manner dependent on tumour cell-intrinsic STING. Finally, we show that CIN and pervasive cGAS activation in micronuclei are associated with ER stress signalling, immune suppression and metastasis in human triple-negative breast cancer, highlighting a viable strategy to identify and therapeutically intervene in tumours spurred by CIN-induced inflammation.
A natural language fMRI dataset for voxelwise encoding models
Authors: LeBel Amanda , Wagner Lauren , Jain Shailee , Adhikari-Desai Aneesh , Gupta Bhavin , Morgenthal Allyson , Tang Jerry , Xu Lixiang , Huth Alexander G. 
Published: August 2023

AbstractSpeech comprehension is a complex process that draws on humans’ abilities to extract lexical information, parse syntax, and form semantic understanding. These sub-processes have traditionally been studied using separate neuroimaging experiments that attempt to isolate specific effects of interest. More recently it has become possible to study all stages of language comprehension in a single neuroimaging experiment using narrative natural language stimuli. The resulting data are richly varied at every level, enabling analyses that can probe everything from spectral representations to high-level representations of semantic meaning. We provide a dataset containing BOLD fMRI responses recorded while 8 participants each listened to 27 complete, natural, narrative stories (~6 hours). This dataset includes pre-processed and raw MRIs, as well as hand-constructed 3D cortical surfaces for each participant. To address the challenges of analyzing naturalistic data, this dataset is accompanied by a python library containing basic code for creating voxelwise encoding models. Altogether, this dataset provides a large and novel resource for understanding speech and language processing in the human brain.
DiaTrend: A dataset from advanced diabetes technology to enable development of novel analytic solutions
Authors: Prioleau Temiloluwa , Bartolome Abigail , Comi Richard , Stanger Catherine 
Published: August 2023

AbstractObjective digital data is scarce yet needed in many domains to enable research that can transform the standard of healthcare. While data from consumer-grade wearables and smartphones is more accessible, there is critical need for similar data from clinical-grade devices used by patients with a diagnosed condition. The prevalence of wearable medical devices in the diabetes domain sets the stage for unique research and development within this field and beyond. However, the scarcity of open-source datasets presents a major barrier to progress. To facilitate broader research on diabetes-relevant problems and accelerate development of robust computational solutions, we provide the DiaTrend dataset. The DiaTrend dataset is composed of intensive longitudinal data from wearable medical devices, including a total of 27,561 days of continuous glucose monitor data and 8,220 days of insulin pump data from 54 patients with diabetes. This dataset is useful for developing novel analytic solutions that can reduce the disease burden for people living with diabetes and increase knowledge on chronic condition management in outpatient settings.
A module classification method for light industrial equipment based on improved NSGA2-FCM algorithm
Authors: Zheng Hui , Guo Hanwen , Pang Tonglin , Guo Zijian , Guo Xiao 
Published: August 2023

AbstractIn response to the problem that it is easy to fall into local optimum when using the traditional clustering algorithm to divide the modules, this paper improves the initialisation strategy of the NSGA2 algorithm and combines it with the FCM algorithm to propose an improved NSGA2-FCM algorithm for clustering analysis. Firstly, the FBS mapping is used to model the functional structure of the product system and identify the relationship between the product functional structures. Secondly, a correlation synthesis matrix is constructed based on the relationships between the module division drivers. Finally, the improved NSGA2-FCM algorithm is applied to cluster analysis of the product to derive the best module division scheme. The algorithm avoids falling into local optima by optimising the initialisation strategy of the NSGA2 algorithm, while using the FCM algorithm to improve the accuracy of the clustering. This allows the algorithm to explore the solution space more effectively when finding the best module partitioning solution. Finally, the effectiveness of the algorithm for module classification of light industrial equipment is verified using beer fermenters as a case study.
Integration of plasma and CSF metabolomics with CSF proteomic reveals novel associations between lipid mediators and central nervous system vascular and energy metabolism
Authors: Borkowski Kamil , Seyfried Nicholas T. , Arnold Matthias , Lah James J. , Levey Allan I. , Hales Chadwick M. , Dammer Eric B. , Blach Colette , Louie Gregory , Kaddurah-Daouk Rima , Newman John W. 
Published: August 2023

AbstractIntegration of the omics data, including metabolomics and proteomics, provides a unique opportunity to search for new associations within metabolic disorders, including Alzheimer’s disease. Using metabolomics, we have previously profiled oxylipins, endocannabinoids, bile acids, and steroids in 293 CSF and 202 matched plasma samples from AD cases and healthy controls and identified both central and peripheral markers of AD pathology within inflammation-regulating cytochrome p450/soluble epoxide hydrolase pathway. Additionally, using proteomics, we have identified five cerebrospinal fluid protein panels, involved in the regulation of energy metabolism, vasculature, myelin/oligodendrocyte, glia/inflammation, and synapses/neurons, affected in AD, and reflective of AD-related changes in the brain. In the current manuscript, using metabolomics-proteomics data integration, we describe new associations between peripheral and central lipid mediators, with the above-described CSF protein panels. Particularly strong associations were observed between cytochrome p450/soluble epoxide hydrolase metabolites, bile acids, and proteins involved in glycolysis, blood coagulation, and vascular inflammation and the regulators of extracellular matrix. Those metabolic associations were not observed at the gene-co-expression level in the central nervous system. In summary, this manuscript provides new information regarding Alzheimer’s disease, linking both central and peripheral metabolism, and illustrates the necessity for the “omics” data integration to uncover associations beyond gene co-expression.
A population-based longitudinal study on glycated hemoglobin levels and new-onset chronic kidney disease among non-diabetic Japanese adults
Authors: Okawa Yukari , Suzuki Etsuji , Mitsuhashi Toshiharu , Tsuda Toshihide , Yorifuji Takashi 
Published: August 2023

AbstractChronic kidney disease (CKD) is a major global public health problem. Recent studies reported that diabetes and prediabetes are risk factors for developing CKD; however, the exact glycated hemoglobin (HbA1c) cut-off value for prediabetes remains controversial. In this study, we aimed to examine the relationship between HbA1c levels and subsequent CKD development in greater detail than previous studies. Longitudinal data of annual checkups of 7176 Japanese non-diabetic people (male: 40.4%) from 1998 to 2022 was analyzed. HbA1c values were categorized into < 5.0%, 5.0–5.4%, 5.5–5.9%, and 6.0–6.4%. CKD was defined as an estimated glomerular filtration rate < 60 ml/min/1.73 m2. The descriptive statistics at study entry showed that higher HbA1c values were associated with male, older, overweight or obese, hypertensive, or dyslipidemic people. During a mean follow-up of 7.75 person-years, 2374 participants (male: 40.0%) developed CKD. The Weibull accelerated failure time model was selected because the proportional hazards assumption was violated. The adjusted time ratios of developing CKD for HbA1c levels of 5.5–5.9% and 6.0–6.4% compared with 5.0–5.4% were 0.97 (95% confidence interval: 0.92–1.03) and 1.01 (95% confidence interval: 0.90–1.13), respectively. There was no association between HbA1c in the prediabetic range and subsequent CKD development.
Acute effects of caffeine supplementation on taekwondo performance: the influence of competition level and sex
Authors: Ouergui Ibrahim , Delleli Slaheddine , Bridge Craig Alan , Messaoudi Hamdi , Chtourou Hamdi , Ballmann Christopher Garrett , Ardigò Luca Paolo , Franchini Emerson 
Published: August 2023

AbstractThe purpose of this study was to assess the effects of acute caffeine supplementation on physical performance and perceived exertion during taekwondo-specific tasks in male and female athletes with varying expertise. In a double-blinded, randomized, placebo-controlled crossover study design, 52 young athletes from elite (n = 32; 16 males and 16 females) and sub-elite competitive level (n = 20; 10 males and 10 females) participated. Athletes performed taekwondo-specific tasks including the taekwondo-specific agility test (TSAT), 10 s frequency speed of kick test (FSKT-10 s) and multi-bout FSKT (FSKT-multi) under the following conditions: (1) Caffeine (CAF; 3 mg kg−1), placebo (PLA), and no supplement control (CON). Session rating of perceived exertion (s-RPE) was determined after the tests. Findings show that regardless of condition, males performed better than females (p < 0.05) and elite athletes had superior performance compared to their sub-elite counterparts (p < 0.05). For the TSAT (p < 0.001), FSKT-10s (p < 0.001), and FSKT-multi (p < 0.001), CAF enhanced performance in elite female athletes compared to sub-elite females. Likewise, CAF ingestion resulted in superior performance in elite males compared to sub-elite males for FSKT-10s (p = 0.003) and FSKT-multi (p < 0.01). The ergogenic potential of CAF during taekwondo-specific tasks appears to be related to a competitive level, with greater benefits in elite than sub-elite athletes.
M1 transcranial direct current stimulation augments laparoscopic surgical skill acquisition
Authors: Galvin Daniel , Toth Adam J. , O’Reilly Barry , O’Sullivan Ray , Campbell Mark J. 
Published: August 2023

AbstractThe acquisition of basic surgical skills is a key component of medical education and trainees in laparoscopic surgery typically begin developing their skills using simulation box trainers. However, despite the advantages of simulation surgical training, access can be difficult for many trainees. One technique that has shown promise to enhance the deliberate practice of motor skills is transcranial electric stimulation (tES). The purpose of this study was to assess the impact of transcranial direct current stimulation (tDCS) on training induced improvements and retention of traditional time and kinematic based laparoscopic surgical skill metrics. Forty-nine medical students were randomly allocated to a neurostimulation or sham group and completed 5 training sessions of a bead transfer and threading laparoscopic task. Participants in both the sham and stimulation groups significantly improved their time and kinematic performance on both tasks following training. Although we did find that participants who received M1 tDCS saw greater performance benefits in response to training on a bead transfer task compared to those receiving sham stimulation no effect of neurostimulation was found for the threading task. This finding raises new questions regarding the effect that motor task complexity has on the efficacy of neurostimulation to augment training induced improvement and contributes to a growing body of research investigating the effects of neurostimulation on the sensory-motor performance of laparoscopic surgical skill.
Exploiting individual differences to assess the role of place and phase locking cues in auditory frequency discrimination at 2 kHz
Authors: Vinay  , Moore Brian C. J. 
Published: August 2023

AbstractThe relative role of place and temporal mechanisms in auditory frequency discrimination was assessed for a centre frequency of 2 kHz. Four measures of frequency discrimination were obtained for 63 normal-hearing participants: detection of frequency modulation using modulation rates of 2 Hz (FM2) and 20 Hz (FM20); detection of a change in frequency across successive pure tones (difference limen for frequency, DLF); and detection of changes in the temporal fine structure of bandpass filtered complex tones centred at 2 kHz (TFS). Previous work has suggested that: FM2 depends on the use of both temporal and place cues; FM20 depends primarily on the use of place cues because the temporal mechanism cannot track rapid changes in frequency; DLF depends primarily on temporal cues; TFS depends exclusively on temporal cues. This led to the following predicted patterns of the correlations of scores across participants: DLF and TFS should be highly correlated; FM2 should be correlated with DLF and TFS; FM20 should not be correlated with DLF or TFS. The results were broadly consistent with these predictions and with the idea that frequency discrimination at 2 kHz depends partly or primarily on temporal cues except for frequency modulation detection at a high rate.
Implementing automated 3D measurements to quantify reference values and side-to-side differences in the ankle syndesmosis
Authors: Peiffer Matthias , Van Den Borre Ide , Segers Tanguy , Ashkani-Esfahani Soheil , Guss Daniel , De Cesar Netto Cesar , DiGiovanni Christopher W. , Victor Jan , Audenaert Emmanuel , Burssens Arne 
Published: August 2023

AbstractDetection of syndesmotic ankle instability remains challenging in clinical practice due to the limitations of two-dimensional (2D) measurements. The transition to automated three-dimensional (3D) measurement techniques is on the verge of a breakthrough but normative and side-to-side comparative data are missing. Therefore, our study aim was two-fold: (1) to establish 3D anatomical reference values of the ankle syndesmosis based on automated measurements and (2) to determine to what extent the ankle syndesmosis is symmetric across all 3D measurements. Patients without syndesmotic pathology with a non-weight-bearing CT scan (NWBCT; N = 38; Age = 51.6 ± 17.43 years) and weight-bearing CT scan (WBCT; N = 43; Age = 48.9 ± 14.3 years) were retrospectively included. After training and validation of a neural network to automate the segmentation of 3D ankle models, an iterative closest point registration was performed to superimpose the left on the right ankle. Subsequently, 3D measurements were manually and automatically computed using a custom-made algorithm and side-to-side comparison of these landmarks allowed one to investigate symmetry. Intra-observer analysis showed excellent agreements for all manual measurements (ICC range 0.85–0.99) and good (i.e. < 2.7° for the angles and < 0.5 mm for the distances) accuracy was found between the automated and manual measurements. A mean Dice coefficient of 0.99 was found for the automated segmentation framework. The established mean, standard deviation and range were provided for each 3D measurement. From these data, reference values were derived to differ physiological from pathological syndesmotic alignment. Furthermore, side-to-side symmetry was revealed when comparing left to right measurements (P > 0.05). In clinical practice, our novel algorithm could surmount the current limitations of manual 2D measurements and distinguish patients with a syndesmotic ankle lesion from normal variance.
Hierarchical based classification method based on fusion of Gaussian map descriptors for Alzheimer diagnosis using T1-weighted magnetic resonance imaging
Authors: Morsy Shereen E. , Zayed Nourhan , Yassine Inas A. 
Published: August 2023

AbstractAlzheimer’s disease (AD) is considered one of the most spouting elderly diseases. In 2015, AD is reported the US’s sixth cause of death. Substantially, non-invasive imaging is widely employed to provide biomarkers supporting AD screening, diagnosis, and progression. In this study, Gaussian descriptors-based features are proposed to be efficient new biomarkers using Magnetic Resonance Imaging (MRI) T1-weighted images to differentiate between Alzheimer’s disease (AD), Mild Cognitive Impairment (MCI), and Normal controls (NC). Several Gaussian map-based features are extracted such as Gaussian shape operator, Gaussian curvature, and mean curvature. The aforementioned features are then introduced to the Support Vector Machine (SVM). They were, first, calculated separately for the Hippocampus and Amygdala. Followed by the fusion of the features. Moreover, Fusion of the regions before feature extraction was also employed. Alzheimer's disease Neuroimaging Initiative (ADNI) dataset, formed of 45, 55, and 65 cases for AD, MCI, and NC respectively, is appointed in this study. The shape operator feature outperformed the other features, with 74.6%, and 98.9% accuracy in the case of normal vs. abnormal, and AD vs. MCI classification respectively.
A solvable model for symmetry-breaking phase transitions
Authors: Kumar Shatrughna , Li Pengfei , Zeng Liangwei , He Jingsong , Malomed Boris A. 
Published: August 2023

AbstractAnalytically solvable models are benchmarks in studies of phase transitions and pattern-forming bifurcations. Such models are known for phase transitions of the second kind in uniform media, but not for localized states (solitons), as integrable equations which produce solitons do not admit intrinsic transitions in them. We introduce a solvable model for symmetry-breaking phase transitions of both the first and second kinds (alias sub- and supercritical bifurcations) for solitons pinned to a combined linear-nonlinear double-well potential, represented by a symmetric pair of delta-functions. Both self-focusing and defocusing signs of the nonlinearity are considered. In the former case, exact solutions are produced for symmetric and asymmetric solitons. The solutions explicitly demonstrate a switch between the symmetry-breaking transitions of the first and second kinds (i.e., sub- and supercritical bifurcations, respectively). In the self-defocusing model, the solution demonstrates the transition of the second kind which breaks antisymmetry of the first excited state.
Wolbachia has subtle effects on thermal preference in highly inbred Drosophila melanogaster which vary with life stage and environmental conditions
Authors: Strunov Anton , Schoenherr Charlotte , Kapun Martin 
Published: August 2023

AbstractTemperature fluctuations are challenging for ectotherms which are not able to regulate body temperature by physiological means and thus have to adjust their thermal environment via behavior. However, little is yet known about whether microbial symbionts influence thermal preference (Tp) in ectotherms by modulating their physiology. Several recent studies have demonstrated substantial effects of Wolbachia infections on host Tp in different Drosophila species. These data indicate that the direction and strength of thermal preference variation is strongly dependent on host and symbiont genotypes and highly variable among studies. By employing highly controlled experiments, we investigated the impact of several environmental factors including humidity, food quality, light exposure, and experimental setup that may influence Tp measurements in adult Drosophila melanogaster flies. Additionally, we assessed the effects of Wolbachia infection on Tp of Drosophila at different developmental stages, which has not been done before. We find only subtle effects of Wolbachia on host Tp which are strongly affected by experimental variation in adult, but not during juvenile life stages. Our in-depth analyses show that environmental variation has a substantial influence on Tp which demonstrates the necessity of careful experimental design and cautious interpretations of Tp measurements together with a thorough description of the methods and equipment used to conduct behavioral studies.
Cocaine hydrochloride, cocaine methiodide and methylenedioxypyrovalerone (MDPV) cause distinct alterations in the structure and composition of the gut microbiota
Authors: Angoa-Pérez Mariana , Zagorac Branislava , Francescutti Dina M. , Shaffer Zachary D. , Theis Kevin R. , Kuhn Donald M. 
Published: August 2023

AbstractCocaine is a highly addictive psychostimulant drug of abuse that constitutes an ongoing public health threat. Emerging research is revealing that numerous peripheral effects of this drug may serve as conditioned stimuli for its central reinforcing properties. The gut microbiota is emerging as one of these peripheral sources of input to cocaine reward. The primary objective of the present study was to determine how cocaine HCl and methylenedioxypyrovalerone, both of which powerfully activate central reward pathways, alter the gut microbiota. Cocaine methiodide, a quaternary derivative of cocaine that does not enter the brain, was included to assess peripheral influences on the gut microbiota. Both cocaine congeners caused significant and similar alterations of the gut microbiota after a 10-day course of treatment. Contrary to expectations, the effects of cocaine HCl and MDPV on the gut microbiota were most dissimilar. Functional predictions of metabolic alterations caused by the treatment drugs reaffirmed that the cocaine congeners were similar whereas MDPV was most dissimilar from the other two drugs and controls. It appears that the monoamine transporters in the gut mediate the effects of the treatment drugs. The effects of the cocaine congeners and MDPV on the gut microbiome may form the basis of interoceptive cues that can influence their abuse properties.